Page 1

Joint Strategic Needs Assessment

Prevalence Study on Long Term Conditions in Birmingham

Yang Tian, Eric Jager, Chris Stephen, Hashum Mahmood, Jeanette Davis and Mohan Singh

October 2009 VERSION CONTROL AND DOCUMENT GOVERNANCE Version

Final draft

Date

30/10/09

Status

Final draft

File location (public)

http://www.bhwp.nhs.uk/Apps/Content/html/viewContent.as px?fid=89

Filename and path to locate this document

Y:\Public Health\PHIT\Public Health Server\PHIT Team\12. JSNA\Year 2009\Long term conditions


Authors and reviewers Authors: Yang Tian

Public Health Information Team Leader

Birmingham Health and Wellbeing Partnership

Eric Jager

Consultant Demographer

Birmingham Health and Wellbeing Partnership

Chris Stephen

Principal Public Health Information Analyst

NHS South Birmingham

Hashum Mahmood

Epidemiologist

NHS Birmingham East and North

Jeanette Davis

Public Health Information Analyst

Birmingham Health and Wellbeing Partnership

Mohan Singh

Public Health Database Administrator/Analyst

Birmingham Health and Wellbeing Partnership

Reviewers: Dr A.C. Burden

Clinical Director of Long Term Conditions

Heart of Birmingham teaching Primary Care Trust

Dr Chris Spencer-Jones

Director of Public Health

NHS South Birmingham

Dr Richard Mendelsohn

Clinical Director of Chronic Disease Systems

NHS Birmingham North and East

Greg Ball

Principal Demographer

Birmingham City Council

Mary Bosworth

Commissioning Manager

Heart of Birmingham teaching Primary Care Trust

Algar Goredema

Head of Policy

Birmingham City Council

Corrine Ralph

Network Manager

Birmingham, Sandwell and Solihull Cardiac Network

Dr Waqar Malik

Community Diabetes Consultant

NHS Birmingham North and East

Dr Faisel Yunus

Consultant in Public Health

NHS Birmingham North and East

Jyoti Atri

Associate Director of Public Health

NHS South Birmingham

JSNA LTCs Final Version

i


Signed off by: Jim McManus

Director of Public Health for Birmingham

Birmingham Health and Wellbeing Partnership

Iris Fermin

Head of Information and Intelligence

Birmingham Health and Wellbeing Partnership

Contact: Birmingham Public Health Information Team, Suite 203, CIBA Building, 146, Hagley Road, Birmingham B16 9NX Email: phit@bhwp.nhs.uk Telephone: 0121 465 2999 Details of authors and reviewers for each chapter of the report are listed below:

Chapter

Partner(s)

Author(s)

Reviewer(s)

1 Introduction

PHIT

Yang Tian Eric Jager

Jim McManus Iris Fermin

2 Key findings

PHIT/SB

Yang Tian

Chris Spencer-Jones

3 Methods

PHIT/ HOB

Yang Tian Eric Jager

Jim McManus Iris Fermin A.C. Felix Burden

4 Local context

PHIT/BCC

Yang Tian Eric Jager Jeanette Davis

Greg Ball

5 Disease burden

PHIT/HOB/BCC/BEN/ SB

Yang Tian Mohan Singh Jeanette Davis

Mary Bosworth Algar Goredema Richard Mendelsohn A.C. Felix Burden Chris Spencer-Jones

6. LTCs in general

PHIT/BEN/HOB/SB

Yang Tian Jeanette Davis

Richard Mendelsohn A.C. Felix Burden Chris Spencer-Jones

7. People with multiple LTCs

PHIT/HOB

Yang Tian Mohan Singh

A.C. Felix Burden

8. CHD

PHIT/Cardiac network/HOB/SB

Yang Tian

Corrine Ralph A.C. Felix Burden Chris Spencer-Jones

9. Diabetes

PHIT/BEN/HOB

Eric Jager

Waqar Malik A.C. Felix Burden

JSNA LTCs Final Version

ii


Chapter

Partner(s)

Author(s)

Reviewer(s)

10. COPD

BEN/PHIT

Hashum Mahmood Eric Jager

Faisel Yunus Iris Fermin

11. Epilepsy

PHIT/SB

Yang Tian

Chris Spencer-Jones

12. Chronic Kidney Disease

PHIT/HOB

Yang Tian

A.C. Felix Burden

13. Asthma

SB

Chris Stephen

Jyoti Atri

14. Conclusions and future work

PHIT/HOB/SB/BEN

Yang Tian

Jim McManus Iris Fermin A.C. Felix Burden Chris Spencer-Jones Waqar Malik

JSNA LTCs Final Version

iii


Acknowledgements We would like to acknowledge and express our gratitude to all those who provided help for us to make the completion of this JSNA report possible. Especially we would like to thank Dr Chris Spencer-Jones from NHS South Birmingham, Dr A.C. Felix Burden and Dr Andrew Rouse from Heart of Birmingham tPCT, and Dr Richard Mendelsohn and Saj Kahrod from NHS Birmingham East and North for their help in the initial design of the study. We would also like to thank the following people/organisations for their help with data collection and analysis of the study: Hannah Walford from East Region Public Health Observatory for her help with the CHD and COPD prevalence predicting models; Dr David Ansell from UK Renal Registry for provision and interpretation of the renal replacement therapy data; and Jo Lockett and Tracy Savage from the Department of Medicines Management at Keele University for provision and interpretation of the prescribing data. We would like to thank all the reviewers as well for their support and valuable comments. Finally we would like to thank our Director, Jim McManus, and Manager of the team, Dr Iris Fermin, for their continued support in ensuring the completion of this report.

JSNA LTCs Final Version

iv


Contents 1.

2.

Introduction .................................................................................................... 1 1.1.

Definition of long term conditions ............................................................... 1

1.2.

The JSNA context ...................................................................................... 2

1.3.

The national and local policy context ......................................................... 2

1.4.

Objectives of this study .............................................................................. 3

Key findings ................................................................................................... 4 2.1.

Impact of LTCs in Birmingham ................................................................... 4

2.1.1. 2.1.2. 2.2.

Prevention of LTCs and improvement of health ......................................... 4

2.2.1. 2.2.2. 3.

Current status .................................................................................. 4 Looking into the future ..................................................................... 6

Methods .......................................................................................................... 7 3.1.

Definitions .................................................................................................. 7

3.1.1. 3.1.2. 3.2.

Prevalence ...................................................................................... 7 Alternative definitions for LTCs in general........................................ 7

Data sources.............................................................................................. 8

3.2.1. 3.2.2.

Selection of data sources ................................................................ 8 Different sources of information on prevalence ................................ 8

3.3.

Selection of specific LTCs .......................................................................... 8

3.4.

Data analysis ............................................................................................. 9

3.4.1. 3.4.2. 3.5.

Mapping prevalence in GP catchments to wards ............................. 9 Calculating the number of people with multiple LTCs..................... 10

Predicting disease prevalence ................................................................. 10

3.5.1. 3.5.2. 4.

Impact on health .............................................................................. 4 Impact on health and social care services ....................................... 4

Use of currently available prevalence models ................................ 10 Directly applying prevalence rates from studies done elsewhere ... 10

Local context ................................................................................................ 12 4.1.

Age and gender distribution ..................................................................... 12

4.1.1. 4.1.2. 4.2.

Current population structure .......................................................... 12 Projected population structure ....................................................... 13

Ethnicity ................................................................................................... 13

4.2.1. 4.2.2.

Current ethnic distribution .............................................................. 13 Projected ethnic distribution ........................................................... 14

4.3.

Deprivation .............................................................................................. 15

4.4.

Employment ............................................................................................. 16

4.5.

Lifestyle ................................................................................................... 17

JSNA LTCs Final Version

v


4.5.1. 5.

Burden on local health and social care from LTCs.................................... 20 5.1.

Use of community care services .............................................................. 20

5.2.

Use of primary care services.................................................................... 22

5.3.

Use of secondary care services ............................................................... 22

5.3.1. 5.3.2. 5.3.3. 5.4. 6.

Performance against the national target ........................................ 23 Hospital admissions ....................................................................... 23 Hospital bed days .......................................................................... 26

Premature deaths from LTCs ................................................................... 28

LTCs in general ............................................................................................ 33 6.1.

QOF Prevalence ...................................................................................... 34

6.1.1. 6.1.2.

Current prevalence ........................................................................ 34 Trends ........................................................................................... 35

6.2.

Geographical variations ........................................................................... 37

6.3.

Demographical patterns ........................................................................... 37

6.3.1. 6.3.2. 6.3.3.

Age ................................................................................................ 37 Gender .......................................................................................... 38 Ethnicity ......................................................................................... 38

6.4.

Socio-economic status and LTCs............................................................. 40

6.5.

Lifestyle choices and LTCs ...................................................................... 41

6.5.1. 6.5.2. 6.5.3. 6.6. 7.

Life style patterns .......................................................................... 18

Smoking ........................................................................................ 41 Obesity .......................................................................................... 43 Alcohol .......................................................................................... 43

Projection of LTCs in general ................................................................... 45

People with multiple LTCs ........................................................................... 47 7.1.

People with multiple LTCs by PCT ........................................................... 48

7.2.

Geographical variations ........................................................................... 50

7.3.

Demographical patterns ........................................................................... 51

7.3.1. 7.3.2.

Age and gender ............................................................................. 51 Ethnicity ......................................................................................... 53

7.4.

Multiple LTCs and deprivation .................................................................. 57

7.5.

Co-morbidity of common LTCs ................................................................ 58

7.5.1. 7.5.2. 7.5.3. 7.5.4. 7.5.5. 7.5.6. 7.5.7.

CHD .............................................................................................. 58 Diabetes ........................................................................................ 61 CKD............................................................................................... 63 Prevalence of co-morbidities of vascular diseases in HoB tPCT from primary care data........................................................................... 66 COPD ............................................................................................ 69 Asthma .......................................................................................... 71 Epilepsy ......................................................................................... 73

JSNA LTCs Final Version

vi


8.

Coronary heart disease ............................................................................... 75 8.1.

Definitions ................................................................................................ 76

8.2.

Current CHD prevalence and trends ........................................................ 76

8.2.1. 8.2.2. 8.3.

Geographical distribution ......................................................................... 78

8.4.

Demographical patterns ........................................................................... 79

8.4.1. 8.4.2. 8.4.3. 8.5.

8.6.

Smoking ........................................................................................ 85 Diet ................................................................................................ 85 Physical activity ............................................................................. 85 Alcohol .......................................................................................... 86 Obesity .......................................................................................... 86

Clinical risk factors ................................................................................... 86

8.7.1. 8.7.2. 8.7.3. 8.8.

CHD by deprivation quintiles.......................................................... 83 Local implications .......................................................................... 84

Lifestyle risk factors ................................................................................. 84

8.6.1. 8.6.2. 8.6.3. 8.6.4. 8.6.5. 8.7.

Age and gender ............................................................................. 79 Ethnicity ......................................................................................... 80 Local implications .......................................................................... 82

CHD and deprivation................................................................................ 83

8.5.1. 8.5.2.

Blood pressure .............................................................................. 86 Blood cholesterol ........................................................................... 88 Diabetes ........................................................................................ 88

Projected CHD prevalence....................................................................... 88

8.8.1. 8.8.2. 8.8.3. 8.8.4. 8.8.5. 8.8.6. 9.

QOF prevalence ............................................................................ 76 Prevalence based on the Health Survey for England ..................... 77

The APHO CHD Local Model ........................................................ 89 CHD Projections ............................................................................ 89 CHD projections by gender ............................................................ 91 CHD projections by age groups ..................................................... 92 CHD projection by ethnicity............................................................ 92 Limitations of the model and projections ........................................ 93

Diabetes Mellitus .......................................................................................... 95 9.1.

A growing concern worldwide and in the UK ............................................ 95

9.2.

What is diabetes? .................................................................................... 96

9.3.

Types of diabetes .................................................................................... 96

9.3.1. 9.3.2. 9.3.3.

Diabetes Mellitus Type 2 (T2DM)................................................... 96 Diabetes Mellitus Type 1 (T1DM)................................................... 97 The importance of early diagnosis and treatment of diabetes ........ 97

9.4.

Diabetes prevalence in England............................................................... 98

9.5.

Risk factors for type 1 and type 2 diabetes .............................................. 99

9.5.1. 9.5.2.

Obesity ........................................................................................ 100 Ethnicity ....................................................................................... 103

JSNA LTCs Final Version

vii


9.5.3. 9.6.

Diabetes prevalence in Birmingham around 2006 .................................. 106

9.6.1. 9.6.2. 9.7.

Type 1 Diabetes prevalence (T1DM) ........................................... 115 Type 2 diabetes prevalence (T2DM) ............................................ 115 The level of undiagnosed diabetes in Birmingham ....................... 116

Projecting future prevalence .................................................................. 117

9.9.1. 10.

The model ................................................................................... 110 The results................................................................................... 110 Limitations of the model ............................................................... 112

The PHIT estimates ............................................................................... 113

9.8.1. 9.8.2. 9.8.3. 9.9.

Diagnosed diabetes prevalence from GP-practices data (QOF) .. 106 Distribution by ward ..................................................................... 109

Population-based estimates of diabetes prevalence: the YHPHO PBS Diabetes Model, Phase 3 ............................................................. 109

9.7.1. 9.7.2. 9.7.3. 9.8.

Diabetes and deprivation ............................................................. 105

Projected number of persons with diabetes, 2010-2020 .............. 118

Chronic obstructive pulmonary disease .................................................. 123

10.1.

A growing concern worldwide and in the UK .......................................... 123

10.2.

What is COPD? ..................................................................................... 123

10.2.1. 10.3.

Risk Factors ........................................................................................... 124

10.3.1. 10.3.2. 10.3.3. 10.4.

10.4.2. 10.4.3.

11.

Smoking as a risk factor .............................................................. 125 Smoking in Birmingham PCTs ..................................................... 125 Deprivation and COPD prevalence .............................................. 126

COPD prevalence in Birmingham .......................................................... 129

10.4.1.

10.5.

‘The missing millions’ ................................................................... 124

Current Diagnosed COPD prevalence from GP-practices data (QOF) .................................................................................................... 129 COPD prevalence by ward .......................................................... 130 Population-based estimates of COPD prevalence: the ERPHO COPD model ............................................................................... 131

The level of undiagnosed COPD in Birmingham .................................... 135

Epilepsy ...................................................................................................... 137

11.1.

Definition................................................................................................ 138

11.2.

Current epilepsy prevalence and trends ................................................. 138

11.3.

Geographical variation ........................................................................... 141

11.4.

Demographical patterns ......................................................................... 141

11.4.1. 11.4.2. 11.4.3. 11.5.

Epilepsy by age ........................................................................... 142 Epilepsy by gender ...................................................................... 142 Local implications ........................................................................ 143

Epilepsy and deprivation ........................................................................ 145

11.5.1.

Epilepsy prevalence by deprivation quintiles ................................ 145

JSNA LTCs Final Version

viii


11.5.2. 11.6.

Clinical risk factors ................................................................................. 146

11.6.1. 11.6.2. 11.6.3. 11.7.

Cause of epilepsy ........................................................................ 146 Misdiagnosis of epilepsy .............................................................. 146 Epilepsy and learning disabilities ................................................. 146

Projected prevalence of epilepsy ........................................................... 147

11.7.1. 11.7.2. 11.7.3. 11.7.4. 12.

Local implications ........................................................................ 146

Applying current prevalence rates to projected population ........... 147 Projected prevalence of epilepsy ................................................. 147 Projected prevalence of epilepsy by age and gender ................... 148 Limitations of the projection ......................................................... 150

Chronic kidney disease ............................................................................. 152

12.1.

Definition................................................................................................ 153

12.2.

Current CKD prevalence ........................................................................ 153

12.3.

Renal replacement therapy prevalence .................................................. 155

12.4.

Geographical variations ......................................................................... 156

12.5.

Demographical patterns ......................................................................... 157

12.5.1. 12.5.2. 12.5.3. 12.6.

CKD and deprivation .............................................................................. 162

12.6.1. 12.6.2. 12.7.

Smoking ...................................................................................... 166 Obesity ........................................................................................ 166

Projected prevalence ............................................................................. 166

12.9.1. 12.9.2. 12.9.3. 12.9.4. 13.

Hypertension ............................................................................... 164 Diabetes ...................................................................................... 165

Life style risk factors .............................................................................. 165

12.8.1. 12.8.2. 12.9.

CKD prevalence by deprivation quintiles...................................... 162 Local implications ........................................................................ 163

Clinical risk factors ................................................................................. 164

12.7.1. 12.7.2. 12.8.

Age and gender ........................................................................... 157 Ethnicity ....................................................................................... 160 Local implications ........................................................................ 160

Applying current prevalence rates to projected population ........... 166 Projected prevalence of CKD....................................................... 167 Projected prevalence of CKD by age and gender ........................ 168 Limitations of the projection ......................................................... 169

Asthma ........................................................................................................ 171

13.1.

Introduction and Key Facts .................................................................... 171

13.1.1. 13.1.2. 13.1.3. 13.2.

Risk Factors for the Development of Asthma ............................... 172 Occupational Asthma................................................................... 173 Asthmatic Triggers ....................................................................... 174

Prevalence of Asthma ............................................................................ 174

13.2.1.

Recorded Prevalence .................................................................. 174

JSNA LTCs Final Version

ix


13.2.2. 13.2.3. 13.2.4. 13.3.

Management of Asthma ......................................................................... 178

13.3.1. 13.3.2. 13.3.3. 13.4.

Prevalence by Age and Sex......................................................... 176 Asthma Prevalence by Socio-Economic Status and Ethnicity ...... 176 Predicting Asthma Prevalence ..................................................... 177 Prescriptions ................................................................................ 178 Asthma Reviews .......................................................................... 178 Smoking Prevalence in Young Asthmatics................................... 179

Hospital Admissions due to Asthma ....................................................... 179

13.4.1.

Admission Rates by Age and Sex ................................................ 179

13.5.

Mortality due to Asthma ......................................................................... 182

13.6.

Conclusions ........................................................................................... 183

14.

Conclusions and future work .................................................................... 184

14.1.

Conclusions ........................................................................................... 184

14.1.1. 14.1.2. 14.1.3. 14.1.4. 14.2.

Burden of LTCs ........................................................................... 184 Disease prevalence of common LTCs ......................................... 184 Determinants of the prevalence of LTCs ...................................... 185 Projections of future disease prevalence ..................................... 185

Future work ............................................................................................ 185

15.

Appendix A ICD codes used for LTCs ...................................................... 187

16.

Appendix B Appraisal on the data sources .............................................. 188

17.

Appendix C Projection models ................................................................. 193

17.1. 18.

CHD model ............................................................................................ 193

Appendix D Projected CHD prevalence by

demographical groups ........................................................................................ 195 18.1.

Projected CHD by gender ...................................................................... 195

18.2.

Projected CHD by age group ................................................................. 197

18.3.

Projected CHD by ethnicity .................................................................... 201

19.

Appendix E Projected population for Birmingham

and the PCTs ....................................................................................................... 206 20.

Appendix F Projected epilepsy prevalence by

demographics...................................................................................................... 208 21.

Appendix G Projected prevalence of CKD by

demographical groups ........................................................................................ 211 22.

Appendix H Top 20 co morbidities of common

JSNA LTCs Final Version

x


LTCs ..................................................................................................................... 213 22.1.

CHD

................................................................................................... 213

22.2.

Diabetes ................................................................................................ 217

22.3.

CKD

22.4.

COPD ................................................................................................... 221

22.5.

Asthma .................................................................................................. 223

22.6.

Epilepsy ................................................................................................. 225

................................................................................................... 219

23.

Appendix I Estimated prevalence of diabetes .......................................... 229

24.

References.................................................................................................. 233

JSNA LTCs Final Version

xi


List of Figures Figure 4.1

Population by age group and gender, Birmingham and England, 2007 .............................................................................................. 12

Figure 4.2

Population projection by sex and age group, Birmingham, 2010 and 2020 .............................................................................................. 13

Figure 5.1

Use of community (social) care services by people with LTCs, England, 2005/06 (DOH, 2007a) ................................................... 21

Figure 5.2

Use of primary care services by people with LTCs, West Midlands, 2006 .............................................................................................. 22

Figure 5.3

Emergency bed days rates against the national target, Birmingham, 2002/03 – 2006/07......................................................................... 23

Figure 5.4

Percentage of hospital admissions from common LTCs* (as the primary diagnosis), Birmingham and PCTs, 2001/02 to 2006/07 ... 24

Figure 5.5

Percentage of hospital bed days from common LTCs* (as the primary diagnosis), Birmingham and PCTs 2001/02 to 2006/07 .... 26

Figure 5.6

Percentage of premature deaths (under 75s) caused by common LTCs*, 3-year rolling average, 1995/97 to 2005/07, Birmingham and PCTs ............................................................................................. 28

Figure 5.7

Age-standardised mortality rates of common LTCs, males, PCTs, Birmingham, West Midlands and England, 2005-07 ...................... 30

Figure 5.8

Age-standardised mortality rates of common LTCs, females, Birmingham, PCTs, England and West Midlands, 2005-07 ............ 31

Figure 6.1

Prevalence of common LTCs, Birmingham, PCTs and England, 2007/08 ......................................................................................... 34

Figure 6.2

Map – Prevalence of limiting long-term illness by ward and PCT in Birmingham, 2001 ......................................................................... 37

Figure 6.3

Prevalence of LTCs by age group, West Midlands Region, 2006 .. 38

Figure 6.4

Age-standardised prevalence* of limiting long-term illness by NSSEC social class group, Birmingham, 2001 ................................... 40

Figure 6.5

Ward level prevalence of limiting long-term illness (2001 Census) against IMD score 2004 for income and employment, Birmingham 41

Figure 6.6

Current smoking status for people with and without LTCs, West Midlands, 2007 .............................................................................. 42

Figure 6.7

Number of cigarettes smoked per day for people with and without LTCs, West Midlands, 2007 ........................................................... 42

Figure 6.8

Obesity status for people with and without LTCs, West Midlands, 2007 .............................................................................................. 43

Figure 6.9

Percentage of people who had drink in the 7 days prior to the interview by people with and without LTCs, West Midlands, 2007 . 44

Figure 6.10

Frequency of drinking alcohol for people with and without LTCs, West Midlands, 2007 ..................................................................... 44

Figure 7.1

Crude prevalence rate (%) of people with multiple LTCs by PCT, Birmingham, 2006/07..................................................................... 49

JSNA LTCs Final Version

xii


Figure 7.2

Age-standardised* prevalence rate (%) of people with multiple LTCs by PCT, Birmingham, 2006/07 ....................................................... 49

Figure 7.3

Crude prevalence rate of multiple LTCs by ward, Birmingham, 2006/07 ......................................................................................... 50

Figure 7.3

Number and percentage of people with multiple LTCs by age group and PCT, males, Birmingham 2006/07 .......................................... 51

Figure 7.4

Number and percentage of people with multiple LTCs by age group and PCT, females, Birmingham 2006/07 ....................................... 52

Figure 7.5

Crude prevalence rates (%) of multiple LTCs by ethnic group and PCT, males, Birmingham, 2006/07 ................................................ 55

Figure 7.6

Crude prevalence rates (%) of multiple LTCs by ethnic group and PCT, females, Birmingham, 2006/07 ............................................. 55

Figure 7.7

Age standardised rate* (per 100,000) of multiple LTCs by ethnic group, Birmingham, 2006/07.......................................................... 56

Figure 7.8

Age standardised prevalence rate* (%) of multiple LTCs by local deprivation quintile**, Birmingham, 2006/07 .................................. 57

Figure 8.1

Trend of QOF unadjusted prevalence of CHD, Birmingham, PCTs and England, 2004/05 to 2007/08 .................................................. 77

Figure 8.2

Prevalence of CHD* by gender, England, 1994 – 2006 ................. 78

Figure 8.3

Prevalence of CHD by ward, Birmingham 2007/08 ........................ 79

Figure 8.4

Estimated numbers of people with CHD by age group and PCT, males, Birmingham, 2007 .............................................................. 82

Figure 8.5

Estimated numbers of people with CHD by age group and PCT, females, Birmingham, 2007 ........................................................... 83

Figure 8.6

Age adjusted prevalence* of treated CHD by gender and deprivation quintiles, England and Wales, 1994/98 .......................................... 84

Figure 8.7

Hypertension prevalence Birmingham, PCTs and England, 2004/05 – 2007/08 ...................................................................................... 87

Figure 9.1

Trend in diabetes prevalence, England, 1991-2006 ....................... 98

Figure 9.2

Prevalence rate of registered diabetes by deprivation quintile, England ....................................................................................... 105

Figure 9.3

Trend of QOF Unadjusted prevalence of Diabetes, Birmingham, PCTs and England, 2004/05 to 2007/08 ...................................... 107

Figure 9.4

Prevalence of diabetes by ward, Birmingham 2007/08 ................ 109

Figure 10.1

Natural history of lung function decline (Lundback B and Lindberg A, 2003) ........................................................................................... 125

Figure 10.2

Smoking prevalence by PCT, Birmingham, 2009 ......................... 126

Figure 10.3

Correlation of Birmingham Wards and COPD prevalence ............ 127

Figure 10.4

Correlation of Birmingham Wards and COPD prevalence, adjusted .. ................................................................................................... 128

Figure 10.5

Trend of QOF Unadjusted prevalence of COPD, Birmingham, PCTs and England, 2004/05 to 2007/08 ................................................ 129

Figure 10.6

QOF COPD prevalence by ward, Birmingham, 2007/08 .............. 130

JSNA LTCs Final Version

xiii


Figure 11.1

Trend of epilepsy prevalence, PCTs, Birmingham and England, 2004/05 to 2007/08 ...................................................................... 139

Figure 11.2

Rate of defined daily doses of GP prescription of anti-epileptic drugs by PCT, April 2000 to May 2009, Birmingham ............................. 140

Figure 11.3

Epilepsy prevalence by ward, Birmingham, 2007/08 .................... 141

Figure 11.4

Age standardised treated epilepsy prevalence rate (per 1,000 patients) by gender, England and Wales, 1994 and 1998 (Purcell et al. 2002) ...................................................................................... 143

Figure 11.5

Estimated numbers* of people with epilepsy by age group and PCT, males, 2007 ................................................................................. 144

Figure 11.6

Estimated numbers* of people with epilepsy by age group and PCT, females, 2007 .............................................................................. 144

Figure 11.7

Prevalence of treated epilepsy (per 1,000 patients), by gender and deprivation quintile* of GP practice, England and Wales, 1994 to 1998 (Purcell et al. 2002) ............................................................. 145

Figure 11.8

Projected numbers of people with epilepsy by PCT, Birmingham, 2010, 2015 and 2020 ................................................................... 148

Figure 11.9

Projected number of people with epilepsy by age group and PCT, males, 2020 in comparison with estimated prevalence in 2007.... 149

Figure 11.10 Projected number of people with epilepsy by age group and PCT, females, 2020 in comparison with estimated prevalence in 2007 . 150 Figure 12.1

CKD (stage 3 and 4) prevalence, Birmingham, the PCTs and England, 2006/07 to 2007/08 ....................................................... 154

Figure 12.2

Age standardised prevalence ratio* of renal replacement treatment (RRT), Birmingham PCTs and England, 2004 to 2007................. 156

Figure 12.3

CKD (stage 3 and 4) prevalence by ward, Birmingham, 2007/08 . 157

Figure 12.4

CKD (stage 3 to 5) prevalence rate by gender and age group, England, 2003 (Stevens et al. 2007) ............................................ 158

Figure 12.5

Prevalence rate of RRT patients per million population by age and gender on 31/12/07, United Kingdom (David Ansell , Terry Feest, Andrew Williams, Chris Winearls. 2008) ...................................... 159

Figure 12.6

Relation between standardised rate ratio for renal replacement therapy and proportion of non-Whites in Primary Care trusts in England (Ansell et al. 2008) ......................................................... 160

Figure 12.7

Estimated CKD (stage 3 to 5) prevalence by age group and PCT, males, Birmingham, 2007 study (Stevens et al. 2007) ................. 161

Figure 12.8

Estimated CKD (stage 3 to 5) prevalence by age group and PCT, females, Birmingham, 2007 (Stevens et al. 2007)........................ 162

Figure 12.9

Proportion of CKD patients presented by deprivation quintile and disease stage, Sheffield, 1995 – 2005 (Bello et al. 2008) ............ 163

Figure 12.10 Age standardised accept rates of RRT by social deprivation group, England, 2007 (Ansell et al. 2008) ............................................... 163 Figure 12.11 Hypertension prevalence Birmingham, PCTs and England, 2004/05 – 2007/08 .................................................................................... 164

JSNA LTCs Final Version

xiv


Figure 12.12 Projected number of people* with CKD (stage 3 to 5) PCT, Birmingham, 2010, 2015 and 2020 .............................................. 167 Figure 12.13 Projected number of people with CKD (stage 3 to 5) by age group and PCT, males, 2020 in comparison with estimated prevalence in 2007 ............................................................................................ 168 Figure 12.14 Projected number of people with CKD (stage 3 to 5) by age group and PCT, females, 2020 in comparison with estimated prevalence in 2007 ............................................................................................ 169 Figure 13.1

Substances identified as sensitizing agents for asthma ............... 173

Figure 13.2

Self-reported asthmatic triggers ................................................... 174

Figure 13.3

Recorded asthma prevalence ...................................................... 175

Figure 13.4

Recorded vs. expected asthma prevalence ................................. 175

Figure 13.5

Asthma prevalence by age and sex ............................................. 176

Figure 13.6

The percentage of patients with asthma who have had an asthma review in the previous 15 months................................................. 178

Figure 13.7

Percentage of patients with asthma between the ages of 14 and 19 in whom there is a record of smoking status in the previous 15 months ........................................................................................ 179

Figure 13.8

Emergency hospital admissions per 100,000 population ............. 180

Figure 13.9

Asthma hospital admissions rates per 1,000 population .............. 181

Figure 13.10 Percentage of admissions by age group for males and females .. 181 Figure 13.11 Age standardised mortality rate for asthma, 2005 – 2007 ............ 182 Figure 13.12 Age standardised mortality due to asthma 1993 – 2007 .............. 182 Figure 13.13 Mortality rate for asthma by age group, England 2005 – 2007 ..... 183

JSNA LTCs Final Version

xv


List of Tables Table 1.1

Common long term conditions ......................................................... 1

Table 4.1

Ethnicity groups for Birmingham, West Midlands and England, 2006 ..................................................................................................... 14

Table 4.2

Projections of population in Birmingham by ethnic group, 2011, 2016, 2021 and 2026 (Simpson 2007) ........................................... 15

Table 4.3

Population by SOA level IMD quintile, Birmingham and the PCTs, 2007 .............................................................................................. 16

Table 4.4

Key figures for Work Deprivation in Birmingham, West Midlands and England, 2006 - 2007 ................................................................... 17

Table 4.5

Key figures for life style in Birmingham, West Midlands and England, 2003-2005 and 2007-2008 ............................................................ 17

Table 4.6

Life style patterns in population ..................................................... 18

Table 5.1

Number of hospital admissions by common LTCs (as the primary diagnosis) and percentage out of all hospital admissions, Birmingham PCTs, 2006/07 ........................................................... 25

Table 5.2

Number of hospital bed days from common LTCs (as primary diagnosis) and percentage out of all hospital bed days, Birmingham PCTs, 2006/07............................................................................... 27

Table 5.3

Number of premature deaths by common LTCs and percentage out of all premature deaths, Birmingham PCTs, 2005-2007................. 29

Table 6.1

Suggested prevalence rates of LTCs in general from different information sources ....................................................................... 33

Table 6.2

Trend of common LTCs prevalence by disease, Birmingham, 2004/05-2007/08 ........................................................................... 35

Table 6.3

Trend of common LTCs prevalence by disease and PCT, 2004/052007/08 ......................................................................................... 36

Table 6.4

Prevalence of limiting long term illnesses by age group and ethnicity, Birmingham, 2001 ......................................................................... 38

Table 6.5

Limiting long-term illnesses projections to year 2021 (Simpson 2007). ............................................................................................ 46

Table 7.1

Prevalence of people with multiple LTCs by PCT, Birmingham, 2006/07 ......................................................................................... 48

Table 7.2

Ethnic distribution of people with multiple LTCs Birmingham and the three PCTs, 2006/07...................................................................... 53

Table 7.3

Top three co morbidities with CHD by PCT, Birmingham, 2006/07 59

Table 7.4

Prevalence of three-way co-morbidities with CHD by PCT, Birmingham, 2006/07..................................................................... 60

Table 7.5

Top three co morbidities with diabetes by PCT, Birmingham, 2006/07 ......................................................................................... 61

Table 7.6

Prevalence of three-way co-morbidities with diabetes by PCT, Birmingham, 2006/07..................................................................... 63

JSNA LTCs Final Version

xvi


Table 7.7

Top three co morbidities with CKD by PCT, Birmingham, 2006/07 64

Table 7.8

Prevalence of three-way co-morbidities with CKD by PCT, Birmingham, 2006/07..................................................................... 66

Table 7.9

Prevalence of cardiovascular diseases in people above the age of 40, HoB tPCT, 2007 and 2008 ....................................................... 67

Table 7.10

Co-morbidities with CHD in people above the age of 40, HoB tPCT, 2007 and 2008............................................................................... 67

Table 7.11

Co-morbidities with atrial fibrillation in people above the age of 40, HoB tPCT, 2007 and 2008 ............................................................. 68

Table 7.12

Co-morbidities with CKD in people above the age of 40, HoB tPCT, 2007 and 2008............................................................................... 68

Table 7.13

Co-morbidities with Diabetes in people above the age of 40, HoB tPCT, 2007 and 2008..................................................................... 68

Table 7.14

Three way co-morbidities of cardiovascular diseases in people above the age of 40, HoB tPCT, 2007 and 2008............................ 69

Table 7.15

Top three co morbidities with COPD by PCT, Birmingham, 2006/07.. ..................................................................................................... 70

Table 7.16

Top three co morbidities with asthma by PCT, Birmingham, 2006/07 ..................................................................................................... 72

Table 7.17

Top three co morbidities with epilepsy by PCT, Birmingham, 2006/07 ..................................................................................................... 73

Table 8.1

Prevalence of CHD* by gender and age group, England, 1994 – 2006 .............................................................................................. 80

Table 8.2

Age adjusted prevalence* of cardiovascular conditions by ethnic group, males England, 2004 .......................................................... 81

Table 8.3

Projected CHD prevalence in Birmingham and PCTs up to 2020... 90

Table 9.1

Prevalence of diagnosed diabetes by type, sex and age, 2006, England ......................................................................................... 99

Table 9.2

Example calculation of the Diabetes Index, England males 1991 100

Table 9.3

Diabetes prevalence forecasts based on two scenarios of obesity levels ........................................................................................... 101

Table 9.4

Prevalence rate of underweight, healthy weight, overweight and obese school children by ethnic group, England, 2007/08 ........... 101

Table 9.5

Obesity in England, Birmingham and PCTS, 2007/2008 .............. 102

Table 9.6

Impact of change in obesity levels on diabetes prevalence: an example from Birmingham East and North PCT .......................... 103

Table 9.7

Diabetes by sex and ethnic group, adults aged 16 and over, 2004, England ....................................................................................... 104

Table 9.8

Diagnosed Diabetes Prevalence (all types) in England, Birmingham and PCTs, 2004/05 to 2007/08 ................................ 108

Table 9.9

Estimated Type 1 and Type 2 Diabetes Prevalence (diagnosed and undiagnosed), by sex; England, West Midlands, Birmingham and PCTs, 2005 ................................................................................. 111

JSNA LTCs Final Version

xvii


Table 9.10

Estimated diabetes prevalence rates from QOF data by type, sex and PCT, 2007/08 ....................................................................... 114

Table 9.11

Diabetes Mellitus prevalence in Birmingham and PCTs, 2006 by type and sex ................................................................................ 115

Table 9.12

Comparison of total estimated Type 1 and Type 2 Diabetes Prevalence with diagnosed prevalence from GP practice data, England Birmingham and PCTs, 2005 ......................................... 117

Table 9.13

Projected prevalence rates for T1DM and T2DM by sex, 2006, 2010-2025 ................................................................................... 118

Table 9.14

Comparing the Three PCTS on major risk factors for diabetes using 2007 data .................................................................................... 119

Table 9.15

Projected number of people with T1DM or D2TM by sex, 2010-2020 for three scenarios of population projections................................ 120

Table 10.1

COPD prevalence locally and nationally ...................................... 130

Table 10.2

Effect of drop in smoking rates on COPD prevalence, Birmingham and PCTs, 2010 – 2020 ............................................................... 132

Table 10.3

Projected COPD prevalence by sex; Birmingham and PCTs, 20102020 ............................................................................................ 133

Table 10.4

Projected COPD prevalence by broad age groups; Birmingham and PCTs, 2010-2020 ........................................................................ 134

Table 10.5

Projected COPD prevalence by major ethnic groups; Birmingham and PCTs, 2010-2020.................................................................. 135

Table 10.6

Modeled COPD prevalence in Birmingham PCT’s ....................... 136

Table 11.1

Epilepsy prevalence rate (per 1,000 patients) by gender and age group, England and Wales, 1994 and 1998 (Purcells et al. 2002) 142

Table 12.1

National Kidney Foundation KDOQI staging for CKD................... 153

Table 13.1

Projected prevalence of asthma .................................................. 177

Table 13.2

Spend on BNF Chapter 3, 2007/08 .............................................. 178

Table A.1

ICD-10 and ICD-9 codes used for LTCs ..................................... 187

Table B.1

Data sources used in this study ................................................... 188

Table C.1

Relative risk ratios for local CHD model ....................................... 193

Table D.1

Projected CHD prevalence in Birmingham and PCTs up to 2020 – females ........................................................................................ 195

Table D.2

Projected CHD prevalence in Birmingham and PCTs up to 2020 – males ........................................................................................... 196

Table D.3

Projected CHD prevalence in Birmingham and PCTs up to 2020 – Aged 16 – 44 ............................................................................... 197

Table D.4

Projected CHD prevalence in Birmingham and PCTs up to 2020 – aged 45 – 64 ............................................................................... 198

Table D.5

Projected CHD prevalence in Birmingham and PCTs up to 2020 – Aged 65 – 74 ............................................................................... 199

Table D.6

Projected CHD prevalence in Birmingham and PCTs up to 2020 – aged 75 and above ...................................................................... 200

JSNA LTCs Final Version

xviii


Table D.7

Projected CHD prevalence in Birmingham and PCTs up to 2020 – White ethnic group ....................................................................... 201

Table D.8

Projected CHD prevalence in Birmingham and PCTs up to 2020 – Mixed race ................................................................................... 202

Table D.9

Projected CHD prevalence in Birmingham and PCTs up to 2020 – Black ethnic group ....................................................................... 203

Table D.10

Projected CHD prevalence in Birmingham and PCTs up to 2020 – Asian ethnic group ....................................................................... 204

Table D.11

Other Ethnic communities Projected CHD prevalence in Birmingham and PCTs up to 2020 ................................................................... 205

Table E.1

Projected population by gender and aged group, Birmingham and PCTs, 2010, 2015 and 2020 ........................................................ 206

Table F.1

Projected number of people with epilepsy by gender and age group, Birmingham and PCTs, 2010, 2015 and 2020 ............................. 208

Table G.1

Projected number of people with CKD (stage 3 to 5) by gender and age group (aged 18 and above), Birmingham and PCTs, 2010, 2015 and 2020 ..................................................................................... 211

Table H.1

Prevalence of top 20 co-morbidities with CHD ............................. 213

Table H.2

Prevalence rate (per 100,000) of top 20 co-morbidities with CHD 215

Table H.3

Prevalence rate (per 100,000) of top 20 co-morbidities with Diabetes ................................................................................................... 217

Table H.4

Prevalence rate (per 100,000) of top 20 co-morbidities with CKD 219

Table H.5

Prevalence rate (per 100,000) of top 20 co-morbidities with COPD ... ................................................................................................... 221

Table H.6

Prevalence rate (per 100,000) of top 20 co-morbidities with Asthma . ................................................................................................... 223

Table H.7

Prevalence rate (per 100,000) of top 20 co-morbidities with Epilepsy ................................................................................................... 225

Table H.8

Prevalence rate (per 100,000) of top 20 co-morbidities with Epilepsy + Learning Disabilities..................................................................... 227

Table I.1

Estimated number of people with diagnosed or undiagnosed diabetes, by type, sex and ten-year age groups, Birmingham, 2006 ................................................................................................... 229

Table I.2

Estimated number of people with diagnosed or undiagnosed diabetes, by type, sex and ten-year age groups, BEN PCT, 2006.... ................................................................................................... 230

Table I.3

Estimated number of people with diagnosed or undiagnosed diabetes, by type, sex and ten-year age groups, HoB tPCT, 2006 ... ................................................................................................... 231

Table I.4

Estimated number of people with diagnosed or undiagnosed diabetes, by type, sex and ten-year age groups, SB PCT, 2006 232

JSNA LTCs Final Version

xix


Glossary Acronym

Definition

APHO

Association of Public Health Observatories

BEN

Birmingham East and North

BHWP

Birmingham Health and Wellbeing Partnership

BME

Black and Minority Ethnicity

CHD

Coronary Hearth Disease

CKD

Chronic Kidney Disease

COPD

Chronic Obstructive Pulmonary Disease

CVD

Cardiovascular Disease

GHS

General Household Survey

GP

General Practice

GPRD

General Practice Research Database

HDL

High-Density Lipoprotein

HES

Hospital Episode Statistics

HOB

Heart of Birmingham

HSfE

Health Survey for England

ICD

International Classification of Diseases

IMD

Indices of Multiple Deprivation

JSNA

Joint Strategic Needs Assessment

LA

Local Authority

LLTI

Limiting Long Term Illness

LTC

Long Term Condition

NHS

National Health Service

NSTS

National Strategic Tracing Service

ONS

Office of National Statistics

PCT

Primary Care Trust

PHIT

Public Health Information Team

PSA

Public Service Agreement

JSNA LTCs Final Version

xx


QOF

Quality and Outcome Framework

SB

South Birmingham

SHA

Strategic Health Authority

SOA

Super Output Area

SUDEP

Sudden Unexpected Death in Epilepsy

SUS

Secondary Usage Service

T1DM

Type 1 Diabetes Mellitus

T2DM

Type 2 Diabetes Mellitus

tPCT

Teaching Primary Care Trust

WHO

World Health Organisation

JSNA LTCs Final Version

xxi


1. Introduction This study is part of the 2009 Joint Strategic Needs Assessment (JSNA) for Birmingham. The study aims to (i) investigate current disease prevalence and related risk factors for common long term conditions (LTCs) in Birmingham and the PCTs, and (ii) project future disease prevalence for strategic planning. This study is the first phase of the needs assessment for people with LTCs in Birmingham. The second phase of the assessment will be an evaluation of the current health and social services. These two phases together will create insights into the needs of the population and the gaps in the currently available services. These insights will form the basis for making recommendations to commissioners.

1.1. Definition of long term conditions Long term conditions (LTCs), such as diabetes, heart disease, and chronic obstructive pulmonary disease, are chronic illnesses that have a limiting impact on a person’s lifestyle. As defined in the Department of Health (DoH)’s guidance document ‘Raising the Profile of Long Term Conditions Care’ (DOH, 2007a), LTCs are conditions that cannot, at present, be cured, but can be controlled by medication and other therapies. The life of a person who gets a LTC will be changed forever – there is no return to ‘normal’. There are 15.4 million people living with a LTC in England. Numbers are expected to rise due to an ageing population and unhealthy lifestyle choices. Table 1.1 lists common LTCs as suggested by the Long Term Conditions Clinical Pathway Group at NHS West Midlands (NHS West Midlands, 2008). Table 1.1

Common long term conditions

Group

Conditions

Vascular

Coronary heart disease (CHD), diabetes, stroke, peripheral vascular disease, renal disease (CKD)

Respiratory

Chronic obstructive pulmonary disease (COPD), asthma, emphysema

Musculoskeletal and skin

Osteoarthritis, rheumatoid arthritis, psoriasis, eczema

Neurological

Multiple-sclerosis, cerebral palsy, epilepsy, Parkinson’s disease

Immune diseases and endocrine

Thyroid disorders, Lupus (SLE)

Gastro-intestinal diseases

Coeliac disease, inflammatory bowel disease, diverticulitis

Cancers

Breast cancer, colonic cancer, prostate cancer

Mental health

Depression, anxiety, learning difficulties

Unknown

Chronic fatigue syndrome

JSNA LTCs Final Version

1


LTCs cover a wide range of conditions. In this report, we have included as many of the LTCs listed in Table 1.1 as possible, depending on data availability. Alternative definitions for LTCs in general are given in 3.1.2. Definitions of individual conditions are given in disease-specific sections in Chapter 8 to Chapter 13.

1.2. The JSNA context The requirement for conducting regular JSNA was created by the Local Government and Public Involvement in Health Act (British Government 2007). It is based on the belief that the process of creating a JSNA will lead to stronger partnerships between communities, local government, and the National Health Service (NHS); and stronger partnerships will provide a firm foundation for commissioning that improves the provision of health and social care and reduces inequalities. As stated in the ‘Guidance on Joint Strategic Needs Assessment’ (DOH, 2007b), the focus of JSNA includes: •

Understanding the current and future needs for the population’s health and wellbeing, for both the short term (three to five years) to inform Local Area Agreements, and the longer term (five to ten years) to inform strategic planning.

Commissioning services and interventions that promote better health and wellbeing and reduce inequalities.

This prevalence study fits into the JSNA focus by investigating the current population suffering from LTCs in Birmingham and predicting future numbers of patients. Better understanding of the risk factors and current prevalence of LTCs means better understanding of the needs of people suffering from one or more LTCs. This study, together with the second phase of the needs assessment (i.e. service evaluation), will identify gaps between need and supply of services, thus informing the strategic planning to reduce inequalities.

1.3. The national and local policy context Improving care for people with a LTC is one of the biggest challenges facing health and social care organisations. Several policy documents have been published by the Department of Health (DoH) which set out current thinking for management of LTCs. ‘Supporting People with Long Term Conditions: An NHS and Social Care Model to support local innovation and integration’ was published in January 2005 (DOH, 2005). It describes a strategy for the management of people with LTCs. One of the key aspects of the model is a requirement for local health communities to identify all patients with LTCs within their area. In 2007, Lord Ara Darzi carried out the NHS Stage Review (Darzi, Lord 2008) and LTCs was one of his eight priorities. The national target relating to LTCs is to improve the health of people with long term conditions by (i) offering a personalised care plan for those most at risk; and (ii) improving care in primary care and community settings for people with long term conditions to the extent that emergency bed days will be reduced by 5% by 2008 from the 2003/04 baseline (DOH 2007c). In the West Midlands region, the strategy document ‘Our NHS, Our Future – NHS Next Stage Review’ was published by NHS West Midlands in April, 2008. It sets out a vision for the management of LTCs in the region, and it proposes an algebra of effective health care for LTC patients called POETIC (i.e. Patient and carer-centred, JSNA LTCs Final Version

2


Outcome focused, Evidence-based, Team-orientated, Integrated and Cost-effective by clinically governed). It also provides examples of good practice and local guides for the prevention and management of the most common LTCs. Understanding and identification of current and future prevalence of LTCs is also an important aspect of implementing these strategies. There is currently no city-wide strategy for managing LTCs in Birmingham. It is expected that this prevalence study, combined with the already planned evaluation of health and social care services for LTCs (i.e. second phase of the needs assessment), will inform the generation of a Birmingham city LTCs strategy.

1.4. Objectives of this study Objectives of this study are: •

To investigate the burden of LTCs in Birmingham in terms of use of health and social care services and premature deaths.

To provide an overview of local disease prevalence of all common LTCs.

To investigate the determinants of LTCs prevalence, in terms of demographic factors, deprivation and life style choices.

To project disease prevalence for a number of selected LTCs.

JSNA LTCs Final Version

3


2. Key findings This chapter sets out key findings in terms of (i) the impact of long term conditions (LTCs) in Birmingham; and (ii) the implications on prevention of LTCs and improvement of health.

2.1. Impact of LTCs in Birmingham The important LTCs locally are identified according to their impact on health and on health and social care services locally.

2.1.1.

Impact on health

LTCs account for about 70% of all premature death (i.e. death under 75 years old) in Birmingham.

The LTCs that have the greatest impact on health, as measured by size of contribution to premature death (and thus life expectancy) are CVD and cancer.

2.1.2.

Impact on health and social care services

People with LTCs are intensive users of health care (both primary and secondary care) and social care services locally.

They utilise 47% of all GP consultations, 35% of all practice nurse appointments, 35% of all hospital admissions and 45% of all hospital bed days in Birmingham.

The LTCs that have the most impact on health care services, measured in resource utilisation are: advanced CKD (18% of all hospital admissions), mental health conditions (20% of all hospital bed days), CVD (7% of all hospital bed days) and cancer (7% of all hospital admissions and 7% of all hospital bed days).

2.2. Prevention of LTCs and improvement of health This study sets out the extent to which prevention (or preventative management) of LTCs could improve health in the population and reduce dependency on health/social care services in Birmingham.

2.2.1.

Current status

The overall premature deaths (i.e. deaths under 75s) from LTCs in Birmingham have reduced.

1

From 1995/97 to 2005/07, the contribution (i.e. proportion) to premature deaths from LTCs has decreased from 71.1% to 66.7%; a reduction by 6%.

In particular, premature death rate1 of CVD has reduced by 40% from 1995/07 to 2005/07 (from 173.08 to 104.32 per 100,000); premature death

Directly standardised mortality rate (DSR) for under 75s

JSNA LTCs Final Version

4


rate from cancer has reduced by 14% in the same period (from 146.74 to 126.70 per 100,000) in Birmingham. Some LTCs have higher prevalence (as measured by QOF) than the national average or prevalence has increase in the recently years, possibly requiring more health and social care resources than necessary. •

High prevalence of diabetes in HoB tPCT (5.1%) and BEN PCT (4.3%); of COPD in SB PCT (1.6%) and advanced CKD (i.e. stage 5) in HoB tPCT (1,389 pmp) and BEN PCT (1,003 pmp).

Increased prevalence between 2004/05 - 2007/08 across Birmingham: hypertension (from 10.76% to 11.88%), cancer (from 0.41% to 0.89%), diabetes (from 3.88% to 4.36%), mental health conditions (from 0.67% to 0.90%) and chronic kidney disease2 (CKD, from 2.26% to 2.80%).

As to the co-morbidities of LTCs, hypertension, CHD, diabetes, asthma and mental illness have been identified as the most common LTCs that co-exist with other LTCs.

Age, ethnicity, deprivation, smoking and obesity are the main risk factors for LTCs in Birmingham as elsewhere in England. •

Birmingham has a relatively younger population in comparison with the national average, but this population will now age.

Ethnicity and social deprivation have also been identified as associated with most LTCs. These associations raise concerns locally as: (i) Birmingham has a large proportion of population of Black and Minority Ethnic (BME) group (33%). This population is likely to increase significantly; and combined with relatively high deprivation (half of its population in the most deprived quintile nationally).

The current local prevalence of smoking and obesity raises concerns: (i) Higher prevalence of obesity in adults is seen in BEN PCT (8.8%) and HoB tPCT (8.3%) than the national average (7.6%); (ii) Much higher prevalence of childhood obesity3 in Birmingham (23.1%) than England (15.4%); and (iii) Smoking prevalence in Birmingham (25.2%) is 15% higher than the national average (22.0%).

Hypertension and diabetes are clinical risk factors for most vascular diseases. Birmingham has higher prevalence of diabetes and severe hypertension, compared with the national average.

There are a number of issues that need to be addressed in order to develop the best strategy to tackle LTCs: •

2 3

Underreporting of QOF prevalence, especially in HoB tPCT area means that we may lack a clear understanding of the size of the problem. Underreporting could mean failure to identify conditions early when treatment is most costeffective.

From 2006/07 to 2007/08 Year six children

JSNA LTCs Final Version

5


2.2.2.

There is relatively high prevalence of diabetes and advanced CKD where lifestyle change in the patient can bring great benefit; the current picture suggests that work to reduce smoking and obesity is not proportionate to the size of the problem.

Looking into the future

A noticeable predicted change of the population in Birmingham is in the ethnic distribution. •

By 2026, more than half the city’s population will be from the BME group (52%). This trend indicates that attention is needed to those LTCs that are associated with BME group and services/interventions targeting lifestyle issues in certain ethnic groups are needed.

Prevalence of all the LTCs covered by this report are projected as likely to increase in 10 years’ time, either due to the change in population or the change in the prevalence of related risk factors.

Issues that need to be addressed to tackle LTCs: •

Improved sharing of primary care and social care data on individuals to enable accurate modelling.

Local surveys looking in greater detail at key LTCs, in particular diabetes and obesity.

An improved understanding of the contribution of mental health to the burden of LTCs.

JSNA LTCs Final Version

6


3. Methods This chapter describes the methods used in this study to achieve the four objectives set out in Section 1.3.

3.1. Definitions 3.1.1.

Prevalence

Prevalence is defined as ‘the number of instances of a given disease or medical condition, in a given population at a given time’ (Last 2001). In epidemiological studies, prevalence is a measure generally used for long-term illnesses as opposed to ‘incidence’ used for short-term illnesses, which measures ‘the number of new cases of a given disease or medical condition, in a given population at a give time’ (Last 2001). In this study, prevalence generally refers to annual prevalence defined as ‘the total number of persons in a defined population with the disease at any time during a year. It includes cases of the disease arising before but extending into or through the year, as well as those having their inception during the year’ (Last 2001). When ‘prevalence’ of a disease in a defined population is related to the number of individuals in that population, we obtain the annual prevalence rate, which is defined as ‘the total number of cases of disease in a given population during a year, divided by the number of individuals in the population’ (Last 2001). It is common to study prevalence with reference to specific groups within the population, resulting in specific prevalence rates. The most commonly used specific prevalence rates in this study are prevalence rates for males/females, for different age groups, for different ethnic groups, for different socio-economic groups, and for groups resident in different areas in Birmingham.

3.1.2.

Alternative definitions for LTCs in general

As the prevalence data on LTCs in this study were collected from different information sources, several alternative definitions for ‘LTCs in general’ were used in this study, depending on the data sources. For data collected from the Quality and Outcome Framework (QOF) database, LTCs in general included conditions as: CHD, heart failure, stroke and transient ischaemic attack, hypertension, diabetes, COPD, Epilepsy, Cancer, mental health, asthma, dementia and chronic kidney disease. For data collected from the death registrations and hospital episode statistics (HES), LTCs in general included all the conditions listed in Table 1.1. Details of the ICD-9 and ICD-10 codes used for the conditions can be found in Table A.1 in Appendix A. For data collected from General Household Survey (GHS) and the Health Survey for England (HSfE), self reported long standing illnesses and disability was used as a proxy for LTCs in general. For data collected from the census, self reported limiting long term illness (LLTI) was used. This variable records whether a person perceives that they have a limiting long-term illness, health problem or disability which limits their daily activities or the JSNA LTCs Final Version

7


work they can do, including problems that are due to old age. A study on interpreting self reported limiting long term illness (Cohan.G, Forbes.J, Garraway.M 1995) shows that rates of limiting long term illness were much higher than reported in the Census. Scores on general and physical health scales had strong associations with it. Reported prevalence of many common illnesses was between two and three times higher among those with limiting long term illness.

3.2. Data sources 3.2.1.

Selection of data sources

This prevalence study is based on currently available health data from routinely collected data sources (e.g. Hospital Episode Statistics) and national surveys (e.g. Health Survey for England) rather than from a local prevalence survey study. All the available data sources were reviewed and appropriate data sources were selected based on the criteria below: • suitability of purpose • accessibility • reliability of the data source • timeliness of data Table B.1 in Appendix B provides an appraisal of all the data sources used in this study.

3.2.2.

Different sources of information on prevalence

Five different types of sources of information on disease prevalence were used in this study: •

Prevalence from population – based studies (e.g. HSfE) that make use of objective techniques in terms of diagnosis, e.g. COPD using spirometric measurements

Prevalence from population – based studies (e.g. GHS) on self – reported illnesses

Prevalence from GP registers (e.g. QOF)

Prevalence from hospital data (e.g. HES data) and

Prevalence from various research studies.

3.3. Selection of specific LTCs Rather than studying prevalence of all LTCs, it was decided that in this needs assessment we would focus on a smaller number of diseases based on the following criteria: •

Burden from the disease on local health and social services

Current state of knowledge of local prevalence of the disease and availability of a needs assessment

JSNA LTCs Final Version

8


The selection of the conditions was carried out based on the following three steps: 1. Identifying conditions that cause the most premature deaths (i.e. death under 75 years of age) in Birmingham 2. Reviewing existing needs assessments for specific diseases 3. Discussing with local commissioners and public health experts on their views regarding conditions that would more urgently require a needs assessment. Several circulatory conditions, cancers and respiratory conditions were identified in step 1. However, cancers and stroke were excluded from the list in step 2, as they had already been carried out by other stakeholders of the partnership. Chronic kidney disease (CKD) and epilepsy were suggested in step 3. Six specific conditions were finally identified, namely: Coronary Heart Disease (CHD), diabetes, Chronic Obstructive Pulmonary Disease (COPD), epilepsy, chronic kidney disease and asthma. Individual studies on each of the condition are described in Chapter 8 to Chapter 13 of this report.

3.4. Data analysis All statistical analysis in this study was carried out using SPSS version 17. Two data manipulating methods were used in the analysis, as described below.

3.4.1.

Mapping prevalence in GP catchments to wards

Prevalence data collected from QOF is based on GP catchments area. The GP catchments areas do not always have clear boundaries. However, for the purpose of the JSNA, the prevalence needs to be broken down by government administrative areas (such as constituency and ward) for city wide planning. To map the prevalence in GP catchments area to wards, the following steps were taken: 1. Taking postcodes of each GP’s registered population from the National Strategic Tracing Service (NSTS) database 2. Mapping the postcodes into wards 3. Calculating the number of people from each GP in each ward 4. Applying the prevalence rate for each GP in a ward to the GP population in that ward 5. Calculating the prevalence for each ward by adding up the prevalence from each GP in the ward as calculated in Step 4. An assumption was made when using this method that prevalence rate of each disease is evenly distributed within each GP catchments area. This assumption might not be applicable to some GP catchments areas where high prevalence was seen in certain sub-areas of the overall GP catchments area. However, as individual patient’s level primary care data was not available when the report was written, this method was used as an alternative.

JSNA LTCs Final Version

9


3.4.2.

Calculating the number of people with multiple LTCs

The number of people with multiple LTCs was calculated based on the secondary care data (i.e. hospital episodes statistics (HES) data). HES records up to 13 diagnoses for each hospital episode (i.e. one primary diagnosis and 12 secondary diagnoses). Whenever an episode had 2 or more LTCs (as shown in Table 1.1) as diagnoses, the patient of the episode was counted as a person with multiple LTCs. The HES data for 2006 was used to calculate the current prevalence of people with multiple LTCs. An assumption was made when using this method that all people with LTCs were admitted to hospitals at least once over the 12 months period (April 2006 to March 2007). This assumption, however, indicated the figures calculated tended to be underestimating as those people with LTCs who were not admitted to hospitals were not counted in.

3.5. Predicting disease prevalence Predicting future prevalence of LTCs is one of the objectives of this study. Three main methods were used to predict disease prevalence, as described below.

3.5.1.

Use of currently available prevalence models

There are a number of predicting models for disease prevalence in the UK developed by the Association of Public Health Observatories (APHO) (http://www.apho.org.uk/). Models are currently available for the following diseases: cancer, chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), coronary heart disease (CHD), diabetes, hypertension, mental illness and stroke. As suggested in the JSNA Guidance (DOH. 2007b), these models can be used to predict local disease prevalence. The APHO models are based on nation-wide study usually HSfE and come up with nation-wide prevalence. Risk factors are identified (commonly age, gender, deprivation, ethnicity and for some diseases smoking status) and the distribution of these risk factors in any population used to predict prevalence in these populations. The APHO models for CKD, COPD, CHD and diabetes were tested and used in this study. The following two steps were taken to test the models: •

Comparing the prevalence predicted by the model with QOF prevalence

•

Validating the accuracy of Birmingham data that were used as predictors in the models, such as ethnicity and smoking rates

One disadvantage of this approach is that Birmingham itself, and particularly some wards are markedly different from the national average, in terms of both disease prevalence and prevalence of certain risk factors. Consequently, the prevalence predicted from these models is likely to have wide confidence intervals.

3.5.2.

Directly applying prevalence rates from studies done elsewhere

When an appropriate risk factor prevalence model was not available for certain diseases, a literature review was carried out on prevalence of disease in areas comparable to Birmingham. For epilepsy, a study done by the Office of National JSNA LTCs Final Version

10


Statistics and University College London (Purcell.B, et al. 2002) was identified and the patterns of epilepsy prevalence suggested by this study were then applied to the ONS population projection to predict the future prevalence of epilepsy among specific population groups in Birmingham.

JSNA LTCs Final Version

11


4. Local context Health inequalities are driven by inequalities in society. Health is affected by many different factors, such as lifestyle, material wealth, job security, housing conditions, and the health services. This chapter describes these factors in Birmingham to provide local context for prevalence of LTCs.

4.1. Age and gender distribution 4.1.1.

Current population structure

According to the mid-year population estimates from the Office of National Statistics (ONS) in 2007, Birmingham has a population of just over a million (1,010,200). Approximately 49% (496,200) are male and 51% are female (514,000). The population pyramid (Figure 4.1) below shows the age and gender distributions. Figure 4.1

Population by age group and gender, Birmingham and England, 2007

90+

England

85-89

Males

80-84

Females

75-79 70-74 65-69 60-64

Age group

55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 5

4

3

2

1

0

1

2

3

4

5

Percentage out of total population

Data source: ONS 2007 mid year population estimates Figure 4.1 shows: •

Children under school leaving age (i.e. age 0 - 19) represent 28.1% (283,600) of the Birmingham population. Persons of retirement age (age 65+) account for 13.5% (136,700).

•

Compared with the age structure of England, Birmingham has a larger proportion of children and young people, particularly in the 20-24 age band; and a smaller proportion of persons of older age groups.

JSNA LTCs Final Version

12


4.1.2.

Projected population structure

Figure 4.2 shows the projected population by age group and gender in Birmingham for the year 2010 and 2020, based on ONS 2006 projection. It shows that in the next 10 years, •

Increase in population will be seen in young age groups (aged 0-14), the thirties (aged 30-39) and the fifties (aged 50-59) groups for both males and females

Decrease in population will be seen in the late teens, the early twenties group (aged 15-19) and the forties group (aged 40-49)

Details of the population projection by age group and gender for the three PCTs in Birmingham are shown in Table E.1 in Appendix E. Figure 4.2

Population projection by sex and age group, Birmingham, 2010 and 2020

85+ 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 60

40

20

0

20

40

60

population (thousand) Male 2010

Male 2020

Female 2010

Female 2020

Data source: ONS population projection

4.2. Ethnicity 4.2.1.

Current ethnic distribution

Table 4.1 shows the ethnic distribution in the Birmingham population, compared with West Midlands and England. •

About a third (32.7%) of the population in Birmingham is of non-white ethnicity (i.e. Black and Minority Ethnicity (BME) group). A further break down shows that within the BME group, Pakistanis represents 11%, Indian 6% and Black Caribbean 4.5%.

JSNA LTCs Final Version

13


The proportion of BME in Birmingham (32.7%) is approx 1.5 times higher than West Midlands (13.5%) and approx 3 times the average across England (11.3%).

Table 4.1

Ethnicity groups for Birmingham, West Midlands and England, 2006 Birmingham

Ethnic groups

%

West Midlands %

N*

England %

N*

N*

White

67.3

667.0

86.5

5,366.7

88.7

45,018.1

Asian or Asian British

20.7

207.9

8.2

441.2

5.5

2,786.6

Black or Black British

6.7

67.0

2.4

130.9

2.8

1,403.0

Mixed

3.2

31.8

1.7

91.6

1.6

829.5

Chinese or other

2.3

22.9

1.1

59.6

1.4

725.7

Total

100

1,106.5

100

5,366.7

100

50,762.9

*Thousand Data source: ONS population estimates by ethnic group mid 2006

4.2.2.

Projected ethnic distribution

Table 4.2 shows projected population in Birmingham by ethnic group up to 2026. The projection was done by the Cathie Marsh Centre for Census and Survey Research at the University of Manchester, on behalf of the Birmingham City Council. The projection shows that: •

The proportion of White population will reduce even further and by 2026, less than half (48%) of Birmingham’s population will be White.

The proportion of Caribbean population will reduce slightly from 5% in 2011 to 4% in 2026

The proportion of African population will increase from 2% in 2011 to 4% in 2026

The proportion of Indian population will stay consistent at about 6%

The proportion of Pakistani population will increase from 15% in 2011 to 21% in 2026

The proportion of Bangladeshi population will increase slightly from 3% to 4%

The proportion of Other ethnic group will increase from 8% in 2011 to 12% in 2026

Details of the projected population by ethnic group and age can be found in another publication of the JSNA: The demographic profiles.

JSNA LTCs Final Version

14


Table 4.2

Projections of population in Birmingham by ethnic group, 2011, 2016, 2021 and 2026 (Simpson 2007) Year 2011

Ethnic groups

%

2016 N*

%

2021 N*

%

2026 N*

%

N*

61

623.6

56

592.1

52

560.6

48

527.7

Caribbean

5

47.1

4

45.5

4

43.5

4

41.4

African

2

18.6

3

26.7

3

35.7

4

45.8

Indian

6

61.2

6

62.4

6

63.0

6

63.0

15

155.3

17

180.9

19

206.5

21

232.4

Bangladeshi

3

32.1

4

37.5

4

42.7

4

47.8

Chinese

1

9.0

1

10.6

1

12.1

1

13.5

Other

8

82.3

9

100.0

11

117.5

12

133.8

Total

100

1,029.1

100

1,055.6

100

1,081.5

100

1,105.3

White

Pakistani

*Thousand

4.3. Deprivation According to Index of Multiple Deprivations (IMD) 2007 published by ONS, Birmingham is one of the most deprived Local Authorities nationally. •

Birmingham is ranked as the 10th most deprived Local Authority in England (out of 354 Local Authorities), in terms of overall IMD score (i.e. the higher the score the more deprived).

Birmingham is also ranked as THE MOST deprived Local Authority nationally, in terms of income and employment.

Table 4.3 shows the distribution of population in Birmingham and the three PCTs by deprivation quintile (20%) nationally, based on the Super Output Area (SOA) level IMD score 2007 and the ONS SOA level population estimate 2007. It shows that •

More than half (56%; 568,576) of Birmingham’s population is in the most deprived quintile SOAs (i.e. 20%) nationally. Approx one in five (21%; 207,417) people in Birmingham live in the 2nd most deprived quintile; 16% (157,638) live in the 3rd quintile; one in twenty (5%; 53,226) live in the 2nd quintile and only about one in fifty (2%, 23,390) live in the least deprived (1st) quintile.

More than 90% (92.4%) of Birmingham’s population is in the 3rd, 4th and 5th quintile.

JSNA LTCs Final Version

15


BEN PCT has the majority (60%) of its population living in the most deprived quintile nationally. It also has the most diverse population locally in terms of deprivation, as it has the largest proportion (as compared to the other two PCTs) of population in the 2nd quintile (9%) and 1st quintile (5%).

HOB tPCT has the largest proportion of population (75%, 200,796) living in the most deprived quintile nationally. All of HOB PCTs’ population are in the 3rd, 4th and 5th quintiles.

SB PCT has the smallest proportion of population (37%) in the 5th quintile locally. However, approx 95% of its population are in the 3rd, 4th and 5th quintiles.

Table 4.3

Population by SOA level IMD quintile, Birmingham and the PCTs, 2007 quintile (20%)

BEN %

Most Deprived

Least Deprived

HOB n

%

SB %

n

Birmingham n

%

n

5

60.45

244558

74.58

200796

36.63

123222

56.28

568576

4

13.55

54823

19.94

53699

29.40

98895

20.53

207417

3

11.57

46795

5.48

14754

28.56

96089

15.60

157638

2

9.10

36818

0.00

0

4.88

16408

5.27

53226

1

5.33

21577

0.00

0

0.54

1813

2.32

23390

Data source: SOA IMD score and ranking – Indices of Multiple Deprivations 2007 SOA population – ONS mid year population estimate 2007 Deprivation quintiles – PHIT calculation

4.4. Employment Table 4.4 shows key figures for work deprivation in Birmingham, West Midlands and England. In general, Birmingham is more deprived in terms of employment. The unemployment rate in Birmingham is nearly two thirds higher (63.6%) than that in England. The proportion of job seekers in Birmingham is three times as that in England.

JSNA LTCs Final Version

16


Table 4.4

Key figures for Work Deprivation in Birmingham, West Midlands and England, 2006 - 2007 Birmingham

West Midlands

Economic Activity Rate (Apr 06 – Mar 07)

68.9%

77.3%

78.6%

Employment Rate (Apr 06 – Mar 07)

62.2%

73%

74.3%

9%

5.6%

5.5%

22%

16%

14%

Job seekers (Aug 06)

6%

3%

2%

Incapacity benefits (Aug 06)

9%

7%

7%

Unemployment Rate (Apr 06 – Mar 07) People of working age claiming a key benefit (Aug 06)

England

Data source: ONS, Neighbourhood Statistics

4.5. Lifestyle Table 4.5 provides a summary of life style indicators in Birmingham, in comparison with West Midlands and England. The data presented are from two national surveys: Healthy Survey for England by the NHS Information Centre and Active People Survey by Sport England. Table 4.5

Key figures for life style in Birmingham, West Midlands and England, 2003-2005 and 2007-2008 Year

Birmingham

West Midlands

England

Adults who smoke

2003/5

24.9%

24.0%

24.1%

Binge drinking adults*

2003/5

17.8%

17.9%

18.0%

Healthy eating adults**

2003/5

25.1%

25.1%

26.3%

Physically active adults***

2007/8

16.9%

19.1%

21.3%

Obese adults****

2003/5

23.4%

26.5%

23.6%

* ** *** ****

Binge drinking: men were defined as having indulged in binge drinking if they had consumed 8 or more units of alcohol on the heaviest drinking day in the previous seven days; for women the cut-off was 6 or more units of alcohol. Healthy eating: five or more portions of fruit and vegetables on the previous day Physically active: 30 minutes of moderate intensity sport and active recreation on at least three days a week basis. Obese: BMI > 30

Data source: Physically active adults: Active People Survey, Sport England All other indicators: Synthetic estimates of healthy life styles, NHS Information Centre

JSNA LTCs Final Version

17


Figures in Table 4.5 show that: •

In terms of proportion of people who smoke, binge drink and are obese, Birmingham is not much different from the national average (i.e. difference within 1 percentage point).

•

Compared with the national average, smaller proportion of people living in Birmingham eat healthily (1.2 percentage points lower) and physically active (4.4 percentage points lower).

4.5.1.

Life style patterns

Table 4.6 summarizes the patterns in population of five life style indicators: smoking, alcohol drinking, diet, physical activity and obesity. The summary is based on data from a local smoking prevalence survey for smoking and HSfE for all the other life style indicators. Therefore, smoking is the local pattern while the other indictors are national patterns using the national patterns as proxies. Table 4.6

Life style patterns in population Age

Gender

Ethnicity

Socio-economic

Smoking

The tendency to smoke decreases with age.

More men than women smoke

Overall in Birmingham more whites smoke than any other ethnic group.

The latest prevalence report we have shows that the poorer the group you belong to the more likely you are to smoke

Alcohol drinking

Consumption of more than the maximum decreases with age, this trend is consistent since 1998

Trend data shows that men are more likely to consume more than the recommended dose than women particularly in the 65+ age group

Excessive drinking is fairly uncommon amongst ethnic groups with the possible exception of the Irish and Black Caribbean communities

Evidence suggests that the higher the socioeconomic group the higher the tendency to take a drink and drink to excess.

Diet

NA

NA

Whites have a higher calorific intake than any other ethnic group. Consistent with this their intakes of saturated fats and salts are also higher, however those in the Asian and Black Caribbean communities

Those living in the poorest quintiles consume food with higher calorific value than their counterparts in the higher quintiles. However, the saturated fat and salt levels amongst these individuals are

JSNA LTCs Final Version

18


Table 4.6

Life style patterns in population Age

Gender

Ethnicity

Socio-economic

whilst consuming less do have high intakes of saturated fats.

also higher – indicating that their food is more unhealthy

Physically activity

There is a propensity to exercise less as we get older, with over a third of all adults exercising up to 45 but the % diminishes to around 10% by mid sixties.

More men than women exercise at all levels.

Whilst percentages are low; more people from the black and Irish communities take regular exercise than any other groups. Indeed, black females exercise more than the norm.

Fewer people in the lower quintiles take physical activity than their wealthier counterparts.

Obesity

A tendency to be overweight or obese increases with age

Overall men are slightly more prone to obesity or being overweight with age. However, in 75+ the percentages are virtually equal

More people of black original are either obese or overweight than their other ethnic counterparts. The numbers are even higher in females of both black groups.

People in the higher quintiles are more inclined to have a high BMI i.e. over 25; than people in the lower quintiles.

JSNA LTCs Final Version

19


5. Burden on local health and social care from LTCs Key messages for commissioners Key findings: • People with LTCs are intensive users of health care (both primary and secondary care) and social care services • People with mental health conditions, cancer, stroke, multiple sclerosis, cerebral palsy, and arthritis are high users of social care services • People with mental health conditions, CVD and CKD are high users of secondary care services • LTCs account for about 70% of all premature death (i.e. death under 75 years old) in Birmingham; most of the deaths are caused by cancer and CVD. Issues raised from the study: • Local social care services data cannot identify service users with LTCs • Data on the usage of primary care services (e.g. number of GP appointments) are not available • The national target of reducing emergency bed days by 5% in 2008 (from the 2003/2004 baseline) remains challenging for Birmingham. People with LTCs are the most intensive users of the most expensive health and social care services (DOH. 2007a). In addition, many LTCs (e.g. CVD, respiratory diseases and cancer) lead to premature death (i.e. death under the age of 75), which is accountable for large costs to the healthcare services. This chapter investigates the burden on local health and social care services from LTCs. Four areas are investigated into: (i) use of community (social) care services, (ii) use of primary care services, (iii) use of secondary care services and (iv) premature deaths from LTCs.

5.1. Use of community care services People with LTCs are high users of social care and community services (DOH. 2007). DH nationally prescribed community matrons with local targets for Very High Intensive Users (of hospital inpatient care), as a solution to avoid inpatient care through earlier intervention, longer term packages of care on discharge (readmissions were high) and better coordination of services that would maintain people at home. This data was nationally reported via the SHA to the DH in a quarterly basis. Risk prediction tools such as PARR++ were designed to identify those people, as in West Midlands. From a social care perspective, earlier admissions to residential care could be avoided if earlier intervention was in place and a study in Hants showed that intense health input and rehab as soon as people suffered stroke, did result in less health and social care needs and therefore costs when discharged from hospital. A written description of the underlying health condition of the service user is recorded on the internal social care ‘carefirst’ database but this is not expressed consistently or in a form that can be interrogated easily. A system is being developed to collect this information so it can inform service design and partnership/commissioning strategies. Preliminary results from the first quarter April-July 2009 on new referrals show that stroke, multiple sclerosis, cerebral palsy, and arthritis are the predominant health conditions. A range of other health conditions are found in the remaining new JSNA LTCs Final Version

20


referrals. Further work will be done to tighten the definition of each health category to maximize its usefulness. Increasingly the physically disabled adult group with substantial or critical needs, will either be cared for in a residential or nursing care setting or purchase community based care with personalised budgets. These two very distinct pathways pose additional organisational, risk management and market development challenges. The ratio of younger adults (18-64 yrs) to older adults (over 65 yr) receiving nursing or residential care have become more similar over time and are approximately 3 younger adults to 37-38 older adults in these institutions. Community based care has a different profile and this gap is widening over time. In the last 2 years there were 3 younger adults (18-64 yr) to about 10 older adults (over 65 yrs). Delayed transfers of care pose a key challenge in terms of cost of care, and a lack of appropriate provision particularly in relation to appropriate housing. Figure 5.1 shows the use of community (social) care services by people with LTCs by condition and type of services in England, 2005/06. It shows that: •

People with mental health conditions are particularly high users of these services, being twice as likely to have used local social care services in the last six months and almost three times as likely to have used community nurse services.

•

Those with other LTCs are also more intensive users of services; for example, those with cancer, muscular problems and diabetes are all more likely to have used community nurse services.

Figure 5.1

Use of community (social) care services by people with LTCs, England, 2005/06 (DOH, 2007a)

Data source: Usage and Attitudes Survey 2005/06 for England

JSNA LTCs Final Version

21


5.2. Use of primary care services People with LTCs are high users of primary care services. Figure 5.2 shows the proportion of usage of primary care services (i.e. GP consultations and practice nurse appointments) from people with and without LTCs in West Midlands, based on the General Household Survey (GHS) 2006. It shows that in 2006 people with LTCs used disproportionately more primary care services than people without a LTC: •

37.7% (661) of all people participated in the survey (1,751) reported that they suffered from a LTC

•

This group accounted for 53.4% (150) of all GP appointments and 64.9% (85) of all practice nurse appointments that were reported to had been attended during the two weeks prior the survey

When this report was written, data on the usage of primary care services in Birmingham were not available. Figure 5.2

Use of primary care services by people with LTCs, West Midlands, 2006

Percentage of population/ percentage of service used

100%

35.1%

80%

46.6% 62.3%

60%

40% 64.9% 53.4% 20%

37.7%

0% Proportion of LTCs in the sample

GP consultations

LTC

Practice nurse appointments

No LTC

Data source: General Household Survey 2006

5.3. Use of secondary care services The national target for managing LTCs is to reduce the use of secondary care services by supporting people with LTCs via primary and community care. In addition, increasing self care and level of independence are key outcomes required of any LTC strategy. This section looks first at secondary care services and assesses the local performance against the national target. It then investigates the use of secondary care services from people with LTCs, in terms of hospital admissions and bed days. All data presented in this part are from the Secondary Usage Service (SUS) data for the years 2001/02 to 2005/06, and Hospital Episode Statistics (HES) data for the year 2006/07. Due to data quality concerns, SUS data for the year 2007/08 are not reported.

JSNA LTCs Final Version

22


5.3.1.

Performance against the national target

The national target for managing LTCs is to reduce dependency and is measured as reduction of emergency bed days by 5% by 2008 from the 2003/04 baseline. The related national indicator is NI 174: Emergency Bed Days (Department for Communities and Local Government 2008). Figure 5.3 shows the trend of age standardised rates of emergency bed days (per 100,000 population) for Birmingham from year 2002/03 (i.e. April 2002 – March 2003) to 2006/07, against the PSA trajectory. It shows that: •

From 2003/04 to 2006/07, the rate of emergency bed days in Birmingham had increased by 8.5% (4,642 per 100,000 population).

The latest year’s (2006/07) performance was at 59,564 per 100,000 population. This was 12.7% higher than the trajectory (52,850 per 100,000 population).

The rate increased significantly by 9.7% from 2002/03 to 2003/04 (from 50,059 to 54,922); then continued to increase at a smoother pace (at approximately 2.7% increase annually) and reached the peak in 2006/07 (59,564 per 100,000 population).

The 5% reduction target will remain challenging if the current trend continues.

Age standardised rates, per 100,000 population

Figure 5.3

Emergency bed days rates against the national target, Birmingham, 2002/03 – 2006/07

65000

60000

55000

50000

45000 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007 2007-2008 baseline year

Birmingham

Year

target year (5% reduction)

National target trajectory

Data source: Secondary usage service (SUS)

5.3.2.

Hospital admissions

Figure 5.4 shows proportion of hospital admissions from common LTCs (based on the primary diagnosis) in Birmingham, breaking down by PCTs, from in-patient year 2001/02 (i.e. April to March) to 2006/07. It shows that:

JSNA LTCs Final Version

23


More than one in every three hospital admissions (35.0%) was from LTCs in the year 2006/07.

The proportion of admissions from LTCs had increased continuously from 23.9% in 2001/02 to 35.0% in 2006/07, which was a 46.4% increase in proportion.

For South Birmingham PCT (SB PCT), the proportion had increased from 8.7% to 10.1% (16.1% increase in proportion)

For Heart of Birmingham tPCT (HoB tPCT), the proportion had increased from 6.7% to 7.8% (16.5% increase in proportion)

For Birmingham East and North PCT (BEN PCT), the proportion had increased from 8.5% to 17.1% (more than doubled in proportion).

The noticeable increase of hospital admissions from LTCs (in term of proportion) in BEN PCT from 2003/04 to 2004/05 needed further investigation. As the data presented here were from the SUS system, which was an un-cleaned version of HES, the increase could be caused by data quality rather than reflecting the truth. These figures were decided to be revisited once all the historical HES data were available to the PHIT team. Figure 5.4

Percentage of hospital admissions from common LTCs* (as the primary diagnosis), Birmingham and PCTs, 2001/02 to 2006/07

Percentage of all hospital admissions

100% 90% 80% 70%

67.3%

66.3%

65.0%

15.1%

15.4%

17.1%

6.1%

6.8%

7.3%

7.8%

9.0%

9.6%

10.7%

11.0%

10.1%

2002/2003

2003/2004

2004/2005

2005/2006

2006/2007

76.1%

74.9%

75.1%

20%

8.5%

8.9%

9.2%

10%

6.7%

7.2%

8.7% 2001/2002

60% 50% 40% 30%

0%

Inpatient year LTCs - SB

LTCS - HoB

LTCs - BEN

Non - LTCs

Data source: year 2001/02 to 2005/06 – Secondary Usage Service (SUS) year 2006/07 – Hospital Episode Statistics (HES) *common LTCs as defined in Appendix A

Table 5.1 shows the number of hospital admissions by common LTCs (based on the primary diagnosis) and the proportion out of all hospital admissions. It shows that in the year 2006/07:

JSNA LTCs Final Version

24


Chronic kidney failure (i.e. CKD stage 5) was by far the top LTC that accounted for nearly one in every five (18.4%) hospital admissions in Birmingham, followed by cancers (6.9%)

For SB PCT, higher proportion of hospital admissions was seen from Osteoarthritis (2.3%), mental illnesses (1.7%) and diabetes (0.9%), compared with the Birmingham distribution

For HOB tPCT, higher proportion of hospital admissions was seen from asthma (1.0%), compared with the Birmingham distribution

For BEN PCT: higher proportion of hospital admissions was seen from chronic renal failure (22.1%), compared with the Birmingham distribution.

Table 5.1

Number of hospital admissions by common LTCs (as the primary diagnosis) and percentage out of all hospital admissions, Birmingham PCTs, 2006/07 SB PCT

HOB tPCT

BEN PCT

%

%

Birmingham

Conditions

%

Chronic renal failure (CKD stage 5)

15.9

13970

14.8

11107

22.1

29359

18.4

54436

Cancers

7.3

6397

6.5

4858

6.9

9136

6.9

20391

CHD

1.5

1328

1.8

1315

1.7

2195

1.6

4838

Osteoarthritis

2.3

2020

1.1

851

1.3

1744

1.6

4615

Mental illnesses

1.7

1471

1.2

917

1.1

1420

1.3

3808

COPD

0.8

730

0.6

470

0.8

1090

0.8

2290

Asthma

0.6

548

1.0

782

0.6

812

0.7

2142

Diabetes mellitus

0.9

751

0.5

402

0.5

719

0.6

1872

Stroke

0.7

623

0.6

418

0.5

721

0.6

1762

Heart failure

0.4

357

0.6

455

0.5

641

0.5

1453

Diverticulitis

0.5

467

0.2

151

0.4

579

0.4

1197

Epilepsy

0.4

325

0.4

268

0.3

411

0.3

1004

Other LTCs

1.1

971

1.5

1141

1.3

1756

1.3

3868

All LTCs*

34.0

29958

30.9

23135

38.0

50583

35.0

103676

All hospital admissions

100

88118

100

74840

100

132968

100

295926

n

n

n

%

n

Data source: Hospital Episodes Statistics (HES); * all LTCs as defined in Appendix A

It is worth noticing that all hospital admissions data reported in this section are only based on the primary diagnosis (i.e. primary cause of hospital admission). As some JSNA LTCs Final Version

25


LTCs (e.g. diabetes) have many other medical complications, the number of hospital admissions that involve a LTC as a secondary diagnosis of the admission should be much bigger. An example is that as stated by the 2009 national audit on diabetes about 20% of all hospital inpatients have diabetes in the UK.

5.3.3.

Hospital bed days

Figure 5.5 shows percentage of hospital bed days from common LTCs (based on the primary diagnosis) in Birmingham and the PCTs. It shows that: •

Approximately 45.4% of all hospital bed days was for LTCs in 2006/07.

The proportion of bed days from LTCs varied over the years (from 2001/02 to 2006/07) from about 35% to 45%.

For SB PCT, the proportion varied from approx 9% to 16%

For HoB tPCT, the proportion varied from approx 7% to 11%

For BEN PCT, the proportion varied from approx 11% to 18%.

The noticeable higher proportion of bed days from LTCs in the year 2006/07 could be explained by the different data sources used. The 2006/07 figure was based on the HES data, while figures for the rest years were based on SUS data. As the HES data was the cleaned version of SUS, the 2006/07 figures were considered as more accurate. These figures were decided to be revisited when the historical HES data were available to the PHIT team. Figure 5.5

Percentage of hospital bed days from common LTCs* (as the primary diagnosis), Birmingham and PCTs 2001/02 to 2006/07

Percentage of all hospital be days

100% 90% 80% 70%

64.6%

55.6% 69.9%

70.5%

65.6%

68.7%

60% 50% 40% 30% 20% 10%

17.7% 12.4% 7.9% 15.1%

0% 2001/2002

11.8% 13.8%

12.7%

7.2%

7.1%

9.1%

9.7%

2002/2003

2003/2004

11.1%

11.0%

7.6%

7.6%

15.0%

12.6%

15.8%

2004/2005

2005/2006

2006/2007

Inpatient year LTCs - SB

LTCS - HoB

LTCs - BEN

Non - LTCs

Data source: year 2001/02 to 2005/06 – Secondary Usage Service (SUS); year 2006/07 – Hospital Episode Statistics *common LTCs as defined in Appendix A

JSNA LTCs Final Version

26


Table 5.2 shows the number of hospital bed days from patients with common LTCs (as primary diagnosis) and percentage out of all hospital bed days for Birmingham and the PCTs in the year 2006/07. Table 5.2

Number of hospital bed days from common LTCs (as primary diagnosis) and percentage out of all hospital bed days, Birmingham PCTs, 2006/07 SB PCT

HOB tPCT

BEN PCT %

Birmingham

Conditions

%

n

%

Mental Illness

20.2

74803

21.3

56707

19.7

84306

20.3

215816

Cancer

7.8

28953

6.5

17295

6.2

26433

6.8

72681

Stroke

5.3

19507

4.5

11915

4.8

20368

4.9

51790

CHD

2.3

8401

2.2

5812

2.8

12083

2.5

26296

Osteoarthritis

2.8

10537

1.6

4370

2.3

9689

2.3

24596

COPD

1.8

6727

1.3

3592

2.2

9583

1.9

19902

Heart failure

1.5

5619

2.1

5557

1.9

7908

1.8

19084

Diabetes mellitus

0.6

2106

0.7

1873

0.4

1653

0.5

5632

Asthma

0.4

1548

0.7

1943

0.5

2026

0.5

5517

Epilepsy

0.4

1578

0.3

896

0.4

1856

0.4

4330

Chronic renal failure (CKD stage 5)

0.3

1003

0.3

860

0.6

2448

0.4

4311

Other LTCs

1.5

5609

1.9

5020

1.7

7288

1.7

17917

All LTCs*

45.3

168028

44.0

117308

44.2

188876

44.5

474212

All hospital bed days

100

371146

100

266484

100

427112

100

1064742

n

n

%

n

Data source: Hospital Episodes Statistics (HES) *all LTCs as defined in Appendix A

Figures in Table 5.2 show that in 2006/07 •

Mental illnesses were by far the top LTC that accounted for more one in every five (20.3%) hospital bed days in Birmingham

Cancers (6.8%), Stroke (4.9%), CHD (2.5%) and osteoarthritis (2.3%) were also among the top five LTCs that were accountable for hospital bed days in Birmingham

For SB PCT, higher proportion of hospital bed days was seen from cancers (7.8%) and osteoarthritis (2.8%), compared with the Birmingham distribution

JSNA LTCs Final Version

27


For HOB tPCT, higher proportion of hospital bed days was seen from mental illnesses (21.3%) and asthma (0.7%) but lower proportion from COPD (1.3%), compared with the Birmingham distribution

For BEN PCT: higher proportion of hospital bed days was seen from CHD (2.8%), COPD (2.2%) and chronic renal failure (0.6%), compared with the Birmingham distribution.

It is worth noticing that all the usage data on secondary care reported in Section 5.3 are counted only based on the primary diagnosis of the hospital episode. As most LTCs have complications of non-LTCs it is worth looking into the hospital admissions and bed days from LTCs as secondary diagnosis as well. However, due to the concerns over the data quality of SUS data, it was decided that the investigation into the secondary diagnosis will be left till all the historical HES data is available to the PHIT team.

5.4. Premature deaths from LTCs Many LTCs are among the leading causes of premature death (i.e. death under 75 of age) nationally. This part investigates the contribution to premature deaths in Birmingham from LTCs. Mortality rates for under 75s of common LTCs in Birmingham and the three PCTs are also compared with regional and national average. Data presented in this part are from the death registrations from the Office of National Statistics (ONS). Figure 5.6 shows the percentage of premature deaths from LTCs in Birmingham from 1995/97 to 2005/07, breaking down by PCT. Figure 5.6

Percentage of premature deaths (under 75s) caused by common LTCs*, 3year rolling average, 1995/97 to 2005/07, Birmingham and PCTs

Percentage of all deaths under 75s

100% 90%

28.9%

28.9%

29.7%

30.9%

31.3%

31.2%

31.1%

31.8%

32.3%

33.2%

33.3%

30.7%

30.1%

29.6%

28.9%

29.1%

29.3%

29.1%

28.5%

27.8%

27.7%

27.6%

16.8%

17.4%

17.2%

16.8%

16.6%

16.6%

16.6%

16.5%

16.9%

16.7%

16.4%

23.6%

23.7%

23.5%

23.4%

23.0%

22.9%

23.2%

23.1%

23.1%

22.4%

22.7%

1995 1997

1996 1998

1997 1999

1998 2000

1999 2001

2000 2002

2001 2003

2002 2004

2003 2005

2004 2006

2005 2007

80% 70% 60% 50% 40% 30% 20% 10% 0%

Year LTCs - SB

LTCs - HOB

LTCs - BEN

Non-LTCs

Data source: ONS annual death data 1995 – 2007 *common LTCs as defined in Appendix A

Figure 5.6 shows that

JSNA LTCs Final Version

28


LTCs were consistently the major cause of premature death from 1995/97 to 2005/07, accounting for about 70% of all premature deaths in Birmingham

From 1995/97 to 2005/07, the contribution to premature deaths from LTCs had slightly decreased from 71.1% to 66.7%, which was a reduction by 6%

The reduction was distributed across all three PCTs in Birmingham, of which the contribution from South Birmingham PCT has reduced by 4% (from 23.6% to 22.7%), HoB tPCT had reduced by 2% (from 16.8% to 16.4%), and BEN PCT had reduced by 10% (from 30.7% to 27.6%).

Table 5.3 shows the number of premature deaths by common LTCs for Birmingham and the three PCTs in Birmingham during the period 2005 to 2007. Table 5.3

Number of premature deaths by common LTCs and percentage out of all premature deaths, Birmingham PCTs, 2005-2007 SB PCT

HOB tPCT

BEN PCT

%

n

%

Birmingham

Conditions

%

Cancers

36.5

1177

28.8

751

34.8

1434

33.8

3362

CHD

16.3

525

17.0

445

16.8

691

16.7

1661

Stroke

5.5

179

5.3

138

5.8

239

5.6

556

COPD

4.9

157

3.9

101

3.7

152

4.1

410

Diabetes mellitus

1.5

49

2.2

58

1.6

65

1.7

172

Mental Illness

1.3

41

1.6

41

1.2

49

1.3

131

Heart failure

0.8

25

0.7

18

0.6

25

0.7

68

Epilepsy

0.7

24

0.8

22

0.4

16

0.6

62

Hypertensive disease

0.5

17

0.5

14

0.3

14

0.5

45

CKD

0.6

18

0.4

10

0.4

16

0.4

44

Other LTCs

1.3

42

1.2

31

1.2

50

1.2

123

69.9

2254

62.4

1629

66.9

2751

66.7

6634

100.0

3226

100.0

2610

100.0

4115

100.0

9951

All LTCs* All deaths under 75s

n

%

n

n

Data source: ONS annual death data 2005 – 2007 *all LTCs as defined Appendix A

Table 5.3 shows that: •

Cancers (33.8%), CHD (16.7%), Stroke (5.6%), COPD (4.1%) and Diabetes (1.7%) were the top five LTCs accountable for premature deaths in Birmingham

JSNA LTCs Final Version

29


The three PCTs shared the same top 10 LTCs accountable for premature deaths in Birmingham

For SB PCT, cancers (36.5%) and COPD (4.9%) were accountable for larger proportion of premature deaths compared with Birmingham

For HOB tPCT: cancers (28.8%) were accountable for smaller proportion while diabetes (2.2%) and mental illness (1.6%) were accountable for larger proportion of premature deaths, compared with Birmingham

BEN PCT shared very similar distribution of LTCs accountable for premature deaths with Birmingham

It is also worth noticing that many patients with diabetes and CKD die of conditions such as CHD. However, on their death certificates diabetes and CKD are normally not mentioned. Therefore, the number of premature deaths caused by diabetes and CKD as listed in Table 5.3 is underestimated. Figure 5.7 and Figure 5.8 show the age standardised premature death rates of seven common LTCs: CHD, Diabetes, COPD, epilepsy, cancers, stroke and hypertensive diseases for males and females, Birmingham, the PCTs, West Midlands and England.

Age standardised mortality rate per 100,000 population

Figure 5.7

Age-standardised mortality rates of common LTCs, males, PCTs, Birmingham, West Midlands and England, 2005-07

180.00 160.00 140.00 120.00 100.00 80.00 60.00 40.00 20.00 0.00 CHD

Diabetes

COPD

Epilepsy

Cancers

Stroke

ENGLAND

West Midlands SHA

Birmingham

SB PCT

HOB tPCT

BEN PCT

Hypertensive diseases

Data source: NCHOD

Figure 5.7 shows that during the period 2005 to 2007, for males •

The premature death rates of all the listed LTCs in Birmingham were higher than the national average, apart from hypertensive diseases. The largest difference was seen in diabetes (more than doubled, 118% higher), epilepsy (79% higher) and CHD (43% higher).

JSNA LTCs Final Version

30


SB PCT had higher premature death rates of all the listed LTCs than the national average, apart from hypertensive diseases. The largest difference was seen in diabetes (70% higher), epilepsy (53% higher) and stroke (34% higher).

HoB tPCT had higher premature death rates of all the listed LTCs than the national average. The largest difference was seen in diabetes (more than threefold, 270% higher), epilepsy (more than threefold, 217% higher), COPD (89% higher) and CHD (85% higher).

BEN PCT had higher premature death rates of all the listed LTCs than the national average, apart from hypertensive diseases. The largest difference was seen in diabetes (84% higher), CHD (38% higher) and epilepsy (33% higher).

Age standardised mortality rate per 100,000 population

Figure 5.8

Age-standardised mortality rates of common LTCs, females, Birmingham, PCTs, England and West Midlands, 2005-07

120.00

100.00

80.00

60.00

40.00

20.00

0.00 CHD

Diabetes

COPD

Epilepsy

Cancers

Stroke

ENGLAND

West Midlands SHA

Birmingham

SB PCT

HOB tPCT

BEN PCT

Hypertensive diseases

Data source: NCHOD

Figure 5.8 shows that during the period 2005 to 2007, for females •

The premature death rates of all the listed LTCs in Birmingham were higher than the national average. The largest difference was seen in diabetes (more than doubled, 120% higher), stroke (36% higher) and hypertensive diseases (33% higher).

SB PCT had higher premature death rates of all the listed LTCs than the national average. The largest difference was seen in epilepsy (92% higher), diabetes (76% higher) and COPD (52% higher).

HoB tPCT had higher premature death rates of all the listed LTCs than the national average. The largest difference was seen in diabetes (more than threefold, 228% higher), hypertensive diseases (more than doubled, 103% higher) and CHD (77% higher).

JSNA LTCs Final Version

31


•

BEN PCT had higher premature death rates of all the listed LTCs than the national average, apart from epilepsy and hypertensive diseases for females. The largest difference was seen in diabetes (more than doubled, 105% higher), Stroke (51% higher) and CHD (30% higher).

JSNA LTCs Final Version

32


6. LTCs in general Key messages for commissioners Key findings: • The estimated prevalence of LTCs in general is different from various data sources, from as low as 6.1% (from HES) to as high as 37.7% (from the General Household Survey) in Birmingham. • According to QOF, prevalence of most LTCs was consistent over the 4-year period from 2004/05 to 2007/08. • QOF prevalence of several LTCs had increased considerably in Birmingham: hypertension, cancer and chronic kidney disease (CKD) • The prevalence of LTCs in general is associated with age, social deprivation and life style choices. Issues raised from the study: • The data sources for the prevalence of LTCs in general are mainly national census and surveys. It is normally estimated based on self-reported variables and can be overestimated. Estimate based on the secondary care data sources (i.e. HES) could be underestimated. Primary care data on prevalence of LTCs in general is not available. This chapter investigates prevalence of LTCs in general. Alternative definitions of LTCs in general can be found in Section 3.1.2. Table 6.1 shows the overall prevalence of LTCs in general from different information sources used in this chapter. Table 6.1

Suggested prevalence rates of LTCs in general from different information sources

Data source

Definition used

Prevalence rate

Area

General Household Survey 2006

Self reported long standing illness

37.7%

West Midlands

Health Survey for England 2007

Self reported long standing illness

33.8%

West Midlands

19.7%

Birmingham

Census 2001

Self reported limiting long term illness (for working age population only (age 16 – 74))

Hospital Episodes Statistics 2006/07

Common LTCs as listed in Table 1.1

6.1%

Birmingham

Several determinant factors to the prevalence are taken into account in the prevalence study. These include demographical factors, socio-economic factors and life style choices. This chapter also provides future projections of LTCs in general in Birmingham based on a study done by the University of Manchester (Simpson. Ludi. 2007).

JSNA LTCs Final Version

33


6.1. QOF Prevalence The Quality and Outcome Framework (QOF) is a voluntary incentive scheme that rewards GP practices for implementing systematic improvements in quality of care for patients. Quality Management and Analysis System (QMAS) is a national system for England that supports the QOF. GPs report annually of the number of people registered under various conditions as part of the QOF and these are all recorded in the QMAS system. A very high proportion of practices (>98%) participate in the QOF scheme making the register a good measure of prevalence for particular diseases in the population. This part presents data of disease prevalence from QOF for Birmingham and the PCTs. As QOF only records prevalence by individual conditions, all data presented in this part are broken down by conditions. People with multiple LTCs are counted under each disease that they are registered to, therefore, summing up the prevalence rates for each disease does not give the prevalence rate of all the LTCs listed.

6.1.1.

Current prevalence

Figure 6.1 shows prevalence of common LTCs for Birmingham PCTs in 2007/08, in comparison with Birmingham and England. Figure 6.1

Prevalence of common LTCs, Birmingham, PCTs and England, 2007/08

QOF Prevalence (%)

14.00% 12.00% 10.00% 8.00% 6.00% 4.00% 2.00%

C

As th m a hr D on e m ic en kid tia ne y di Le se ar as ni ng e di ab ilit ie s

ea lth

er an c

en ta lh

M

C

ps y Ep ile

O PD C

St ro ke yp er t en D ia sio be n te s m el l it us H

H

C HD ea rt fa ilu re

0.00%

Conditions SB

HOB

BEN

Birmingham

England

Data source: QOF

Figure 6.1 shows that: •

Birmingham shared similar pattern of prevalence across the common LTCs, with England, with exceptions of slightly lower prevalence in CHD (3.09%), stroke (1.37%) and hypertension (11.88%), and higher prevalence in diabetes (4.36%). Most of the difference was driven by the prevalence of these conditions in HOB tPCT

JSNA LTCs Final Version

34


SB PCT shared very similar pattern of prevalence across the common LTCs with England, with an exception of higher prevalence of CKD (3.8%)

HoB tPCT was lower than the national average in circulatory (i.e. CHD (2.3%), stroke (0.9%) and hypertension (10.2%)) and respiratory (i.e. COPD (0.7%) and asthma (5.4%)) conditions. However, higher than the national average in diabetes (5.1%)

BEN PCT shared similar pattern of prevalence across the common LTCs with England, with exceptions of diabetes (4.3%) higher than the national average and CKD (2.5%) lower than the national average.

6.1.2.

Trends

Table 6.2 shows the prevalence of common LTCs in Birmingham from 2004/05 (i.e. April 2004 to March 2005) to 2007/08, based on QOF. Table 6.2

Trend of common LTCs prevalence by disease, Birmingham, 2004/052007/08

Conditions

Unadjusted prevalence 2004/05 N

Coronary Heart Disease (CHD)

%

2005/06 N

%

2006/07 N

%

2007/08 N

%

36081

3.27

36272

3.23

35812

3.18

35081

3.09

4722

0.43

4695

0.42

8526

0.76

8022

0.71

13903

1.26

15039

1.34

15467

1.37

15546

1.37

118668

10.76

127572

11.36

133038

11.81

134737

11.88

Diabetes

42757

3.88

45719

4.07

47196

4.19

49442

4.36

COPD

13031

1.18

13330

1.19

13764

1.22

14099

1.24

Epilepsy

6226

0.56

6508

0.58

6400

0.57

6320

0.56

Cancer

4537

0.41

6676

0.59

8571

0.76

10059

0.89

Mental health

7375

0.67

8183

0.73

9747

0.87

10208

0.90

64610

5.86

66730

5.94

66564

5.91

65789

5.80

Heart failure* Stroke and transient ischaemic attack Hypertension

Asthma Dementia

n/a

n/a

n/a

n/a

3719

0.33

3847

0.34

Chronic kidney disease

n/a

n/a

n/a

n/a

25455

2.26

31714

2.80

Learning disabilities*

n/a

n/a

n/a

n/a

3308

0.29

3528

0.31

Data source: QOF * definition changed from ‘CHD and heart failure’ to ‘heart failure only’ in April 2006

JSNA LTCs Final Version

35


Table 6.2 shows that: •

Prevalence of most LTCs was consistent over the 4-year period from 2004/05 to 2007/08.

Prevalence of LTCs that had increased considerably were in hypertension (from 10.76% in 2004/05 to 11.88% in 2007/08), cancer (from 0.41% in 2004/05 to 0.89% in 2007/08) and chronic kidney disease (CKD) (from 2.26% in 2006/07 to 2.80% in 2007/08).

The top five most prevalent LTCs in Birmingham were hypertension (11.88%), asthma (5.80%), diabetes (4.36%), CHD (3.09%) and CKD (2.80%).

It is worth noting that the sharp increase in heart failure in QOF is due do a change of definition from ‘CHD and heart failure’ to ‘heart failure only’ in April 2006. Table 6.3 shows trend of common LTCs’ prevalence by disease and PCT from year 2004/05 to 2007/08. The PCT level trend was similar to the Birmingham trend: prevalence for most LTCs was consistent across the 4 years, except for increase in prevalence of heart failure, hypertension, diabetes and CKD. Table 6.3

Trend of common LTCs prevalence by disease and PCT, 2004/05-2007/08

Conditions

Unadjusted prevalence (%) SB 04/ 05

05/ 06

HOB 06/ 07

07/ 08

04/ 05

05/ 06

BEN

06/ 07

07/ 08

04/ 05

05/ 06

06/ 07

07/ 08

CHD

3.4

3.3

3.3

3.2

2.4

2.4

2.4

2.3

3.8

3.7

3.7

3.6

Heart failure*

0.5

0.4

0.8

0.8

0.3

0.3

0.6

0.8

0.5

0.5

0.8

0.8

Stroke

1.5

1.6

1.6

1.6

0.8

0.9

0.9

0.9

1.4

1.5

1.5

1.5

11.5

11.9

12.3

12.3

8.8

10.0

10.4

10.2

11.5

11.9

12.4

12.8

Diabetes

3.3

3.5

3.7

3.8

4.7

4.9

5.1

5.1

3.8

4.0

4.0

4.3

COPD

1.4

1.5

1.5

1.6

0.6

0.6

0.7

0.7

1.4

1.3

1.4

1.4

Epilepsy

0.6

0.6

0.6

0.6

0.4

0.4

0.4

0.4

0.6

0.7

0.6

0.6

Cancer

0.5

0.7

0.9

1.1

0.3

0.4

0.5

0.5

0.5

0.7

0.8

1.0

Mental health

0.6

0.6

1.0

1.0

1.0

1.0

1.0

1.0

0.6

0.7

0.7

0.8

Asthma

6.2

6.2

6.1

6.1

5.4

5.6

5.6

5.4

5.8

6.0

5.9

5.8

Dementia

n/a

n/a

0.4

0.4

n/a

n/a

0.2

0.2

n/a

n/a

0.3

0.4

CKD

n/a

n/a

3.0

3.8

n/a

n/a

1.5

2.0

n/a

n/a

2.2

2.5

Learning disabilities*

n/a

n/a

0.3

0.3

n/a

n/a

0.3

0.3

n/a

n/a

0.3

0.3

Hypertension

Data source: QOF * definition changed from ‘CHD and heart failure’ to ‘heart failure only’ in April 2006

JSNA LTCs Final Version

36


6.2. Geographical variations Prevalence of LTCs varied in the 40 wards in Birmingham from 14.1% to 24.6% in 2001 based on Census data, as illustrated in Figure 6.2. There are a number of factors that cause the geographical variations including age, socio-economic status and lifestyle choices. Figure 6.2

Map – Prevalence of limiting long-term illness by ward and PCT in Birmingham, 2001

Data source: Census 2001

6.3. Demographical patterns This part investigates the Prevalence of LTCs in general in different demographical groups. Data presented in this part are from the Census 2001 and the General Household Survey (GHS) 2006.

6.3.1.

Age

Age is the major drive demographical factor for LTCs. Figure 6.3 shows proportion of people with LTCs by age group in 2006 for the West Midlands region, based on data from the GHS 2006. It shows that •

By the age of 50, more than one third of the population (36.3%, 90) had got at least one LTC

By the age of 70, about 60% (58.5%, 138) of the population had got at least one LTC

JSNA LTCs Final Version

37


The number of LTCs that each person had was also highly related to age.

Figure 6.3

Prevalence of LTCs by age group, West Midlands Region, 2006

Percentage with one or more LTCs

80.0% 70.0% 14.8%

60.0% 15.7%

50.0% 40.0% 30.0%

10.0%

24.2%

5.9% 5.7%

20.0%

19.3%

0.5%

0.4%

3.6%

2.6%

11.3%

11.5%

0-9

10-19

0.5%

1.2%

2.1%

3.5%

15.9%

16.3%

20-29

30-39

25.0%

13.6%

8.8%

7.3%

23.7%

27.6%

29.2%

30.2%

40-49

50-59

60-69

70-79

25.0%

0.0% 80 and above

Age group One LTC

Two LTCs

Three or more LTCs

Data source: General Household Survey 2006

6.3.2.

Gender

According to GHS 2006, 35.7% (301) of males in West Midlands had long standing illness, as opposed to 29.8% (359) of females. Chi-square test showed that the difference between genders was not statistically significant.

6.3.3.

Ethnicity

Table 6.4 shows proportion of people with LTCs by ethnic group breaking down by age group in Birmingham, based on 2001 Census. It shows that the ethnic distribution of people with LTCs varied in different age groups, with higher proportion of children (i.e. age 0 – 15) with LTCs in Black group and higher proportion of older people (i.e. age 50+) in Asian group. Table 6.4

Prevalence of limiting long term illnesses by age group and ethnicity, Birmingham, 2001

Age 0 – 15

Age 16 – 49

Age 50 – 64

Ethnic group

%

N

%

White – British

5.2

6,678

11.2

32,961

30.3

32,665

55.9

79,422

White – Irish

5.0

98

15.6

1,538

37.4

3,483

55.5

62,436

White – Other

4.9

94

8.7

791

30.8

544

52.5

5,440

JSNA LTCs Final Version

N

%

Age 65 and over

N

%

N

38


Table 6.4

Prevalence of limiting long term illnesses by age group and ethnicity, Birmingham, 2001

Age 0 – 15

Age 16 – 49 %

Age 50 – 64

Ethnic group

%

Mixed – White and Black Caribbean

6.5

605

12.3

733

43.1

88

55.7

1,007

Mixed – White and Black African

4.3

27

10.4

79

31.8

14

51.1

117

Mixed – White and Asian

5.8

192

12.9

341

42.6

98

50.0

9

Mixed – Other

6.4

153

13.5

258

40.8

62

60.7

65

Asian – Indian

3.6

501

10.8

3,424

43.6

2,830

53.1

51

Asian – Pakistani

5.5

2,161

13.2

7,050

52.4

3,314

65.0

2,288

Asian – Bangladeshi

4.9

420

11.8

1,198

54.5

780

63.2

3,090

Asian – Other

4.9

156

11.9

639

42.7

383

64.2

482

Black or Black British – Black Caribbean

6.3

664

12.6

3,219

40.5

2,343

58.0

353

Black or Black British – Black African

3.5

61

6.4

242

28.7

134

58.2

3,482

Black or Black British – Other

8.0

168

13.7

460

45.8

77

57.8

137

Chinese or Other Ethnic Group – Chinese

3.3

26

4.5

155

30.0

146

51.7

89

Chinese or Other Ethnic Group – Other

5.0

82

8.4

323

38.3

143

60.1

239

N

%

Age 65 and over

N

%

N

N

Data source: Census 2001 ONS – nomis (labour market statistics)

Figures in Table 6.4 show that: •

For the age group 0 – 15 years old, slightly higher proportion of LTCs were seen in ethnic groups: Black other (8.0%), Mixed White and Black Caribbean (6.5%), Mixed other (6.4%) and Black Caribbean (6.3%)

For the age group 16 – 49 years old, slightly higher proportion of LTCs was seen in the ethnic groups: White Irish (15.6%), Asian Pakistani (13.2%), Mixed White and Asian (12.9%) and Black Caribbean (12.6%)

JSNA LTCs Final Version

39


For the age group 50 – 64 years old, higher proportion of LTCs was seen in the ethnic groups: Asian Bangladeshi (54.5%), Asian Pakistani (52.4%) and Black other (45.8%)

For the 65 and over, higher proportion of LTCs was seen in the ethnic groups: Asian Pakistani (65.0%), Asian other (64.2%), Asian Bangladeshi (63.2%) and Mixed other (60.7%).

6.4. Socio-economic status and LTCs Socio-economic status is another determinant factor for LTCs. Figure 6.4 shows agestandardised rates of limiting long-term illness by the NS-SEC social class groups (as defined in Census 2001) in Birmingham, based on Census 2001. Figure 6.4

Age-standardised prevalence* of limiting long-term illness by NS-SEC social class group, Birmingham, 2001 Long-term unemployed

18.9

Never worked

34.2

Routine occupations

16.2

Semi-routine occupations

14.2

Lower supervisory and technical occupations

13.3

Small employers and own account workers

14.7

Intermediate occupations

10.2

Lower managerial and professional occupations

9.9

Higher managerial and professional occupations - Higher professional occupations

7.2

Higher managerial and professional occupations - Large employers and higher managerial occupations

8.0 0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

Percentage of people with LTCs out of the NS-SEC group

* Directly standardisation using England population as reference population Data source: Census 2001, ONS – nomis (labour market statistics) Age standardised rates – PHIT calculation

Figure 6.4 shows that in 2001: •

The prevalence of LTCs was higher in lower socio-economic groups

The highest proportion of people with LTCs was seen in those who never worked (34.2%); followed by long-term unemployed (18.9%)

The lowest proportions of people with LTCs were seen in the higher managerial (8%) and professional occupations group (7.2%). Figure 6.5 shows ward level prevalence of LTCs (based on Census 2001) against 2004 IMD score for the income and employment domain (i.e. the higher the score the more deprived) in Birmingham. Pearson correlation test on the relation between IMD scores and prevalence of LTCs shows association between deprivation and

JSNA LTCs Final Version

40


prevalence of LTCs: more deprived (i.e. in terms of income and employment) wards had higher prevalence of LTCs. •

Prevalence of LTCs was positively associated with IMD score for income (coefficient = 0.48, P<0.01)

â&#x20AC;˘

Prevalence of LTCs was positively associated with IMD score for employment (coefficient = 0.57, P<0.001).

Figure 6.5

Ward level prevalence of limiting long-term illness (2001 Census) against IMD score 2004 for income and employment, Birmingham

Data source: Census 2001 and Indices of Multiple Deprivation (IMD) 2004

6.5. Lifestyle choices and LTCs This part investigates the relationship between lifestyle choices, such as smoking, alcohol drinking and obesity, and the prevalence of LTCs in general. All the data presented in this part are from the Health Survey for England (HsfE) 2007. Data on the prevalence of lifestyle risk factors are generally collected by representative surveys such as the Health Survey for England (HsfE). These surveys can provide accurate estimates for large areas (i.e. countries of the UK, regions of England) but the sample frame and sample size do not allow for estimates to be made for small areas (i.e. local authorities, wards). For this reason, life style patterns for the West Midlands region were used as a proxy for Birmingham.

6.5.1.

Smoking

Smoking is related to many LTCs. Research from the World Health Organization (WHO) has estimated the impact of smoking on total disease burden (both mortality and morbidity) in terms of disability-adjusted life years (DALYs) lost. The World Health Report 2002 estimated that in developed countries around 12% of all disease burden (World Health Organisation 2002). Figure 6.6 shows current smoking status for people with and without LTCs in the West Midlands in 2007, based on the HsfE. It shows that the difference in current smoking status between people with LTCs and without LTCs was not significant. For both groups, about 80% were non smokers and 20% were smokers.

JSNA LTCs Final Version

41


Figure 6.6

Current smoking status for people with and without LTCs, West Midlands, 2007

Percentage in LTCs and non-LTCs populations

90.0% 80.0%

80.0%

78.9%

70.0% 60.0% 50.0% 40.0% 30.0% 21.1%

20.0%

20.0% 10.0% .0% current non-smoker

current smoker Smoking status LTC

No LTC

Data source: Health Survey for England 2007

However, when looking at the amount of cigarettes consumed per day for people who smoke, difference showed between people with and without LTCs. Figure 6.7

Number of cigarettes smoked per day for people with and without LTCs, West Midlands, 2007 60.0% Percentage in LTCs and non-LTCs population

51.9% 50.0% 40.0% 40.0%

36.7%

35.1%

30.0% 23.3% 20.0% 13.0% 10.0%

.0% 1 to 10 cigarettes

11 to 20 cigarettes

More than 20 cigarettes

Number of cigarettes smoked per day LTC

No LTC

Data source: Health Survey for England 2007

As illustrated in Figure 6.7, people with LTCs tended to be heavier smokers: â&#x20AC;˘

The majority of smokers who were without a LTC (51.9%) were having one to ten cigarettes per day while the proportion for those with LTCs was only 36.7%

JSNA LTCs Final Version

42


More than one in five (23.3%) smokers who were with LTCs were having more than 20 cigarettes per day, while the proportion for those without a LTC was only 13%

About 40% of smokers who were with LTCs were having 11 to 20 cigarettes per day, while the proportion for those without a LTC was only 35.1%.

6.5.2.

Obesity

Obesity is one of the risk factors for highly prevalent LTCs as CHD and diabetes. The adverse effects of excess weight are more pronounced when fat is concentrated in the abdomen. This is known as central or abdominal obesity and is assessed using the waist to hip ratio. The World Health Organization’s World Health Report 2002 estimated that over 7% of all disease burden in developed countries was caused by raised body mass index (BMI) (World Health Organization2002). Figure 6.8 shows obesity status for people with and without LTCs in the West Midlands in 2007. Figure 6.8

Obesity status for people with and without LTCs, West Midlands, 2007 66.5%

70.0% Percentage in LTCs and non-LTCs population

61.4% 60.0% 50.0% 40.0% 30.0%

23.5%

20.0%

15.0% 16.3%

17.2%

10.0% .0% Normal-weight

Over-weight

Obese

Obesity group LTC

No LTC

Data source: Health Survey for England 2007

According to the figures shown in Figure 6.8, higher proportion (approx 6 percentage points higher) of obesity (i.e. BMI > 30) was seen in those with LTCs.

6.5.3.

Alcohol

Long-term heavy alcohol drinking is related to conditions such as liver disease, heart disease, certain forms of cancer, and pancreatitis (http://www.who.int/dietphysicalactivity/publications/trs916/download/en/index.html). The World Health Report 2002 estimates that over 9% of all disease burden in developed countries is caused by alcohol consumption (World Health Organisation 2002). The Government currently advises that ‘regular consumption of between three and four units a day by men’ and ‘between two and three units a day by women of all ages will not lead to any significant health risk’. Consuming in excess of four units on the heaviest drinking day of the week in men, or over three units in women, is not advised.

JSNA LTCs Final Version

43


Figure 6.9 shows that about 70% of people with LTCs said they had had drink within the 7 days prior to the interview. The proportion was approx 75% for people without LTC. Chi-square test showed the difference was not statistically significant. Figure 6.9

Percentage of people who had drink in the 7 days prior to the interview by people with and without LTCs, West Midlands, 2007

Percentage of people with and without LTCs

80.0%

74.6% 70.1%

70.0% 60.0% 50.0% 40.0% 29.9% 30.0%

25.4%

20.0% 10.0% .0% Yes

No Whether had drink in last 7 days LTC

No LTC

Data source: Health Survey for England 2007

Figure 6.10 shows frequency of alcohol drinking for people with and without LTCs in the West Midlands region in 2007, based on data from the Health Survey for England. The frequency was estimated based on peopleâ&#x20AC;&#x2122;s answers to the question how many days in the 7 days prior to the interview that they had had a drink. Figure 6.10 Frequency of drinking alcohol for people with and without LTCs, West Midlands, 2007

Percentage of people with and without LTCs

30.0% 27.0%

25.0%

24.6% 22.6% 19.5% 19.0%

20.0%

17.3%

16.4%

15.0% 9.7%

10.0%

10.8% 8.8%

7.7% 4.9%

6.2% 5.6%

5.0% .0% 1 day

2 days

3 days

4 days

5 days

6 days

7 days

Number of days in the last 7 had a drink LTC

No LTC

Data source: Health Survey for England 2007

Figure 6.10 shows that:

JSNA LTCs Final Version

44


People with LTCs tended to be more frequent drinkers of whom 22.6% drank on a daily basis, compared with 17.3% for those without any LTC

Approx 46.7% of people with LTCs drank at least once every 2 days, and the proportion for people without LTC was 37.2%.

6.6. Projection of LTCs in general In January 2009, ‘Projections of limiting long term illness and disability for Birmingham’ was produced by Cathie Marsh Centre for Census and Survey Research at the University of Manchester (Simpson 2007). This report was commissioned by Birmingham City Council. This part summarizes findings from the report. Details of the projection can be found in the original report. The estimates and projections are based on age specific limiting long term illness (LLTI) rates from the 2001 censuses and disability rates from the Health Survey for England (2000/01). Data on population size and age composition are taken from the ONS mid year estimates (2001-05) and the 2006 based ONS population projections (Simpson 2007).

Relational models were used to generate district estimates using local LLTI schedules and the national relationship between LLTI and disability schedules. The projections used the prevalence ratio methodology where the product of the age specific LLTI/disability rates and the ONS 2006 based population projections give the projected number of people with an LLTI or disability (Simpson 2007). There are four sets of LLTI projections: •

Static LLTI projection – Assumes that LLTI rates remain as in 2001 for each year of the projection

Intercensal change – Continues district change in LLTI between 1991 and 2001 using census data

Pessimistic projection–Increases LLTI rates based upon the highest rates observed in GHS (1991-04)

Optimistic projection – Decreases LLTI rates based upon the lowest rates observed in GHS (1991-04)

Table 6.5 shows the projection to year 2021 of LLTIs in Birmingham in comparison with the projections of England, North Ireland, Scotland, UK and Wales. •

Assuming that LLTI remains at the levels recorded in the 2001 census, the number of people with an LLTI in Birmingham will increase by 11% from 192,400 in 2001 to 212,600 in 2021.

In the Pessimistic projection the population with an LLTI is projected to increase by 30% so that 23% people in Birmingham have an LLTI in 2021 (250,300).

In the Optimistic projection the population with an LLTI is projected to increase by 4% so that 18% of people in Birmingham have an LLTI in 2021 (200,000) (Simpson 2007).

JSNA LTCs Final Version

45


Table 6.5

Limiting long-term illnesses projections to year 2021 (Simpson 2007).

Area

Static 2001

2011

Pessimistic 2021

2011

2021

Optimistic 2011

2021

186,271

Intercensal change 2011

2021

200,433

208,788

236,947

Prevalence (N) Birmingham

192,428

197,467

212,627

232,838

250,324

Crude prevalence rate (%) Birmingham

19.5

19.0

19.1

22.4

22.5

17.9

18.0

20.1

21.3

England

17.9

18.5

19.6

21.9

23.0

17.5

18.4

18.5

19.6

UK

18.4

19.2

20.4

22.6

23.7

18.1

19.1

19.3

20.6

JSNA LTCs Final Version

46


7. People with multiple LTCs Key messages for commissioners Key findings: • Prevalence of multiple LTCs (based on secondary care data) is 2.7% in Birmingham • Prevalence of multiple LTCs is associated with age and social deprivation • Hypertension, CHD, diabetes, asthma and mental illness (including learning disability) are the most common LTCs that are in co-morbidities with other LTCs Issues raised from the study: The prevalence of multiple LTCs is underestimated as it is based on the secondary care data (i.e. HES). The availability of primary care data is the key to an accurate estimate and projection of the prevalence of multiple LTCs as well as co-morbidities in Birmingham. This data is currently only available for HoB tPCT for the vascular LTCs. People with more than one LTC are categorized as the vulnerable high risk people for case management in the Department of Health’s Supporting people with Long Term Conditions, An NHS and Social Care Model to support local innovation and integration plan (DOH 2005). This part investigates the prevalence of people with multiple LTCs in Birmingham and the PCTs. A person with multiple LTCs is defined in this study as hospital inpatient who have two or more LTCs (as listed in Table 1.1) recorded as the primary or secondary diagnosis of the hospital episode that the patient is admitted for. Details of the method used to calculate the number of people with multiple LTCs (and single LTC from HES) are described in Section 3.4.2. The data presented in this chapter are from the hospital episode statistics (HES) data 2006/07(i.e. April 06 – March 07). In the year 2006/07, 61,080 people in total were identified as having at least one LTC (i.e. as listed in Table 1.1). This equates to 6.1% of the city’s population (1,006,503) as in 2006. Among them, 27,484 people in total were identified as with multiple LTCs in Birmingham. This equals to 2.7% of the city’s population as in 2006. In addition to HES data, data was used for HoB tPCT from the deadly trio database (i.e. primary care data) to present the prevalence of co-morbidities in HoB tPCT. At the time when the report was written these data were not available for BEN PCT and SB PCT, however it was in the agenda that the database would collect data from all GP practices in Birmingham in future. Thus a more accurate estimate of co-morbidity based on both primary care and secondary care data would be possible. This chapter describes geographical, demographical and socio-economical distributions of people with LTCs in Birmingham. It also investigates co-morbidities of common LTCs in the city and the PCTs.

JSNA LTCs Final Version

47


7.1. People with multiple LTCs by PCT Table 7.1 shows the prevalence of people with multiple LTCs in Birmingham by PCT and gender, in the year 2006/07. Table 7.1

Prevalence of people with multiple LTCs by PCT, Birmingham, 2006/07 Male N

Female %

N

%

Missing

Total

N

N

SB PCT

4471

45.2%

5421

54.8%

HOB tPCT

3957

50.2%

3929

49.8%

1

7887

BEN PCT

4583

47.2%

5120

52.8%

2

9705

13011

47.3%

14470

52.6%

3

27484

Birmingham

9892

Data source: HES 2006/07

Table 7.1 shows that: •

There were in total 27,484 people in Birmingham identified as with multiple LTCs, 9,892 of them were in SB PCT, 7,887 in HoB tPCT and 9,705 in BEN PCT.

There were slightly more females (52.6%; 14,470) with multiple LTCs than males (47.3%; 13,011) in Birmingham. BEN PCT shared similar gender distribution with Birmingham while SB PCT had slightly larger proportion of females (54.8%; 5421) and HOB tPCT had slightly smaller proportion of females (49.8%; 3,929)

Using the number of people with multiple LTCs in Birmingham (as shown in Table 7.1) and the ONS population estimate 2006, crude prevalence rate (%) of people with multiple LCTs in Birmingham was calculated, as shown in Figure 7.1. It shows that in the year 2006/07 •

The overall prevalence rate of people with multiple LTCs in Birmingham was about 2.7%, with slightly higher rate in females (2.8%) than in males (2.6%)

The prevalence rate in SB PCT (2.9%) was slightly higher than Birmingham, with the rate in females (3.1%) slightly higher than in males (2.8%)

The prevalence rate in HOB tPCT (2.9%) was slightly higher than Birmingham, with very similar rates in males and females

The prevalence rate in BEN PCT (2.4%) was slightly lower than Birmingham, with slightly higher rate in females (2.5%) than in males (2.3%)

JSNA LTCs Final Version

48


Crude prevalence rate (%) of people with multiple LTCs

Figure 7.1

Crude prevalence rate (%) of people with multiple LTCs by PCT, Birmingham, 2006/07 3.5%

2.5%

3.1% 2.9% 2.8%

2.9% 2.9% 2.9%

3.0% 2.5%2.4% 2.3%

2.6%

2.8% 2.7%

2.0% 1.5% 1.0% 0.5% 0.0% BEN PCT

HOB tPCT Males

SB PCT Females

Birmingham

Persons

Data source: HES 2006/07 ONS population estimate mid 2006 PHIT calculation

Figure 7.2 shows the age-standardised prevalence rate of people with multiple LTCs by PCT in Birmingham in 2006/07. Age-standardised* prevalence rate (%) of people with multiple LTCs by PCT, Birmingham, 2006/07

Age standardised prevalence rate (%) of multiple LTCs

Figure 7.2

4.5%

3.8%

4.0%

3.5% 3.3%

3.5% 3.0%

2.3%

2.6% 2.5% 2.4%

SB PCT

BIRMINGHAM

2.5% 2.5% 2.0%

2.0% 2.1% 2.0%

2.4%

1.5% 1.0% 0.5% 0.0% BEN PCT

HOB tPCT Males

Females

All Persons

* Directly standardisation using European Reference population Data source: HES 2006/07 ONS population estimate mid 2006 PHIT calculation

Figure 7.2 shows that after adjusted for age, the difference between the PCTs was getting bigger and the gender distribution changed too.

JSNA LTCs Final Version

49


The overall prevalence rate of people with multiple LTCs in Birmingham was about 2.5%, with slightly higher rate in males (2.6%) than in females (2.4%)

The prevalence rate in SB PCT (2.4%) was similar to Birmingham, with the rate in females (2.3%) slightly lower than in males (2.5%)

The prevalence rate in HOB tPCT (3.5%) was higher than Birmingham, with males (3.8%) higher than females (3.3%)

The prevalence rate in BEN PCT (2.0%) was lower than Birmingham, with slightly higher rate in males (2.1%) than in females (2.0%)

7.2. Geographical variations Figure 7.3 shows the crude prevalence rate of multiple LTCs in Birmingham by ward. Figure 7.3

Crude prevalence rate of multiple LTCs by ward, Birmingham, 2006/07

Data source: HES 2006/07 ONS population estimate mid 2006 PHIT calculation

Figure 7.3 shows that in the year 2006/07: •

Ward level prevalence rate of multiple LTCs varied from 2.3% to 4.2% in Birmingham

JSNA LTCs Final Version

50


The prevalence was most various in HoB PCT catchments area, with prevalence in five wards below the city’s average, while Ladywood the highest of all wards in Birmingham

The prevalence in the northern wards (BEN PCT’s catchments area) and the southern wards (SB PCT’s catchments area) were in the middle rage

The geographical difference of disease prevalence is usually caused by the demographical and socio-economical variations of the areas.

7.3. Demographical patterns This part describes the prevalence of multiple LTCs in Birmingham and the PCTs in different age, gender and ethnic groups.

7.3.1.

Age and gender

Figure 7.3 shows the prevalence (i.e. numbers) and prevalence rate (i.e. percentage) of males with multiple LTCs in each age group by PCT in Birmingham, in the year 2006/07. Number and percentage of people with multiple LTCs by age group and PCT, males, Birmingham 2006/07

Percentage of people with multiple LTCs

30.00%

1,600 1,400

25.00%

1,200 20.00%

1,000

15.00%

800 600

10.00%

400 5.00%

200

0.00%

Number of people with multiple LTCs

Figure 7.3

0 0-9

10-19

20-29

30-39

40-49

50-59

60-69

70-79 80 and above

Age group Birmingham %

SB PCT %

HOB tPCT %

SB PCT numbers

HOB tPCT numbers

BEN PCT numbers

BEN PCT %

Data source: HES 2006/07 ONS mid year population estimate 2006 PHIT calculation

Looking at the prevalence rate of people with multiple LTCs in each age group (i.e. bars in the chart), it shows that in year 2006/07 •

The prevalence rate (i.e. percentage) of multiple LTCs in males was positively associated with age across all PCTs in Birmingham. Approximately 14% of males in the 70-79 group and 19% in the 80 and above group were living with multiple LTCs

JSNA LTCs Final Version

51


HoB tPCT had the highest rate among all three PCTs in Birmingham, across all age groups. Approx 20% of males in the 70-79 group and 25% in the 80 and above group were living with multiple LTCs

The age pattern of the number of people with multiple LTCs (i.e. lines in the chart) shows that in year 2006/07 •

The prevalence (i.e. number) of multiple LTCs in males was positively associated with age until the age of 80. It then decreased a bit in the 80 and above group.

It started to increase steeply from the age of 50.

Figure 7.4 shows the number and percentage (out of each age group) of females with multiple LTCs, by age group and PCT, for females in Birmingham, in the year 2006/07. Number and percentage of people with multiple LTCs by age group and PCT, females, Birmingham 2006/07

25.00%

2000

Percentage of people with multiple LTCs

1800 20.00%

1600 1400

15.00%

1200 1000

10.00%

800 600

5.00%

400 200

0.00%

Number of people with multiple LTCs

Figure 7.4

0 0-9

10-19

20-29

30-39

40-49

50-59

60-69

70-79 80 and above

Age group Birmingham %

SB PCT %

HOB tPCT %

SB PCT numbers

HOB tPCT numbers

BEN PCT numbers

BEN PCT %

Data source: HES 2006/07 ONS mid year population estimate 2006 PHIT calculation

Looking at the percentage of people with multiple LTCs in each age group (i.e. bars in the chart), it shows that in year 2006/07 •

The prevalence rate (i.e. percentage) of multiple LTCs in females was positively associated with age across all PCTs in Birmingham. Approx 11% of females in the 70-79 group and 16% in the 80 and above group were living with multiple LTCs

HoB tPCT had the highest rate among all three PCTs in Birmingham, across all age groups. Approx 15% of females in the 70-79 group and 21% in the 80 and above group were living with multiple LTCs

JSNA LTCs Final Version

52


The age pattern of the number of people with multiple LTCs (i.e. lines in the chart) shows that in year 2006/07 •

The prevalence (i.e. number) of multiple LTCs in females was positively associated with age, except for the very old age group (i.e. 80 and above) in HoB tPCT.

It started to increase steeply from the age of 50.

7.3.2.

Ethnicity

Table 7.2 shows the ethnic distribution of people with multiple LTCs in Birmingham, breaking down by PCT and gender. It shows that in 2006/07: •

The majority (19,025; 69.2%) of people with multiple LTCs in Birmingham were of White ethnic background. The PCT break down shows that SB PCT had the largest proportion of people with multiple LTCs from the White ethnic group (81.5%; 8,065), followed by BEN PCT (77.5%; 7,516). Less than half (43.7%; 3,444) of HoB tPCT’s prevalence of multiple LTCs was from White ethnic group.

Asian was the second largest ethnic group (4,090; 14.9%) that accounted for people with multiple LTCs in Birmingham. HoB tPCT had 30.9% (2,439) of their population with multiple LTCs from this group followed by BEN PCT (11.5%; 1,1114) and SB PCT (5.4%; 537)

People of Black background were accounted for 6.3% (1,720) of the prevalence of multiple LTCs in Birmingham. HoB tPCT had 14.5% (1,146) of their population with multiple LTCs from this group followed by BEN PCT (6.3%; 1,720) and SB PCT (2.7%; 265)

Ethnicity of a large proportion (7.9%; 2,175) of people with multiple LTCs was unknown (i.e. either not stated by the patient or not recorded).

Table 7.2

Ethnic distribution of people with multiple LTCs Birmingham and the three PCTs, 2006/07

Ethnic group

SB PCT

HOB tPCT

BEN PCT

Birmingham

Males Asian or Asian British

287

6.4%

1267

32.0%

546

11.9%

2100

16.1%

Black

129

2.9%

540

13.6%

150

3.3%

819

6.3%

Mixed

25

0.6%

34

0.9%

11

0.2%

70

0.5%

White

3606

80.7%

1690

42.7%

3531

77.0%

8827

67.8%

63

1.4%

71

1.8%

20

0.4%

154

1.2%

361

8.1%

355

9.0%

325

7.1%

1041

8.0%

Chinese and other Not known

JSNA LTCs Final Version

53


Table 7.2

Ethnic distribution of people with multiple LTCs Birmingham and the three PCTs, 2006/07

Ethnic group

SB PCT 4471

Total

HOB tPCT

100.0%

3957

BEN PCT

Birmingham

100.0%

4583

100.0%

13011

100.0%

Females Asian or Asian British

250

4.6%

1172

29.8%

568

11.1%

1990

13.8%

Black

136

2.5%

606

15.4%

159

3.1%

901

6.2%

Mixed

30

0.6%

33

0.8%

33

0.6%

96

0.7%

White

4459

82.3%

1754

44.6%

3985

77.8%

10198

70.5%

74

1.4%

54

1.4%

23

0.4%

151

1.0%

472

8.7%

310

7.9%

352

6.9%

1134

7.8%

5421

100.0%

3929

100.0%

5120

100.0%

14470

100.0%

Chinese and other Not known Total

Persons Asian or Asian British

537

5.4%

2439

30.9%

1114

11.5%

4090

14.9%

Black

265

2.7%

1146

14.5%

309

3.2%

1720

6.3%

Mixed

55

0.6%

67

0.8%

44

0.5%

166

0.6%

White

8065

81.5%

3444

43.7%

7516

77.5%

19025

69.2%

Chinese and other

137

1.4%

125

1.6%

43

0.4%

305

1.1%

Not known

833

8.4%

665

8.4%

677

7.0%

2175

7.9%

9892

100.0%

7886

100.0%

9703

100.0%

27481

100.0%

Total Data source: HES 2006/07

Figure 7.5 and Figure 7.6 show the crude prevalence rate (%) of multiple LTCs by ethnic group for males and females in Birmingham in 2006/07, based on hospital episode data (HES 2006/07) and ONS population estimate 2006. Figure 7.5 shows that in the year 2006/07, for males: â&#x20AC;˘

The crude prevalence rate of multiple LTCs was higher in the White ethnic group (2.7%), followed by Black group (2.6%) and Asian group (2.0%).

â&#x20AC;˘

The crude prevalence rate of multiple LTCs was much lower in the Chinese and others group (1.3%) and Mixed group (0.4%). However, as there were a large proportion of patients whose ethnicity were unknown (7.9% of all people with multiple LTCs), the extremely lower prevalence rate in the Mixed group might due to the reason that ethnicity was not recorded for them.

JSNA LTCs Final Version

54


â&#x20AC;˘

HOB tPCT had the highest prevalence rates for Asian (2.2%), Black (3.1%) and White (3.4%) groups. In particular, the prevalence rate in the Black ethnic group was much higher than Birmingham.

â&#x20AC;˘

BEN PCT had consistently the lowest prevalence rates for all five ethnic groups.

Figure 7.5

Crude prevalence rates (%) of multiple LTCs by ethnic group and PCT, males, Birmingham, 2006/07 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% Asian or Asian British SB PCT

Black

HOB tPCT

Mixed

BEN PCT

White

Chinese and other

Birmingham

Data source: HES 2006/07 ONS population estimate mid 2006 PHIT calculation

Figure 7.6

Crude prevalence rates (%) of multiple LTCs by ethnic group and PCT, females, Birmingham, 2006/07 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% Asian or Asian British SB PCT

Black

HOB tPCT

Mixed

BEN PCT

White

Chinese and other

Birmingham

Data source: HES 2006/07 ONS population estimate mid 2006 PHIT calculation

Figure 7.6 shows that in the year 2006/07, for females:

JSNA LTCs Final Version

55


The crude prevalence rate of multiple LTCs was higher in the White ethnic group (2.9%), followed by Black group (2.6%) and Asian group (1.9%).

The crude prevalence rate of multiple LTCs was much lower in the Chinese and others group (1.4%) and Mixed group (0.6%). However, as there were a large proportion of patients whose ethnicity was unknown (7.9%), the extremely lower prevalence rate in the mixed group might due to the reason that ethnicity was not recorded for them.

HOB tPCT had the highest prevalence rates for Asian (2.1%), Black (3.1%) and White (3.6%) groups.

BEN PCT had consistently the lowest prevalence rates for all five ethnic groups, apart from the mixed group.

Figure 7.7 shows the age standardised rate (%) of multiple LTCs by ethnic group in Birmingham during the year 2006/07. It is worth noticing that as population distribution by age, gender and ethnicity is only available from the 2001 Census, the age standardised rates presented in Figure 7.7 are calculated based on 2001 census population data. As a result, the calculated rates are slightly overestimated as the population in Birmingham has grown from 977,090 in 2001 to 1,006,503 in 2006 (i.e. 3% increase). Figure 7.7 shows that after adjusted for age, •

The difference between ethnic groups was smaller, with the prevalence rate of multiple LTCs still slightly higher in the White group (2.8%), followed by Asian (2.7%) and the Chinese and others group (2.6%).

The prevalence was still the lowest in the mixed ethnic group (1.0%)

Age standardised rate (%) of multiple LTCs

Figure 7.7

Age standardised rate* (per 100,000) of multiple LTCs by ethnic group, Birmingham, 2006/07 3.00%

2.79% 2.83% 2.79%

2.69%

2.64%

2.50%

2.66%

2.70% 2.66% 2.55% 2.54% 2.47% 2.37%

2.00%

1.50% 1.21% 0.98% 1.00%

0.80%

0.50% 0.00% White

Mixed

Males

Asian

Females

Black

Chinese and others

All Persons

* Directly standardisation using ONS population estimate for England mid 2007 as reference population Data source: HES 2006/07 Census 2001 population PHIT calculation

JSNA LTCs Final Version

56


7.4. Multiple LTCs and deprivation Figure 7.8 shows the age standardised prevalence rate of multiple LTCs in Birmingham by local deprivation quintile (i.e. quintile calculated based on IMD 2007 scores for Birmingham Super Output Areas only) in the year 2006/07. It shows that: •

The prevalence rate of LTCs was associated with social deprivation in Birmingham.

The rate in the most deprived quintile (i.e. 5th quintile) at 3.5% which was more than twofold (122% higher) of the rate in the most affluent quintile (i.e. 1st quintile) at 1.58%.

The largest difference was between the 1st and the 2nd quintiles (38.6% increase) and between the 4th and the 5th quintile (21.1% increase)

Age standardised prevalence rate (%) of multiple LTCs

Figure 7.8

Age standardised prevalence rate* (%) of multiple LTCs by local deprivation quintile**, Birmingham, 2006/07

4.00% 3.50% 3.50% 2.89%

3.00%

2.66%

2.50%

2.19%

2.00% 1.58% 1.50% 1.00% 0.50% 0.00% Q1 most affluent

Q2

Q3

Q4

Q5 most deprived

* Directly standardisation using European Reference population ** Local deprivation quintile based on IMD 2007 Data source: HES 2006/07 ONS population estimate Mid 2006 PHIT calculation

JSNA LTCs Final Version

57


7.5. Co-morbidity of common LTCs This part investigates the co-morbidity of common LTCs in Birmingham. It describes the prevalence of the common co morbidities of the six common LTCs that are covered by this report: • CHD • diabetes • CKD • COPD • asthma • epilepsy The top three co-morbidities of LTCs listed in Table 1.1 with the six conditions above are described. In addition, three-way co-morbidities of the conditions are also investigated into. Details of the top 20 co-morbidities for each condition can be found in Appendix H.

7.5.1.

CHD

There were in total 10,432 patients recorded on HES 2006/07 as having CHD in Birmingham. Out of all the people who were identified as with multiple LTCs (27,485) in Birmingham in the year 2006/07, 32.8% (9,004) of them were with CHD. The most common co morbidities (i.e. top three) with CHD were: hypertensive diseases, diabetes and heart failure. Table 7.3 shows the top three co morbidities (i.e. hypertensive diseases, diabetes and heart failure) with CHD by PCT in Birmingham. It shows that: •

Hypertensive diseases were the most prevalent co morbidity with CHD in Birmingham, with 5,481 people identified as having both CHD and hypertensive diseases. This accounted for 52.5% of all CHD inpatients, 15.3% of all GP registered CHD prevalence in Birmingham. It also equated to a crude prevalence rate of 544.7 per 100,000 population

Diabetes was the second most prevalent co morbidity with CHD in Birmingham, with 2,723 people identified as having both CHD and diabetes. This accounted for 26.1% of all CHD inpatients, 7.6% of all GP registered CHD prevalence in Birmingham. It also equated to a crude prevalence rate of 270.6 per 100,000 population

Heart failure was the third most prevalent co morbidity with CHD in Birmingham, with 1,136 people identified as having both CHD and heart failure. This accounted for 10.9% of all CHD inpatients, 3.2% of all GP registered CHD prevalence in Birmingham. It also equated to a crude prevalence rate of 112.9 per 100,000 population

SB PCT shared similar prevalence rate of [CHD + hypertensive diseases] with Birmingham, while the rate of [CHD + diabetes] and [CHD + heart failure] was lower than Birmingham

HOB tPCT had higher prevalence rate of all three co morbidities with CHD, compared with Birmingham

JSNA LTCs Final Version

58


BEN PCT had similar prevalence rate of [CHD + diabetes] and []CHD + heart failure] with Birmingham and lower prevalence rate of [CHD + hypertensive diseases]

Table 7.3

Top three co morbidities with CHD by PCT, Birmingham, 2006/07

Hypertensive diseases

N

% out of all CHD inpatients (persons)*

5481

52.5%

% out of QOF CHD prevalence**

Crude prevalence rate (per 100,000)***

15.3%

544.7

SB PCT

1811

51.7%

14.6%

538.9

HOB tPCT

1715

62.4%

23.0%

635.0

BEN PCT

1955

46.7%

12.2%

488.7

7.6%

270.6

Diabetes

2723

26.1%

SB PCT

757

21.6%

6.1%

225.3

HOB tPCT

925

33.6%

12.4%

342.5

BEN PCT

1041

24.9%

6.5%

260.2

3.2%

112.9

Heart failure

1136

10.9%

SB PCT

320

9.1%

2.6%

95.2

HOB tPCT

335

12.2%

4.5%

124.0

BEN PCT

481

11.5%

3.0%

120.2

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

The co morbidities with CHD (as shown in Table 7.3) were further investigated into and prevalence of three way co morbidities was calculated, as shown in Table 7.4. It shows that in 2006/07 •

The prevalence rate of [CHD + hypertensive diseases + diabetes] was 159.5 per 100,000, which was about 15.4% of all CHD inpatients, 4.5% of GP registered CHD population in Birmingham.

The prevalence rate of [CHD + hypertensive diseases + heart failure] was 51.7 per 100,000, which was about 5.0% of all CHD inpatients, 1.5% of GP registered CHD population in Birmingham.

JSNA LTCs Final Version

59


â&#x20AC;˘

The prevalence rate of [CHD + diabetes + heart failure] was 54.8 per 100,000, which was about 5.3% of all hospital CHD inpatients, 1.5% of GP registered CHD population in Birmingham.

â&#x20AC;˘

HOB tPCT had the highest prevalence rates of all the three-way comorbidities with CHD. In particular, [CHD + heart failure + diabetes] doubled Birmingham average.

Details of the prevalence and prevalence rate of the top 20 co morbidities with CHD can be found in Appendix H. Table 7.4

Prevalence of three-way co-morbidities with CHD by PCT, Birmingham, 2006/07 % out of all CHD inpatients (persons)*

N

[CHD + hypertensive diseases + diabetes]

1605

SB PCT

412

HOB tPCT

15.4%

% out of QOF CHD prevalence**

Crude prevalence rate (per 100,000)***

4.5%

159.5

11.8%

3.3%

122.6

634

23.1%

8.5%

234.8

BEN PCT

559

13.4%

3.5%

139.7

[CHD + hypertensive diseases + heart failure]

520

1.5%

51.7

SB PCT

124

3.5%

1.0%

36.9

HOB tPCT

199

7.2%

2.7%

73.7

BEN PCT

197

4.7%

1.2%

49.2

[CHD + heart failure + diabetes]

551

1.5%

54.8

SB PCT

77

2.2%

0.6%

22.9

HOB tPCT

335

12.2%

4.5%

124.0

BEN PCT

139

3.3%

0.9%

34.7

5.0%

5.3%

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

JSNA LTCs Final Version

60


7.5.2.

Diabetes

Out of all the people who were identified as with multiple LTCs (27,485) in Birmingham in the year 2006/07, 31.4% (8,639) of them were with diabetes. The most common co morbidities (i.e. top three) with diabetes were: hypertensive diseases, CHD and asthma. Table 7.5 shows the top three co morbidities (i.e. hypertensive diseases, CHD and asthma) with diabetes by PCT in Birmingham. Table 7.5

Top three co morbidities with diabetes by PCT, Birmingham, 2006/07

Hypertensive diseases

N

% out of all diabetes inpatients (persons)*

5589

52.4%

% out of QOF diabetes prevalence**

Crude prevalence rate (per 100,000)***

11.8%

555.5

SB PCT

1583

48.3%

11.4%

471.1

HOB tPCT

2199

61.3%

13.9%

814.3

BEN PCT

1807

47.6%

10.3%

451.7

5.8%

270.6

CHD

2723 SB PCT HOB tPCT

BEN PCT Asthma

25.5%

757

23.1%

5.4%

225.3

925

25.8%

5.9%

342.5

1041

27.4%

6.0%

260.2

2.1%

99.7

1003

9.4%

SB PCT

272

8.3%

2.0%

80.9

HOB tPCT

412

11.5%

2.6%

152.6

BEN PCT

319

8.4%

1.8%

79.7

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

Table 7.5 shows that: â&#x20AC;˘

Hypertensive diseases were the most prevalent co morbidity with diabetes in Birmingham, with 5,589 people identified as having both diabetes and

JSNA LTCs Final Version

61


hypertensive diseases. This accounted for 52.4% of all diabetes inpatients, 11.8% of all GP registered diabetes prevalence in Birmingham and also equated to a crude prevalence rate of 555.5 per 100,000 population •

CHD was the second most prevalent co morbidity with diabetes in Birmingham, with 2,723 people identified as having both CHD and diabetes. This accounted for 25.5% of all diabetes inpatients, 5.8% of all GP registered CHD prevalence in Birmingham and also equated to a crude prevalence rate of 270.6 per 100,000 population

Asthma was the third most prevalent co morbidity with diabetes in Birmingham, with 1,003 people identified as having both diabetes and asthma. This accounted for 9.4% of all diabetes in patients, 2.1% of all GP registered diabetes prevalence in Birmingham and also equated to a crude prevalence rate of 99.7 per 100,000 population

SB PCT had lower prevalence rates of all three co morbidities with Birmingham, however, this was mainly due to that the overall prevalence of diabetes was lower in SB PCT, as the percentage of the co-morbidities out of the QOF diabetes prevalence was similar between SB PCT and Birmingham

HOB tPCT had higher prevalence rate of all three co morbidities with diabetes compared with Birmingham. This was mainly due to that the overall prevalence of diabetes was higher in HoB tPCT

BEN PCT had lower prevalence rate of all three co morbidities with diabetes comparing with Birmingham. However, this was mainly due to that the overall prevalence of diabetes was lower in BEN PCT, as the percentage of the co morbidities out of the QOF diabetes prevalence was similar between BEN PCT and Birmingham

The co morbidities with diabetes (as shown in Table 7.5) were further investigated into and prevalence of three-way co morbidities was calculated, as shown in Table 7.6. It shows that in 2006/07 •

The prevalence rate of [diabetes + CHD + hypertensive diseases] was 159.5 per 100,000, which was about 15.1% of all diabetes inpatients, 3.4% of GP registered diabetes population in Birmingham.

The prevalence rate of [diabetes + hypertensive diseases + asthma] was 51.5 per 100,000, which was about 4.9% of all diabetes inpatients, 1.1% of GP registered diabetes population in Birmingham.

The prevalence rate of [diabetes + CHD + asthma] was 26.6 per 100,000, which was about 2.5% of all hospital diabetes inpatients, 0.6% of GP registered diabetes population in Birmingham.

HOB tPCT had the highest prevalence rates of all the three-way comorbidities with diabetes.

JSNA LTCs Final Version

62


Table 7.6

Prevalence of three-way co-morbidities with diabetes by PCT, Birmingham, 2006/07 N

% out of all diabetes inpatients (persons)*

[Diabetes + hypertensive diseases + CHD]

1605

SB PCT

412

HOB tPCT

15.1%

% out of QOF diabetes prevalence**

Crude prevalence rate (per 100,000)***

3.4%

159.5

12.6%

3.0%

122.6

634

17.7%

4.0%

234.8

BEN PCT

559

14.7%

3.2%

139.7

[Diabetes + hypertensive diseases + asthma]

518

1.1%

51.5

SB PCT

136

4.2%

1.0%

40.5

HOB tPCT

232

6.5%

1.5%

85.9

BEN PCT

150

4.0%

0.9%

37.5

[Diabetes + CHD + asthma]

268

0.6%

26.6

SB PCT

54

1.6%

0.4%

16.1

HOB tPCT

115

3.2%

0.7%

42.6

BEN PCT

99

2.6%

0.6%

24.7

4.9%

2.5%

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

7.5.3.

CKD

Out of all the people who were identified as with multiple LTCs (27,485) in Birmingham in the year 2006/07, 7.1% (1,957) of them were with CKD. The most common co morbidities (i.e. top three) with CKD were: hypertensive diseases, diabetes and CHD. Table 7.7 shows the top three co morbidities (i.e. hypertensive diseases, diabetes and CHD) with CKD by PCT in Birmingham.

JSNA LTCs Final Version

63


Table 7.7

Top three co morbidities with CKD by PCT, Birmingham, 2006/07

Hypertensive diseases

N

% out of all CKD inpatients (persons)*

758

29.2%

% out of QOF CKD prevalence**

Crude prevalence rate (per 100,000)***

3.0%

75.3

SB PCT

238

29.6%

2.1%

70.8

HOB tPCT

251

38.0%

5.2%

92.9

BEN PCT

269

23.8%

2.9%

67.2

2.4%

61.2

Diabetes

616

23.7%

SB PCT

190

23.7%

1.7%

56.5

HOB tPCT

197

29.8%

4.1%

72.9

BEN PCT

229

20.2%

2.5%

57.2

2.0%

51.6

CHD

519

20.0%

SB PCT

197

24.5%

1.7%

58.6

HOB tPCT

116

17.6%

2.4%

43.0

BEN PCT

206

18.2%

2.2%

51.5

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

Table 7.7 shows that: â&#x20AC;˘

Hypertensive diseases were the most prevalent co morbidity with CKD in Birmingham, with 758 people identified as having both CKD and hypertensive diseases. This accounted for 29.2% of all CKD inpatients, 3.0% of all GP registered CKD prevalence in Birmingham and also equated to a crude prevalence rate of 75.3 per 100,000 population

â&#x20AC;˘

Diabetes was the second most prevalent co morbidity with CKD in Birmingham, with 616 people identified as having both diabetes and CKD. This accounted for 23.7% of all CKD inpatients, 2.4% of all GP registered CKD prevalence in Birmingham and also equated to a crude prevalence rate of 61.2 per 100,000 population

JSNA LTCs Final Version

64


CHD was the third most prevalent co morbidity with CKD in Birmingham, with 519 people identified as having both CHD and CKD. This accounted for 20.0% of all CKD inpatients, 2.0% of all GP registered CKD prevalence in Birmingham and also equated to a crude prevalence rate of 51.6 per 100,000 population

SB PCT had lower prevalence rates of [CKD + Hypertensive diseases] and [CKD + diabetes], and higher rate of [CKD + CHD] compared with Birmingham. However, as the overall prevalence of CKD was higher in SB PCT, the percentage of all the co-morbidities out of the QOF CKD prevalence was lower in SB PCT than Birmingham

HOB tPCT had higher prevalence rate of all three co morbidities with CKD, apart from the [CKD + CHD] compared with Birmingham. The percentage out of the QOF CKD prevalence was higher in HoB than Birmingham too. This was mainly due to that the overall prevalence of CKD was lower in HoB tPCT

BEN PCT had lower prevalence rate of [CKD + Hypertensive diseases] and [CKD + diabetes], and similar rate of [CKD + CHD] comparing with Birmingham. The percentage of the co morbidities out of the QOF CKD prevalence was similar between BEN PCT and Birmingham

The co morbidities with CKD (as shown in Table 7.7) were further investigated into and prevalence of three-way co morbidities was calculated, as shown in Table 7.8. It shows that in 2006/07 •

The prevalence rate of [CKD + hypertensive diseases + diabetes] was 25.9 per 100,000, which was about 1.0% of GP registered CKD population in Birmingham.

The prevalence rate of [CKD + hypertensive diseases + CHD] was 17.4 per 100,000, which was about 0.7% of GP registered CKD population in Birmingham.

The prevalence rate of [CKD + diabetes + CHD] was 16.1 per 100,000, which was about 0.6% of GP registered CKD population in Birmingham.

HOB tPCT had the highest prevalence rate of the [diabetes + hypertensive diseases + CKD]. Prevalence rate of all the other three-way co morbidities were similar across all three PCTs.

JSNA LTCs Final Version

65


Table 7.8

Prevalence of three-way co-morbidities with CKD by PCT, Birmingham, 2006/07 N

% out of all CKD inpatients (persons)*

[Diabetes + hypertensive diseases + CKD]

261

SB PCT

76

HOB tPCT

10.1%

% QOF CKD prevalence**

Crude prevalence rate (per 100,000)***

1.0%

25.9

9.5%

0.7%

22.6

104

15.8%

2.2%

38.5

BEN PCT

81

7.2%

0.9%

20.2

[CKD + hypertensive diseases + CHD]

175

0.7%

17.4

SB PCT

57

7.1%

0.5%

17.0

HOB tPCT

49

7.4%

1.0%

18.1

BEN PCT

69

6.1%

0.7%

17.2

[CKD + CHD + Diabetes]

162

0.6%

16.1

SB PCT

53

6.6%

0.5%

15.8

HOB tPCT

47

7.1%

1.0%

17.4

BEN PCT

62

5.5%

0.7%

15.5

6.7%

6.2%

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

7.5.4.

Prevalence of co-morbidities of vascular diseases in HoB tPCT from primary care data

Primary care data on LTCs were extracted from 60 General Practices (out 80 in total) in HoB tPCT area on a database system called ‘Deadly Trio’. Data presented in this section are from the ‘Deadly Trio’ system on co-morbidities of vascular diseases in HoB tPCT area. Primary care data is a more suitable source for estimating the prevalence of multiple LTCs, in comparison with secondary care data source. As expected, prevalence reported from the primary care data is higher than that from the secondary care data sources. A project aiming to extract primary care data from all GP practices in Birmingham was planned when the report was written. This together with the secondary care data source (i.e. HES) will provide a better base for more accurate estimate of the prevalence of people with multiple LTCs. JSNA LTCs Final Version

66


7.5.4.1. Prevalence of vascular diseases in HoB tPCT Table 7.9 shows the prevalence of common vascular diseases in people above the age of 40 in HoB tPCT. It shows that hypertension (32%), diabetes (16%) and CHD (7%) are highly prevalent in HoB tPCT area. Table 7.9

Prevalence of cardiovascular diseases in people above the age of 40, HoB tPCT, 2007 and 2008

Disease or condition

Numbers in 2007

% out of age

Numbers in 2008

% out of age

Atrial Fibrillation

1452

1.64%

1476

1.65%

CHD

6655

7.53%

6655

7.44%

CKD

4653

5.27%

5935

6.63%

13396

15.16%

14427

16.12%

Heart Failure

1441

1.63%

1362

1.52%

Hyperlipidaemia

2760

3.12%

2813

3.14%

27938

31.62%

28824

32.21%

Diabetes

Hypertension Data source: HoB tPCT Deadly trio database

7.5.4.2. Two way co-morbidities of vascular diseases in HoB tPCT Table 7.10 to Table 7.13 shows the common two way co morbidities with CHD, atrial fibrillation, CKD and diabetes. Table 7.10 Co-morbidities with CHD in people above the age of 40, HoB tPCT, 2007 and 2008

Disease or condition

Numbers in 2007

% out of age

Numbers in 2008

% out of age

CHD & CKD

1270

1.44%

1524

1.70%

CHD & Diabetes

2452

2.77%

2612

2.92%

CHD & Heart Failure

844

0.96%

805

0.90%

CHD & Hyperlipidameia

795

0.90%

761

0.85%

CHD and AF

534

0.6%

535

0.6%

4628

5.24%

4657

5.20%

CHD & Hypertension Data source: HoB tPCTDeadly trio database

JSNA LTCs Final Version

67


Table 7.11 Co-morbidities with atrial fibrillation in people above the age of 40, HoB tPCT, 2007 and 2008

Disease or condition

Numbers in 2007

% out of age

Numbers in 2008

% out of age

Af & CHD

534

0.60%

535

0.60%

AF & CKD

346

0.39%

418

0.47%

AF & Diabetes

380

0.43%

415

0.46%

AF & Heart Failure

404

0.46%

364

0.41%

AF & Hyperlipidameia

101

0.11%

115

0.13%

1025

1.16%

1054

1.18%

AF& Hypertension Data source: HoB tPCT Deadly trio database

Table 7.12 Co-morbidities with CKD in people above the age of 40, HoB tPCT, 2007 and 2008

Disease or condition CKD & Diabetes

Numbers in 2007

% out of age

Numbers in 2008

% out of age

1988

2.25%

2481

2.77%

CKD & Heart Failure

478

0.54%

528

0.59%

CKD & Hypertension

3662

4.14%

4665

5.21%

359

0.41%

456

0.51%

CKD & Hyperlipidameia Data source: HoB tPCT Deadly trio database

Table 7.13 Co-morbidities with Diabetes in people above the age of 40, HoB tPCT, 2007 and 2008

Disease or condition

Numbers in 2007

% out of age

Numbers in 2008

% out of age

Diabetes & Heart Failure

571

0.65%

585

0.65%

Diabetes & Hyperlipidameia

949

1.07%

993

1.11%

8486

9.60%

9139

10.21%

Diabetes & Hypertension Data source: HoB tPCT Deadly trio database

JSNA LTCs Final Version

68


7.5.4.3. Three-way co-morbidities of vascular diseases in HoB tPCT Table 7.14 shows the three way co-morbidities of vascular diseases in people above the age of 40 in HoB tPCT area. Table 7.14 Three way co-morbidities of cardiovascular diseases in people above the age of 40, HoB tPCT, 2007 and 2008 2007 Condition

2008

Prevalence

Prevalence rate (%)

Prevalence

Prevalence rate (%)

Af & CHD & CKD

172

0.19%

189

0.21%

AF & Chd & Diabetes

171

0.19%

189

0.21%

Af & CHD & H F

230

0.26%

208

0.23%

65

0.07%

74

0.08%

Af & CHD & Hypertension

407

0.46%

423

0.47%

CHD & CKD & Diabetes

589

0.67%

733

0.82%

CHD & CKD & HF

322

0.36%

350

0.39%

CHD & CKD & HD

153

0.17%

193

0.22%

CHD & CKD & HT

1024

1.16%

1255

1.40%

183

0.21%

237

0.26%

82

0.09%

85

0.09%

Af & CHD & hyperlipidaemia

CKD & Diabetes &HD Diabetes & Heart Failure & CHD Data source: HoB tPCT Deadly trio database

7.5.5.

COPD

Out of all the people who were identified as with multiple LTCs (27,485) in Birmingham in the year 2006/07, 10.4% (2,854) of them were with COPD. The most common co morbidities (i.e. top three) with COPD were: hypertensive diseases, CHD and mental illness. Table 7.15 shows the top three co morbidities (i.e. hypertensive diseases, CHD and mental illness) with COPD, as well as the three-way co-morbidity of [COPD + hypertension + CHD] by PCT in Birmingham.

JSNA LTCs Final Version

69


Table 7.15 Top three co morbidities with COPD by PCT, Birmingham, 2006/07 % out of all COPD inpatients (persons)*

N Hypertensive diseases

1144

32.8%

% out of QOF COPD prevalence**

Crude prevalence rate (per 100,000)***

8.3%

113.7

SB PCT

376

32.5%

6.6%

111.9

HOB tPCT

336

42.8%

15.9%

124.4

BEN PCT

432

27.9%

7.3%

108.0

6.7%

91.8

CHD

924

26.5%

SB PCT

315

27.2%

5.5%

93.7

HOB tPCT

227

28.9%

10.7%

84.1

BEN PCT

382

24.7%

6.4%

95.5

3.9%

53.8

Mental illness

541

15.5%

SB PCT

219

18.9%

3.8%

65.2

HOB tPCT

116

14.8%

5.5%

43.0

BEN PCT

206

13.3%

3.5%

51.5

[COPD + hypertension + CHD]

391

2.8%

38.9

SB PCT

127

11.0%

2.2%

37.8

HOB tPCT

124

15.8%

5.9%

45.9

BEN PCT

140

9.0%

2.4%

35.0

11.2%

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

Table 7.15 shows that: â&#x20AC;˘

Hypertensive diseases were the most prevalent co morbidity with COPD in Birmingham, with 1,144 people identified as having both COPD and hypertensive diseases. This accounted for 32.8% of all COPD inpatients, 8.3% of all GP registered COPD prevalence in Birmingham and also equated to a crude prevalence rate of 113.7 per 100,000 population

JSNA LTCs Final Version

70


CHD was the second most prevalent co morbidity with COPD in Birmingham, with 924 people identified as having both COPD and mental illness. This accounted for 26.5% of all COPD inpatients, 6.7% of all GP registered COPD prevalence in Birmingham and also equated to a crude prevalence rate of 91.8 per 100,000 population

Mental illness was the third most prevalent co morbidity with COPD in Birmingham, with 541 people identified as having both COPD and mental illness. This accounted for 15.5% of all COPD inpatients, 3.9% of all GP registered COPD prevalence in Birmingham and also equated to a crude prevalence rate of 53.8 per 100,000 population

SB PCT had similar prevalence rates of [COPD + Hypertensive diseases] and [COPD + CHD] to Birmingham. The prevalence rate of [COPD + mental illness] was higher in SB PCT than in Birmingham. However, as the overall prevalence of COPD was higher in SB PCT, the percentage of all the comorbidities out of the QOF COPD prevalence was lower in SB PCT than Birmingham

HOB tPCT had higher prevalence rate of all [COPD + hypertensive diseases] but lower rates of the other two. The percentage out of the QOF COPD prevalence was higher in HoB than Birmingham. This was mainly due to that the overall prevalence of COPD was lower in HoB tPCT

BEN PCT had similar prevalence rate of all three co-morbidities with COPD with Birmingham. The percentage of the co morbidities out of the QOF COPD prevalence was similar between BEN PCT and Birmingham too.

The prevalence rate of the three-way co-morbidity of [COPD + hypertension + CHD] in Birmingham was 38.9 per 100,000. It was higher in HoB tPCT.

7.5.6.

Asthma

Out of all the people who were identified as with multiple LTCs (27,485) in Birmingham in the year 2006/07, 17.5% (4,822) of them were with asthma. The most common co morbidities (i.e. top three) with COPD were: hypertensive diseases, diabetes and CHD. Table 7.16 shows the top three co morbidities (i.e. hypertensive diseases, diabetes and CHD) with asthma by PCT in Birmingham. It shows that: •

Hypertensive diseases were the most prevalent co morbidity with asthma n Birmingham, with 2,104 people identified as having both asthma and hypertensive diseases. This accounted for 22.4% of all asthma inpatients, 3.2% of all GP registered asthma prevalence in Birmingham and also equated to a crude prevalence rate of 209.1 per 100,000 population

Diabetes was the second most prevalent co morbidity with asthma in Birmingham, with 1003 people identified as having both asthma and diabetes. This accounted for 10.7% of all asthma inpatients, 1.5% of all GP registered asthma prevalence in Birmingham and also equated to a crude prevalence rate of 99.7 per 100,000 population

JSNA LTCs Final Version

71


CHD was the third most prevalent co morbidity with asthma in Birmingham, with 1000 people identified as having both asthma and CHD. This accounted for 10.6% of all asthma inpatients, 1.5% of all GP registered asthma prevalence in Birmingham and also equated to a crude prevalence rate of 99.4 per 100,000 population

Table 7.16 Top three co morbidities with asthma by PCT, Birmingham, 2006/07

Hypertensive diseases

N

% out of all asthma inpatients (persons)*

2104

22.4%

% QOF Asthma prevalence**

Crude prevalence rate (per 100,000)***

3.2%

209.1

SB PCT

725

22.7%

3.1%

215.7

HOB tPCT

740

25.7%

4.2%

274.0

BEN PCT

639

19.2%

2.5%

159.7

1.5%

99.7

Diabetes

1003

10.7%

SB PCT

272

8.5%

1.2%

80.9

HOB tPCT

412

14.3%

2.3%

152.6

BEN PCT

319

9.6%

1.2%

79.7

1.5%

99.4

CHD

1000

10.6%

SB PCT

297

9.3%

1.3%

88.4

HOB tPCT

321

11.2%

1.8%

118.9

BEN PCT

382

11.5%

1.5%

95.5

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

Table 7.16 also shows that: •

SB PCT had higher prevalence rates of [asthma + Hypertensive diseases] but lower rate of [asthma + diabetes] and [asthma + CHD], in comparison to Birmingham. The percentage of all the co-morbidities out of the QOF asthma prevalence was similar in SB PCT and in Birmingham

HOB tPCT had higher prevalence rate of all three co-morbidities with asthma. The percentage out of the QOF asthma prevalence was also higher in HoB than Birmingham.

JSNA LTCs Final Version

72


â&#x20AC;˘

BEN PCT had lower prevalence rate of all three co-morbidities with asthma than Birmingham. The percentage of the co morbidities out of the QOF asthma prevalence was similar between BEN PCT and Birmingham.

The prevalence of three-way co-morbidities with asthma was very low and it is not reported here. Details of the top 20 co-morbidities with asthma can be found in Appendix H.

7.5.7.

Epilepsy

Out of all the people who were identified as with multiple LTCs (27,485) in Birmingham in the year 2006/07, 4.7% (1,304) of them were with epilepsy. The most common co morbidities (i.e. top three) with COPD were: mental illness, hypertensive diseases and asthma. Table 7.11 shows the top three co morbidities (i.e. hypertensive diseases, diabetes and CHD) with asthma by PCT in Birmingham. Table 7.17 Top three co morbidities with epilepsy by PCT, Birmingham, 2006/07

Mental illness

N

% out of all epilepsy inpatients (persons)*

513

26.1%

% QOF epilepsy prevalence**

Crude prevalence rate (per 100,000)***

8.0%

51.0

SB PCT

177

27.1%

7.5%

52.7

HOB tPCT

183

33.0%

14.0%

67.8

BEN PCT

153

20.2%

5.6%

38.2

5.4%

34.6

Hypertensive diseases

348

17.7%

SB PCT

121

18.5%

5.1%

36.0

HOB tPCT

105

19.0%

8.0%

38.9

BEN PCT

122

16.1%

4.5%

30.5

3.4%

21.4

Asthma

215

10.9%

SB PCT

74

11.3%

3.1%

22.0

HOB tPCT

57

10.3%

4.4%

21.1

BEN PCT

84

11.1%

3.1%

21.0

* Percentage out of HES 2006/07 inpatients (persons) ** Percentage out of QOF prevalence 2006/07 *** Percentage out of ONS population estimate mid 2006 Data source: HES 2006/07 PHIT calculation

Table 7.17 shows that: JSNA LTCs Final Version

73


â&#x20AC;˘

Mental illness was the most prevalent co morbidity with epilepsy in Birmingham, with 513 people identified as having both epilepsy and mental illness. This accounted for 26.1% of all epilepsy in patients, 8.0% of all GP registered epilepsy prevalence in Birmingham and also equated to a crude prevalence rate of 50.1 per 100,000 population

â&#x20AC;˘

Hypertensive diseases were the second most prevalent co morbidity with epilepsy in Birmingham, with 348 people identified as having both epilepsy and hypertensive diseases. This accounted for 17.7% of all epilepsy inpatients, 5.4% of all GP registered epilepsy prevalence in Birmingham and also equated to a crude prevalence rate of 34.6 per 100,000 population

â&#x20AC;˘

Asthma was the third most prevalent co morbidity with epilepsy in Birmingham, with 215 people identified as having both epilepsy and asthma. This accounted for 10.9% of all epilepsy inpatients, 3.4% of all GP registered epilepsy prevalence in Birmingham and also equated to a crude prevalence rate of 21.4 per 100,000 population

The prevalence of three-way co-morbidities with epilepsy was very low and it is not reported here. Details of the top 20 co-morbidities with epilepsy can be found in Appendix H.

JSNA LTCs Final Version

74


8. Coronary heart disease Key messages for commissioners Key findings: • CHD prevalence rate in Birmingham is close to national average except in HoB tPCT, according to QOF where it is lower. • Prevalence of CHD is associated with age, gender, smoking, obesity, hypercholesterolaemia, diabetes, hypertension and social deprivation. • Prevalence of CHD is likely to increase slightly in 2020, based on a projection based on the APHO CHD predicting model which takes gender, ethnic group, age group, smoking status and deprivation into account. Issues raised from this study: • The low QOF prevalence rate in HoB tPCT could be due to its relatively younger population however this needs further investigation. • The prevalence rate of CHD suggested by the Health Survey for England (which the APHO CHD predicting model based on) is much higher than QOF prevalence. This needs further investigation. • For a more accurate projection of future QOF prevalence, a model that takes all risk factors for CHD into account is needed. Big issues for management of CHD: • The screening and management of atrial fibrillation. • Unknown effects of vascular check programme on drug budgets and diagnostic services. • Maintenance of registers. • Ability to analyse and share data across primary and secondary care. Care Quality Commission states that CVD is the country’s biggest killer, causing more that 200,000 deaths a year, representing one in three deaths. The UK has one of highest rates of CVD in Europe (CQC – Closing the gap, September 2009) Coronary heart disease is a condition that affects the blood supply to heart muscle. It occurs when fatty deposits (atheroma) are laid down in the artery walls. These deposits build up, resulting in a narrowing of the artery and a reduction in the supply of blood to the heart muscle. (BHF 2009) Risk of CHD increases with age, smoking, hypercholesterolaemia (high cholesterol levels), diabetes, hypertension (high blood pressure) and is more common in men and those who have close relatives with ischaemic heart disease. CHD includes angina, myocardial infarction (MI) asymptomatic coronary disease or sudden cardiac death secondary to CHD. As described in Chapter 5, there were 1,661 premature deaths (i.e. death under 75s) from CHD in Birmingham during 2005 – 2007. This accounted for 16.7% of all premature deaths over the period. The majority of the deaths were from male (1,260; 76%). This also gives approx 553 premature deaths from CHD in Birmingham every year. Compared with the national average, the mortality rate in Birmingham was higher for both males (43% higher) and females (29% higher).

JSNA LTCs Final Version

75


This chapter investigates the prevalence of CHD in Birmingham and the PCTs. It also projects future prevalence based on current distribution patterns of CHD in terms of demographics, deprivation, lifestyle and clinical risk factors. Data presented in this chapter are from two major sources: QOF and Health Survey for England. APHO CHD predicting model is used for the projection.

8.1. Definitions For the purpose of this study, two categories of disease prevalence for CHD were used: •

Doctor diagnosed CHD prevalence: this is prevalence of doctor diagnosed CHD prevalence. Usually this prevalence counts in Individuals with symptomatic manifestations of coronary atherosclerosis (i.e. sudden cardiac collapse, acute MI, unstable angina, exertional angina and heart failure).

Estimated CHD prevalence based on the ‘risk profile’ of the population: this is prevalence based on the estimation of the population’s risk profile in terms of the prevalence of risk factors of getting CHD in the population. This prevalence includes asymptomatic population and those who are not diagnosed.

8.2. Current CHD prevalence and trends This part describes the prevalence of CHD based on data collected from QOF and HsfE.

8.2.1.

QOF prevalence

Figure 8.1 shows QOF prevalence trend for CHD in the three PCTs in Birmingham in comparison with Birmingham average and England, from 2004/05 to 2007/08. QOF prevalence of CHD in the year 2007/08 suggests that: •

There were 35,081 people in Birmingham who were on the CHD register in the year 2007/08. 12,244 of them were in SB PCT, 7,137 in HoB tPCT and 15,700 in BEN PCT

The prevalence rate of CHD was 3.09% in Birmingham, which was slightly lower than the England’s rate (3.50%)

CHD prevalence rate in SB PCT (3.19%) was slightly higher than Birmingham but lower than England

CHD prevalence rate in HoB tPCT (2.29%) was lower than both Birmingham and England

CHD prevalence rate in BEN PCT (3.58%) was higher than both Birmingham and England.

JSNA LTCs Final Version

76


Figure 8.1

Trend of QOF unadjusted prevalence of CHD, Birmingham, PCTs and England, 2004/05 to 2007/08

4.00%

3.50%

3.00%

2.50%

2.00% 2004/05 SB

2005/06 HOB

BEN

2006/07 Birmingham

2007/08 England

Data source: QOF

The trend of CHD prevalence from year 2004/05 to 2007/08 in Figure 8.1 suggests that: •

CHD prevalence rate had decreased slightly both nationally and locally

Birmingham prevalence had decreased by 5.5%, from 3.27% in 2004/05 to 3.09% in 2007/08. This decrease was larger than the national average (2.2%)

CHD prevalence in SB PCT had decreased by 5.6%, from 3.38% in 2004/05 to 3.19% in 2007/08. This decrease was larger than both Birmingham and national average

CHD prevalence in HOB tPCT had decreased by 3.0%, from 2.36% in 2004/05 to 2.29% in 2007/08. The decrease was smaller than Birmingham but larger than national average

CHD prevalence in BEN PCT had decreased by 6.3%, from 3.82% in 2004/05 to 3.58% in 2007/08. The decrease was bigger than both Birmingham and national average.

8.2.2.

Prevalence based on the Health Survey for England

As part of the Health Survey for England (HsfE), a special survey on cardiovascular disease and risk factors is conducted every three or four years. There have been four surveys on cardiovascular disease conducted so far in the years 1994, 1998, 2003 and 2006. Data from the HsfE (Figure 8.2) suggest that in England:

JSNA LTCs Final Version

77


Prevalence of CHD in 2006 was 6.5% in men and 4.0% in women

From 1994 to 2006, the prevalence of CHD in men had increased by 8.3% (from 6.0% to 6.5%); the prevalence in women had decreased by 2.4% (from 4.1% to 4.0%)

From 2003 to 2006, the prevalence of CHD in men had decreased by 12.2% (from 7.4% to 6.5%) and CHD in women had decreased by 11.1% (from 4.5% to 4.0%)

Compared with the prevalence data collected from QOF, the HsfE data suggest higher prevalence of CHD, as well as sharper decrease in the prevalence in recent years (i.e. from 2003 to 2006). Figure 8.2

Prevalence of CHD* by gender, England, 1994 – 2006

8.0

7.4

Percentage of people with CHD

7.1 7.0

6.5 6.0

6.0 4.6

5.0

4.5

4.1

4.0

4.0 3.0 2.0 1.0 0.0 1994

1998

2003

2006

Year Men

Women

* Adults aged 16 and over Unweighted data for all years Data source: www.heartstats.org Health Survey for England. Cardiovascular disease and risk factors 1994, 1998, 2003 and 2004

8.3. Geographical distribution Figure 8.3 shows CHD prevalence by ward in Birmingham in the year 2007/08, based on QOF data. Details of the method of mapping QOF prevalence to ward are described in Section 3.4.1. It shows that in the year 2007/08: •

Prevalence of CHD was higher in the northern wards of Birmingham (i.e. BEN PCT’s catchments area) and some southern wards of Birmingham (i.e. SB PCT’s catchments area)

The prevalence was lower in central Birmingham wards (HOB tPCT’s catchments area)

JSNA LTCs Final Version

78


The geographical difference of disease prevalence is usually caused by the demographical and socio-economical variations of the areas. In the case of CHD, age of the population plays an important role. Figure 8.3

Prevalence of CHD by ward, Birmingham 2007/08

Data source: QOF PHIT calculation

8.4. Demographical patterns This part uses HsfE data to show CHD prevalence in different demographical groups nationally. It then discusses the local implications of these demographical patterns.

8.4.1.

Age and gender

Table 8.1 shows prevalence of CHD by gender and age groups in England for the years 1994, 1998, 2003 and 2006 based on data collected from the HsfE. It shows that: •

CHD prevalence was higher in males than in females

Prevalence rate increased with age with more than one in four (28.6%) men and around one in five (19.3%) women aged 75 and over living with CHD in England in 2006

Significant increase started from age 55 onwards. From the age group 45 – 54, for every move to the next 10-year age group, the prevalence rate of CHD doubled more or less.

JSNA LTCs Final Version

79


From 1994 to 2006, CHD prevalence in people aged 75 and over had increased by 25.9% in men (from 22.7% to 28.6%) and 21.4% in women (from 15.9% to 19.3%)

From 1994 to 2006, CHD prevalence in the other age groups was more or less consistent.

Table 8.1 Year

Prevalence of CHD* by gender and age group, England, 1994 – 2006 Total

16-24

25-34

35-44

45-54

55-64

65-74

75+

1994

6.0

-

0.3

0.5

3.0

10.3

21.0

22.7

1998

7.1

0.1

0.4

0.9

4.3

13.6

20.2

23.4

2003

7.4

-

-

0.9

3.5

11.1

21.5

26.4

2006

6.5

0.1

0.2

0.6

3.6

10.6

20.8

28.6

1994

4.1

0.2

0.1

0.3

2.3

5.9

10.5

15.9

1998

4.6

-

0.3

0.6

1.8

6.3

12.5

18.4

2003

4.5

0.2

-

0.4

2.0

5.9

9.7

18.4

2006

4.0

0.1

0.1

0.3

1.3

3.5

10.0

19.3

Males

Females

* Adults aged 16 and over Unweighted data for all years Data source: www.heartstats.org Health Survey for England. Cardiovascular disease and risk factors 1994, 1998, 2003 and 2004

8.4.2.

Ethnicity

The 2004 HsfE focuses specifically on the health of minority ethnic groups and provides prevalence of cardiovascular diseases (CVD) in different ethnic groups. Table 8.2 shows age adjusted prevalence of CVD by ethnic group in England, for males and females. Table 8.2 shows that in 2004 •

The prevalence of angina and heart attack was higher in Indian (4.9% and 3.9%) and Pakistani (6.9% and 4.1%) men than the general population (4.8% and 3.8%)

The prevalence of all CHD in Black African and Chinese men was much lower than in the general population

There was less ethnic variation in the prevalence of CHD in women

JSNA LTCs Final Version

80


â&#x20AC;˘

The prevalence of CHD in the Black and Minority Ethnic (BME) group women was lower than that in the general population.

Table 8.2

Age adjusted prevalence* of cardiovascular conditions by ethnic group, males England, 2004

Angina

Heart attack (MI)

Heart murmur

Abnormal Heart rhythm

Other heart trouble

Weighted base

Unweighted base

%

%

%

%

%

N

N

Males Black Caribbean

3.4

3.2

1.6

3.8

1.0

480

414

Black African

0.7

-

0.4

0.4

0.8

377

390

Indian

4.9

3.9

1.8

1.9

2.6

903

550

Pakistani

6.9

4.1

2.6

3.0

2.9

423

433

Bangladeshi

3.1

2.9

0.7

1.6

-

178

411

Chinese

1.6

0.3

1.6

3.1

0.6

151

348

Irish

4.0

3.0

2.6

4.5

1.7

1,776

497

General population**

4.8

3.8

3.1

5.1

2.8

7,202

6,602

Black Caribbean

1.5

1.4

2.7

2.8

2.3

676

653

Black African

0.5

-

1.7

2.5

1.3

476

469

Indian

3.2

1.0

1.5

3.0

1.6

1,067

634

Pakistani

2.5

1.1

1.4

2.9

1.6

499

508

Bangladeshi

2.0

0.6

1.0

2.3

1.0

208

478

Chinese

1.2

-

0.8

3.1

1.0

163

375

Irish

2.5

0.8

2.1

6.3

1.4

2,369

656

General population**

3.4

1.7

3.4

5.6

1.8

7,634

8,234

Females

* Adults aged 16 and over Age-standardised percentages (standardised risk ratio x prevalence in general population) ** HsfE 2003 data Data source: www.heartstats.org Health Survey for England. The Health of Minority Ethnic Groups 2004

JSNA LTCs Final Version

81


8.4.3.

Local implications

The population structure of Birmingham suggests that Birmingham has a relatively young population with large proportion of BME groups, as compared with the population structure of England (as described in Section 4.2). The projected demographical profile of Birmingham suggests that this young and BME characteristics of Birmingham population will continue in the next 10 years, especially in HoB tPCT and part of the BEN PCT areas. The current (and projected) population structure of Birmingham suggests two groups that higher prevalence of CHD will be seen in future: â&#x20AC;˘

Younger aged men with BME background, most of whom living in HoB tPCT and parts of BEN PCT

â&#x20AC;˘

Older aged women with White ethnic background, most of whom living in areas like SB PCT and wards like Sutton in BEN PCT.

Figure 8.4 and Figure 8.5 show estimated number of people with CHD in Birmingham by age group and PCT, for males and females (i.e. bars in the graph). The numbers were calculated by applying the CHD prevalence rate by age group for England (i.e. the pink line in the graph) from the HsfE 2006 to the age-specific population estimate from ONS mid-year population estimate 2007. Estimated numbers of people with CHD by age group and PCT, males, Birmingham, 2007

35.0

8000

30.0

7000 3347

25.0 2880

6000 5000

20.0

1430

10.0 5.0 0.0

4000

2029

15.0

1423 3000

904 27

52

170

838

24

50

116

462

26

48

141

697

16-24

25-34

35-44

45-54

1798

2000 2429

2730

65-74

75+

1000

Estimated number of people with CHD**

CHD prevalence rate (%), 2006*

Figure 8.4

0 55-64

Age group SB

HOB

BEN

CHD prevalence rate 2006

* data source: HsfE 2006 ** calculated based on applying the CHD prevalence rates to local age-specific population structure from ONS midyear population estimate 2007, PHIT calculation

JSNA LTCs Final Version

82


Figure 8.5

Estimated numbers of people with CHD by age group and PCT, females, Birmingham, 2007

25.0

9000

20.0

7000 3552

6000

15.0 5000 1379

10.0

3000

1569 5.0

0.0

26

27

88

25

22

27

309 174 267

681 321 618

1293

25

53 72

16-24

25-34

35-44

45-54

55-64

65-74

772

4000

2000 3103 1000

Estimated number of people with CHD**

CHD prevalence rate (%), 2006*

8000

0 75+

Age group SB

HOB

BEN

CHD prevalence rate 2006

* data source: HsfE 2006 ** calculated based on applying the CHD prevalence rates to local age-specific population structure from ONS midyear population estimate 2007, PHIT calculation

Figure 8.4 and 8.5 show that: •

The number of people with CHD (bars in the chart) was highly associated with age, for both males and females, across all PCTs

The estimated numbers shared similar age pattern with the prevalence rates (line in the chart).

8.5. CHD and deprivation This section investigates the relationship between CHD and social deprivation. Data presented in this part are from the ONS Key Health Statistics. Local implications of the relationship are also discussed.

8.5.1.

CHD by deprivation quintiles

Figure 8.6 shows age adjusted prevalence of treated CHD by gender and deprivation quintiles based on data collected from ONS Key Health Statistics from General Practice, 2000. It shows that: •

Prevalence of CHD increased with deprivation quintile, for both men and women

The prevalence of CHD in men was 32.3% higher in the most deprived quintile (4.1%) than in the least deprived quintile (3.1%)

JSNA LTCs Final Version

83


The prevalence of CHD in women was 52.9% higher in the most deprived quintile (2.6%) than the least deprived quintile (1.7%)

For both genders, the increase of CHD prevalence rate from the 4th to the 5th quintile was larger than the increase between any other quintiles

Figure 8.6

Age adjusted prevalence* of treated CHD by gender and deprivation quintiles, England and Wales, 1994/98

4.5

4.1

Percentage of treated CHD

4.0 3.5

3.6

3.6

3.4 3.1

3.0

2.6

2.5 2.0

2.1 1.7

2.2

1.9

1.5 1.0 0.5 0.0 Q1: least deprived

Q2

Q3

Q4

Q5: most deprived

Deprivation quintile Men

Women

* Age-standardised using the European Standard population Data source: www.heartstats.org ONS Key Health Statistics from General Practice 2000

8.5.2.

Local implications

As described in Section 4.3, Birmingham is one of the most deprived local authorities nationally and more than half of Birmingham’s population lives in the most deprived quintile (i.e. 5th quintile) nationally. The large proportion of Birmingham residents living in the 3rd, 4th and 5th quintile (more than 90%) indicates higher prevalence of CHD due to deprivation locally. Interestingly, HOB PCT, which has the largest proportion of population living in the 5th quintile, has lower prevalence of CHD (as illustrated in Figure 8.1), compared with the other two PCTs. This seems to contradict the association between social deprivation and CHD prevalence. However, the lower prevalence rate in HOB tPCT is mainly due to the reason that HOB PCT also has the youngest population in Birmingham and age is more strongly associated with the prevalence of CHD.

8.6. Lifestyle risk factors There are a number of risk factors for CHD that are related to people’s life style choices. The prevalence of these risk factors suggests the population at risk of getting CHD in future. These risk factors are usually used in predicting models to project future CHD prevalence.

JSNA LTCs Final Version

84


8.6.1.

Smoking

Smoking increases the risk of CHD. A 50-year cohort study of British doctors found that mortality from CHD is around 60% higher in smokers (and 80% higher in heavy smokers) than in non-smokers (Doll et al. 2004). Second hand smoke (smoke that has been exhaled by a smoker) is also harmful to cardiovascular health. Regular exposure to second hand smoke increases the risk of CHD by around 25% (http://www.bhf.org.uk). In developed countries, research from the World Health Organization (WHO) estimates that over 20% of CHD is due to smoking. According to the synthetic estimates based on the HsfE 2003 to 2005, smoking prevalence in Birmingham was 24.9% (as described in Section 4.5). It is slightly higher than the prevalence in West Midlands (24.0%) and England (24.1%). Smoking prevalence in Birmingham in various demographic and socio-economic groups is described in Section 4.5.1. It suggests that smoking prevalence was higher in the older age group, as well as White ethnic group and more deprived groups. The target groups of smoking related CHD should be in these groups.

8.6.2.

Diet

It is now universally recognised that a diet which is high in fat, particularly saturated fat, sodium and sugar and which is low in complex carbohydrates, fruit and vegetables increases the risk of cardiovascular disease (CVD). These risks are outlined in the World Health Organization 2003 report Diet, nutrition and the prevention of chronic diseases. The World Health Report 2002 estimated that around 4% of all disease burden in developed countries was caused by low fruit and vegetable consumption, and that just under 30% of CHD in developed countries was due to fruit and vegetable consumption levels below 600g/day (WHO 2003) The percentage of healthy eating adults in Birmingham (25.1%) is slightly lower than that of England (26.3%), as described in Section 4.5. The patterns of diet in different demographic and socio-economic groups indicate that the target group of diet related CHD locally should be in the White ethnic group (for high calorific intake), Asian and Black Caribbean (for saturated fat intake), and the more deprived groups (for unhealthy diet in general).

8.6.3.

Physical activity

People who are physically active have a lower risk of CHD. To produce the maximum benefit the activity needs to be regular and aerobic (http://www.bhf.org.uk). Recent research from the WHO highlighted the importance of physical inactivity as a major risk factor for CHD. The 2002 World Health Report estimated that that over 20% of CHD in developed countries was due to physical inactivity (less than 2.5 hours per week moderate intensity activity or 1 hour per week vigorous activity). The proportion of physically active adults in Birmingham (16.9%) is lower than both West Midlands (19.1%) and England (21.3%), according to the Active People Survey (http://www.sportengland.org). The physical activity patterns (as described in 4.5) suggest that the target group of CHD due to lack of physical activity will be in the older age groups and the more deprived groups areas.

JSNA LTCs Final Version

85


8.6.4.

Alcohol

While moderate alcohol consumption (one or two drinks a day) reduces the risk of CVD, at high levels of intake – particularly in ‘binges’ – the risk of CVD is increased (http://www.bhf.org.uk). The World Health Report 2002 estimates that 2% of CHD in men in developed countries is due to alcohol. However, the impact of alcohol consumption in women in developed countries is estimated to be positive – if no alcohol were consumed, there would be a 3% increase in CHD (WHO 2002). The binge drinking rate in Birmingham (17.8%) is about the same as that in West Midlands (17.9%) and England (18.0%), according to Health Survey for England. The binge drinking patterns (as described in 4.5.1) indicate that the younger age groups, males in the 65+ age group and the Irish and Black Caribbean groups should be the target group of alcohol consumption related CHD in future.

8.6.5.

Obesity

Overweight and obesity increase the risk of CHD. As well as being an independent risk factor, obesity is also a major risk factor for high blood pressure, raised blood cholesterol, diabetes and impaired glucose tolerance. The WHO’s World Health Report 2002 estimated that around a third of CHD and ischaemic stroke and almost 60% of hypertensive disease in developed countries is due to overweight. The proportion of obese adults in Birmingham (23.4%) is about the same as the national average (23.6%). However, the prevalence of obese children (i.e. Year 6 children) was at 23.1%, which is 50% higher than the national average (15.4%). The obesity patterns in population (as described in Section 4.5) suggest that the target group of future CHD due to obesity should be in children and young people and the Black ethnic groups.

8.7. Clinical risk factors There are a number of clinical risk factors for CHD, including hypertension, raised serum cholesterol levels and diabetes mellitus (http://www.bhf.org.uk). This part investigates these clinical risk factors for CHD locally.

8.7.1.

Blood pressure

Risk of CHD is directly related to both systolic and diastolic blood pressure levels. The World Health Report 2002 estimates that around 11% of all disease burden in developed countries is caused by raised blood pressure, and that over 50% of CHD in developed countries is due to systolic blood pressure levels in excess of the theoretical minimum (115mmHg) (http://www.bhf.org.uk). Figure 8.7 shows the trend of hypertension prevalence in Birmingham, the PCTs and England during the period 2004/05 to 2007/08, based on QOF data. It shows that: •

Hypertension was a high prevalent condition nationally with 12.8% of England’s population with hypertension in 2007/08.

The prevalence of hypertension had increased both locally and nationally during the 4-year period from 2004/05 to 2007/08.

JSNA LTCs Final Version

86


In the year 2007/08, the prevalence rate in Birmingham (11.9%) was lower than the England’s rate (12.8%), so was the three PCTs with SB PCT at 12.3%, HoB tPCT at 10.2% and BEN PCT at 12.7%.

Figure 8.7

Hypertension prevalence Birmingham, PCTs and England, 2004/05 – 2007/08

14.00% 13.00% 12.00% 11.00% 10.00% 9.00% 8.00% 2004/05 SB

2005/06 HOB

BEN

2006/07

2007/08

Birmingham

England

Data source: QOF

The QOF prevalence for Birmingham and the PCTs seems to suggest that hypertension was not a local issue particularly. However, as suggested by premature death rates of hypertensive diseases (described in 5.4), HoB tPCT had very high premature death rate (more than doubled of the national average), which suggested that the QOF prevalence for HoB tPCT could be underestimated. In addition, QOF prevalence does not break down by the severity of the condition however the different patterns between prevalence and death could be that although HoB tPCT had an overall lower prevalence of hypertension, it might had larger proportion of more severe hypertensive patients. Looking at the prevalence of co-morbidities with hypertension with its medical complications such as CHD, as described in Section 8.5.4, the prevalence (estimated from data collected from primary care) of comorbidities with hypertension was high in HoB tPCT area, this also indicate the high severity of hypertension in this area. In addition, the demographical and socio-economical distribution patterns of hypertension (based on the Health Survey for England) suggest that: •

Hypertension was highly associated with age.

Hypertension prevalence was not correlated with income in males, but negatively correlated with income in females, with higher prevalence in the lower income groups.

Hypertension was higher prevalent in Black Caribbean, Irish men and Indian men, compared to the general population.

JSNA LTCs Final Version

87


Local implications of these patterns are that the current lower prevalence (than the national average) was probably due to the relatively young population of Birmingham. However, the local target groups for hypertension such as the low income females, Black Caribbean and Indian men will bring burden of CHD in future.

8.7.2.

Blood cholesterol

Risk of CHD is directly related to blood cholesterol levels. Blood cholesterol levels can be reduced by drugs, physical activity and by dietary changes, in particular a reduction in the consumption of saturated fat (http://www.bhf.org.uk/). The World Health Report 2002 (WHO 2002) estimates that over 60% of CHD in developed countries is due to total blood cholesterol levels in excess of the theoretical minimum (3.8mmol/l). The demographical and socio-economical distribution patterns of high levels of blood cholesterol (i.e. 5.0mmol/l and over) (based on the Health Survey for England) suggest that: •

Blood cholesterol level was more prevalent in males in younger age groups (up to 44) and in females in older age groups (45 onwards), with the highest prevalence seen in age group 45-64, for both males and females.

Blood cholesterol level was not correlated with income.

Blood cholesterol levels were higher in White ethnic group than the BME group.

These distribution patterns of blood cholesterol levels do not suggest any particular concerns locally, as Birmingham population is characterised by deprivation and BME group. However, the age distribution suggests that certain areas of Birmingham still need to be targeted as potential high blood cholesterol population.

8.7.3.

Diabetes

Diabetes substantially increases the risk of CHD. Men with non-insulin dependent (Type 2) diabetes have a two to four fold greater annual risk of CHD, with an even higher (three to fivefold) risk in women with Type 2 diabetes (http://www.bhf.org.uk). Diabetes not only increases the risk of CHD but also magnifies the effect of other risk factors for CHD such as raised cholesterol levels, raised blood pressure, smoking and obesity. Local prevalence of diabetes is high, especially in HoB tPCT area which indicates burden of CHD caused by diabetes locally. Details of local diabetes prevalence are described in Chapter 9 of the report.

8.8. Projected CHD prevalence An individual’s probability of developing CHD is predicted by a combination of factors including age, gender, smoking, blood pressure, cholesterol levels, diabetes mellitus and a previous history of atherosclerotic disease. This section describes a CHD prevalence model developed by the Association of Public Health Observatories (APHO) and the projected CHD prevalence for Birmingham up to 2020 based on the model.

JSNA LTCs Final Version

88


8.8.1.

The APHO CHD Local Model

The APHO model was recommended by the JSNA guideline as a tool to predict future prevalence of diseases locally (DOH 2007b). This is a regression model using factor data collected from HsfE to predict the outcome of interest as ‘patient-reported doctor-diagnosed CHD’ (called IHD in HsfE), which is also the variable used for CHD prevalence in HsfE. Three logistic regression models were built taking various predictors into account. The Local Model recommended to be used for local CHD prevalence prediction as data on predictors were available at local authority and PCT level. The five predictors in the model are: • • • • •

Gender Ethnic group Age group Smoking status Deprivation

Demographic data (i.e. gender and age group) used to construct the model was collected from HsfE. Ethnicity data was collected from the HsfE 2004. The HsfE 2004 was the last survey to include an ethnic minority boost, and the boost sample was used for the modelling. However there were relatively small numbers of whites in the HsfE 2004 sample, and they were not asked to respond to many questions, including those on CHD, presumably to save resources for the boost itself. The HsfE 2004 boost sample was therefore merged with the HsfE 2003, which was the year with the largest number of identical variables. Deprivation data was collected from the IMD 2004 LA and PCT level scores. Baseline smoking status was collected from the synthetic estimates of life style based on the HsfE. Assumptions on the change of smoking prevalence were allowed to make to project CHD prevalence based on different assumptions of the future change of smoking prevalence. Details of the regression model are shown in Table C1 in Appendix C. In addition to the local model, the APHO also created a Complete Model which includes other predictors as BMI, diabetes, family history of CVD, previous experience of angina and MI, education and hypertension status. However, as many of these data are not available locally, this model cannot be used for local projection.

8.8.2.

CHD Projections

Three scenarios of future smoking prevalence in the population in Birmingham were given to make projections of CHD prevalence: •

Scenario 1: No decline in smoking – assumes that 2008 prevalence of 25.2% for all three PCTs and Birmingham LA. No change over time. Use weighted distribution of smoking by age and gender England (HsfE 2005) to give local distribution, same smoking patterns in all ethnic groups. Assume ex-smoking rate is same as England (HsfE 2005)

Scenario 2: decline in smoking prevalence of 0.4% per year. In all age-gender groups, ex-smoking prevalence increases to match decrease in smoking prevalence. Use weighted distribution of smoking by age and gender England (HsfE 2005) to give local distribution. Same smoking patterns in all ethnic groups. Assume baseline ex-smoking rate is same as England (HsfE 2005)

JSNA LTCs Final Version

89


â&#x20AC;˘

Scenario 3: strong effect smoking ban tapers off (i.e. 1.5% annual reduction first two years, 1.0% annual reduction the next five years, 0.5% annual reduction the final five years). In all age-gender groups, ex-smoking prevalence increases to match decrease in smoking prevalence. Use weighted distribution of smoking by age and gender England (HsfE 2005) to give local distribution. Same smoking patterns in all ethnic groups. Assume baseline ex-smoking rate is same as England (HsfE 2005).

Table 8.3 shows projected CHD prevalence in Birmingham and the three PCTs up to 2020, based on the APHO model. Table 8.3

Projected CHD prevalence in Birmingham and PCTs up to 2020 Birmingham Year

Scenario 1

Scenario 2

Scenario 3

N

%*

SB PCT N

%*

HoB tPCT N

%*

BEN PCT N

%

2008

56946

7.2%

15100

5.4%

12064

5.8%

24377

7.9%

2009

57118

7.2%

15094

5.4%

12081

5.8%

24439

7.9%

2010

57350

7.2%

15164

5.4%

12099

5.8%

24518

7.9%

2015

59390

7.2%

15723

5.5%

12597

5.9%

25323

7.9%

2020

62198

7.4%

16466

5.6%

13145

6.0%

26525

8.1%

2008

56946

7.2%

15100

5.4%

12064

5.8%

24377

7.9%

2009

57138

7.2%

15099

5.4%

12085

5.8%

24447

7.9%

2010

57390

7.2%

15175

5.4%

12108

5.8%

24535

7.9%

2015

59536

7.2%

15763

5.5%

12630

5.9%

25384

8.0%

2020

62459

7.4%

16538

5.6%

13205

6.0%

26634

8.1%

2008

56946

7.2%

15100

5.4%

12064

5.8%

24377

7.9%

2009

57193

7.2%

15114

5.4%

12098

5.8%

24470

7.9%

2010

57500

7.2%

15206

5.4%

12133

5.8%

24581

7.9%

2015

59806

7.3%

15838

5.5%

12691

5.9%

25497

8.0%

2020

62769

7.5%

16623

5.6%

13275

6.1%

26764

8.2%

* % out of persons aged 16+

Table 8.3 sows that:

JSNA LTCs Final Version

90


The projected prevalence of CHD is similar in the three scenarios of smoking change in future

The projected prevalence of CHD in 2020 in Birmingham is around 7.5% for all three scenarios. It will be about 5.6% for SB PCT, 6.1% for HoB tPCT and 8.2% for BEN PCT

Increase in the prevalence (i.e. number) of CHD in Birmingham is projected in all three scenarios, with an increase of 8.9% in scenario 1 (from 57,118 to 62,198), 9.1% in scenario 2 (from 57,138 to 62,459) and 9.7% in scenario 3 (from 57,193 to 62,769), from the year 2009 to 2020

For SB PCT, increase in the prevalence of CHD is projected in all three scenarios, with an increase of 9.1% in scenario 1(from 15,094 to 16,466), 9.5% in scenario 2 (from 15,099 to 16,538) and 10.0% in scenario 3 (from 15,114 to 16,623), from the year 2009 to 2020

For HOB tPCT, increase in the prevalence of CHD is projected in all three scenarios, with an increase of 8.8% in scenario 1 (from 12,081 to 13,145), 9.3% in scenario 2 (from 12,085 to 13,205) and 9.7% in scenario 3 (from 12,098 to 13,275), from the year 2009 to 2020

For BEN PCT, increase in the prevalence of CHD is projected in all three scenarios, with an increase of 8.5% (from 24,439 to 26,525)in scenario 1, 8.9% in scenario 2 (from 24,447 to 26,634) and 9.4% in scenario 3 (from 24,470 to 26,764) in scenario 3, from the year 2009 to 2020

Interestingly, Scenario 3 predicted slightly higher prevalence than the other two scenarios. This is due to an issue in the predicting model that the probability of getting CHD in the ex-smokers is higher than the current smokers. Details of the cause of the issue are described in Section 8.8.6.2.

8.8.3.

CHD projections by gender

Table D.1 and D.2 in Appendix D show projected CHD prevalence in Birmingham and the three PCTs for females and males, up to 2020, based on the APHO model. It shows that: •

The projected prevalence of CHD is similar in the three scenarios of smoking change in future, for both females and males

Projected CHD prevalence in males is higher than in females

The projected prevalence of CHD for females in 2020 in Birmingham is around 5.9% for all three scenarios. It will be about 4.4% for SB PCT, 4.8% for HoB tPCT and 6.5% for BEN PCT

The projected prevalence of CHD for males in 2020 in Birmingham is around 9.0% for all three scenarios. It will be about 6.9% for SB PCT, 7.4% for HoB tPCT and 10.0% for BEN PCT.

JSNA LTCs Final Version

91


8.8.4.

CHD projections by age groups

Table D.3 to Table D.6 in Appendix D show projected CHD prevalence up to 2020 for different age groups (i.e. aged 16-44, 45-64, 65-74 and 75 and above) for Birmingham and the three PCTs. The figures show that: •

The projected prevalence of CHD is similar in the three scenarios of smoking change in future, for all age groups

Projected CHD prevalence is positively associated with age, with almost one in three aged 75 and above with CHD (31%) in Birmingham by year 2020

The projected prevalence of CHD for age group 45 – 64 shows that in 2020, the figure is around 9.0% in Birmingham, for all three scenarios. It will be about 6.3% for SB PCT, 9.0% for HoB tPCT and 9.0% for BEN PCT, as shown in Table D.4 in Appendix D

The projected prevalence of CHD for age group 65 – 74 shows that in 2020, almost one in three (31%) in this age group will be with CHD in Birmingham, for all three scenarios. It will be about 17.0% for SB PCT, 23.4% for HoB tPCT and 23.2% for BEN PCT, as shown in Table D.5 in Appendix D

The projected prevalence of CHD for age group 75 and above shows that in 2020, almost one in four (23%) in this age group will be with CHD in Birmingham, for all three scenarios. It will be approx 24% for SB PCT, 31% for HoB tPCT and 31% for BEN PCT, as shown in Table D.6 in Appendix D

8.8.5.

CHD projection by ethnicity

Table D.7 to Table D.11 show projected CHD prevalence up to 2020 by ethnic groups (i.e. White, Mixed race, Black, Asian and Other ethnic group) for Birmingham and the three PCTs. The figures show that: •

The projected prevalence of CHD is similar in the three scenarios of smoking change in future, for all ethnic groups

Projected CHD prevalence is higher in the White group (approx 9%) than other ethnic groups in 2020. This is probably due to the fact that the White group has older populations compared to the other groups in Birmingham.

The projected prevalence of CHD for White ethnic group shows that in 2020, the figure is approx 9% in Birmingham, for all three scenarios. It will be about 6% for SB PCT, 8% for HoB tPCT and 9% for BEN PCT, as shown in Table D.7 in Appendix D

The projected prevalence of CHD for Black ethnic group shows that in 2020 the prevalence will be approx 4% for Birmingham, HoB tPCT and BEN PCT. SB will have a lower prevalence of 2% in the Black population, as shown in Table D.9 in Appendix D. The difference in terms of prevalence rate in Black population is very different between SB PCT and the rest of Birmingham

The projected prevalence of CHD for Asian ethnic group shows that in 2020, the prevalence will be similar across all three PCTs in Birmingham, with

JSNA LTCs Final Version

92


Birmingham 5.6%, SB PCT 4.1%, HoB tPCT 5.2% and BEN PCT 5.0%, as shown in Table D.10 in Appendix D It is worth noticing that these figures are not adjusted by age, therefore, the difference between ethnicity shown in tables D.7 to D.11 in Appendix D should be considered in combination of the age of population of the ethnic groups.

8.8.6.

Limitations of the model and projections

The APHO predicting model of CHD prevalence (i.e. the Local Model) takes into consideration age, gender, ethnicity, deprivation and smoking status of the population. It is a useful and easy to use tool for local projections of future CHD prevalence in Birmingham and PCTs. However there are several issues that can affect the accuracy of the projection using this model. These issues are described below.

8.8.6.1. Predictors in the model The APHO local model for CHD prevalence does not include the life style risk factors (other than smoking) and the clinical risk factors, as described in this chapter. Missing these predictors can affect the result of the prediction. Using diabetes as an example, the CHD projection for Birmingham can be underestimated as diabetes was not considered and it is a highly prevalent condition locally. Nevertheless, the exclusion of these predictors is mainly due to the data availability issue locally. To get a more accurate prediction, locally data on prevalence of the life style and clinical risk factors for CHD need to be collected.

8.8.6.2. CHD prevalence in the ex-smokers The result from the three smoking scenarios gives an unexpected pattern between CHD prevalence and smoking. It predicts that the CHD prevalence is higher when there is more reduction in smoking. This seems to suggest that smoking is a ‘protective factor’ rather than a risk factor for CHD, which contradicts all the previous studies on smoking’s impact on heart diseases. The reason for this ‘odd’ pattern of CHD vs. smoking is that the model is built based on data collected from the HsfE and the variable used is ‘self-reported doctor diagnosed CHD’. However, there is a bias in this variable as many people tend to give up smoking after they are diagnosed with CHD. This group of people then become ex-smokers with CHD. As a result, a higher probability CHD is given to the ex-smokers than the current smokers in the predicting model. In the scenarios used in the projection, all the reduction in smoking was considered as current smokers becoming ex-smokers. Therefore more reduction in smoking predicts higher prevalence in CHD. This issue has been raised with the authors of the model at APHO and hopefully it can be addressed in future versions of the model.

8.8.6.3. Variation in deprivation Deprivation quintile was a predictor used in the model. According to the IMD 2007, Birmingham LA, HoB tPCT and BEN PCT are all in the most deprived quintile (5th quintile) nationally while SB PCT was in the second most deprived quintile (4th quintile) nationally. As the CHD prevalence was predicted for Birmingham and the three PCTs independently, the local variation in deprivation (i.e. SB PCT less deprived than the other two PCTs) was not adjusted when predicting CHD JSNA LTCs Final Version

93


prevalence for Birmingham. As a result, the summing up of the three PCTs’ prevalence did not add up to Birmingham’s prevalence. A more accurate way to do the projection may be to project based on smaller geographical areas (e.g. ward) and take into account the social deprivation level (i.e. IMD scores) of the small areas and combine the predicted prevalence to calculate the Birmingham and PCT’s prevalence.

JSNA LTCs Final Version

94


9. Diabetes Mellitus Key messages for commissioners Key findings: • Diabetes Mellitus prevalence rate in Birmingham is higher than the national average, especially in HoB tPCT area. • Prevalence of diabetes is associated with ethnicity, obesity and social deprivation. • Prevalence of diabetes is likely to increase due to the change of population in the city.

Joint Strategic Needs Assessment

Issues raised from this study: • Projection of future prevalence of diabetes in Birmingham and the PCTs is an issue without primary care data. The projection using models built based on national trend cannot be apply locally as Birmingham is an outlier. Therefore primary care data is needed for a more accurate projection. Big issues for management of diabetes: • Prevention, in particular around life style risk factors such as obesity.

9.1. A growing concern worldwide and in the UK Diabetes mellitus is sweeping the globe as a silent epidemic largely contributing to the growing burden of non-communicable diseases and mainly encouraged by decreasing levels of activity and increasing prevalence of obesity. Recent Reports released by the World Health Organisation (WHO: www.who.int/whr/2003/en) and the International Diabetes Federation (International Diabetes Federation: IDF report, 2003 at www.idf.org/home/index.cfm) are alarming. In 2003, it was estimated that 194 million people were diabetic, representing a global prevalence exceeding 3% of the world population (and 5.1% for those aged 20 to 79). The trend is increasing and the number is expected to reach 333 million (or 6.3%) by the year 2025 (Bouyateb et al. 2004).

Around 3% of people in England are known to have diabetes; however it is estimated that another 1.4% of the population are undiagnosed. Among the nine English regions, the North East has the highest estimated prevalence: 4.73% and the South East the lowest: 3.86%. It is estimated that by 2010, overall prevalence will be over 5%, taking into account the combined effects of an ageing population and predicted increases in obesity levels. Diabetes already costs the NHS an estimated £5m per day and the Department of Health itself estimates that around five per cent of total NHS expenditure (and up to 10 per cent of hospital in-patient expenditure) is used for the care of people with diabetes. The Department of Health also estimated that there are currently 2.35 million people with diabetes in England. This is predicted to grow to more than 2.5 million by 2010. Diabetes UK in its Position Statement (June 2006) (Diabetes UK 2006) writes that it expects that the number of people with diabetes will reach 3 million by the end of the decade (2010).

JSNA LTCs Final Version

95


9.2. What is diabetes? Diabetes is a chronic and progressive disease that has an impact upon almost every aspect of life. Diabetes is the leading cause of blindness in people of working age in the UK. It affects infants, children, young people and adults of all ages, and is becoming more common. Diabetes is a group of diseases with different causes but similar manifestations. One common feature is a raised level of glucose in the blood. This is due to the lack of the hormone insulin and/or an inability of the body to respond to insulin. Insulin is a hormone that enables the glucose from food to be incorporated into cells, and subsequently to be used as energy by the body. Long term complications are likely to occur if levels of glucose in the blood are left unchecked. Common complications are: eye disease, potentially leading to blindness; kidney failure; foot ulcers and amputations. Diabetes is also associated with an increased risk of coronary heart disease and hypertension. In extreme circumstances ketoacidosis or hypoglycaemia may occur, which can lead to coma and death, if untreated. It is a disease that can be prevented through lifestyle measures. Those affected may go undiagnosed for some time, but once diagnosed, diabetes can be managed and treated successfully. Early detection and management greatly reduces the risk of complications and early death.

9.3. Types of diabetes There are many different types of diabetes, some of which are quite rare. This paper is restricted to the more common forms of diabetes, known as Type 1 and Type 2.

9.3.1.

Diabetes Mellitus Type 2 (T2DM)

Type II diabetes is caused by the body not responding well to its own insulin. It is the most prevalent form of diabetes with more than 90% of all identified diabetes cases falling into this category. The Department of Health estimates that life expectancy in T2DM patients, is reduced by up to 10 years (DH website, May 2009). Increase in the prevalence of T2DM is linked to, in particular, rising levels of obesity and the ageing of the population. Some ethnic groups when not deprived are relatively protected from T2DM: these are mainly White from southern parts of Europe and include England. T2DM is traditionally associated with middle age, with most people being diagnosed at over the age of 40. However, whilst prevalence still remains low, the number of children and young adults diagnosed with T2DM is increasing, with the majority being from ethnic minority backgrounds (Feltbower et al. 2003; Haines et al. 2007; Ehtisham et al. 2004).

Onset of T2DM is usually preceded by a period of impaired glucose tolerance (IGT). The disease is characterised by a combination of insulin deficiency and insulin resistance in which either characteristic may be predominant. As levels of glucose in the blood increase, symptoms such as tiredness, frequent urination, increased thirst, weight loss, blurred vision and frequent infections may appear. Those with the disease may go undiagnosed for some time.

JSNA LTCs Final Version

96


The causal factors associated with the development of T2DM are complex and not fully understood. In women, intrauterine factors have been implicated and adults who had low birth weight for gestational age, are at higher risk. Genetic factors are likely to play a part, as there are racial differences in incidence and familial tendencies, although no major gene has been identified. Obesity is a major risk factor for diabetes and both lifestyle factors (diet and exercise) and environmental factors that lead to the consumption of foods with high fat and sugar contents, together with sedentary behaviour are likely to be contributing to rising levels of obesity.

9.3.2.

Diabetes Mellitus Type 1 (T1DM)

Diabetes mellitus Type 1 is caused when the insulin producing cells in the pancreas are destroyed. T1DM tends to be diagnosed at a young age (with approximately 50% diagnosed by the age of 15 and 90% by the age of 30). It can occur at any age and age specific incidence of T1DM is flat from the age of 20 onwards. The disease is a serious cause of premature death. The Department of Health states on its website (May 2009) that life expectancy is reduced by at least fifteen years for someone with Type 1 diabetes. Although the process behind the destruction of the insulin producing cells is not fully understood, it is most likely to be an autoimmune response, which means that the body attacks its own cells in the pancreas. Complications may arise if there is prolonged exposure to raised levels of glucose in the blood. Complications for T1DM are similar to those described for T2DM. They are more likely to occur at a younger age due to the earlier exposure to high levels of glucose in the blood. Genetic predisposition and environmental factors such as viral infection, early exposure to cow’s milk and vitamin D deficiency have been debatably implicated as potential triggers (British Medical association 2004). The remainder of this chapter investigates the prevalence of diabetes in Birmingham and the PCTs and projects future prevalence based on current distribution patterns of diabetes in terms of demographics, deprivation, lifestyle and clinical risk factors.

9.3.3.

The importance of early diagnosis and treatment of diabetes

Progression of both types of diabetes can be slowed down, if not halted. Scholars at the University of Birmingham write that “there is now proof that, both in type 1 and type 2 diabetes, effective control of hyperglycaemia prevents the development and progression of the microvascular complications of diabetes (retinopathy, neuropathy and nephropathy).“ Attainment of near-normal glycaemic control, while minimizing the risk of hypoglycaemia, is a priority” (Rhys Williams and H Farrar 2008). It is for this reason that Diabetes UK has for many years been calling for the establishment of active programmes to identify people with in particular T2DM at an early stage, to ensure appropriate diabetes care and treatment. Such programmes would also reduce the devastating and costly complications of coronary heart disease, renal disease, blindness, stroke and foot disease that are often associated with undiagnosed type 2 diabetes. Nevertheless evidence on the effectiveness of current programmes is still insufficient.

JSNA LTCs Final Version

97


9.4. Diabetes prevalence in England Reliable trend data on diabetes prevalence are available from the series of Health Survey for England studies. Figure 9.1 shows trend in diabetes by sex for combined type 1 and type diabetes for the years 1991, 1993, 1994, 1998, 2003 and 2006. The picture is clear: diabetes increases steadily, prevalence is consistently higher in men than in women, and the gender gap is increasing from no gap in 1991 to 1.4% difference in 2006. Figure 9.1

Trend in diabetes prevalence, England, 1991-2006 Diabetes by sex, adults aged 16 and over, 1991 to 2006, England 6

Prevalence of diabetes (%)

5

4

3

2

Men Women

1

0 1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Notes:

Self-reported diagnosis of either Type 1 or Type 2 diabetes. From 2003, data are weighted for non-response. Source: Joint Health Surveys Unit (2008) Health Survey for England 2006 Cardiovascular disease and risk factors. The Information Centre: Leeds

Table 9.1 gives a picture of self-reported diabetes prevalence, by type of diabetes, sex and age groups for the latest year 2006. Key observations from Table 9.1 are: •

5.6% of men aged 16 in England have diagnosed diabetes of either Type 1 or Type 2, compared to only 4.2% of women.

T2DM is much more common than T1DM in both men and women.

T1DM tends to be diagnosed at a young age in both men and women, but can occur at any age. The modal prevalence for T1DM age group is 25-34 for men, but 45-54 for women.

Age is a key risk factor for T2DM. The Health Survey for England 2006 suggests that male diabetes prevalence increases from about 1% in the age group 16-34 to 13.5% in the age group of those aged 75 years and over. Female prevalence in the age group 16-34 is similar to men, but diabetes prevalence rises less sharply with age to about 10.4% for women aged 75 and older.

JSNA LTCs Final Version

98


Table 9.1

Prevalence of diagnosed diabetes by type, sex and age, 2006, England

SEX

All ages

16-24

25-34

35-44

45-54

55-64

65-74

75+

%

%

%

%

%

%

%

%

Type 1 Diabetes

0.5

0.6

0.9

0.6

0.2

0.4

0.2

-

Type 2 Diabetes

5.1

0.2

0.3

1.8

5.8

8.1

15.4

13.5

Types 1 and 2 combined

5.6

0.8

1.2

2.4

6.0

8.5

15.7

13.5

Men

Unweighted base

5,625

650

862

1,183

1,050

1,126

437

317

Weighted base

6,854

1,041

1,129

1,356

1,123

1,015

694

496

Women Type 1 Diabetes

0.5

0.6

0.6

0.4

1.3

0.2

-

0.4

Type 2 Diabetes

3.7

0.3

0.5

0.8

2.3

5.9

10.4

10.4

Types 1 and 2 combined

4.2

0.9

1.2

1.2

3.6

6.0

10.4

10.6

Unweighted base

6,923

794

1,148

1,494

1,279

1,268

470

470

Weighted base

7,307

1,014

1,160

1,379

1,141

1,049

768

796

Notes: Self-reported diagnosis of either Type 1 or Type 2 diabetes. Source: Joint Health Surveys Unit (2008) Health Survey for England 2006. Cardiovascular disease and risk factors. The Information Centre: Leeds.

9.5. Risk factors for type 1 and type 2 diabetes There are a number of other risk factors of getting diabetes of any kind. The Yorkshire and Humber Regional Health Observatory (YHPHO) states that prevalence of diabetes is increasing as obesity levels increase and overall physical activity levels remain low. Getting diabetes is generally linked to: • • • • •

Ethnic origin Family history Increasing levels of obesity and overweight Low levels of physical activity Calorie intake from food

JSNA LTCs Final Version

99


Some of these risk factors (age, ethnic origin, family history) cannot be changed. But others, like obesity, food intake and physical activity, are related to peopleâ&#x20AC;&#x2122;s life style and can be influenced through e.g. health intervention programmes. Diabetes can be prevented by increasing public awareness of the condition and of the early symptoms (such as increased thirst, blurred vision). People at risk need to be supported to change their lifestyle by losing weight, increasing physical activity and eating a healthier diet. Tackling obesity, promoting physical activity and a healthy diet are vital for diabetes delaying or even preventing long-term complications of diabetes. Below we will briefly discuss in fairly general terms some of these risk factors that are commonly associated with the risk of getting diabetes of any kind. The three factors are lifestyle factors, especially obesity (section 9.5.1), ethnicity (9.5.2) and deprivation (9.5.3)

9.5.1.

Obesity

Being overweight or obese strongly increases the risk of diabetes, also because being obese is often associated with other lifestyle risk factors like lack of physical exercise and intake of a diet which is high in saturated fat, sodium and sugar and low in complex carbohydrates, fruit and vegetables. This strong association between obesity, lack of exercise and less than optimal diet explains why levels of obesity have steadily decreased over the past years, and obesity has now become the key factor in the rise in levels of diabetes prevalence. The odds of contracting diabetes becoming increasingly higher with increased Body Mass Index (BMI), the indicator generally used to measure obesity. The Yorkshire and Humber Public Health Observatory (YHPHO) in designing their diabetes prevalence model refers to a study by JM Rimm er alia that estimated the impact of BMI on the incidence of diabetes by calculating the odds-ratio of getting diabetes for people with different BMIs. People with a BMI of 31-33 have a 11.6 larger change of getting/being diabetic (Yorkshire and Humber Public Health Observatory 2008). YHPHO also analyzed trends in the diabetes index based on HsfE data from 1991 to 2006. The diabetes index is a measure that reflects increases in diabetes due to obesity increases alone and is computed by multiplying the percentages in BMI groups (e.g. BMI <25, 25-29, 30+) with the relative risks of Type 2 diabetes for those BMI groups, as shown in the Table 9.2. Table 9.2

Example calculation of the Diabetes Index, England males 1991

Body Mass Index (BMI)

A

B

A*B

% population

Relative risk of T2DM

Diabetes Index

< 25

47.6

1

47.6

25-29

39.9

2.33

93

30+

12.5

4.98

62.3

Total

100

JSNA LTCs Final Version

202.8

100


The diabetes index for England increased between 1986-91 and 2005 from 193.2 to 254.1 for men, from 195.9 to 234.7 for women and with a continuation of current trends the diabetes index is on course to reach by 2025 a value of 324.1 for men, and 279.3 for women. If the current trends in levels of obesity were to continue, YHPHO predicts that by 2025 diabetes prevalence for England will have increased to 6.48% and that by that year approximately 43% of the increase in diabetes prevalence will be due to the ageing population and 57% will be due to increasing obesity. See Table 9.3. Table 9.3 Year

Diabetes prevalence forecasts based on two scenarios of obesity levels Scenario 1: 1 Obesity rise continues & population change

Scenario 2: Obesity maintained at 2005 level & population change

% of diabetes prevalence increase die to population change

% of diabetes prevalence increase die to obesity rise

Rate

Number

Rate

Number

2005

4.48%

2,262,484

4.48%

2,262,484

2010

4.95%

2,561,421

4.71%

2,434,164

47.6%

52.4%

2015

5.42%

2,874,066

4.91%

2,600,833

45.1%

54.9%

2020

5.94%

3,229,734

5.13%

2,788,676

44.4%

55.6%

2025

6.48%

3,605,133

5.35%

2,974,995

43.4%

56.6%

Based on extrapolation of 1991-2006 trend in Body Mass Index distribution in the Health Survey for England Source: YPHHO PBS Diabetes Prevalence model Phase 3: Key Findings, May 2008

Ethnicity is also related to being overweight and obese. In school years of reception and year six, Chinese children have the highest healthy weight and the lowest obese prevalence while Asian or Asian British children have the highest underweight prevalence. Black or Black British children are the more overweight and obese than any other ethnic group children as shown In Table 9.4. Table 9.4

Prevalence rate of underweight, healthy weight, overweight and obese school children by ethnic group, England, 2007/08

Ethnic group

Prevalence rate (%) Underweight Reception

Year 6

Healthy weight Reception

Year 6

Overweight Reception

Year 6

Obese Reception

Year 6

White

0.8

1.2

76.5

67.4

13.5

14.2

9.1

17.3

Mixed

1.3

1.5

76.7

63.9

12.2

14.2

9.8

20.4

JSNA LTCs Final Version

101


Table 9.4

Prevalence rate of underweight, healthy weight, overweight and obese school children by ethnic group, England, 2007/08

Ethnic group

Prevalence rate (%) Underweight Reception

Year 6

Healthy weight Reception

Overweight

Year 6

Reception

Year 6

Obese Reception

Year 6

Asian or Asian British

4.0

3.9

76.9

60.5

8.6

14.1

10.4

21.5

Black or Black British

1.4

1.2

69.9

56.9

14.0

15.5

14.8

26.4

Chinese

1.5

2.9

84.1

70.9

8.8

12.4

5.7

13.7

Any Other

1.4

1.7

72.7

61.0

13.1

14.9

12.8

22.4

Unknown

1.2

1.3

76.2

66.2

13.0

14.4

9.6

18.1

Total

1.3

1.4

76.2

66.0

13.0

14.3

9.6

18.3

Source: National Childhood Measurement Programme (NCMP)

9.5.1.1. Relevance for Birmingham Levels of obesity in Birmingham and its PCTs are higher than in England as a whole as shown in Table 9.5 Table 9.5

Obesity in England, Birmingham and PCTS, 2007/2008

Risk factor

Obesity

Prevalence

2007/2008

BEN PCT

HOB tPCT

SB PCT

West Midland SHA

England*

8.8%

8.3%

7.8%

8.4%

7.6%

Source: QOF 2007/2008 (Reported in: NHS Birmingham East and North; Diabetes Mellitus Health Needs Assessment in NHS Birmingham East and North, April 2009) * Unadjusted prevalence and source is QMAS database

Compared with England Birmingham has a younger age structure. Therefore, if current trends of rising obesity persist, an even higher share of the increase in diabetes prevalence will be caused by obesity alone. In BEN PCT three scenarios were used to predict diabetes prevalence, as shown in Table 9.6.

JSNA LTCs Final Version

102


Table 9.6

Impact of change in obesity levels on diabetes prevalence: an example from Birmingham East and North PCT

SCENARIO

ASSUMPTIONS

Diabetes Prevalence rate

Scenario 1

2001 obesity level, 2010 population projection

5.35%

Scenario 2

2010 population projection, 2010 predicted obesity

5.85%

Scenario 3

2010 population projection, 1995 obesity levels

4.89%

Source: NHS Birmingham East and North DHNA report December 2007

Comparison of scenarios 1 and 2 show that the rise in the level of obesity between 2001 and 2010 would result in an 0.5% increase in diabetes prevalence. Comparison of scenarios 1 and 3 show that if the projected levels of obesity for 2010 could be curtailed to 1995 levels, the diabetes prevalence rate would decline by nearly one percent.

9.5.2.

Ethnicity

It is well documented that prevalence of diabetes differs by ethic group. Rhys Williams and H Farrar of the University of Birmingham highlight the most important studies and conclude in a general overview that the prevalence of diabetes in populations of non-Caucasian origin is higher, sometimes much higher, than in the White populations of the same age. For adults, diabetes (mainly type 2 diabetes) is 2-4 times as common (depending on gender and age) in people of South Asian origin as in those of Caucasian origin. People of South Asian origin are heterogeneous and prevalence may vary among them, although detailed analysis of prevalence in relation to area of origin and religion suggests that there is much less difference between South Asian groups than there is between them and their Caucasian neighbours. In people of Afro-Caribbean origin, prevalence is also high and the majority of diabetes is T2DM. The 2004 round of the Health Survey for England survey included a section on the health of minority ethnic groups and from this survey we derived the results shown in Table 9.7 Compared to the general population (data from the 2003 HsfE survey), the Black and Asian ethnic groups (excluding Chinese) have considerably higher diabetes prevalence rates, in particular for T2DM. The rates for T2DM for the Asian and Black populations are respectively 7.2% and 6.0%, compared to only 3.8% in the general population. But there is a lot of diversity among these main groups. Black Caribbeans have much higher rates (8.3%) than Black Africans (â&#x20AC;&#x2DC;onlyâ&#x20AC;&#x2122; 3.0%), and among the Asian groups the rates for Indians, Pakistani and Bangladeshi Chinese are nearly double or more than double the rate for the general population. The Chinese, however, appear to be less diabetic than the general population. The same pattern also applies to the male and female subgroups, with male rates being higher than female rates.

JSNA LTCs Final Version

103


Table 9.7

Diabetes by sex and ethnic group, adults aged 16 and over, 2004, England

General population

Black all

Asian exclude Chinese

Black Caribbean

Black African

Indian

Pakistani

Bangladeshi

Chinese

Irish

%

%

%

%

%

%

%

%

%

%

Type of diabetes

Men and women

Type 1

0.43

0.54

0.12

0.68

0.37

0.00

0.00

0.42

0.00

0.00

Type 2

3.41

5.98

7.19

8.34

3.04

7.43

7.89

6.12

3.35

2.69

Types 1 and 2

3.80

6.52

7.53

9.02

3.42

7.85

8.00

6.59

3.54

2.86

14,836

1,92 6

3,014

1,067

859

1,18 4

941

889

723

1,15 3

Unweighted base

Type of diabetes

Men

Type 1

0.6

0.60

0.41

0.5

0.7

0.9

0.0

0.2

0.3

-

Type 2

3.8

6.98

8.26

9.5

4.3

9.2

7.3

8.0

3.4

3.6

Types 1 and 2

4.3

7.57

8.67

10.0

5.0

10.1

7.3

8.2

3.8

3.6

804

1,394

414

390

550

433

411

348

497

Unweighted base

6,602

Type of diabetes

Women

Type 1

0.3

0.51

0.24

0.8

0.1

0.0

0.2

0.6

0.0

0.3

Type 2

3.1

5.26

6.27

7.6

2.0

5.9

8.4

4.5

3.3

2.0

Types 1 and 2

3.4

5.77

6.54

8.4

2.1

5.9

8.6

5.2

3.3

2.3

8,234

1,12 2

1,620

653

469

634

508

478

375

656

Unweighted base

Notes: Type 1 diabetes defined as doctor-diagnosed diabetes with diagnosis age <35 and currently on insulin. Data are weighted for non-response. General population data from Health Survey for England 2003 as data not available for 2004.

Source: Department of Health (2005) Health Survey for England 2004. The Health of Minority Ethnic Groups. The Stationery Office: London.

JSNA LTCs Final Version

104


9.5.2.1. The interaction of ethnicity and obesity and the risk of type 2 diabetes Being of a particular ethnic origin and having a relatively high Body Mass Index both increase the risk of having diabetes or becoming diabetic. However, the relationship between BMI and diabetes appears to be modified by ethnic group. Available data suggest that the relative risks of T2DM are greatest at lower BMIs but that relative risks for different ethnic groups tend to converge at higher BMIs (over 30). In other words, in low BMI sub-populations, you would expect more difference between ethnic groups in diabetes prevalence, but this difference becomes less significant at higher levels of obesity.

9.5.2.2. Ethnicity and childhood obesity Williams and Farrar also state that for diabetes in children, there is little difference between incidence in the various ethnic groups. Data from the National Childhood Measurement Programme (NCMP) shown in the Table 8.8 about obesity among school children help to qualify this general statement. The Table shows that between starting school (reception) and getting to year 6, the percentage of obese children rises from nearly 10 percent to close to 20 percent. Although most groups do not stray much from the average, Chinese children have much lower obese prevalence, whereas Black or Black British children are much more overweight and obese than other ethnic group children.

9.5.3.

Diabetes and deprivation

Deprivation is strongly associated with unhealthy diet, physical inactivity, smoking, obesity and high blood pressure. These factors are mainly responsible for onset of diabetes and its complications, and deprivation therefore increases the risk of becoming diabetic. This is indeed borne out by data. For example, the Yorkshire and Humber Public Health Observatory analyzed data from the National Diabetes Audits for the years 2003/04, 2004/05, 2005/06 and 2006/07 and the results in Figure 9.2 show a systematic increase of diabetes prevalence with increased levels of deprivation. In 2006/07 prevalence in the least deprived quintile 1 was 3.18% versus 4.95% in the most deprived quintile 5. Figure 9.2

Prevalence rate of registered diabetes by deprivation quintile, England

Registered prevalence rate (%)

6

5

4

3

2

1

0 NCASP 2001

NDA 2003/4

Quintiles 1 least deprived

JSNA LTCs Final Version

Quintiles 2

NDA 2004/5 Quintiles 3

NDA 2005/6 Quintiles 4

NDA 2006/7

Quintiles 5 most deprived

105


It is worth noting that these data from the National Diabetes Audit stem from GP clinic records that only cover diagnosed diabetes patients and that these data have not been standardized for age and ethnicity. The differences in diabetes prevalence rates shown in figure 9.2 may well be larger in reality because at the national level it is likely that there is a. more undiagnosed diabetes in the more deprived areas b. higher proportion of high-risk ethnic minority groups in deprived areas Figure 9.2 also brings out that over time the gap in diabetes prevalence between the third and fifth quintile groups is growing from only 0.27% in 2001 to 0.86% in 2006/07. As 56% of the Birmingham population falls into quintiles 5 (see section 4.3 of this report) one would expect the diabetes prevalence rates in Birmingham to be higher than in England due to the deprivation alone.

9.6. Diabetes prevalence in Birmingham around 2006 Three different estimates the rate of diabetes prevalence will be presented in this section. The first estimate in section 9.6.1 gives the registered and therefore diagnosed disease prevalence based on QoF data aggregated from registers of the Birmingham’s GP practices. The second source (section 9.6.2) gives the total diabetes prevalence (diagnosed and undiagnosed) by types of diabetes, sex and broad age groups available from a model developed by the Yorkshire and Humber Regional Health Observatory. Given serious limitations of the YHPHO model, the PHIT unit made an attempt to overcome the limitations of the YHPHO model and produced alternative estimates, and these are described in section 9.6.3

9.6.1.

Diagnosed diabetes prevalence from GP-practices data (QOF)

Figure 9.3 and Table 9.8 show the QOF prevalence trend for diabetes in the three PCTs in Birmingham in comparison to Birmingham and England, from year 2004/05 to 2007/08. It is useful to realize that QOF data are only available for both sexes, not separately for males and females, and that they represent diagnosed diabetes only. For the most recent year 2007/08, the QOF prevalence of diabetes data show that: •

There are nearly 2.1 million people registered on the diabetes lists of the general practitioners’ clinics in the UK. This represents the total of all types of diabetes.

There are currently (2007/08) 49,442 people in Birmingham who were on the diabetes register, distributed over the three PCTs as follows: 14,682 in SB PCT, 15,997 in HoBt PCT and 18,763 in BEN PCT. SB PCT has a relatively low share of diabetes registered persons compared to its population share, whereas HoB-t PCT has a relatively large share of registered diabetes.

The prevalence rate for diagnosed diabetes was 4.36% in Birmingham, higher than England’s rate (3.9%).

JSNA LTCs Final Version

106


Among the PCTS, diabetes prevalence is highest by far in HoB tPCT (5.13%), followed by BEN PCT (4.28%), and SB PCT (3.83%). BEN’s prevalence is similar to the Birmingham average, whereas South Birmingham’s prevalence is even slightly lower than England.

Figure 9.3

Trend of QOF Unadjusted prevalence of Diabetes, Birmingham, PCTs and England, 2004/05 to 2007/08 6.00% 5.00% 4.00% 3.00% 2.00% 1.00% 0.00% 2004/05 SB

2005/06 HOB

BEN

2006/07 Birmingham

2007/08 England

Data source: QOF

The trend in diabetes prevalence from year 2004/05 to 2007/08 suggests that: •

Diabetes prevalence rates have slowly but steadily increased both nationally and locally. The number of people with diagnosed diabetes in England increased by nearly 322,000. or by 18.2% during the period.

Birmingham diabetes prevalence has increased by about 6,700 registered patients, or by 15.6% from 2004/05 to 2007/08. This increase was thus slower than the national increase.

Diabetes prevalence in SB PCT increased by about 2,000 registered patients, or by 15.6%, similar to Birmingham, slower than England.

Diabetes prevalence in HOBt PCT increased by about 1,800 registered patients, or by 12.7%. This increase is below the national and the Birmingham rate of increase.

Diabetes prevalence in BEN PCT has decreased by about 2,900 registered patients, or by 18.1%. This increase is close to the national and higher than the Birmingham national rate of increase.

Birmingham and PCTs follows the global trend of increase in diabetes prevalence and, like globally, this is also strongly associated with the increase in the levels of obesity.

It worth noticing that there is a large prevention programme in HoB tPCT which started in 2002 as a pilot but became mainline by 2005; in addition, in 2007/8 HoB

JSNA LTCs Final Version

107


tPCT and BEN had a mass case finding exercise. These programmes may affect the registered diabetes prevalence. Table 9.8

Diagnosed Diabetes Prevalence Birmingham and PCTs, 2004/05 to 2007/08

AREA

ENGLAND

BIRMINGHAM

BEN PCT

HOB tPCT

SB PCT

Year

Practice List Size

(all

types)

in

England,

Diabetes Register

Diabetes Prevalence rate (unadjusted)

Count

Rate

2004/05

52,833,584

1,766,391

3.30%

2005/06

53,214,483

1,890,663

3.60%

2006/07

53,681,098

1,961,976

3.70%

2007/08

54,009,831

2,088,335

3.90%

2004/05

1,103,350

42,757

3.88%

2005/06

1,123,482

45,719

4.07%

2006/07

1,126,076

47,196

4.19%

2007/08

1,134,333

49,442

4.36%

2004/05

421,823

15,875

3.76%

2005/06

434,587

17,290

3.98%

2006/07

434,853

17,483

4.02%

2007/08

438,641

18,763

4.28%

2004/05

300,433

14,187

4.72%

2005/06

309,177

15,010

4.85%

2006/07

310,460

15,795

5.09%

2007/08

312,070

15,997

5.13%

2004/05

381,094

12,695

3.33%

2005/06

379,718

13,419

3.53%

2006/07

380,763

13,918

3.66%

2007/08

383,622

14,682

3.83%

Source: Computed by PHIT from QOF data

JSNA LTCs Final Version

108


9.6.2.

Distribution by ward

Figure 9.4 shows diabetes prevalence by ward in Birmingham in 2007/08, based on QOF data. Details of the method of mapping QOF prevalence to ward are described in Section 3.4.1. It shows that in the year 2007/08: •

Prevalence of diabetes was particularly high in Central Birmingham wards (HOB tPCT’s catchments area) that are among the most ethically diverse and the most deprived.

The prevalence was low in wards that are relatively well-off, like Sutton Four Oaks, Sutton Trinity, Sutton Vesey, Harborne (in BEN PCT) and Selly Oak, Edgbaston and Harborne in SB PCT)..

Figure 9.4

Prevalence of diabetes by ward, Birmingham 2007/08

Data source: QOF PHIT calculation

9.7. Population-based estimates of diabetes prevalence: the YHPHO PBS Diabetes Model, Phase 3 There are no recent or even less recent health surveys that have generated reliable estimates for diabetes prevalence for Birmingham, even less so for areas within Birmingham. It has become standard practice therefore to rely on prevalence models that are often generated by one of member organisations of the Association of Public Health Observatories (APHO). For diabetes, the Yorkshire and Humber Regional

JSNA LTCs Final Version

109


Health Observatory first developed a diabetes prevalence model in 2004 that since was updated twice. The latest Phase 3 release has produced estimates of the current number of people in Birmingham and the three PCTs with Type 1 and Type 2 diabetes. The model also made a forecast of the future numbers of diabetes patients. In this section we discuss the model and give its results form this model for Birmingham and the three PCTs.

9.7.1.

The model

For full details about the model, please download the PBS Diabetes Model Phase 3 Technical Briefing Document from www.yhpho.org.uk. As no single study could be found that provided diabetes population prevalence rates in all ethnic groups, the PBS Diabetes Prevalence Model was developed on the basis of data from a number of UK screening studies that provided diabetes prevalence data by age, sex and ethnic group. ‘White’ and ‘Asian’ Type 2 diabetes prevalence rates used in the model were those observed in the European white and South Asian populations in two Coventry diabetes studies (1991, 1993). For Black ‘Type 2 diabetes prevalence rates use was also made of a London (Brent) study (1993). Type 1 diabetes prevalence rates were based on a study of 418,200 people in Wales (2002). The main Coventry studies that underpin the YHPHO model were conducted between 1986 -1991. These and other studies were then used to create a model that produces diabetes prevalence estimates in three series: • • •

2005 diabetes prevalence rates at PCT level by age groups, sex and ethnic groups 2005 diabetes prevalence rates at PCT and ward level by age groups and sex 2010-2025 overall diabetes prevalence rates at PCT level (no breakdowns)

Given that the underpinning studies are all more than a decade old, the model was adjusted to account for the increasing trend in obesity by adjustment factors based on the ratio of the diabetes indices for subsequent years (see 9.5.1 for further details) As numerous UK studies have also demonstrated a strong positive association between increasing socio-economic deprivation and the prevalence of T2DM. In PBS phase 3 the estimate of T2DM prevalence was adjusted using data from the 2005/06 National Diabetes Audit derided from GP practices. As was noted in section 8.5.3 the adjustment process may have underestimated the real ‘deprivation gap’ in diabetes prevalence.

9.7.2.

The results

The overall diabetes prevalence rates from the model for England, West Midlands, Birmingham and PCTs by sex are given in Table 8.10. It shows that Birmingham has an estimated 2005 diabetes prevalence rate of 5.14%, higher than West Midlands (5.14%) and higher than England (4.48%). Within Birmingham, BEN and SB PCTs have prevalence rates higher than Birmingham. According to the model, the Heart of Birmingham has a diabetes prevalence rate even lower than England. This estimate is suspect: although HOB

JSNA LTCs Final Version

110


PCT has a relatively young population (lower risk group), it also has a very high proportion of Asian and Black population which count as high risk groups and is the most deprived PCT in the country. Striking points in Table 9.9 are: 1. Overall prevalence: the level of diabetes prevalence rate implied by the YHPHO model for Birmingham (both sexes) is 5.14%, about one percent point higher than the comparable QOF prevalence. This is plausible, although for most LTCs we see a larger gap between QOF data and other sources that estimate diagnosed and undiagnosed prevalence. 2. Gender difference: the model predicts a diabetes prevalence rate of 4.56% for Birmingham males, and a higher rate of 5.68% for Birmingham females. This finding is contrary to evidence from Health Survey for England studies that systematically report higher diabetes prevalence for males. However, the gender difference is particularly sensitive to age: males have higher rates of type 2 than females until about age 70. 3. Differences between PCTs: the model predicts diabetes prevalence for both sexes to be, from high to low, 5.45% for SB PCT, 5.44% for BEN PCT and 4.27% for Hob tPCT. The QOF prevalence data indicate an exact reversal with HOB tPCT having the highest rate (4.85%), and SB PCT the lowest (3.53%). Also this model finding is counter-intuitive. Hob tPCT is the most deprived PCT and has the largest non-British White population. Table 9.9

Estimated Type 1 and Type 2 Diabetes Prevalence (diagnosed and undiagnosed), by sex; England, West Midlands, Birmingham and PCTs, 2005

AREA

Base population

People with DMT1 or DMT2

Prevalence rate

Persons England

50,465,625

2,262,484

4.48%

West Midlands

5,350,708

254,996

4.77%

Birmingham

1,002,982

51,531

5.14%

BEN PCT

396,900

21,595

5.44%

HoB tPCT

269,557

11,501

4.27%

SB PCT

336,524

18,354

5.45%

24,757,796

940,502

3.80%

2,630,563

107,880

4.10%

Males England West Midlands

JSNA LTCs Final Version

111


Table 9.9

Estimated Type 1 and Type 2 Diabetes Prevalence (diagnosed and undiagnosed), by sex; England, West Midlands, Birmingham and PCTs, 2005

AREA

Base population

People with DMT1 or DMT2

Prevalence rate

Birmingham

491,666

22,414

4.56%

BEN PCT

193,495

9,327

4.82%

HoB tPCT

135,179

5,235

3.87%

SB PCT

162,993

7,827

4.80%

25,707,829

1,321,983

5.14%

2,720,145

147,117

5.41%

Birmingham

511,316

29,117

5.69%

BEN PCT

203,406

12,268

6.03%

HoB tPCT

134,379

6,266

4.66%

SB PCT

173,531

10,527

6.07%

Females England West Midlands

Source: Yorkshire and Humber Regional Health Observatory, PBS diabetes Population Prevalence Model, Phase 3 (May 2008)

9.7.3.

Limitations of the model

The second and third results imply that the YHPHO model findings need to be used with caution, if at all. Two more pieces of evidence cast doubt on the model results: •

The model estimates the number of people with diagnosed and undiagnosed diabetes to be 11,500 compared to 15,000 people listed with GP practices in HOB tPCT area as diabetes patients.

The ethnic group distribution by PCT area used in the model indicates a percentage White in Birmingham of about 70% with virtually no variation among the PCTs. Comparable statistics from the Office of National Statistics on the percentage of White population for Birmingham is 67.7%, but with huge variation among the PCT areas ranging from 82.7% in SB PCT to 37.0% in HOB tPCT.

The evidence presented above fits in with a YHPHO statement made in February 2009 saying that the model may underestimate true diabetes prevalence: “The model may no longer be providing the most robust data on diabetes prevalence. Whilst some of the assumptions included in the model were based on

JSNA LTCs Final Version

112


the best available evidence at the time of development, the progression of diabetes information and diabetes prevalence data in particular means that these assumptions may no longer be appropriate”(YHPHO 2009). The statement continues with highlighting the main discrepancies between the model and recent evidence: •

Gender: The PBS Diabetes Prevalence model suggests diabetes prevalence among women is greater than in men whereas other data sources suggest that men have a higher prevalence of the condition.

Ethnicity: Other data sources suggest that the higher risk of diabetes experienced by Black and Asian ethnic groups may be greater than the adjustment used in the PBS model.

T1DM in children: the model assumes no change in diabetes prevalence among young children, whereas studies suggest an increasing incidence particularly among young children.

It also worth noticing that that estimates using the YHPHO model have been incorrect for HoB tPCT since they were first published (i.e. version 1) and have not improved. The reason for this is that HoB tPCT is an outlier, particularly in terms of ethnicity and social deprivation.

9.8. The PHIT estimates Both the QOF data and the data from the YHPHO do not give enough confidence in the diabetes prevalence estimates for Birmingham. The QOF data give an underestimate of the total diabetes prevalence, do not give any age/sex specific detail nor breakdown of diabetes by type, but do provide the most reliable distribution of diabetes prevalence by PCT. The YHPHO model possibly underestimates the crude diabetes prevalence to some extent, but not to a large extent, and provides a plausible breakdown of diabetes prevalence by T1DM and T2DM. However, the model’s breakdown by PCT and sex is unreliable and its age-breakdown not very specific. A third source is the series of the Health Survey for England. These surveys do not provide information at the Birmingham level, but is possibly the best source for patterns of diabetes prevalence by sex and age. The preferred method to provide a relatively accurate estimate would be using local primary care data (i.e. local QOF prevalence data broken down by age, sex and type of diabetes). However, at the time the report was written, these data were only available for 60 GP practices in HoB tPCT area. As a result, the PHIT team devised a method that made use of the strong features of each of the three sources as described in the paragraph above which form the basis for the diabetes prevalence estimates given in this section. The PHIT method generates diabetes prevalence rates by type of diabetes, by sex and by ten-year age groups for Birmingham and the three PCTs. The estimation procedure consisted of five steps, as follows: 1. The pattern of diabetes prevalence by PCT from the QOF was accepted. Prevalence rate for BEN PCT, HOB tPCT and SB PCT are respectively 2% lower, 18% higher and 12% lower than the overall Birmingham rate.

JSNA LTCs Final Version

113


2. The gender gap in DM prevalence for England from the 2006 HsfE was accepted. Male prevalence from this source is 5.6%, female prevalence 4.2%, hence male prevalence exceeds female prevalence by 33%. Use of this assumed gender gap and the PCT male and female population shares made it possible to estimate the sex-specific DM prevalence rates from QOF data. 3. The pattern of T1DM and T2DM prevalence available from the YHPHO model was accepted and was used to further disaggregate the QOF prevalence rates from step 2. The resulting DM rates by PCT, sex and type are given in Table 9.10. 4. The estimated level of diabetes prevalence for Birmingham for both sexes, both types from the YHPHO model was accepted as nearly correct, but this estimate was raised by 10% from 5.14% to 5.65% to account for the fact that YHPHO acknowledges that the effect of ethnicity and deprivation in the model might be underestimated. All values in the table opposite were raised taking account of PCT differences. For example, For HOB (T2DM, male) the raised rate is 6.85% which is 5.28% (i.e. QOF estimate) * 1.10 (i.e. raise YHPHO estimate by 10%) * 1.18 (i.e. HOB QOF prevalence is 18% higher than Birmingham). 5. Finally, the age/sex pattern of diabetes prevalence available from the 2006 Health Survey for England was assumed to be applicable to Birmingham and the ratio of each of the age-specific rates to â&#x20AC;&#x2DC;all agesâ&#x20AC;&#x2122; used to derive the agespecific rates for Birmingham and the three sub-areas. A small adjustment was made to include T1DM estimate for 0-15 year olds which was taken as 0.20% throughout. This figure was arbitrarily imputed based on evidence from a Tayside study in 1998 (which found the rate to be 0.14%) and evidence from literature that the level of T1DM in children has risen in recent years. Table 9.10 Estimated diabetes prevalence rates from QOF data by type, sex and PCT, 2007/08 Birmingham Both sexes Male Female BEN PCT Both sexes Male Female HOB tPCT Both sexes Male Female SB PCT Both sexes Male Female Source: estimated from QOF data

Type 1 & 2 4.36 5.00 3.75 Type 1 & 2 4.28 4.91 3.68 Type 1 & 2 5.13 5.86 4.40 Type 1 & 2 3.83 4.50 3.38

Type 1 0.28 0.42 0.19 Type 1 0.26 0.39 0.17 Type 1 0.40 0.58 0.27 Type 1 0.24 0.37 0.16

Type 2 4.08 4.57 3.56 Type 2 4.02 4.52 3.51 Type 2 4.73 5.28 4.12 Type 2 3.59 4.13 3.22

The estimated number of people around 2006 by type of diabetes, sex and age and the corresponding rates are given in Appendix I for Birmingham (Table I.1) and each of the PCTs in tables I.2 to I.4.

JSNA LTCs Final Version

114


Here we highlight the main findings using Table 9.11. Table 9.11 Diabetes Mellitus prevalence in Birmingham and PCTs, 2006 by type and sex Type of diabetes

Sex

Birmingham N

Type 1

Type 2

Type 1 and 2

%

SB PCT N

%

HoBt PCT N

%

BEN PCT N

%

Both sexes

4,039

0.40

1,432

0.36

1,493

0.55

1,114

0.33

Male

2,773

0.56

981

0.50

1,018

0.75

774

0.48

Female

1,266

0.25

451

0.22

475

0.35

340

0.21

Both sexes

52,816

5.25

20,781

5.19

16,465

6.10

15,569

4.63

Male

29,434

5.97

11,458

5.86

9,268

6.85

8,708

5.36

Female

23,382

4.56

9,324

4.55

7,197

5.34

6,861

4.17

Both sexes

56,855

5.65

22,214

5.55

17,958

6.65

16,683

4.96

Male

32,206

6.53

12,439

6.36

10,285

7.60

9,482

5.83

Female

24,648

4.80

9,775

4.77

7,672

5.70

7,201

4.38

Source: PHIT

9.8.1.

Type 1 Diabetes prevalence (T1DM)

T1DM is far rarer than T2DM and makes up approximately 7% of the total. It is estimated that around 4,000 people in Birmingham have this condition. An estimated 0.4% of people in Birmingham have this condition. Inherent to the estimation method, HOB has the highest prevalence rate, but given that HOB has a smaller population than the other PCTs, the number of T1DM patients (= about 1,500) is of the same magnitude as SB PTC who both have a higher number than BEN PCT (= 1,114). The data show that number of men with T1DM is about twice the number of women with this condition. This is true only if Birmingham follows the same gender pattern as the England data from the 2006 Health Survey for England. T1DM can occur at any age, usually peaks in the age group 25-34 and declines after that to very low levels in the older population. T2DM is very rare at lower ages and reaches a peak among the elderly. The average age of the T1DM patient is 17 years, whereas the average T2DM patient is 64 years old.

9.8.2.

Type 2 diabetes prevalence (T2DM)

Birmingham had an estimated number of nearly 53,000 T2DM patients, which is 5.25% of the Birmingham population, of which 21,000 were resident in BEN PCT, 16,500 in HOB tPCT and 15,500 in SB PCT. The T2DM prevalence rates vary from 6.10% in HOB tPCT to 4.63% in BEN PCT. Inherent to the estimation method, out of the 53,000 T2DM patients 30,000 are men and 23,000 women.

JSNA LTCs Final Version

115


9.8.3.

The level of undiagnosed diabetes in Birmingham

How well are diabetes patients known to and registered by the health system? Or in other words, what is the approximate level of undiagnosed diabetes in Birmingham? It is clear that not all diabetes is diagnosed. Estimates vary for the percentage of diabetes which is undiagnosed. Diabetes UK in 2001 fact sheet no 2 estimated that there would be around one million people in the UK who have diabetes which has yet to be diagnosed. A few years later and based on a survey that Diabetes UK commissioned in 2005, the researcher showed that 60% of localities in England now have programmes in place to identify people with diabetes early. In spite of this the researchers still estimate that approximately 750,000 million people with diabetes in UK remain undiagnosed. This figure was extrapolated from an estimated 667,000 for England alone. How many of these 2/3 of a million should be allocated to West Midlands or Birmingham could not be traced. The Health Survey for England 2003 suggests that 3.1% of men and 1.5% of women aged 35 and over have undiagnosed diabetes. If we apply these percentages to the Birmingham 2006 population we get 8,864 people (of which 6,651 men and 2,213 women) who have some type of diabetes but are not diagnosed as such. Some indication of the level of undiagnosed diabetes can be obtained when we compare the number of diabetes patients registered with GP practices (QOF data, see 9.6.1) with the estimates of diagnosed and undiagnosed diabetes given in 9.6.3. Table 9.12 gives this comparison, and it shows the following: •

There is an estimated number of 371,821 people in England whose diabetes was not diagnosed in 2005, which is about 16% of the total number of people with diabetes.

In Birmingham there would be about 11,000 people, or nearly 20%, who have diabetes without being diagnosed. This percentage varies among the PCTs: 27% for SB PCT, 19% for HOB PCT and 18% for BEN PCT.

The YHPHO model would have resulted in odd statistics, as e.g. for HOB the number of people on the diabetes lists of the general practices is larger than the YHPHO estimate of the total diagnosed and undiagnosed prevalence.

The estimated value of 11,136 undiagnosed diabetes patients for Birmingham is more than 2,000 higher than the estimate of 8,864 if Health Survey for England estimates are applied to the Birmingham population. This could indicate a slight overestimation of the diabetes prevalence rates in the PHIT method.

Another factor that introduces uncertainty is that there are 1,120,295 people registered with Birmingham GP practices, which exceeds the total Birmingham population by 110,000.

JSNA LTCs Final Version

116


Table 9.12 Comparison of total estimated Type 1 and Type 2 Diabetes Prevalence with diagnosed prevalence from GP practice data, England Birmingham and PCTs, 2005 AREA

England

YHRHO model

PHIT estimate T1DM and D2DM

Diabetes Register List, 2005/06

Persons with nondiagnosed diabetes (PHIT)

Implied % not diagnosed

N

N

N

N

%

2,262,484

1,890,663

371,821

16.43%

Birmingham

51,531

56,855

45,719

11,136

19.59%

BEN PCT

21,595

22,214

17,290

4,924

17.94%

HoB tPCT

11,501

17,958

15,010

2,948

19.19%

SB PCT

18,354

16,683

13,419

3,264

27.01%

Source: YHPHO , PBS diabetes Population Prevalence Model, Phase 3 (May 2008); and PHIT estimates; QOF data

9.9. Projecting future prevalence Besides estimating current DM prevalence, YHPHO also forecasted its future trend and based the forecast on the assumption that the rising levels of obesity since the beginning of the 1990s will lineally increase onward from 1991-2006 up to at least 2025, which for Birmingham (both sexes) resulted in modelled increase in prevalence from an estimate of 5.44% in 2005 to 7.09% in 2025. For the estimates presented in this section we have accepted the YHPHO predicted end year value of 7.09%. For the base year 2006 we use our own estimated DM prevalence rate which is slightly higher than the YHPHO estimate. This implies that we anticipate a less sharp increase in DM prevalence than in the YHPHO model. We argue that this is probable, given that obesity has become one of the main public health concerns and the NHS is making considerable investments to stem the tide. Having fixed the level of DM prevalence in the base year (2006) and in the end year (2025) for persons in Birmingham, we then assumed a linear pattern of change between 2006 and 2025 to estimate the DM prevalence rate for 2010, 2015 and 2020. Finally this trend for Birmingham persons was made sex-specific and broken down by PCTs by assuming that the 2006 gender and PTC differences would hold in future. Table 9.13 shows the resulting trajectory of the trend in DM prevalence rates in 2006 and for 2010, 2015, 2020 and 2025.

JSNA LTCs Final Version

117


Table 9.13 Projected prevalence rates for T1DM and T2DM by sex, 2006, 2010-2025

Both sexes 2006

2010

2015

2020

2025

Birmingham

5.65%

6.01%

6.37%

6.73%

7.09%

BEN PCT

5.55%

5.90%

6.26%

6.61%

6.96%

HOB tPCT

6.65%

7.07%

7.50%

7.92%

8.35%

SB PCT

4.96%

5.28%

5.60%

5.91%

6.23%

Males 2006

2010

2015

2020

2025

Birmingham

6.53%

6.94%

7.36%

7.78%

8.19%

BEN PCT

6.36%

6.77%

7.17%

7.58%

7.98%

HOB tPCT

7.60%

8.08%

8.57%

9.05%

9.53%

SB PCT

5.83%

6.21%

6.58%

6.95%

7.32%

Females 2005

2010

2015

2020

2025

Birmingham

4.80%

5.11%

5.42%

5.72%

6.03%

BEN PCT

4.77%

5.08%

5.38%

5.68%

5.99%

HOB tPCT

5.70%

6.06%

6.42%

6.79%

7.15%

SB PCT

4.38%

4.66%

4.93%

5.21%

5.49%

9.9.1.

Projected number of persons with diabetes, 2010-2020

The number of people with diabetes in future years is mainly a function of trends in the â&#x20AC;&#x2DC;risk factorsâ&#x20AC;&#x2122; which are in particular age and sex, obesity, deprivation and ethnic group as discussed in previous sections of this report. Below we will present the projected number of diabetes patients in future years only broken down by sex and PCT, and no longer also by age and type of diabetes. In principle we could have done this by pro-rating the detailed prevalence rates for 2006 by sex, age, PCT and DM type to the higher projected total DM prevalence for 2010, 2015 and 2020. However, this would merely have been a mathematical exercise which could have given the reader a false sense of accuracy. We recall the following regarding the extent to which the risk factors are accounted for:

JSNA LTCs Final Version

118


1. PCT-differences in DM prevalence re based on QOF prevalence for the most recent year and degree of differences are maintained in the projections. 2. Gender differences are based on the latest 2006 Health Survey for England, and this difference is maintained in the projections. 3. Age differences are based on the latest 2006 Health Survey for England, and this difference is maintained in the projections. 4. Obesity is taken into account by assuming that the level of obesity will slow down form the observed 1990-2006 trend for England and is reflected in the projected total prevalence rates by sex and PCT. 5. Deprivation and ethnicity are incorporated as â&#x20AC;&#x2DC;risk factorsâ&#x20AC;&#x2122; in the YHPHO model but there was strong evidence that both important factors were given not enough weight in the DM prevalence rate for persons in Birmingham. To counteract this, the YHPHO DM prevalence rate was raised by 10% to obtain estimates for the base year 2006. Table 9.14 highlights the main differences between the three PCTs regarding diabetes risk factors. The real number of DM patients in each of the PCTs in future years will largely depend on how the PCTs will fare with regard to these factors. Table 9.14 Comparing the Three PCTS on major risk factors for diabetes using 2007 data INDICATOR

BEN PCT

HOB tPCT

SB PCT

Obesity

8.80%

8.30%

7.80%

Index of Multiple Deprivation (IMD) score

38.89

48.26

30.86

10

1

34

Mean age

37.11

32.33

38.06

Mid-2007 male population 80 years and over (2007, N)

6,227

2,419

5,155

Mid-2007 female population 80 years and over (2007, N)

11,458

4,022

10,259

Percentage population 80+, both sexes (%)

4.43%

2.40%

4.60%

Total population

401,400

271,700

337,100

White British (N)

284,900

86,500

256,500

White British (%)

71.0%

31.8%

76.1%

IMD Rank (out of 152)

ETHNICITY (ONS 2007)

JSNA LTCs Final Version

119


Table 9.14 Comparing the Three PCTS on major risk factors for diabetes using 2007 data INDICATOR

BEN PCT

HOB tPCT

SB PCT

Black Caribbean, Indian, Bangladeshi and Pakistani (%)

18.9%

49.2%

9.8%

Black Caribbean (N)

11,400

25,200

7,600

Indian (N)

10,000

36,500

14,100

Pakistani (N)

48,300

55,800

9,800

Bangladeshi (N)

6,300

16,200

1,400

Table 9.15 finally gives the projected numbers of people with diabetes by sex and PCT over the next decade. These numbers are computed by multiplying the prevalence rates given in Table 9.13 with the projected total populations obtained from the ONS population projections and two scenarios of PHIT projections that were discussed in Chapter 4: The Local Context. Table 9.15 Projected number of people with T1DM or D2TM by sex, 2010-2020 for three scenarios of population projections AREA

PHIT S1 (incl migration)

PHIT S2 (No migration)

2010

2010

2015

2020

2015

ONS

2020

2010

2015

2020

Both sexes Birmingham

61,846

67,136

73,232

62,720

69,509

76,833

62,548

68,741

75,106

BEN PCT

24,153

26,797

29,869

24,269

26,908

29,825

23,933

26,318

28,865

HOB tPCT

19,485

20,926

22,623

19,997

22,629

25,473

19,797

21,791

23,726

SB PCT

18,208

19,414

20,740

18,455

19,972

21,535

18,818

20,631

22,516

Males Birmingham

34,932

38,060

41,663

35,387

39,291

43,488

35,224

38,776

42,410

BEN PCT

13,587

15,164

16,978

13,639

15,148

16,789

13,386

14,741

16,189

HOB tPCT

11,193

12,046

13,073

11,457

12,943

14,526

11,330

12,489

13,612

SB PCT

10,152

10,850

11,612

10,291

11,201

12,174

10,509

11,547

12,610

Females

JSNA LTCs Final Version

120


Table 9.15 Projected number of people with T1DM or D2TM by sex, 2010-2020 for three scenarios of population projections AREA

PHIT S1 (incl migration)

PHIT S2 (No migration)

ONS

2010

2015

2020

2010

2015

2020

2010

2015

2020

Birmingham

26,914

29,076

31,569

27,333

30,217

33,345

27,324

29,964

32,695

BEN PCT

10,565

11,632

12,891

10,630

11,760

13,037

10,547

11,578

12,676

HOB tPCT

8,293

8,880

9,550

8,539

9,686

10,947

8,467

9,302

10,114

SB PCT

8,056

8,564

9,128

8,164

8,771

9,361

8,310

9,084

9,906

Birmingham in 2010 is likely to have around 63,000 people with DM. If the 2001-07 trend in migration persists, the number is likely to be around 1,000 less (PHIT S1). The number of people with DM should be expected to rise to between 73,000 and 77,000 by 2020. Birmingham East and North PCT (BEN PCT): BEN PCT’s DM prevalence rate is projected to go up from 5.6% in 2006 to 6.6% in 2020. In 2010 BEN will have around 24,000 people with DM in all projection scenarios and this number is expected to rise to close to 30,000. Currently BEN PCT has got: • Relatively high levels of obesity compared to HOB tPCT and SB PCTs • 19% of the population are member of high-risk ethnic groups (Black Caribbeans, Indians, Pakistani and Bangladeshi) • An Index of Multiple Deprivation which is 10th highest in the country • A relatively old population: 4.4% are aged 80 or over, representing 17,500 persons, of which 6,000 are men, and 11,500 women. If 2001-07 levels of migration persist, BEN PCT will have little relief of its diabetes burden, but given the load presented by obesity, deprivation and ethnicity, the projected numbers are thought to be plausible. ‘High obesity now’ also means that intervention programmes could make a relatively big difference. Heart of Birmingham Teaching PCT (HOB tPCT): HOB tPCT‘s DM prevalence rate is projected to go up from 6.7% in 2006 to 8.4% in 2020. In 2010. HOB-T PCT will have between 19,500 and 20,000 people with DM, and the numbers are expected to between 22,600 (PHIT S1) and 25,500 (PHIT S2) in 2020. Currently HOB PCT has got: • 8.3% obesity level, average for Birmingham • Nearly half of its the population is member of high-risk ethnic groups (Black Caribbeans, Indians, Pakistani and Bangladeshi) • An Index of Multiple Deprivation which is the highest in the country JSNA LTCs Final Version

121


A young population: only 2.4% of its population is aged 80 or over, representing 6,500 persons, of which 2,500 are men, and 4,000 women.

If 2001-07 levels of migration persist, HOB tPCT will be exporting nearly halve of potential growth in number of DM patients. Give its young age structure, age-related increase in diabetes is not going to be a major factor. Programmes that are likely to curtail diabetes in HOB tPCT should be a mixture of general interventions that improve the standard of living and targeted campaigns for Black Caribbean and Asian population to raise awareness what can be done to ensure that ‘being at risk of getting’ does not turn into ‘having’ diabetes. South Birmingham PCT(SB PCT): SB PCT’s DM prevalence rate is projected to go up by less than a per cent from 4.96% in 2006 to 5.91% in 2020. In 2010 SB PCT will have between 18,000 and 19,000 with DM, the numbers are expected to rise to between 20,700 (PHIT S1) and 21,600 (PHIT S”) in 2020. The ONS projections are based on levels of fertility that are higher than the level of fertility in South Birmingham in recent years and are considered not plausible. Currently SB PCT has got: • The lowest level of obesity among the three PCTs • Less than 10% of its population are member of high-risk ethnic groups (Black Caribbeans, Indians, Pakistani and Bangladeshi) • The lowest level of deprivation among the three PCTs, although still ranked 34th out of 152 PCTs in the country. • The oldest population among the three PCTs: the mean age of a SB resident is over 38 years, and 4.60% of the population is 80 years or older, representing 15,500 persons, of which 5,200 are men, and 10,300 women. If 2001-07 levels of migration persist, SB PCT and BEN PCT would be exporting of its diabetes burden, but in both PHIT scenario projections the number of pensioners per 100 of the working population is expected to increase. Given the relatively light load presented by obesity, deprivation and ethnicity, SB PCT’s focus in curtailing diabetes prevalence should focus on managing and preventing diabetes among the elderly.

JSNA LTCs Final Version

122


10. Chronic obstructive pulmonary disease Key Messages for commissioners • • • • •

COPD prevalence ranges from 0.67% - 1.55% across Birmingham PCT’s . COPD has strong links with smoking prevalence. Modelling suggests only a quarter of disease is being ascertained via QOF. Proactive prioritisation of smoking cessation is required. An increase in awareness and knowledge of COPD in terms of symptoms, risk factors is required amongst public, patients, commissioners, policy makers and medical professionals. Reduce inequalities via engagement with socially deprived and Black minority & Ethnic groups.

Joint Strategic Needs Assessment •

10.1. A growing concern worldwide and in the UK Chronic obstructive pulmonary disease (COPD) is a slow developing lung disease involving the airways, leading to a gradual loss of lung function. It is a leading cause of mortality worldwide (Calverley PM, Walker P. 2003) and projected to be fifth in terms of worldwide disease burden by 2020 (Global Initiative for chronic obstructive lung disease. Global Strategy for the diagnosis, management and prevention of COPD, Updated 2008). COPD is characterised by airflow obstruction (NICE CG12 – February 2004) and

is a progressive yet largely preventable lung disease. In the UK it is estimated that 30,000 people a year die from COPD (ONS 2006). This corresponds to 5.7 per cent of adult male and 4 percent of adult female deaths, including a significant number of premature deaths. In addition, 1.4% of the population consult their general practitioners (GPs) for COPD each year. COPD accounts for 2% of hospital admission spells and over 3 percent of bed-days in adults, costing the NHS £800 million, and leading to 24 million working days lost each year. Current research estimates that there are 3.7 million people with COPD in the UK, (Shahab et al. 2006) despite only 900,000 having been diagnosed (Thorax 2004). A British Lung Foundation survey in May 2007 concluded that 89% of people in the UK and 85% of smokers had never heard of COPD, demonstrating the current unawareness of the condition. In spite of its imperceptibility, COPD is the UK’s fifth leading cause of death and is the second highest cause of emergency admission to hospital (COPD NSF Development team at the department of health – January 2008). It represents a significant burden to the health services with estimates of £500 million (Thorax 2004) a year being the direct cost of care in hospitals. Individual costs vary with severity, with the annual cost of treating an individual with mild COPD being £149 whereas treating severe COPD is nearly ten times as much at £1037.

10.2. What is COPD? The working definition of COPD, as in the 2008 update of Global Initiative for chronic Obstructive Lung Disease (GOLD) guidelines is “a preventable and treatable disease with some significant extra-pulmonary effects that may contribute to the severity in individual patients. Its pulmonary component is characterised by airflow limitation that is not fully reversible, with the airflow limitation usually progressive and associated with an abnormal inflammatory response of the lung to noxious particles or gases.”

JSNA LTCs Final Version

123


COPD is a chronic condition that leads to lung damage and is characterised by damage to the airways, resulting in them becoming narrower and making it difficult to inhale and exhale air from the lungs. The condition is uncommon in people who have never smoked and has strong links with deprivation. The symptoms of the disease usually develop insidiously thus creating difficulties in determining its incidence. Also there is no single test for diagnosing COPD, resulting in diagnosis being dependent on medical judgement, patient history, physical assessment and verification of airway impediment by spirometry. COPD is usually clinically defined by spirometric measurements of the forced expiratory volume in one second (FEV1) and the forced vital capacity (FVC). The British Thoracic Society (BTS) defined COPD as FEV1 / FVC < 0.70 and FEV1 < 0.80. Key features of COPD include: • Airway difficulty – classified as reduced FEV1 (forced expiratory volume in 1 second) and a reduced FEV1 / FVC ratio (FVC = forced vital capacity)3 • In contrast to asthma (airway obstruction reversible), airway obstruction is not fully reversible • Dyspnoea and cough leading to an impaired quality of life • Extensive airway restriction takes place before symptoms • Smoking is a major aetiological causal factor, though not all smokers will have COPD, and non-smokers may also develop COPD • Occupational exposure to dusts of various kinds may also cause COPD

10.2.1. ‘The missing millions’ Given the insidious nature of the disease and the lack of a single test in determining COPD, most patients are diagnosed only when the severity of the disease has already caused permanent lung damage. Awareness of the condition is generally low and it is thought that COPD is highly under-diagnosed or misdiagnosed. These undiagnosed/ unaware people are referred to as the ‘missing millions’ in a 2007 report by the British Lung Foundation (British Lung Foundation 2007). This is a major concern. Although COPD is not curable, if detected early the development of the condition can be reduced with suitable supervision and management. Smoking cessation is a major facet in reducing the progress of COPD, as well as other preventative activities including vaccination against influenza and pneumococcal disease. Clinical confirmation of COPD needs spirometeric instruments which are not universally available in primary care.

10.3. Risk Factors Manifestation of disease is characterised by chronic cough, sputum production, wheezing and dysponea. (Wilt TJ et al. 2005) COPD usually develops in long-time smokers, resulting in patients having a range of co-morbidities related to smoking or age. Noxious gases, pollution, passive smoking, chronic respiratory infections and genetic susceptibility (alpha-1 antitrypsin) are other potential risk factors for COPD.

JSNA LTCs Final Version

124


10.3.1. Smoking as a risk factor One of the most important risk factor for COPD is smoking (British Lung Foundation 2007), with 73% of COPD mortality associated with smoking It is estimated 50% of smokers develop COPD (Lopez et al. 2006), although non-smokers can also be affected by COPD. Lung function declines with age irrespective of smoking status (Figure 10.1), but in an average non smoker (solid blue line) lung function will not decrease to a critical level (FEV1 < 1 litre per second) or even to the level where clinical symptoms develop ((FEV1 < 2 litre per second) Figure 10.1 Natural history of lung function decline (Lundback B and Lindberg A, 2003)

Smokers experience an increase in the rate of age-related loss in FEV1 compared with non-smokers (red, green, and blue lines). After lung function declines to threshold levels, clinical symptoms develop (black dotted lines). When a smoker stops smoking, the rate of FEV1 loss again approximates to that of a non-smoker (blue dotted line). This demonstrates the importance of smoking cessation in COPD sufferers.

10.3.2. Smoking in Birmingham PCTs The Birmingham Prevalence Survey 2009 showed the smoking prevalence to be 25% for Birmingham, with little variance among the PCTs (Birmingham East & North (BEN) 26%, Heart of Birmingham (HOB) 24% and South Birmingham (SB) 25%, Figure 10.2. The key findings of the Birmingham Prevalence Survey 2009 were:

JSNA LTCs Final Version

125


• • • • • • • •

25.2% (±1.1%) of the adult population are currently smokers Prevalence is higher among men, in younger age groups and in lower socioeconomic groups Lower prevalence among BMEs Health risks are the main motivation to quit smoking 64% of smokers have tried to quit and 49% of smokers would still like to give up High frequency of attempts to quit – high levels of lapsing/churn Most successful quitters received support Encouraging support for both current and possible new measures – even among many current smokers

Figure 10.2 Smoking prevalence by PCT, Birmingham, 2009

Smoking Prevalence – by PCT area 100%

Non-smokers Ex-smokers Smokers

90% 80%

48%

52%

52%

23%

22%

25%

26%

24%

25%

Total

East North

Heart

South

70%

58%

60% 50% 40%

27% 18%

30% 20% 10% 0%

Birmingham Smoking Prevalence Survey 2009

10.3.3. Deprivation and COPD prevalence Deprivation will not directly increase risk of getting COPD but will be a factor that indirectly increases risk through environmental factors like damp housing, higher occupational exposure to sources of dust/asbestos, fewer resources to seek and receive appropriate medical care etc. It is expected therefore that socioeconomic deprivation has been associated with COPD in both longitudinal and cross-sectional analyses (Dewar M and Curry R. 2006), but the correlation is not necessarily very high. In 2007 the Index of Multiple deprivation (IMD) ranked Birmingham as the 14th most deprived local authority in the UK. Correlations between deprivation and COPD prevalence across the Birmingham wards show a weak correlation initially (r2 = 0.019), Figure 10.3, but when adjusted with omission of outliers, the association is strong (r2 = 0.4851), i.e. nearly 50% of COPD can be explained by deprivation and statistically significant (p< 0.05), Figure 10.4. The omitted wards all contain a high proportion of Black Minority & Ethnic (BME) groups and may highlight the unawareness of COPD in these communities. A recent report prepared by the Picker Institute indicated that patients from South Asian origins were not interacting with

JSNA LTCs Final Version

126


COPD services including pulmonary rehabilitation and actively participating in self management. This may explain the low prevalence seen in the highly ethnic wards across Birmingham. Figure 10.3 Correlation of Birmingham Wards and COPD prevalence

JSNA LTCs Final Version

127


Figure 10.4 Correlation of Birmingham Wards and COPD prevalence, adjusted

JSNA LTCs Final Version

128


10.4. COPD prevalence in Birmingham Two different estimates of COPD prevalence will be presented. The first estimate is based on the registered population, obtained from the Quality & Outcomes Framework (QOF) from registers of the Birmingham’s GP practices (section 10.4.1). The second source (section 10.4.2) gives the total COPD prevalence (diagnosed and undiagnosed) sex and broad age groups available from a model developed by Eastern Region Regional Health Observatory (ERPHO).

10.4.1. Current Diagnosed COPD prevalence from GP-practices data (QOF) Figure 10.5 shows the QOF prevalence trend for COPD in the three PCTs in Birmingham in comparison to Birmingham and England, from year 2004/05 to 2007/08. It is useful to realize that QOF data are only available for both sexes, not separately for males and females, and that they represent diagnosed COPD only. Figure 10.5 Trend of QOF Unadjusted prevalence of COPD, Birmingham, PCTs and England, 2004/05 to 2007/08 1.80% 1.60% 1.40% 1.20% 1.00% 0.80% 0.60% 0.40% 0.20% 0.00% 2004/05

2005/06 SB

HOB

2006/07 BEN

Birmingham

2007/08 England

Table 10.1 shows that current 2007/08 England prevalence is 1.48% (Roberts 2008) in 2007/08, for Birmingham it is 1.19% with prevalence’s ranging from 0.67% to 1.55% across the Birmingham PCT’s (Table 10.1). According to the data, COPD prevalence has slightly increased since 2004/05. It is remarkable that registered COPD prevalence in HOB about half the level of prevalence in the other two PCTs. HOB tPCT has a younger population, large BME communities and contains some of the most deprived parts of the Birmingham population.

JSNA LTCs Final Version

129


Table 10.1 COPD prevalence locally and nationally Year

SB

HOB

BEN

Birmingham

England

2004/05

1.41%

0.64%

1.36%

1.18%

1.4%

2005/06

1.46%

0.64%

1.34%

1.19%

1.4%

2006/07

1.50%

0.68%

1.36%

1.22%

1.4%

2007/08

1.55%

0.67%

1.39%

1.24%

1.5%

Source: QOF data

The data are thought to be a vast underestimation due to current under-diagnosis/ misdiagnosis and unawareness of the condition.

10.4.2. COPD prevalence by ward Figure 10.6 shows the variation in COPD prevalence among the 40 wards in Birmingham for 2007/08. No particular pattern related to demographical and socioeconomic variations emerges. Figure 10.6 QOF COPD prevalence by ward, Birmingham, 2007/08

Data source: QOF PHIT calculation

JSNA LTCs Final Version

130


10.4.3. Population-based estimates of COPD prevalence: the ERPHO COPD model Due to the under-diagnosis and misdiagnosis of COPD, a modelling tool is often required to ascertain a better understanding of the prevalence of COPD instead of just relying on figures from primary care. For COPD we were able to use a predictive model developed by the Eastern Region Public Health Observatory (ERPHO) which enables a better understanding of the burden of COPD. It is a population-based regression model which incorporates most of the high-risk factors, which are: • • • • • •

Smoking Status Gender Ethnic group Age group Smoking status Deprivation

The model was used to get an estimate of current prevalence as well as a forecast of future prevalence for the years 2010, 2015 and 2020. The model is based on the 2001 Health Survey for England Survey, which was the last nation-wide survey in which COPD was incorporated as a special topic. In this survey COPD patients were identified on the basis of spirometric measurement, not on the basis of answers to screening questions which would have meant that the results would were ‘selfdiagnosed’ COPD. Spirometric measurements are a good proxy for ‘clinical diagnosis’. In the generic model smoking prevalence is incorporated based on a national smoking prevalence rate of 25%. In the Birmingham application of the model we used three scenarios of current and future smoking prevalence so that we could assess the impact of a drop in smoking prevalence due to e.g. the introduction of a smoking ban in public places. The three scenarios were: • Scenario 1: No decline in smoking – assumes that 2008 prevalence of 25.2% for Birmingham and all three PCTs. This rate is fractionally above the national average • Scenario 2: decline in smoking prevalence of 0.4% per year, with an end value of 20.4% in 2020. • Scenario 3: strong effect of smoking ban tapers off (i.e.1.5% annual reduction first two years, 1.0% annual reduction the next five years, 0.5% annual reduction the final five years) during the period to an end value of 14.7% in 2020. In implementing the scenarios in the model, certain assumptions needed to be made, the most important of which are: • In all scenarios only three groups of smoking status were used: non-smokers, ex-smokers and smokers. A drop in smoking prevalence rate was incorporated by a shift from smoking to ex-smoking, leaving the non-smoking factor unaffected • Ethnic groups have the same smoking patterns

JSNA LTCs Final Version

131


10.4.3.1.

COPD and smoking status

Table 10.2 shows the effect that a decline in smoking rate would have on the COPD prevalence rates. Scenario 1 assumes continuation of the smoking prevalence rate at the level of 25.2%, scenario 3 is a projection of the steepest decline in smoking rates. The projections seem to indicate that there is little gain from a drop in the smoking rate on the number of COPD patients. For example, without a drop in smoking Birmingham would be expected to have 40,259 COPD patients, with a drastic drop (scenario 3) there would be 36,209. The reason for this unexpected result is largely caused by a limitation of the model. The model incorporates a drop in smoking rate by transferring numbers of smokers to the ex-smoker category. In the model the odds (based on survey evidence) for male ex-smokers are hardly smaller than the odds for smokers. The reason for this ‘odd’ pattern is that that many people tend to give up smoking after they are diagnosed with COPD. We would have seen different results if the model would have been able to incorporate the effect of ‘ageing’ (boys and girls turning 16 year old who do not smoke/start smoking) and if smoking status could have been defined in greater detail to include categories of occasion smoker/regular smoker; occasional ex-smoker, regular ex-smoker. However, there is still a gap in reliable data on smoking at this level of detail. Table 10.2 Effect of drop in smoking rates on COPD prevalence, Birmingham and PCTs, 2010 – 2020 Scenario

1

2

3

Year

Birmingham

SB PCT

HOB tPCT

N

%

N

2008

37,272

4.70

12,359

4.45

8,826

4.28

16,087

5.22

2009

37,386

4.69

12,388

4.43

8,855

4.26

16,144

5.21

2010

37,529

4.68

12,447

4.42

8,880

4.25

16,202

5.21

2015

38,711

4.71

12,841

4.46

9,183

4.28

16,686

5.23

2020

40,259

4.79

13,358

4.53

9,511

4.36

17,390

5.31

2008

37,272

4.70

12,359

4.45

8,826

4.28

16,087

4.15

2009

37,241

4.67

12,339

4.41

8,819

4.24

16,083

5.22

2010

37,238

4.64

12,349

4.39

8,808

4.21

16,080

5.19

2015

37,665

4.58

12,490

4.33

8,926

4.16

16,249

5.17

2020

38,407

4.57

12,737

4.32

9,056

4.15

16,614

5.09

2008

37,272

4.70

12,359

4.45

8,826

4.28

16,087

3.90

2009

36,842

4.62

12,205

4.36

8,721

4.20

15,916

5.22

2010

36,436

4.54

12,080

4.29

8,611

4.12

15,745

5.14

2015

35,722

4.35

11,840

4.11

8,447

3.94

15,436

5.06

2020

36,209

4.31

12,000

4.07

8,516

3.90

15,692

4.83

JSNA LTCs Final Version

%

N

%

BEN PCT N

%

132


Smoking is the prime risk factor for COPD. We recall that the results of COPD prevalence by sex, age and ethnicity in the previous sections are all based on scenario 1 that is assuming that there will not be any decline in smoking prevalence up to 2020. Results from scenario 2 and 3 which assume a slow and a fast decline in smoking rates will result in lower COPD prevalence rates.

10.4.3.2.

COPD and gender

Projected COPD prevalence, Table 10.3 shows that the estimated COPD prevalence for men is higher than for women. In Birmingham the male and female rates in 2008 are 5.50% versus 3.95%. Male COPD rates are projected to increase, while the female rates only marginally go up. The difference is explained by men smoking more than women. COPD rates are highest in BEN PCT and lowest in HOB PCT for both sexes throughout the period. HOBâ&#x20AC;&#x2122;s young population is the likely cause of this difference. South Birmingham has a lower prevalence rate than BEN PCT. Although SB have a slightly older population and its level of deprivation is one quintile lower than BENâ&#x20AC;&#x2122;s. Table 10.3 Projected COPD prevalence by sex; Birmingham and PCTs, 2010-2020 Birmingham Gender

Males

Females

Both sexes

%

SB PCT

HoB tPCT

%

%

BEN PCT %

Year

N

2008

21,149

5.50

6,828

5.11

5,150

5.00

9,171

6.50

2009

21,223

5.48

6,846

5.08

5,167

4.99

9,211

6.50

2010

21,325

5.48

6,878

5.08

5,183

4.97

9,263

6.40

2015

22,157

5.54

7,163

5.15

5,396

5.02

9,598

6.40

2020

23,179

5.66

7,494

5.27

5,621

5.13

10,064

6.50

2008

16,123

3.95

5,531

3.84

3,676

3.56

6,916

4.32

2009

16,163

3.94

5,542

3.82

3,688

3.54

6,933

4.30

2010

16,205

3.93

5,569

3.81

3,696

3.53

6,939

4.30

2015

16,554

3.93

5,677

3.81

3,788

3.53

7,089

4.28

2020

17,080

3.96

5,864

3.85

3,890

3.57

7,326

4.32

2008

37,272

4.70

12,359

4.45

8,826

4.28

16,087

5.22

2009

37,386

4.69

12,388

4.43

8,855

4.26

16,144

5.21

2010

37,529

4.68

12,447

4.42

8,880

4.25

16,202

5.21

2015

38,711

4.71

12,841

4.46

9,183

4.28

16,686

5.23

2020

40,259

4.79

13,358

4.53

9,511

4.36

17,390

5.31

JSNA LTCs Final Version

N

N

N

133


10.4.3.3.

COPD and age

Table 10.4 shows clearly that there is a steep age profile in COPD prevalence. All across Birmingham less than 2% of those younger than 45 years are having COPD in 2008 and no rise in prevalence is predicted. •

Among the 45-64 year olds the prevalence is around 6% with no rise expected.

Among the 65-74 olds prevalence is around 12% across Birmingham, again with no rise expected.

Among those 75 years or older the rate is reaches the 13% with some increase during the years.

Table 10.4 Projected COPD prevalence by broad age groups; Birmingham and PCTs, 2010-2020 Birmingham Age group

16-44

45-64

65-74

75+

%

SB PCT

HoB tPCT

%

%

BEN PCT %

Year

N

2008

8,193

1.82

2,573

1.68

2,471

1.85

3,149

1.92

2009

8,222

1.82

2,588

1.68

2,484

1.85

3,150

1.92

2010

8,234

1.81

2,593

1.67

2,489

1.84

3,152

1.91

2015

8,253

1.79

2,592

1.65

2,505

1.82

3,155

1.89

2020

8,508

1.81

2,668

1.67

2,573

1.84

3,266

1.91

2008

12,515

6.08

4,265

5.66

2,750

6.11

5,500

6.43

2009

12,580

6.05

4,289

5.64

2,758

6.09

5,532

6.40

2010

12,653

6.03

4,311

5.61

2,778

6.07

5,564

6.37

2015

13,083

5.97

4,463

5.56

2,872

6.01

5,748

6.32

2020

13,633

6.12

4,659

5.70

2,988

6.16

5,985

6.46

2008

7,947

11.57

2,550

10.63

1,876

12.26

3,521

11.97

2009

7,979

11.53

2,558

10.61

1,876

12.26

3,545

11.98

2010

7,986

11.56

2,558

10.61

1,876

12.26

3,552

12.00

2015

8,321

11.59

2,672

10.65

1,966

12.29

3,683

12.00

2020

8,591

11.58

2,753

10.63

2,025

12.27

3,814

11.99

2008

8,616

12.77

2,970

11.69

1,729

13.72

3,917

13.23

2009

8,605

12.79

2,952

11.71

1,737

13.79

3,916

13.27

2010

8,656

12.86

2,984

11.75

1,737

13.79

3,934

13.29

2015

9,054

12.97

3,113

11.88

1,840

13.94

4,100

13.44

2020

9,527

13.03

3,278

11.96

1,925

14.05

4,324

13.56

JSNA LTCs Final Version

N

N

N

134


10.4.3.4.

COPD and ethnicity

The greatest burden of disease in terms of ethnic group in Birmingham and its constituents PCTâ&#x20AC;&#x2122;s will be in the White population. Across Birmingham there is projected to be an increase between 2008 â&#x20AC;&#x201C; 2020 in the prevalence of COPD in the White population, remain stable among the Black population and a decrease in the Asian population. Table 10.5 Projected COPD prevalence by major ethnic groups; Birmingham and PCTs, 2010-2020 Birmingham Ethnic group

White

Black

Asian

SB PCT

HoB tPCT

%

BEN PCT

Year

N

%

N

2008

30,215

5.08

11,283

4.60

4,823

4.98

14,109

5.62

2009

30,297

5.06

11,307

4.58

4,835

4.96

14,155

5.61

2010

30,413

5.16

11,361

4.58

4,847

4.95

14,205

5.61

2015

31,373

5.19

11,724

4.61

5,017

4.99

14,632

5.63

2020

32,688

5.28

12,206

4.69

5,214

5.08

15,268

5.72

2008

2,988

5.63

518

4.56

1,722

5.92

748

5.88

2009

2,999

5.62

520

4.54

1,728

5.90

751

5.88

2010

3,007

5.48

523

4.54

1,732

5.89

753

5.88

2015

3,096

5.52

536

4.58

1,787

5.95

772

5.91

2020

3,197

5.63

553

4.63

1,845

6.02

800

5.97

2008

4,069

2.82

558

2.61

2,281

2.84

1,231

2.76

2009

4,089

2.82

560

2.60

2,291

2.83

1,238

2.76

2010

4,109

2.61

563

2.59

2,301

2.82

1,245

2.75

2015

4,242

2.63

580

2.60

2,379

2.83

1,283

2.76

2020

4,373

2.65

599

2.64

2,451

2.88

1,323

2.80

N

%

%

N

10.5. The level of undiagnosed COPD in Birmingham The magnitude of undiagnosed cases of COPD can be ascertained by comparing the model estimates with the recorded prevalence of COPD, to indicate the extent of the unmet needs in COPD. In the UK this is facilitated by GP performance payments for COPD management through the Quality and Outcomes Framework (QOF) of the GP Contracts based on electronic register of all patients with diagnosed COPD. If this is linked to case finding and intervention, there is a potential for reducing the population burden and progression of the disease. The average QOF-diagnosed prevalence of COPD in England reported in 2007-08 through QOF was only 1.5%. This indicates that around 600,000 or nearly half of the 1.3 million COPD cases remain undiagnosed. A relatively large number of these individuals live in London or North of England. Many of such cases will continue their risk behaviours and eventually present themselves to the health services at later stages as more severe cases, possibly through emergency hospital admissions, with considerable cost to individuals the NHS and society. An audit of 80,000 COPD admissions showed that 70% of them are of patients not previously admitted with the condition.

JSNA LTCs Final Version

135


Table 10.6 compares the QOF data with the results of the ERPHO model. It indicates that the level of undiagnosed COPD in Birmingham, and in all the three PCTs, is higher than in England. In South Birmingham an estimated 6,400 people have COPD without being diagnosed (52%); in BEN the number is 10,000 or 62%, and in HOB PCT 6,735, being 75% of the total estimated number of COPD patients in 2007/08 Table 10.6 Modeled COPD prevalence in Birmingham PCTâ&#x20AC;&#x2122;s ERPHO model (2008)

COPD Register List, 2007/08

N

N

Persons with nondiagnosed COPD N

Birmingham

37,272

14,122

23,150

62.11%

Birmingham East and North Heart of Birmingham Teaching South Birmingham

16,087

6,085

10,002

62.17%

8,826

2,091

6,735

76.31%

12,359

5,946

6,413

51.89%

AREA

% COPD not diagnosed %

Source: ERPHO Prevalence Model, and QOF data

JSNA LTCs Final Version

136


11. Epilepsy Key messages for commissioners Key findings: • Epilepsy prevalence rate in Birmingham is close to national average except in HoB tPCT. • Prevalence of epilepsy is associated with age and social deprivation. • Prevalence of epilepsy is stable, but likely to increase due to the change of population in the city. Issues raised from this study: • The low QOF prevalence rate in HoB tPCT could be due to that it has younger population however this needs further investigation. • The factor driving increased prescription of anti-epileptic drugs (while the prevalence is consistent) might due to the increase of other uses (e.g. pain relief) of the drugs and the emergence of new anti-epileptic drugs. This needs further investigation. Big issues for management of epilepsy: • Improved preventative management (e.g. reducing poor birth outcomes) • Measures to help poorly controlled epilepsy (especially in association with learning disability and diabetes) Epilepsy is a neurological condition which presents in as many as 50 different types. It is caused by excess electrical activity in the brain and is diagnosed when someone has recurrent seizures. Over 440,000 people have epilepsy in the UK. It is the most serious neurological condition and a major LTC comparable, in terms of numbers of people affected, with insulin dependent diabetes (www.jointepilepsycouncil.org.uk) People with epilepsy have a risk of premature death that is two to three times higher than in the general population (Cockerell et al. 1995). Most premature deaths among people with epilepsy are directly related to the epilepsy itself. Every year in the UK about 1,000 people die because of epilepsy, and most of these deaths are associated with seizures. Sudden unexpected death in epilepsy (SUDEP) is the principal cause of death in people with chronic epilepsy and has been estimated to account for about 500 deaths each year in the UK. There were 81 deaths caused by epilepsy in Birmingham during the period 20052007, which gives approximately 27 deaths per year. Approximately three in four deaths (62, 76.5%) caused by epilepsy in Birmingham (from 2005 to 2007) were premature deaths (i.e. death under 75s). Compared with the national average, the death rate of epilepsy in Birmingham is 52% higher, especially in males (79% higher). Details of the local disease burden of epilepsy are described in Chapter 5. This chapter investigates the prevalence of epilepsy in Birmingham and the PCTs. It first looks into the prevalence of epilepsy locally, in terms of trend, demographical and socio-economical, and geographical distribution; it then describes clinical risk factors for epilepsy; and finally this chapter describes the projection of future prevalence of epilepsy in Birmingham. Data presented in this chapter are from the following sources:

JSNA LTCs Final Version

137


• • •

QOF Prescription data on epilepsy control drugs A study on epilepsy prevalence in England and Wales by Purcell et al. (Purcell et al. 2002) based on data from the General Practice Research Database (GPRD) of 211 GP practices collected

11.1. Definition For the purpose of this study the disease prevalence for epilepsy was defined as doctor registered epilepsy prevalence. i.e. patients registered with a GP as epileptic.

11.2. Current epilepsy prevalence and trends Figure 11.1 shows QOF prevalence trend for epilepsy in the three PCTs in Birmingham in comparison with Birmingham and England, from year 2004/05 to 2007/08. Current QOF prevalence of epilepsy suggests that in the year 2007/08: •

There were in total 6,320 people in Birmingham who were on the epilepsy register. Among them, 2,403 were in SB PCT, 1,229 in HoB tPCT and 2,688 in BEN PCT

The prevalence rate of epilepsy was 0.56% in Birmingham, which was slightly lower than the England’s rate (0.6%)

Epilepsy prevalence in SB PCT (0.63%) was slightly higher than both Birmingham and England average. It was also the highest among all three PCTs in Birmingham

Epilepsy prevalence in HoB tPCT (0.39%) was lower than both Birmingham and England average.

Epilepsy prevalence in BEN PCT (0.61%) was slightly higher than both Birmingham and England average

As suggested by the death rates from epilepsy, in 2005-07, HOB tPCT had the highest death rate among all three PCTs in Birmingham (3.53 per 100,000), followed by SB PCT (2.82 per 100,000) and BEN PCT (1.80 per 100,000). If we compare the distribution pattern of deaths with the QOF prevalence of epilepsy, it gives different pictures, especially around HOB tPCT – It has lower prevalence but higher death rate. An explanation for this may be that QOF prevalence rate for HOB tPCT was underestimated because the denominator of rate, GP registered population in HOB tPCT, was overestimated. Population data from the National Strategic Tracing Service (NSTS) and ONS population estimate show that in 2007 the size of GP registered population (315,422) in HOB tPCT was 16% larger than that of the ONS estimation (271,740). This is usually caused by situations such as patients who have moved away from the area are still on their old GP’s registration.

JSNA LTCs Final Version

138


Figure 11.1 Trend of epilepsy prevalence, PCTs, Birmingham and England, 2004/05 to 2007/08 0.70% 0.65% 0.60% 0.55% 0.50% 0.45% 0.40% 0.35% 0.30% 2004/05 SB

2005/06 HOB

BEN

2006/07

2007/08

Birmingham

England

Data source: QOF

The trend of epilepsy prevalence during the four-year period from 2004/05 to 2007/08 (as shown in Figure 11.1) suggests that: •

Epilepsy prevalence rate had been consistent over the period both nationally and locally

The prevalence in Birmingham first increased from 0.56% in 2004/05 to 0.58% in 2005/06, then decreased to 0.57% in 2006/07 and further decreased back to 0.56% in 2007/08

The prevalence in SB PCT had increased by approx 3%, from 0.61% in 2004/05 to 0.63% in 2007/08

The prevalence in HOB tPCT had consistently been the lowest among the three PCTs in Birmingham. It had decreased by approx 5%, from 0.41% in 2004/05 to 0.39% in 2007/08

Epilepsy prevalence in BEN PCT had decreased by approx 3%, from 0.63% in 2004/05 to 0.61% in 2007/08.

QOF only provides prevalence data for the recent four years (i.e. 2004/05 to 2007/08). In order to investigate the longer term trend of epilepsy prevalence, data on prescription of epilepsy control drugs (from GPs) are used as a proxy to show the long term trend. Prescription data are collected on a monthly basis by the Department of Medicine’s Management at Keele University on behalf of all PCTs in the West Midlands. Data collected include number of prescriptions and cost of the prescriptions in each month for each PCT. Figure 11.2 shows the rate of defined daily doses (DDD) of GP prescription of epilepsy control drugs (per 1,000 population) by month and PCT in Birmingham during the period of April 2000 to June 2009.

JSNA LTCs Final Version

139


Figure 11.2 Rate of defined daily doses of GP prescription of anti-epileptic drugs by PCT, April 2000 to May 2009, Birmingham

rate of defined daily doses per 1,000 population

400 350 300 250 200 150 100 50

Apr-09

Dec-08

Apr-08

Aug-08

Dec-07

Apr-07

Aug-07

Dec-06

Apr-06

Aug-06

Dec-05

Apr-05

Aug-05

Dec-04

Apr-04

Aug-04

Dec-03

Apr-03

Aug-03

Dec-02

Apr-02

Aug-02

Dec-01

Aug-01

Apr-01

Dec-00

Apr-00

Aug-00

0

Month SB PCT

HOB tPCT

BEN PCT

Data source: Department of Medicine’s Management, Keele University

Figure 11.2 shows that during the period of April 2000 to June 2009, the rate of DDD of prescription of epilepsy control drugs had increased significantly across all three PCTs in Birmingham. •

DDD rate in SB PCT had increased by 72.6% from 200.9 DDD per 1,000 population in April 2000 to 346.8 DDD per 1,000 population in June 2009

DDD rate in HOB tPCT had increased by 71.3% from 129.7 DDD (per 1,000 population) in April 2000 to 222.1 prescriptions in June 2009 (per 1,000 population)

DDD rate in BEN PCT had increased by 64.1% from 204.3 DDD per 1,000 populations in April 2000 to 335.4 DDD in June 2009 (per 1,000 population)

The increase in prescription should suggest increase in the prevalence of epilepsy, given the condition that the criteria (e.g. dosage) of drug prescription were consistent over the period. However, as anti – epileptic drugs are also used for pain relief, this creates uncertainty into using prescriptions as a proxy for prevalence. Looking at the trend of DDD of prescription from April 2004 to March 2008 on a yearly basis, which is the same time period covered by QOF, the prescribing data suggests a different trend from QOF prevalence. The prescription trend suggests an increase across all PCTs in Birmingham, with 16.9% in SB PCT, 19.7% in HOB tPCT and 16.1% in BEN PCT while the QOF prevalence suggests a rather consistent trend with slight decrease in HOB tPCT and BEN PCT over the same period. Explanation for the difference in the trend of QOF prevalence and anti-epileptic drug prescription is that GPs were using new anti-epileptic drugs (e.g. lamotrigine) alongside old drugs (e.g. carbamazepine). The prescription data on anti-epileptic drugs are worth further investigating into. The increase of prescription of anti-epileptic drugs with the consistent QOF epilepsy prevalence trend may suggest that even if the future prevalence of epilepsy remains similar to current prevalence, the prescription of epilepsy control drugs and related costs may still increase. However, as described above, there are other factors (e.g. anti-epileptic drugs used for other

JSNA LTCs Final Version

140


purposes) that can drive the increase of anti-epileptic prescribing. These factors need to be taken into account to draw such a conclusion.

11.3. Geographical variation Figure 11.3 shows the geographical variation of epilepsy prevalence in Birmingham, based on QOF data. Details of the method of mapping QOF prevalence to wards are described in Section 3.4.1. Figure 11.3 shows that in the year 2007/08, the ward level prevalence rate of epilepsy varied from 0.35% to 0.82%. •

Higher prevalence of epilepsy was seen in the southern wards of Birmingham (SB PCT’s catchments area) and the northeast wards (BEN PCT’s catchments areas)

Epilepsy prevalence was relatively low in most central Birmingham wards (HOB tPCT and SB PCT catchments areas)

Geographical variation in disease prevalence is usually caused by demographical variations, such as age and ethnicity. Figure 11.3 Epilepsy prevalence by ward, Birmingham, 2007/08

Data source: QOF PHIT calculation

11.4. Demographical patterns This part presents data on age and gender distribution of epilepsy prevalence from a study by Purcell et al. (Purcell et al. 2002). The Purcell et al.’s study was based on

JSNA LTCs Final Version

141


data collected on epilepsy patients from 211 GPs in England and Wales from the General Practice Research Database (GPRD), for the period 1994 to 1998. The age/gender prevalence rate of epilepsy in England and Wales suggested by Purcell et al. was then applied to the local population and estimations were made of the local prevalence of epilepsy.

11.4.1. Epilepsy by age Table 11.1 shows epilepsy prevalence rate (per 1,000 patients) by gender and age group in England and Wales in the year 1994 and 1998 (Purcell et al. 2002). It shows that: â&#x20AC;˘

Epilepsy prevalence rate was positively associated with age. Higher prevalence was seen in older people

â&#x20AC;˘

The overall prevalence for males and females were similar. However, males tended to have higher prevalence than females in older age groups, in particular, the 75 and above age groups

Compared with the QOF Prevalence rate for England (approx 6 per 1,000) during the period 2004/05 to 2007/08 (as illustrated in Figure 11.1), the Purcell et al.â&#x20AC;&#x2122;s study (Purcell et al. 2002) (Table 11.1) suggests higher prevalence rate of epilepsy nationally at approximately 7.1 and 7.7 in 1994 and 1998 accordingly. This seems to suggest a decline in epilepsy nationally, however, as the data were collected from different sources, and the geographical area used was different (i.e. QOF did not include Wales), the difference might be caused by the difference in data collection and data quality. Table 11.1 Epilepsy prevalence rate (per 1,000 patients) by gender and age group, England and Wales, 1994 and 1998 (Purcells et al. 2002)

0-4

5-15

1624

2534

3544

4554

5564

6574

7584

85 and over

all ages

Males 1994

2.1

4.2

6.3

7.2

7.2

7.7

9.0

10.9

13.5

16.2

7.2

1998

1.9

4.4

6.6

7.9

8.0

8.4

9.5

10.9

13.9

15.1

7.7

1994

1.3

4.0

6.8

7.4

7.1

8.3

9.0

8.9

9.2

10.5

7.1

1998

1.8

4.1

6.9

7.9

7.8

8.7

9.0

10.2

9.9

11.0

7.6

Females

11.4.2. Epilepsy by gender Figure 11.4 shows age standardised treated epilepsy prevalence rate (per 1,000 patients) by gender in England and Wales, in 1994 and 1998 (Purcell et al. 2002) It shows that epilepsy prevalence rates for males and females were very similar, only

JSNA LTCs Final Version

142


slightly higher in males than in females. The rates for both genders had increased slightly from the year 1994 to 1998. Figure 11.4 Age standardised treated epilepsy prevalence rate (per 1,000 patients) by gender, England and Wales, 1994 and 1998 (Purcell et al. 2002)

Prevalence rate of epilepsy per 1,000 patients

8.0

7.4

7.0

7.2

6.8

7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 1994

1998 Year Male

Female

11.4.3. Local implications Figure 11.5 and Figure 11.6 show the estimated numbers of people with epilepsy in Birmingham by age group and PCT. It was calculated by applying the age specific prevalence rates in England and Wales (in 1998) suggested by the Purcell et al. (as shown in Table 11.1) to the ONS mid year population estimate (2007) for Birmingham and the PCTs. An assumption was made that the age specific prevalence rates for epilepsy for Birmingham in 2007 was the same as the rates for England and Wales in 1998. Figure 11.5 and Figure 11.6 show that in 2007: •

Although the prevalence rate (i.e. line in the graphs) of epilepsy was positively associated with age, the estimated number of people with epilepsy (i.e. bars in the graphs) was higher in younger age groups in Birmingham. This was mainly due to the relatively young population locally

Larger numbers of people with epilepsy were seen in age group 16 – 54, with the biggest number in age group 25 – 34, for both males and females in Birmingham

The age group distributions were similar between males and females in Birmingham

JSNA LTCs Final Version

143


16

700

14

600

12

500

207

10

226

178

182

6

137

161

198

0

0-4

124

81

200

75

97 30 24 20

300

151

154 108

4 2

400

196

8

57 175

190

188

163

94

161

127

101

42 14 34

100

Estimated number of people with Epilepsy**

Epilepsy prevalence rate (per 1,000 popualtion), 1998*

Figure 11.5 Estimated numbers* of people with epilepsy by age group and PCT, males, 2007

0

5-15 16-24 25-34 35-44 45-54 55-64 65-74 75-84 85 and over Age group SB

HOB

BEN

Epilepsy prevalence rate 1998

Estimated based on the 1998 rates (Purcell et al. 2002) and ONS mid year population estimate 2007

12

700

10

600

8

182

500

214 230 207

6

175 170

4

177

123

84

0-4

5-15

116

125

194

187

179

159

200

79 51

189 27 22 18

300

160 138

83

88

2 0

400

132

107

64 22 58

100

Estimated number of people with Epilepsy**

Epilepsy prevalence rate (per 1,000 popualtion), 1998*

Figure 11.6 Estimated numbers* of people with epilepsy by age group and PCT, females, 2007

0

16-24 25-34 35-44 45-54 55-64 65-74 75-84 85 and over Age group

SB

HOB

BEN

Epilepsy prevalence rate 1998

Estimated based on the 1998 rates (Purcell et al. 2002) and ONS mid year population estimate 2007

JSNA LTCs Final Version

144


11.5. Epilepsy and deprivation The relationship between the prevalence of epilepsy and social deprivation was studied in several studies (Morgan et al. 2000) and a positive association between the two was suggested.

11.5.1. Epilepsy prevalence by deprivation quintiles Figure 11.7 shows the prevalence of treated epilepsy per 1,000 patients by gender and deprivation quintile of GP practice in England and Wales, from 1994 to 1998, based on the study by Purcell et al. (Purcell et al. 2002). It shows that: â&#x20AC;˘

During the period 1994 to 1998, the recorded prevalence of treated epilepsy in the 211 practices showed a clear gradient across the deprivation quintiles for both males and females

â&#x20AC;˘

The prevalence was 6.3 per 1,000 in the least deprived quintile (1st quintile) in females rising to 7.9 per 1,000 in the most deprived quintile (5th quintile). This was a 25% difference in prevalence between the most and the least deprived groups

â&#x20AC;˘

In males these rates were 6.0 and 8.0 per 1,000 respectively, again a 25% difference.

Figure 11.7 Prevalence of treated epilepsy (per 1,000 patients), by gender and deprivation quintile* of GP practice, England and Wales, 1994 to 1998 (Purcell et al. 2002) Males

Females

* Townsend Material Deprivation Score

JSNA LTCs Final Version

145


11.5.2. Local implications As described in Section 4.3, Birmingham is one of the most deprived Local Authorities nationally and more than half of Birmingham’s population is in the most deprived quintile (5th quintile) nationally. The large proportion (more than 90%) of Birmingham residents living in the 3rd, 4th and 5th quintile indicates higher prevalence of epilepsy due to deprivation locally. Interestingly, however, HOB tPCT which is the most deprived PCT area in Birmingham and has the largest proportion of population living in the 5th quintile, has lower prevalence of epilepsy (as illustrated in Figure 11.1), compared with the other two PCTs in Birmingham, based on QOF data. This seems to contradict the association between social deprivation and epilepsy prevalence. Explanations for this may be: •

the lower epilepsy prevalence in HOB tPCT is mainly due to the reason that it has the youngest population in Birmingham and age is also associated with the prevalence of epilepsy QOF prevalence for HOB tPCT is underestimated (as described in Section 11.2)

11.6. Clinical risk factors Clinical risk factors for epilepsy are not as clear as some of the other LTCs reported in this study. This part describes cause and misdiagnosis of epilepsy, as well as the link between epilepsy and learning disabilities.

11.6.1. Cause of epilepsy In approximately 30% of cases the cause of epilepsy is known, in which case it is called ‘symptomatic epilepsy’. Common causes include brain damage (resulting from a head injury or the brain being starved of oxygen), scarring of the brain tissue, a tumour, or chemical/hormonal imbalances. Some types of epilepsy are inherited. Nevertheless, in approximately 60% of the time the cause of epilepsy is not known, and the condition is then known as ‘idiopathic epilepsy’ (www.jointepilepsycouncil.org.uk).

11.6.2. Misdiagnosis of epilepsy Diagnosing epilepsy can be very difficult, given the fact that almost one in 20 people experience a ‘funny turn’ at some time in their life (www.jointepilepsycouncil.org.uk). Due to the complexity of diagnosis, misdiagnosis of epilepsy is not unusual. Misdiagnosis rates of epilepsy in the UK are between 20% - 31% (NICE 2004). Using an assumed rate of 23% (NICE 2004) this equates to 1,454 people (based on QOF prevalence) in Birmingham in 2007/08 with a diagnosis of epilepsy and receiving epilepsy control drugs who do not have the condition. This splits to 553 people in SB PCT, 260 people in HoB tPCT and 618 people in BEN PCT.

11.6.3. Epilepsy and learning disabilities Epilepsy is associated with learning disabilities. Studies show that 14% - 24% of people with an intellectual disability are affected by epilepsy (http://www.library.nhs.uk/learningdisabilities/). The frequency of life-time history of

JSNA LTCs Final Version

146


epilepsy ranges from 7% - 15% of people with mild to moderate intellectual disability; 45% - 67% of people with severe intellectual disability; and 50-82% of people with profound intellectual disability.

11.7. Projected prevalence of epilepsy This section describes the projection of epilepsy prevalence in Birmingham to the year 2020. The purpose of the projection is to provide an estimate of the magnitude of the disease so that future needs of health can be assessed. The projection described in this part is based on the age/gender model of epilepsy prevalence rates in England and Wales in 1998 suggested by Purcell et al (Purcell et al. 2002).

11.7.1. Applying current prevalence rates to projected population In order to project future prevalence of epilepsy, age/gender prevalence rates of epilepsy in England and Wales in 1998 suggested by Purcell et al. (Purcell et al. 2002), as shown in Table 11.1 were used as the predicting model. These rates were applied to projected future local population to calculate the number of people with epilepsy (method is described in Section 3.5.2). No further adjustment on deprivation was used in this study. Assumption was made that the prevalence rate of epilepsy will be consistent to 2020 (i.e. same as the 1998 rate for England and Wales) and the change in prevalence in future will solely come from the change in population. The ONS population projection was used and inputted into the predicting model to calculate the projected number of epileptic patients in each gender/age group in 2020, in Birmingham and the three PCTs. Details of the ONS projected population (by age and gender) in Birmingham are described in Section 4.1.2 and the age and gender distribution of the projected population can be found in Table E.1 in Appendix E.

11.7.2. Projected prevalence of epilepsy Figure 11.8 shows the result of the projection: projected number of people with epilepsy by PCT in Birmingham in the year 2010, 2015 and 2020. It shows that: •

The number of people with epilepsy will increase across all PCTs in Birmingham in the next 10 years.

Projected number of epileptic patients in Birmingham will be 7,904 in 2010, 8,192 in 2015 and 8,471 in 2020. This gives an increase of 7% in 10 years’ time.

SB PCT will have 2,660, 2,751 and 2,841 people with epilepsy in 2010, 2015 and 2020 accordingly. The number of people with epilepsy will increase by 7% in the next 10 years.

HOB tPCT will have 2,141, 2,223 and 2,290 people with epilepsy in 2010, 2015 and 2020 accordingly. The number of people with epilepsy will increase by 7% in the next 10 years.

BEN PCT will have 3,102, 3,218 and 3,340 people with epilepsy in 2010, 2015 and 2020 accordingly. The number of people with epilepsy will increase by 7% in the next 10 years.

JSNA LTCs Final Version

147


Figure 11.8 Projected numbers of people with epilepsy by PCT, Birmingham, 2010, 2015 and 2020

number of people with epilepsy

10000

8000 2751

2841

2141

2223

2290

3102

3218

3340

2010

2015

2020

2660 6000

4000

2000

0 Year BEN

HOB

SB

Data source: PHIT

11.7.3. Projected prevalence of epilepsy by age and gender Figure 11.9 and 11.10 shows the projected number of people with epilepsy in 2020 by age group and PCT (i.e. the bars in the graph), for males and females, in comparison with the estimated prevalence of epilepsy in 2007 (i.e. the lines in the graph). It is worth noticing that as both of the prevalence in 2007 and 2020 are estimated based on the same gender/age prevalence rates suggested by Purcell et al. (Purcell et al. 2002), the difference between the prevalence in 2007 and 2020 shown in the figures are solely due to the change in population (Please see Section 4.1.2 and Appendix E for details of the projected population change in Birmingham and the PCTs to 2020). Figure 11.9 and 11.10 show that: •

The number of projected epilepsy patients will increase by 2020, across all age groups and all PCTs in Birmingham, in comparison with 2007.

Most of the increase will be from the 25 – 34 age group for both males and females, across all PCTs in Birmingham.

SB PCT will see cases increase in the younger age groups (i.e. aged 5 – 34) for both genders. The number of cases in older age groups (aged 65 and above) will remain similar to the 2007 level for both genders, apart from the increase in males of 85 years old and above.

JSNA LTCs Final Version

148


HOB tPCT will see very similar (only slightly increased) numbers of epilepsy patients in each age group in 2020 as in 2007, for both genders. The only exception is the increase in the 25 – 34 groups.

BEN PCT will see increase of epilepsy cases in older age groups (i.e. aged 45 and above) and the 25 – 34 age group, for both genders. The number of cases in younger age groups (aged 24 and below) will remain similar to the 2007 level.

Figure 11.9 Projected number of people with epilepsy by age group and PCT, males, 2020 in comparison with estimated prevalence in 2007

Number of people with epilepsy

300

250

200

150

100

50

0 0-4

5-14

15-24

25-34

35-44

45-54

55-64

65-74

75-84

85+

Age group SB 2020

HOB 2020

BEN 2020

SB 2007

HOB 2007

BEN 2007

Data source: PHIT

JSNA LTCs Final Version

149


Figure 11.10 Projected number of people with epilepsy by age group and PCT, females, 2020 in comparison with estimated prevalence in 2007

Number of people with epilepsy

300 250 200

150 100

50 0 0-4

5-14

15-24

25-34

35-44

45-54

55-64

65-74

75-84

85+

Age group SB 2020

HOB 2020

BEN 2020

SB 2007

HOB 2007

BEN 2007

Data source: PHIT

Details of the age and sex distribution of the projection of epilepsy prevalence for Birmingham and the PCTs can be found in Table F.1 in Appendix F.

11.7.4. Limitations of the projection There are several factors that can affect the accuracy of the projection of future prevalence of epilepsy in Birmingham in this study. An assumption was made in the projection that the age/gender prevalence rate of epilepsy in Birmingham in 2020 will be the same as the rate for England and Wales in 1998 (as suggested by Purcell et al (Purcell et al. 2002). However, this ‘static’ prevalence rate may not be true. Studies are needed on long-term trend of prevalence rate of epilepsy to adjust the change over time in the predicting model. In addition, the gender/age group prevalence rate used in the predicting model was based on data back in 1998, which was over 10 years old. Again the change of rate over time was not adjusted. In addition, the projection is only based on the gender/age group specific prevalence rates and did not take deprivation into account. However as described in Section 11.5, previous studies confirm that the association between prevalence of epilepsy and social deprivation. Therefore, the projection can be underestimated, given the fact that Birmingham is a very deprived area. Finally, misdiagnosis of epilepsy is not adjusted in the prediction. As described in Section 11.6.2, misdiagnosis rate of epilepsy is high (at approx 23%) in the UK. To project the ‘true’ prevalence of epilepsy, the misdiagnosed cases should be

JSNA LTCs Final Version

150


excluded. Arguably, however, as this study looks at the prevalence of ‘doctor registered epilepsy’ (as defined in Section 11.1), all the misdiagnosed cases in theory still should be counted as registered cases. From a needs assessment’s point of view, the misdiagnosed patients still receive the health and social care services for epilepsy patients and the needs of this group of people need to be assessed.

JSNA LTCs Final Version

151


12. Chronic kidney disease Key messages for commissioners Key findings: • QOF CKD (stage 3 and 4) prevalence rate in close to the national average, with higher rate in SB PCT area and lower rate in HoB tPCT area • Renal Replacement Therapy (RRT) prevalence rate is much higher in the Birmingham PCTs than the national average, especially in HoB tPCT area • CKD prevalence is strongly associated with age. It is higher in the BME group too. • CKD stage 5 is associated with social deprivation • Prevalence of CKD is likely to increase due to the change of population in the city.

Joint Strategic Needs Assessment

Key issues from the study: • The different patterns in QOF CKD (stage 3 and 4) prevalence and RRT prevalence indicate signs of late identification of CKD cases in Birmingham, especially in HoB tPCT area • Data availability on long term trend of CKD and related risk factors remains an issue. Big issues for management of CKD: • Improved preventative management of the early stages of CKD • Reduction of the amount of chronic renal failure by ideal management of the acute renal failure. Chronic kidney disease (CKD), also known as chronic kidney failure, is a long-lasting and irreversible condition that is caused by damage to the kidneys (http://www.nhs.uk/Conditions/Kidney-disease-chronic/Pages/Introduction.aspx).The number of people with CKD is not accurately known, because a lack of symptoms in the early stages means it often remains undiagnosed. The introduction of CKD into the QOF has determined that there are 1.5 million people with CKD stages 3-5 (stage 5 being established as renal failure) in England (http://www.nhs.uk/Conditions/Kidney-diseasechronic/Pages/Introduction.aspx). Recent research suggests that one in ten of the population may have CKD. It is less common in young adults, being present in 1 in 50 people. In those aged over 75 years, CKD is present in one out of two people. However, many of the elderly people with CKD may not have ‘diseased’ kidneys, but have normal ageing of their kidneys (www.renal.org) Chronic Kidney Disease is an epidemic worldwide with a growth of 6% - 8% per annum of dialysis patients. People with CKD are roughly twenty times more likely to die of cardiovascular disease than to progress to end-stage renal failure (http://www.cks.nhs.uk/clinical_topics/by_clinical_specialty/kidney_disease_and_urology). In most cases CKD does not cause any symptoms, and is detected because tests are abnormal. These may be urine tests for blood or protein; an X-ray or scan of the kidneys; or a blood test to measure kidney function. CKD is very common, but less than one in ten people with CKD ever require dialysis (artificial kidney treatment) or a kidney transplant.

JSNA LTCs Final Version

152


A test called the eGFR (estimated glomerular filtration rate) is used to measure kidney function. The eGFR is calculated by the laboratory from the level of a chemical called creatinine in the blood. A normal eGFR is about 120 ml/min in young adults (www.renal.org). CKD is divided into 5 stages by the level of GFR, as illustrated in Table 12.1: Table 12.1 National Kidney Foundation KDOQI staging for CKD

Stage of CKD

Description

eGFR 2 (ml/min/1.73m )

1

Kidney damage with normal or raised GFR

>90

2

Kidney damage with mildly reduced GFR

60-90

3

Moderately reduced GFR

30-59

4

Severe reduction in GFR

15-29

5

Kidney failure

<15

This chapter investigates the prevalence of CKD (stage 3 and above) in Birmingham and the PCTs. It first looks into the prevalence of CKD locally, in terms of trend, demographical, socio-economical and geographical distribution; it then describes lifestyle and clinical risk factors for CKD; and finally this chapter projects the future prevalence of CKD (stage 3 and above) in Birmingham and the PCTs up to 2020. Data presented in this chapter are from the sources below. •

QOF Research studies on prevalence of CKD including: Stevens et al.’s study (Stevens et al. 2007) and Bello et al.’s study (Bello et al. 2008)

UK renal registry: The UK Renal Registry is a resource for the development of patient care in renal disease. It was established by the Renal Association with support from the Department of Health, the British Association of Paediatric Nephrologists, and the British Transplant Society.

As kidney disease is going to be included in the Health Survey for England (HsfE) 2009, this will provide richer data resources and thus better understanding of the prevalence of CKD in future. Details of an appraisal on these data sources can be found in Table B.1 in Appendix B.

12.1. Definition For the purpose of this study the disease prevalence for CKD was defined as the prevalence of doctor registered CKD (eGFR < 60, i.e. stage 3 to 5).

12.2. Current CKD prevalence Figure 12.1 shows QOF prevalence trend for CKD in the three PCTs in Birmingham in comparison with Birmingham and England, for years 2006/07 and 2007/08. CKD

JSNA LTCs Final Version

153


prevalence is a new indicator in QOF and it is only collected for two years so far (i.e. 2006/07 and 2007/08). The QOF prevalence is for the prevalence of CKD stage 3 to 5 and for patients aged 18 years old and over. However, as QOF indicators are generally for primary care management while CKD stage 5 (i.e. renal failure) is mainly managed by secondary care, QOF CKD prevalence is more of the prevalence of CKD stage 3 and 4. Current QOF prevalence of CKD suggests that in the year 2007/08: •

CKD was a highly prevalent LTC with 31,714 people (aged 18 years old and over) in total in Birmingham on the CKD (stage 3 and 4) register. Among them, 14,604 were in SB PCT, 6,133 in HoB tPCT and 10,977 in BEN PCT.

The prevalence rate of CKD was 2.80% in Birmingham, which was slightly lower than the England’s rate (2.90%).

CKD prevalence rate in SB PCT (3.81%) was higher than both Birmingham and England average. It was also the highest among all three PCTs in Birmingham.

CKD prevalence rate in HoB tPCT (1.97%) was lower than both Birmingham and England average. It was also the lowest among all three PCTs in Birmingham.

CKD prevalence rate in BEN PCT (2.50%) was slightly lower than both Birmingham and England average.

Figure 12.1 CKD (stage 3 and 4) prevalence, Birmingham, the PCTs and England, 2006/07 to 2007/08 4.00% 3.50% 3.00% 2.50% 2.00% 1.50% 1.00% 0.50% 0.00% 2006/07 SB

HOB

2007/08 BEN

Birmingham

England

Data source: QOF

The two-year ‘trend’ of CKD prevalence rate from 2006/07 to 2007/08 (as shown in Figure 12.1) suggests that:

JSNA LTCs Final Version

154


CKD prevalence rate had increased both nationally and locally, although arguably this increase could be caused by the reason that 2006/07 was the first year that CKD was included in QOF and underreporting should be expected.

The prevalence in Birmingham had increased from 2.26% in 2006/07 to 2.80% in 2007/08, which was an increase of 23.9%.

The prevalence in SB PCT had increased by approx 28.3%, from 2.97% in 2006/07 to 3.81% in 2007/08.

The prevalence in HOB tPCT was the lowest among the three PCTs in Birmingham in both years. It had increased by approx 27.9%, from 1.54% in 2006/07 to 1.97% in 2007/08.

CKD prevalence in BEN PCT had increased by approx 16.3%, from 2.15% in 2006/07 to 2.50% in 2007/08.

It is worth noticing that as CKD is a new indicator in QOF, underreporting is expected for the first year of it (i.e. 2006/07). The sharp increase of CKD is more due to this reason rather than reflecting the real trend. In addition, uncertainty was created in the 2006/07 due to the unclear definition of the diagnosis in the first year of the indicator that some patients were registered on one abnormal eGFR not the two separated test results by 3 months required.

12.3. Renal replacement therapy prevalence Renal replacement therapy (RRT) is a term used to encompass life-supporting treatments for renal failure. It includes haemodialysis, peritoneal dialysis, hemofiltration and renal transplantation. Many advanced CKD patients (i.e. stage 5) receive RRT. The trend of the prevalence of RRT is used in this report as a proxy for the trend of the prevalence of CKD stage 5 (Ansell et al. 2008), as in 31/12/07, there were 37,614 patients in total in England who were on RRT. This equates to a crude prevalence rate of 736 persons per million population (pmp). The crude prevalence rate of RRT in the Birmingham PCTs were much higher, with HoB tPCT at 1,389 pmp (88.7% higher), BEN PCT at 1,003 pmp (36.2% higher) and SB PCT at 872 pmp (18.5% higher). Interestingly, the PCT distribution of RRT prevalence is opposite to that of the QOF CKD (stage 3 and 4) prevalence. HoB tPCT was ranked the lowest in the QOF CKD prevalence and highest in the RRT prevalence; on the other hand, SB PCT changed from the highest in QOF prevalence to the lowest in RRT prevalence. This difference indicates different prevalence pattern between the earlier stages of CKD (i.e. stage 3 and 4) and the most advanced stage of CKD (i.e. stage 5). This difference may also suggest underreporting of earlier stages of CKD in HoB tPCT area as patients are only identified when the CKD develop to advanced stage. The same explanation may also apply to BEN PCT’s lower QOF CKD prevalence rate than the national average but higher RRT prevalence rate. Figure 12.2 shows the age standardised prevalence ratio of RRT in the three Birmingham PCTs in comparison with England, based on data from the UK Renal Registry. It shows that after adjusted for age:

JSNA LTCs Final Version

155


In 2007, the prevalence rate of RRT in Birmingham PCTs was even higher than the national average. HOB tPCT was the highest at 2.44, followed by BEN PCT at 1.47 and SB PCT at 1.26

During the period from 2004 to 2007, the prevalence rate of RRT was consistent both nationally and locally, except the continuous decrease in SB PCT area.

Figure 12.2 Age standardised prevalence ratio* of renal replacement treatment (RRT), Birmingham PCTs and England, 2004 to 2007

Standardized prevalence ratio

3

2.5

2

1.5

1

0.5

0 2004

2005

2006

2007

Year BEN PCT

HOB tPCT

SB PCT

England

Data source: UK renal registry http://www.renalreg.com/ * Indirect standardisation using UK population as reference

As the QOF prevalence rate (in Figure 12.1) is unadjusted, it is hard to compare the age standardised prevalence ratio of RRT (in Figure 12.2) with it. However, the increased gap between Birmingham PCTs and the national in RRT prevalence (after adjust for age) may indicate that if adjust for age the local QOF prevalence should be higher than the national average as well, as Birmingham has a relatively younger population.

12.4. Geographical variations Figure 12.3 shows the geographical variation of CKD (stage 3 and 4) prevalence in Birmingham, based on QOF data. Details of the method of mapping QOF prevalence to wards are described in Section 3.4.1. It shows that in the year 2007/08, the ward level prevalence rate of CKD varied from 1.40% to 5.28%. •

Higher prevalence of CKD was seen in the southern and southeast wards of Birmingham (SB PCT’s catchments area) and some of the north wards (BEN PCT’s catchments areas)

CKD prevalence was relatively low in most central Birmingham wards and some northern wards (HOB tPCT and BEN PCT catchments areas)

JSNA LTCs Final Version

156


Geographical variation in disease prevalence is usually caused by demographical variations, such as age and ethnicity. Figure 12.3 CKD (stage 3 and 4) prevalence by ward, Birmingham, 2007/08

Data source: QOF PHIT calculation

12.5. Demographical patterns This section presents data on age, gender and ethnicity distribution of CKD prevalence from two sources. Stevensâ&#x20AC;&#x2122;s study on CKD prevalence in England (Stevens et al. 2007) is part of the NEOERICA (New Opportunities for Early Renal Intervention by Computerised Assessment) project and it use a sample of 38,263 patients who are 18 years old and above and with a valid creatinine value recorded in the regions of Kent, Manchester, and Surrey in the UK to study the risk factors of CKD (Ansell et al. 2008). In addition, data from the UK Renal Registry on demographical patterns of patients on the RRT registry are also presented in this section.

12.5.1. Age and gender The risk of developing chronic kidney disease increases with age. Figure 12.4 shows the CKD (stage 3 to 5) prevalence rate (%) by gender and age group in England in 2003, based on the Stevensâ&#x20AC;&#x2122;s study (Stevens et al. 2007).

JSNA LTCs Final Version

157


Figure 12.4 CKD (stage 3 to 5) prevalence rate by gender and age group, England, 2003 (Stevens et al. 2007)

48.61%

50.00%

44.75% Percentage of CKD Stage 3 to 5

41.68% 40.00% 33.16% 27.86%

30.00%

20.00%

17.65% 13.09%

10.00% 2.69% 0.79% 0.18% 0.71% 0.17% 0.01%

6.89% 3.08% 2.79%

0.00% 18-24

25-34

35-44

45-54

55-64

65-74

75-84

85+

Age group Males

Females

Figure 12.4 shows that in 2003: •

The prevalence rate of CKD was highly associated with age that by the age of 75, more than one in four women (27.9%) and more than one in six men (17.7%) were with CKD.

Prevalence of CKD was higher in females than in males in all age groups, apart from the 35-44 group. The same study (Stevens et al. 2007) also reported that the age standardized prevalence rate was 5.8% for males and 10.6% for females. •

The prevalence of CKD started to increase sharply from the age of 55, for both genders. Nearly half of the very elderly people (i.e. aged 85 and above) were with CKD.

The Stevens’s study suggests a higher prevalence of CKD than what is suggested by QOF, this is caused by the reasons below: •

QOF CKD register requires two separated abnormal test results by 3 months’ time interval while the Stevens’s study did not apply the same requirement of two separate test results and this could lead to overestimating

QOF mainly covers stage 3 and 4 patients on the register while the Stevens’s study covers stage 5 CKD as well.

Besides, QOF can be underreporting as CKD is still a relatively new indictor in QOF.

It will provide a more accurate and consistent estimate of age specific CKD prevalence if local primary care data is available.

JSNA LTCs Final Version

158


Figure 12.5 shows the age and gender distribution of prevalence rate of RRT patients from UK Renal Registry. Figure 12.5 Prevalence rate of RRT patients per million population by age and gender on 31/12/07, United Kingdom (David Ansell , Terry Feest, Andrew Williams, Chris Winearls. 2008)

Data source: UK Renal Registry http://www.renalreg.com/

Figure 12.5 shows that: •

The overall UK peak crude prevalence rate occurred in the age band 70-74 at 1,808 pmp.

For all ages, crude prevalence rates in males exceeded those in females, peaking in the 75-79 year age band for males at 2,506 pmp and in females in the 70-74 year age group at 1,314 pmp.

Comparing with the CKD (stage 3 to 5) prevalence rate suggested by Stevens et al. (as shown in Figure 12.4), the RRT prevalence rates show a different age and gender pattern. •

The RRT prevalence was higher in males than in females while the CKD (stage 3-5) prevalence was the other way round

The RRT prevalence peaked in the 70 – 74 age group while the CKD (stage 3-5) prevalence peaked in the eldest age group (i.e. 85 and above)

The reason that causes the difference in the age and sex distribution of the prevalence of RRT and CKD (stage 3 to 5) is that RRT is not suitable for many patients, especially those who have severe co morbidities such as heart failure. The difference might be caused by different age and sex patterns of co morbidities with CKD. This needs further investigation into once the local primary care data on CKD is available to the PHIT team.

JSNA LTCs Final Version

159


12.5.2. Ethnicity Data from UK Renal Registry on the proportion of BME population in each PCT and age gender standardised prevalence ratio (as illustrated in Figure 12.6) show a statistically significant association between the proportion of the BME and the prevalence of RRT in the PCTs in England (Spearman’s correlation coefficient = 0.60, p<0.0001) (Ansell et al. 2008).

Age-gender standardised rate ratio

Figure 12.6 Relation between standardised rate ratio for renal replacement therapy and proportion of non-Whites in Primary Care trusts in England (Ansell et al. 2008) 300 250 200 150 100 50 0 0

10

20

30

40

50

60

70

% non-white Data source: UK Renal Registry

In addition, a study on incidence rates of RRT in Birmingham (Lambie et al. 2002) also shows that there was little change in the incidence rates in 16-54s for all three ethnic groups (i.e. White, Indo-Asian and Black) between the 1991 and 2001 cohorts, and in the White 55-70 age group. There was a significant increase in Black group (648 – 978 pmp) and Indo-Asian (1,032 – 1,335 pmp) in the 55-70 age group. The biggest differences were seen in the >70s. For the White group, the increase was 248% (177 – 440 pmp), for Indo-Asian group 319% (536 – 1,711 pmp) and for Black 617% (301 – 1,858 pmp). However, arguably the sharp increase was mainly due to the improved access to the health services.

12.5.3. Local implications 12.5.3.1.

Age and gender

Figure 12.7 and Figure 12.8 show the estimated number of people with CKD in Birmingham by age group and PCT. It was calculated by applying the age specific prevalence rates in England (in 2003) suggested by Stevens et al. (as shown in Figure 12.4) to the ONS mid year population estimate (2007) for Birmingham and the PCTs. An assumption was made that the age specific prevalence rates for CKD for Birmingham in 2007 was the same as the rates for England in 2003, as suggested by Stevens et al.. Figure 12.7 and Figure 12.8 show that in 2007:

JSNA LTCs Final Version

160


The prevalence rate (i.e. line in the graphs) of CKD was positively associated with age for both genders.

The estimated number of people with CKD (i.e. bars in the graphs) was also positively associated with age, apart from the 85 and above group. This was mainly due to the reason that population size in this group was small.

Larger numbers of people with CKD were seen in age group 55 and above, with the biggest numbers in age group 75 – 84, for both genders in Birmingham

The age group distributions were similar between males and females in Birmingham

The majority of CKD patients were females who accounted for approximately two thirds (66.1%) of all CKD patients in the 75 and above group

Figure 12.7 Estimated CKD (stage 3 to 5) prevalence by age group and PCT, males, Birmingham, 2007 study (Stevens et al. 2007) 3500

50.00% 2968

3000

2444 2412

2500

2061

30.00%

2000

1319 1169

20.00%

10.00%

2 2 2

414345

18-24

25-34

717 596 395 167 201 137

1213

1351

1231 1016

1500 1000

588 405

Number of peeple with CKD

CKD prevalence rate (%)

40.00%

500 0

0.00% 35-44

45-54

55-64

65-74

75-84

85+

Age group SB PCT

HOB tPCT

BEN PCT

CKD prevalence rate (%)*

Data source: PHIT

JSNA LTCs Final Version

161


Figure 12.8 Estimated CKD (stage 3 to 5) prevalence by age group and PCT, females, Birmingham, 2007 (Stevens et al. 2007) 50.00%

6000 5248 5000

4370 4486

4000

3601 30.00% 2548 2310

20.00%

2826 3000 2584 2150

2156 2000

1202 10.00%

413737

960

792 644 573 663 194 214 476 373 177

0.00%

Number of peeple with CKD

CKD prevalence rate (%)

40.00%

1000

0 18-24

25-34

35-44

45-54

55-64

65-74

75-84

85+

Age group SB PCT

HOB tPCT

BEN PCT

CKD prevalence rate (%)*

Data source: PHIT

12.5.3.2.

Ethnicity

The evidence of higher prevalence of RRT in the BME groups and the sharper increase of the incidence in this group in recent years suggest higher burden of the late stage (i.e. stage 5) CKD in Birmingham, especially in areas like HOB tPCT and some areas in BEN PCT which are dominated with the BME group.

12.6. CKD and deprivation The relationship between the prevalence of CKD and social deprivation has been studied in several studies (Bello et al. 2008) and a positive association between the two has been suggested.

12.6.1. CKD prevalence by deprivation quintiles A study by Bello et al. (Bello et al. 2008) based on data collected on 1,657 patients from January 1, 1995 to December 31, 2005 in a Renal Unit in Sheffield, UK suggests that the age-adjusted prevalence of diagnosed CKD at presentation by area of residence, across the five deprivation quintiles, per million population was Q1 (least deprived) = 1,495 pmp, Q2 = 3,530 pmp, Q3 = 3,398 pmp, Q4 = 3,989 pmp, and Q5 (most deprived) = 19,599 pmp. The same study also suggests an increasing trend in the proportion of patients presenting with advanced CKD (stage 5) to the unit from the least deprived (i.e. Q1) to the most deprived category (i.e. Q5), as shown in Figure 12.9.

JSNA LTCs Final Version

162


Figure 12.9 Proportion of CKD patients presented by deprivation quintile and disease stage, Sheffield, 1995 â&#x20AC;&#x201C; 2005 (Bello et al. 2008)

Data from the UK Renal Registry also suggests a positive association between social deprivation and the prevalence rate of RRT, as shown in Figure 12.10 (Ansell et al. 2008). In particular, the sharpest increase was between the second most deprived quintile (i.e. quintile 4) and the most deprived quintile (i.e. quintile 5). A further study by the UK Renal Registry also suggests that the association between social deprivation and prevalence of RRT is mainly due to the high prevalence of conditions like diabetes and hypertension (i.e. clinical risk factors for CKD) in the more deprived population, rather than due to deprivation itself. Figure 12.10 Age standardised accept rates of RRT by social deprivation group, England, 2007 (Ansell et al. 2008)

Acceptance Rate age adjusted

140 135 130

y = 9.81x + 79.07

125

2

R = 0.8165

120 115 110 105 100 95 90 dep1

dep2

dep3

dep4

dep5

Social Deprivation group

12.6.2. Local implications The association between the prevalence of CKD and social deprivation suggests high prevalence of CKD, in particular advanced CKD (i.e. stage 5) in Birmingham, as Birmingham is a very deprived area with more than half of its population in the most deprived quintile nationally (i.e. quintile 5). The prevalence of CKD stage 5 was more

JSNA LTCs Final Version

163


strongly associated with deprivation, compared with CKD stage 3 and 4. This suggests late identification of CKD patients happens more in the more deprived population. Therefore, target areas for early identification of CKD cases should be in the more deprived areas in Birmingham such as HoB tPCT and some areas in BEN PCT.

12.7. Clinical risk factors There are a number of clinical risk factors for CKD, including hypertension and diabetes mellitus (www.renal.org). This part investigates these clinical risk factors for CKD locally.

12.7.1. Hypertension Risk of CKD is directly related to both systolic and diastolic blood pressure levels. The prevalence of hypertension increases with age, and differs between ethnic groups. Hypertension in the young is often associated with a particularly severe form with adverse prognosis, called accelerated or malignant hypertension. People who are African Caribbean have more hypertension and more accelerated hypertension than other ethnic groups. Figure 12.11 shows the trend of hypertension prevalence in Birmingham, the PCTs and England during the period 2004/05 to 2007/08, based on QOF data. Figure 12.11 Hypertension prevalence Birmingham, PCTs and England, 2004/05 – 2007/08 14.00% 13.00% 12.00% 11.00% 10.00% 9.00% 8.00% 2004/05 SB

2005/06 HOB

BEN

2006/07

2007/08

Birmingham

England

Data source: QOF

Figure 12.11 shows that: •

Hypertension was a high prevalent condition nationally with 12.8% of England’s population with hypertension in 2007/08.

The prevalence of hypertension had increased both locally and nationally during the 4-year period from 2004/05 to 2007/08.

JSNA LTCs Final Version

164


In the year 2007/08, the prevalence rate in Birmingham (11.9%) was lower than the England’s rate (12.8%). The prevalence rate in SB PCT (12.3%) and BEN PCT (12.7%) were similar to the England’s level while the prevalence rate in HoB tPCT was lower, at 10.2%.

The QOF prevalence for Birmingham and the PCTs seems to suggest that hypertension was not a local issue particularly. However, as suggested by premature death rates of hypertensive diseases (described in 5.4), HoB tPCT had very high premature death rate (more than doubled of the national average), which suggested that the QOF prevalence for HoB tPCT could be underestimated. In addition, QOF prevalence does not break down by the severity of the condition however the different patterns between prevalence and death could be that although HoB tPCT had an overall lower prevalence of hypertension, it might had larger proportion of more severe hypertensive patients. Looking at the prevalence of co-morbidities with hypertension with its medical complications such as CKD, as described in Section 7.5.4, the prevalence (estimated from data collected from primary care) of comorbidities with hypertension was high in HoB tPCT area, this also indicate the high severity of hypertension in this area. In addition, the demographical and socio-economical distribution patterns of hypertension (based on the Health Survey for England) suggest that: •

Hypertension was highly associated with age.

Hypertension prevalence was not correlated with income in males, but negatively correlated with income in females, with higher prevalence in the lower income groups.

Hypertension was higher prevalent in Black Caribbean, Irish men and Indian men, compared to the general population.

Local implications of these patterns are that the current lower prevalence (than the national average) was probably due to the relatively young population of Birmingham. However, the local target groups for hypertension such as the low income females, Black Caribbean and Indian men will bring burden of CKD in future. Adequate management of hypertension removes or radically reduces the risk of CKD.

12.7.2. Diabetes Diabetes substantially increases the risk of CKD (www.renal.org) Diabetes not only increases the risk of CKD but also magnifies the effect of other risk factors for CKD such as raised blood pressure, smoking and obesity. Local prevalence of diabetes is high, especially in HoB tPCT area. Details of local diabetes prevalence are described in Chapter 8 of the report. Adequate management of diabetes removes or radically reduces the risk of CKD.

12.8. Life style risk factors There are risk factors for CKD that are related to people’s life style choices, although arguably much of the increased risk from the life style choices are actually via the clinical risk factors, as they are also risk factors for conditions such as hypertension and diabetes. Nevertheless, the prevalence of these risk factors suggests the population at risk of getting CKD in future.

JSNA LTCs Final Version

165


12.8.1. Smoking A systematic review of 17 studies on smoking and CKD incident (Jones-Burton et al. 2007) reveals overall evidence for current cigarette smoking as a risk factor for incident CKD. It shows that: â&#x20AC;˘

Out of the 17 studies, seven of them found an overall significant association between smoking and incident CKD, and three studies found a significantly increased risk of CKD in current smokers that was gender and/or dose related.

â&#x20AC;˘

An increased risk of developing CKD among smokers was significantly associated with male gender (relative risk 2.4, 95% confidence interval 1.24.5), >20 cigarettes smoked/day (relative risk 2.3, 95% confidence interval 1.2-4.3), and smoking >40 years (odds ratio 1.45, 95% confidence interval 1.00-2.09).

Local implications of the associations are that stop smoking interventions should target male smokers, heavy smokers and longer term smokers.

12.8.2. Obesity There is now accumulating evidence to suggest that CKD is more common in overweight or obese patients study (Stevens et al. 2007). Many complex factors which include genetic, metabolic, behavioural and environmental factors are responsible for the increasing prevalence in obesity. However, the rapid increase in prevalence suggests that behavioural and environmental influences predominate. CKD should be added to the list of complications of overweight and obesity, regardless of whether the association was independent or through the influence of diabetes, hypertension, CVD, MS and high fructose intake. Studies are needed of randomized controlled trials with either doubling of serum creatinine or progression to ESRD as primary end-points to suggest obesity as a definite risk factor for progression or incident cases of CKD. The proportion of obese adults in Birmingham (23.4%) is about the same as the national average (23.6%). However, the prevalence of obese children (i.e. Year 6 children) was at 23.1%, which is 50% higher than the national average (15.4%). The obesity patterns in population (as described in Section 4.5) suggest that the target group of future CKD due to obesity should be in children and young people and the Black ethnic groups.

12.9. Projected prevalence This section describes the projection of CKD prevalence in Birmingham to the year 2020. The purpose of the projection is to provide an estimate of the magnitude of the disease so that future needs of health can be assessed. The projection described in this part is based on the age/gender model of CKD prevalence rates in England in 2003 suggested by Stevens et al. study (Stevens et al. 2007).

12.9.1. Applying current prevalence rates to projected population In order to project future prevalence of CKD, age/gender prevalence rates of CKD in England in 2003 suggested by Stevens et al.â&#x20AC;&#x2122;s study (Stevens et al. 2007) (as shown in

JSNA LTCs Final Version

166


Figure 12.3) were used as the predicting model. These rates were applied to projected future local population to calculate the number of people with CKD (method is described in Section 3.5.2). No further adjustment on deprivation and other risk factors was used in this study. Assumption was made that the prevalence rate of CKD will be consistent to 2020 (i.e. same as the 2003 rate for England and Wales) and the change in prevalence in future will solely come from the change in population. The ONS population projection was used and inputted into the predicting model to calculate the projected number of CKD patients in each gender/age group in 2020, in Birmingham and the three PCTs. Details of the ONS projected population (by age and gender) in Birmingham are described in Section 4.1.2 and the age and gender distribution of the projected population can be found in Table E.1 in Appendix E.

12.9.2. Projected prevalence of CKD Figure 12.12 shows the result of the projection: projected number of people with CKD by PCT in Birmingham in the year 2010, 2015 and 2020. Figure 12.12 Projected number of people* with CKD (stage 3 to 5) PCT, Birmingham, 2010, 2015 and 2020

Projected number of people with CKD (stage 3 to 5)*

70000 60000 50000

23497

21758

22452

12120

12611

13139

25497

26269

27496

2010

2015

2020

40000 30000 20000 10000 0 Year BEN PCT

HOB tPCT

SB PCT

* age 18 and above Data source: PHIT

Figure 12.12 shows that: •

The number of people with CKD (stage 3 to 5) will increase across all PCTs in Birmingham in the next 10 years.

Projected number of CKD (stage 3 to 5) patients in Birmingham will be 59,375 in 2010, 61,332 in 2015 and 64,132 in 2020. This gives an increase of 8% in 10 years’ time.

JSNA LTCs Final Version

167


SB PCT will have 21,758, 22,452 and 23,497 people with CKD (stage 3 to 5) in 2010, 2015 and 2020 accordingly. The number of people with CKD will increase by 8.0% in the next 10 years.

HOB tPCT will have 12,120, 12,611 and 13,139 people with CKD (stage 3 to 5) in 2010, 2015 and 2020 accordingly. The number of people with CKD will increase by 8.4% in the next 10 years.

BEN PCT will have 25,497, 26,269 and 27,496 people with CKD (stage 3 to 5) in 2010, 2015 and 2020 accordingly. The number of people with CKD will increase by 7.8% in the next 10 years.

12.9.3. Projected prevalence of CKD by age and gender Figure 12.13 and Figure 12.14 show the projected number of people with CKD (stage 3 to 5) in 2020 by age group and PCT (i.e. the bars in the graph), for males and females, in comparison with the estimated prevalence of CKD (stage 3 to 5) in 2007 (i.e. the lines in the graph). As both of the prevalence in 2007 and 2020 are estimated based on the same gender/age prevalence rates suggested by Stevens et al. study (Stevens et al. 2007), the difference between the prevalence in 2007 and 2020 shown in the figures are solely due to the change in population (Please see Section 4.1.2 and Appendix E for details of the projected population change in Birmingham and the PCTs to 2020). Figure 12.13 Projected number of people with CKD (stage 3 to 5) by age group and PCT, males, 2020 in comparison with estimated prevalence in 2007 3500

Number of people with CKD

3000 2500 2000 1500 1000 500 0 18-24

25-34

35-44

45-54

55-64

65-74

75-84

85+

Age group SB 2020

HOB 2020

BEN 2020

SB 2007

HOB 2007

BEN 2007

Data source: PHIT

Figure 12.13 shows that: •

The number of projected CKD (stage 3 to 5) patients will increase by 2020, across all age groups and all PCTs for males in Birmingham, in comparison with 2007. In particular, increase will be seen in the elderly males (aged 65 and above)

JSNA LTCs Final Version

168


Most of the increase will be from the 75 and above groups for males across all PCTs in Birmingham.

All three PCTs shares similar age pattern with Birmingham, in terms of prevalence increase of CKD in males.

Figure 12.14 Projected number of people with CKD (stage 3 to 5) by age group and PCT, females, 2020 in comparison with estimated prevalence in 2007

6000

Number of people with CKD

5000

4000

3000

2000

1000

0 18-24

25-34

35-44

45-54

55-64

65-74

75-84

85+

Age group SB 2020

HOB 2020

BEN 2020

SB 2007

HOB 2007

BEN 2007

Data source: PHIT

Figure 12.14 shows that: •

The number of projected CKD (stage 3 to 5) patients will increase by 2020, across all PCTs for females in Birmingham, in comparison with 2007. In particular, increase will be seen in the elderly males (aged 65 and above), apart of the 75 – 84 group,

Most of the increase will be from the 55 – 74 group and the 85 and above group for females across all PCTs in Birmingham.

All three PCTs shares similar age pattern with Birmingham, in terms of prevalence increase of CKD in females.

Details of the age and sex distribution of the projection of CKD prevalence for Birmingham and the PCTs can be found in Table G.1 in Appendix G.

12.9.4. Limitations of the projection There are several factors that can affect the accuracy of the projection of future prevalence of CKD (stage 3 to 5) in Birmingham in this study. It assumes a stable population, but if migration of young people to inner city areas continues, then there

JSNA LTCs Final Version

169


will be an overestimate since the age distribution may stay the same. Moreover, since the LTCs such as diabetes and hypertension are now better managed with QOF, there should be a radical reduction in the number of patients developing advanced CKD. In addition, the projection of future CKD prevalence can be underestimated due to the reasons given below. An assumption was made in the projection that the age/gender prevalence rate of CKD in Birmingham in 2020 will be the same as the rate for England in 2003 (as suggested by Stevens et al study (Stevens et al. 2007). However, this â&#x20AC;&#x2DC;staticâ&#x20AC;&#x2122; prevalence rate may not be true, especially given the fact that evidence shows that the prevalence of risk factors (e.g. obesity) for CKD is increasing. Studies are needed on long-term trend of prevalence rate of CKD in relation to the impact of all the risk factors. In addition, the gender/age group prevalence rate used in the predicting model was based on data back in 2003, again the change of rate over time was not adjusted. Therefore, the projection can be underestimated. In addition, the projection is only based on the gender/age group specific prevalence rates and did not take deprivation into account. However as described in Section 12.6, previous studies confirm that the association between prevalence of CKD, especially CKD stage 5 and social deprivation. Therefore, the projection can be underestimated, given the fact that Birmingham is a very deprived area. The model did not take ethnicity into account either. Given the fact that incidence of CKD is considerably higher in the BME group (as described in Section 12.5.2), and Birmingham has a large proportion of BME population (as described in Section 4.2), the project can be underestimated. Finally, the model did not take into account all the other clinical and life style risk factors, such as diabetes, hypertension, obesity and smoking. Evidence has shown that prevalence of these risk factors are increasing, especially diabetes and obesity. These should result in increase in the prevalence rate of CKD. Therefore, the projection can be underestimated.

JSNA LTCs Final Version

170


13. Asthma Key messages for commissioners Key findings: • We estimate that there is considerable under-recording of asthma in primary care across all three Birmingham PCTs • HOB tPCT has high rates of emergency admissions for asthma, but a low recorded prevalence • Asthma mortality rates are falling across Birmingham and the gap is narrowing towards the rate for England.

Joint Strategic Needs Assessment

Recommendations: • There needs to be an increased effort to identify asthmatics who are not currently on primary care QOF registers • The appropriate management of asthmatics remains a priority, and concerted efforts need to be made to prevent young asthmatics smoking and to encourage those who do smoke, to stop • The high rate of emergency admissions for asthma in the HOB tPCT population requires further investigation.

13.1. Introduction and Key Facts Asthma is a chronic respiratory disease caused by inflammation of the lower airways, manifesting as attacks of breathlessness or wheezing, which can range in severity from mild to sometimes fatal episodes. Asthma can be distinguished from other conditions which constrict air flow, such as chronic obtrusive pulmonary disease (COPD), by measures of reversibility of these constrictions (asthma is usually reversible). Whilst little is understood about the causes of asthma, harm from the condition is largely preventable, with a range of medications available to alleviate symptoms. Asthma usually occurs in childhood, and is most prevalent in young children; one in five aged between 6 and 7 years old were found to have clinically diagnosed asthma in a recent study (Asher et al. 2006). It is also possible to develop asthma later in life, even with no prior history of the condition. Childhood sufferers often recover in adolescence, although for some the condition will persist into adulthood. Common symptoms include (British Thoracic Society 2009): • Wheezing • Cough • Difficulty breathing • Chest tightness The charity Asthma UK estimated in 2006 that there were 5.2 million asthma sufferers; 4.1 million adults and 1.1 million children. Every year, there are an estimated 4.1 million GP consultations for asthma (Asthma UK 2006), and in 2007/08 there were 62,000 hospital admissions across England (ONS 2007/08). The estimated cost of asthma to the UK economy is £2.3 billion per year. This includes healthcare costs to the NHS of approximately £889 million, benefit costs of approximately £160 million and over 12 million days of lost productivity due to work absence (http://www.asthma.org.uk).

JSNA LTCs Final Version

171


13.1.1. Risk Factors for the Development of Asthma Many factors which influence the prevalence of asthma are innate (age; gender; ethnicity; co-existence / family history of atopic disease (ONS 2007/08) and as such cannot be directly influenced by healthcare. Other factors, such as environmental tobacco smoke, air pollution and exposure to domestic / external allergens allow more room for intervention, although results from clinical trials are often inconclusive. These factors are also known to exacerbate asthma, leading to higher rates of asthmatic episodes, which allows more room for possible interventions to reduce asthma harm.

13.1.1.1.

Demographic Factors

Age and gender play a significant role in the development of asthma. It is well documented that asthma is most prevalent in young (pre-pubescent) males, but the number of cases per head of population declines with age, many â&#x20AC;&#x153;growing outâ&#x20AC;? of the condition in adolescence. Conversely, females are less likely to develop the condition in early childhood, but are less likely to recover in later life, giving rise to a higher prevalence of asthma in females when compared to males after the age of 10 (http://www.cks.nhs.uk). Other demographic factors, such as socio-economic status (SES) and ethnicity, have been suggested to correlate with asthma prevalence. For example, a recent European study of asthma prevalence found that the highest rates of asthma were found in the lowest socio-economic groups, when controlled for ethnicity (BasagaĂąa et al. 2004). The relationships between socio-economic status, ethnicity and asthma are explored further later in this document.

13.1.1.2.

Exposure to Tobacco Smoke & Other Air Pollutants

Smoking and associated environmental tobacco smoke (ETS) are both factors which can have a significant impact upon asthma rates, and the burden of disability resulting from asthma. While environmental tobacco smoke in the home has not been found to have a connection with the aetiology of asthma in children (i.e. it has not been demonstrated that it causes the condition), it has been linked to the persistence of the condition. Studies have suggested smoking lowers the chance of recovering from asthma; the chance of persistent asthma has been found to double in teenagers who start smoking (Rasmussen et al. 2000). Other forms of air pollutants, most notably traffic fumes, have also not been found to be linked with the aetiology of asthma in children, but have found to be irritants, and may provoke acute attacks or aggravate existing asthma in some individuals (Department of Health 2002), however, there is no confirmed causal link with the development of asthma in children.

13.1.1.3.

Exposure to Domestic Allergens

Domestic allergens, such dust mite allergen, or exposure to certain food allergens (such as egg allergens) in pregnancy and early childhood have been suggested to be responsible for past increases asthma prevalence. However, clinical trials have failed to show a consistent causal link between domestic allergen exposure and asthma, and as such domestic allergen avoidance has not been recommended as a strategy for asthma prevention (British Thoracic Society 2009).

JSNA LTCs Final Version

172


13.1.1.4.

Breastfeeding

Breastfeeding has also been linked with a reduction in the prevalence of asthma in children, and with a range of benefits; the promotion of breastfeeding may serve to reduce asthma prevalence and have other health benefits. Modified milk formulae are currently undergoing trials, but have yet to provide evidence that they may have a similar protective effect (British Thoracic Society 2009).

13.1.2. Occupational Asthma Asthma may be developed in the workplace, commonly known as occupational asthma, resulting from exposure to certain substances and irritants. The Health & Safety Executive for England estimates that between 1,500 and 3,000 people in the UK develop occupational asthma each year, and that occupational asthma may be responsible for 9-15% of adult prevalence of the condition (British Occupational Health Research Foundation (2004)). A 1999 Surveillance of Work-Related and Occupational Respiratory Disease (SWORD) study found that the most common substances associated with causing occupational asthma were (Meyer et al. 2001). •

• • • • •

Isocyanates (associated with the manufacture of polyeurathane products, used for products such as automobile seats, varnish, car tyres and many other products) Latex Flour and grain Enzymes Laboratory animals and insects Cobalt

Figure 13.1 Substances identified as sensitizing agents for asthma Substances Identified as Sensitizing Agents for Asthma Source: SWORD '99 (Surveillance of Work-related and Occupation Respiratory Disease)

Enzymes 8%

Laboratory animals & insects Cobalt 7% 6%

Flour and Grain 8%

Latex 9% Other Substances 41%

Isocyanates 21%

The UK Health Safety Executive body recently reviewed the Asthmagen Compendium, an extensive listing of substances linked to occupational asthma, which can be found online at http://www.hse.gov.uk.

JSNA LTCs Final Version

173


13.1.3. Asthmatic Triggers In 2001, as a part of the Health Survey for England, five thousand asthmatics were questioned about the substances and activities which triggered their asthma. The most commonly reported triggers for asthma were: chest infections and colds; cigarette smoke; dust; exercise; cold air; and pollen. Figure 13.2 below shows a full breakdown of the proportion of individuals reporting each substance as a trigger for their asthma: Figure 13.2 Self-reported asthmatic triggers Source: Health Survey for England 80%

% Of Respondents Reporting Substance / Activity Exacerbated Asthma

70% 60% 50% 40% 30% 20% 10%

Cigarette smoke (yours/others)

Pollen

Grass

Chest infections/cold/flu

Exercise

Traffic fumes

Aspirin

Perfume

Other things

Hay or straw

Farm animals (including horses)

Cold air

Being excited or upset

Feathers

Pets

Dust

0%

13.2. Prevalence of Asthma 13.2.1. Recorded Prevalence Asthmatics currently on treatment are recorded by general practices as a part of the quality outcomes framework (QOF), a system designed to improve quality of chronic disease management. There are over 3 million people (5.7%) registered on QOF as suffering from asthma in England. Recorded asthma prevalence in Birmingham is similar to that nationally; there are over 65,000 recorded sufferers, 5.8% of the registered population. A breakdown of asthma prevalence for Birmingham and the 3 Birmingham Primary Care Trusts can be seen in Figure 13.3.

JSNA LTCs Final Version

174


Figure 13.3 Recorded asthma prevalence Source: Quality Outcomes Framework (QOF) 7.0%

6.0%

Prevalence - %

5.0%

4.0%

3.0%

2.0%

1.0%

0.0% Birmingham MCD

NHS Birmingham East & North

Heart of Birmingham tPCT

NHS South Birmingham

England

West Midlands

A method first applied by Doncaster PCT, approved by the Department of Health, uses data derived from Key Health Statistics from General Practice 1998 to model the expected number of registered patients with Asthma (and other conditions). The results of this model indicate that asthma prevalence in Birmingham is lower than expected, as shown in Figure 13.4 below: Figure 13.4 Recorded vs. expected asthma prevalence Source: NHS Comparators (https://nww.nhscomparators.nhs.uk) Recorded % Expected % 10.0 9.2

9.2

9.2

9.1

9.2

9.1

9.0

Percentage Sufferers

8.0 7.0 6.0

6.1

5.8

5.8

5.9

5.4

5.7

5.0 4.0 3.0 2.0 1.0 0.0 NHS Birmingham East & North

Heart of Birmingham tPCT

JSNA LTCs Final Version

NHS South Birmingham

Birmingham MCD

W. Midlands SHA

England

175


13.2.2. Prevalence by Age and Sex There are two available sources of data showing breakdowns of asthma prevalence by age and sex, however, neither source is able to give prevalence rates specific to England. These sources are the Key Statistics for General Practice 1998 (used in the Doncaster model above) and the Health Survey for England 2001. Figure 13.5 below gives a breakdown of the national age-sex specific prevalence of asthma taken from the latter source, with the highest asthma prevalence in young males, and a higher prevalence in females after the age of 20: Figure 13.5 Asthma prevalence by age and sex Source: Health Survey for England

30.00% Males Females 25.00%

20.00%

15.00%

10.00%

5.00%

0.00% 0-9

10 - 19

20 - 29

30 - 39

40 - 49

50 - 59

60 - 69

70 - 79

80+

13.2.3. Asthma Prevalence by Socio-Economic Status and Ethnicity Relatively little information could be found quantifying the link between socioeconomic status (SES), ethnicity and the prevalence of asthma, however, a recent review for the British Medical Journal found the relationship between SES and the aetiology of asthma in children was inconsistent across studies. In terms of asthmatic episodes, a much stronger relationship was found, with higher rates of hospital admissions and mortality found in the most deprived groups (http://www.cks.nhs.uk/asthma/evidence). In adults, some studies have found links between SES and asthma, however, these studies have also often commented on the difficulty of separating asthma and COPD, which leads to problems due to the strong relationship between COPD prevalence and SES. When considering variations in asthma prevalence due to ethnicity, many studies are small scale, or focused on the incidence of asthmatic episodes, not prevalence. The most recent large-scale survey using UK data was a 2007 study of nearly 50,000 children, which found two groups with a statistically significant difference in prevalence. These were Black Caribbean (with above average prevalence) and Bangladeshi (with below average prevalence) (Panico et al. 2007).

JSNA LTCs Final Version

176


Due to the lack of clearly defined relationships between ethnicity, socio-economic status and asthma prevalence, these rates have not been applied to the Birmingham population to predict the numbers of expected sufferers within these groups.

13.2.4. Predicting Asthma Prevalence Over the past 20 â&#x20AC;&#x201C; 40 years, there have been several studies which have found a rising prevalence of asthma, both in the UK and internationally. One intergenerational study of two communities in Scotland found that asthma prevalence in adults aged between 45 and 54 had increased from 3% to 8.2% in a period of only twenty years (Upton et al. 2000). Similarly, another study, focusing on children aged 7 ½ to 8 ½ in Croydon, found a rise from 11.1% to 12.6% in the proportion of children reporting wheezing in the last 12 months between 1978 and 1991 (Anderson et al. 1994). Despite the broad consensus that asthma prevalence has been rising steadily over the last 20-40 years, there is growing evidence that rates in developed countries have reached a plateau and are no longer rising (Anderson 2005). The chart below gives projections for the future asthma prevalence in 2010, 2015 and 2020, based on rates taken from Key Statistics from General Practice 1998 and applied to ONS population predictions. Due to differences in age bandings used by the two sources, the prevalence for 16-24 year olds has been applied to the 15-24 year old age group. Table 13.1 Projected prevalence of asthma Birmingham MCD

NHS Birmingham East & North

2010

2015

2020

2010

2015

2020

Males

37,081

38,756

40,442

14,596

15,259

15,991

Females

39,965

41,345

42,843

15,778

16,361

17,011

Total

77,046

80,101

83,284

30,374

31,620

33,002

Heart of Birmingham tPCT

NHS South Birmingham

2010

2015

2020

2010

2015

2020

Males

10,385

10,884

11,316

12,101

12,612

13,135

Females

10,656

11,053

11,420

13,531

13,932

14,411

Total

21,041

21,937

22,736

25,631

26,544

27,546

Source: ONS (Population Predictions), Key Health Statistics from General Practice 1998 (Age-Specific Prevalence)

JSNA LTCs Final Version

177


13.3. Management of Asthma 13.3.1. Prescriptions The main treatment for asthma is delivered through inhalers containing a mixture of respiratory medications, which vary according to the severity of each patient’s asthma. Prescriptions vary in cost from less than £1 per prescription to over £75 (prescription periods of 1 month). Analysis of prescriptions for asthma is problematic, as similar medications can be used when treating both asthma and COPD. Table 5.1 below shows the prescription costs in 2007/08 for BNF Chapter 3 (COPD and asthma) by PCT for the Birmingham area: Table 13.2 Spend on BNF Chapter 3, 2007/08 Number Registered (Asthma + COPD)*

Estimated Total Spend per Year

Yearly Spend per i Patient

NHS Birmingham East & North

29329

£7.4 million

£253

Heart of Birmingham tPCT

18977

£4.2 million

£225

NHS South Birmingham

31582

£6.8 million

£216

* QOF register

13.3.2. Asthma Reviews Guidance on managing asthma recommends that every patient with stable asthma receives an asthma review from their GP at least once a year (http://www.cks.nhs.uk). Figure 13.6 shows the percentage of patients receiving a review within the previous 15 months for the three Birmingham PCTs. Figure 13.6 The percentage of patients with asthma who have had an asthma review in the previous 15 months Source: Quality Outcomes Framework (QOF): Asthma 6 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% NHS Birmingham East & North

JSNA LTCs Final Version

Heart of Birmingham tPCT

NHS South Birmingham

England

178


13.3.3. Smoking Prevalence in Young Asthmatics In addition to the role smoking and environmental tobacco smoke have in exacerbating asthma, a recent study has demonstrated that a teenage asthmatic that starts smoking has approximately double the chance of their asthma persisting into adulthood when compared to another who does not smoke. This combined with the other health impacts of smoking, highlight the importance of encouraging young people to not take up smoking. As a part of the QOF, GP practices record the number of 14 to 19 year olds with asthma who have a recorded smoking status in the last 15 months, as shown in Figure 13.7 below. Unfortunately, this indicator is not able to show the number of patients whose smoking status is recorded as positive. Figure 13.7 Percentage of patients with asthma between the ages of 14 and 19 in whom there is a record of smoking status in the previous 15 months Source: Quality Outcomes Framework (QOF): Asthma 3 100.0% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% NHS Birmingham East & North

Heart of Birmingham tPCT

NHS South Birmingham

England

13.4. Hospital Admissions due to Asthma 13.4.1. Admission Rates by Age and Sex In 2007/08, there were over 2000 admissions to hospital with asthma cited as a primary cause in Birmingham (Secondary Uses Services, Average admissions 20032007), of which a vast majority (over 95%) were emergency admissions. The highest rate of admissions was in the Heart of Birmingham tPCT area with 292.6 admissions per 100,000, despite having the lowest asthma prevalence of all PCTs. There are a number of possible explanations for the high rate of admissions, including variation in individualsâ&#x20AC;&#x2122; propensity to visit hospital, poor asthma management, or under-recording of asthma prevalence, although these cannot be confirmed without further analysis. The Heart of Birmingham area also reports higher admission rates for males, which is not mirrored in other areas. This is likely to be a result of the relatively young population living in this area, although this also cannot be confirmed without further analysis.

JSNA LTCs Final Version

179


Rates in NHS Birmingham East & North and NHS South Birmingham were lower than the Heart of Birmingham area, with 202.5 and 178.2 admissions per 100,000 respectively, but still above national and west midlands levels. This may partly be explained by higher levels of asthmatic triggers, such as air and traffic pollution, which are associated with urbanised areas like Birmingham. Figure 13.8 Emergency hospital admissions per 100,000 population

Emergency Hospital Admissions per 100,000 Population 2007/08: Birmingham PCTs and Comparators Source: Hospital Episode Statistics (WMPHO Calculations) 350.00

300.00

Males Females Persons

Admissions per 100,000

250.00

200.00

150.00

100.00

50.00

0.00 Birmingham East and North

Heart of Birmingham Teaching

South Birmingham

West Midlands

England

When considering admissions broken down by age and sex, females account for a majority (nearly 55%) of all asthmatic admissions. This is likely to reflect the higher prevalence of asthma in adult females when compared to adult males. The highest age-specific admission rate is found in very young males (aged 0 â&#x20AC;&#x201C; 4), again likely to reflect the high rates of asthma usually found in this age-group. As expected, the very high admission rates for asthma in males falls rapidly in late childhood / early adolescence, when we know a large proportion of asthmatics recover from the condition, and in all age-groups over 10 â&#x20AC;&#x201C; 14, females account for a greater proportion of total admissions.

JSNA LTCs Final Version

180


Figure 13.9 Asthma hospital admissions rates per 1,000 population

Asthma Hospital Admission Rates per 1,000 Population 2007/08 Source: SUS Inpatient 9.00 Males 8.00

Females Persons

Admissions per 1,000

7.00 6.00 5.00 4.00 3.00 2.00 1.00

85 +

84 to

79 80

75

to

74

69

to 70

65

to

to

64

59 60

55

to

to

54

49 50

to

44 45

to

39 40

to 35

to

34

29 to

25

to 20

30

24

19 to

14 15

to

to

10

5

0

to

4

9

0.00

Figures 13.10 below shows the percentage of total admissions accounted for by each age group, for both males and females. Similarly to Figure 13.9 above, this graph highlights the link between the age-sex specific prevalence of asthma, and hospital admissions in these groups. Young males aged between 0 and 9 years account for nearly 24% of all admissions, but this quickly to comparable levels in the 10 â&#x20AC;&#x201C; 14 age group, with females overtaking males for admissions over the age of 15. Figure 13.10 Percentage of admissions by age group for males and females

Percentage of Admissions by Age Group for Males Percentage of Admissions by Age Group for Females 2007/08

2007/08

Source: SUS Inpatient

Source: SUS Inpatient

Over 85 80 - 84 80 - 84

75 - 79

Over 85 0-4

75 - 79

70 - 74 65 - 69

70 - 74

60 - 64 65 - 69

55 - 59

5-9

0-4

50 - 54

60 - 64

45 - 49

55 - 59

40 - 44

10 - 14

50 - 54

35 - 39 15 - 19

30 - 34

45 - 49

25 - 29

20 - 24 40 - 44

20 - 24

35 - 39

15 - 19 10 - 14

JSNA LTCs Final Version

25 - 29 30 - 34

5-9

181


13.5. Mortality due to Asthma Approximately 1350 people die each year as a result of asthma in England. In Birmingham, mortality rates for the condition are higher than those nationally, despite asthma’s relatively low contribution to overall mortality (less than 1% of all deaths in the city). Figure 13.11 below gives a breakdown of mortality rates in Birmingham & Birmingham PCTs against comparator groups: Figure 13.11 Age standardised mortality rate for asthma, 2005 – 2007

Directly Standardised Mortality Rate For Asthma 2005 - 2007 Source: National Centre for Health Outcomes Development (http://nww.nchod.nhs.uk) 2.50 Males Females Persons

Mortality per 100,000

2.00

1.50

1.00

0.50

0.00 Birmingham MCD

NHS Birmingham East & North

Heart of Birmingham tPCT

NHS South Birmingham

England

West Midlands

Mortality due to asthma has fallen extensively over the last 50 years, due to better understanding and management of the condition. Figure 13.12 below shows mortality rates due to asthma from 1993–present; mortality rates have fallen significantly both in Birmingham and England, with less than 1.5 deaths per 100,000 in 2007. Figure 13.12 Age standardised mortality due to asthma 1993 – 2007 Source: NCHOD (http://www.nchod.nhs.uk) 3.50

Birmingham

3.00

Mortality per 100,000

England 2.50

2.00

1.50

1.00

0.50

0.00 1993

1994

1995

JSNA LTCs Final Version

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

182


Figure 13.13 below shows the distribution of mortality by age-group for England. Mortality is very low in all age groups under 75 years, with less than 5 deaths per 100,000, and less than 1 per 100,000 between the ages of 1 and 64. Figure 13.13 Mortality rate for asthma by age group, England 2005 â&#x20AC;&#x201C; 2007 Mortality Rate For Asthma by Age Group England: 2005 - 2007 Source: National Centre for Health Outcomes Development (http://nww.nchod.nhs.uk) 25

Males Females Persons

Mortality per 100,000

20

15

10

5

0 <1

1-4

5-14

15-34

35-64

65-74

75+

13.6. Conclusions The aetiology and epidemiology of asthma are still unclear. Whilst it has been hypothesized that rates have been rising over the last 40 years, there is some evidence to suggest that rates have begun to plateau. No conclusive hypothesis has been put forward for the rise and subsequent plateau of asthma rates, but this could be due to improvements in case ascertainment. With unclear evidence as to the mechanisms through which asthma is caused, and unclear evidence as to the effectiveness of interventions for preventing asthma, it is unlikely that health policy could influence asthma prevalence rates. There is significantly more room, however, to influence harm resulting from asthma, by ensuring adequate provision of respiratory medications, promoting smoking cessation in asthmatics and parents of childhood asthmatics, and possible management of asthmatic triggers such as air pollution. The high rate of emergency admissions for the Heart of Birmingham tPCT area, despite the lower recorded prevalence is worthy of note, and further investigation. The potential to reduce this rate of admissions should be explored.

JSNA LTCs Final Version

183


14. Conclusions and future work This study has investigated the prevalence of common long term conditions (LTCs) in Birmingham and the PCTs as the initial phase of the JSNA. This section draws conclusions, based on the results described in Chapter 5 to Chapter 13 of this report. It also suggests future work that could bring more in-depth analysis of the complex issues around LTCs.

14.1. Conclusions Four objectives were set at the beginning of this study, as described in Chapter 1. This section draws conclusion for each of the objectives.

14.1.1. Burden of LTCs This study has investigated the burden of LTCs in Birmingham in terms of use of health and social care services and premature deaths. These results are described in Chapter 5 of the report. People with LTCs are intensive users of health care (both primary and secondary care) and social care services. People with stroke, multiple sclerosis, cerebral palsy, arthritis and mental health are particularly high users of social care services and people with mental health conditions, CVD and CKD are high users of secondary care services. LTCs account for about 70% of all premature death (i.e. death under 75 years old) in Birmingham, and the death rates for the majority of the LTCs are considerably higher than the national average. Data also has shown that the national target of reducing emergency bed days by 5% in 2008 (using 2003/04 as the baseline) remains challenging for Birmingham.

14.1.2. Disease prevalence of common LTCs This study has investigated the local disease prevalence of LTCs in general in Birmingham as well as several specific LTCs including CHD, diabetes, COPD, epilepsy, CKD and asthma. In addition, prevalence of multiple LTCs and the comorbidities of the conditions also have been investigated. These results are described in Chapter 6 to Chapter 13 of this report. According to QOF, prevalence of most LTCs was consistent over the 4-year period from 2004/05 to 2007/08. The study has highlighted the relative high prevalence locally of conditions like: diabetes in HoB tPCT and BEN PCT, COPD in SB PCT and advanced CKD (i.e. stage 5) in HoB tPCT and BEN PCT. In addition, QOF prevalence of several LTCs had increased considerably from 2004/05 to 2007/08 in Birmingham: hypertension, cancer and chronic kidney disease (CKD). As to the comorbidities of LTCs, hypertension, CHD, diabetes, asthma and mental illness (including learning disability) have been identified as the most common LTCs that coexist with other LTCs. Issues around underreporting of QOF prevalence has been raised from the study, especially disparity with prevalence reported from studies as the Health Survey for England. In particular HoB tPCTâ&#x20AC;&#x2122;s unexpected lower prevalence of several LTCs (e.g. CHD, epilepsy, CKD (earlier stages) and asthma) is not consistent with data from other sources, such as deaths and hospital admissions. The underreporting

JSNA LTCs Final Version

184


issue has also highlighted issues around (early) identification of patients with LTCs locally, or (self) management of established person with the disease or diseases.

14.1.3. Determinants of the prevalence of LTCs This study has investigated the determinants of LTCs prevalence, in terms of demographic factors, deprivation and life style choices. These results are described in Chapter 6 to Chapter 13 of this report. Age has been identified as associated with prevalence of the majority of all the LTCs reported. Ethnicity and social deprivation have also been identified as associated with most LTCs reported. Life style factors, such as smoking and obesity have been identified as associated with the prevalence of many LTCs as well. These findings have identified the future target area/group of LTCs locally (e.g. younger aged men with BME background and older aged women with White background for CHD), as well as areas of interventions/services in prevention and management of LTCs (e.g. interventions for the reduction of smoking and obesity in the general population).

14.1.4. Projections of future disease prevalence This study has projected disease prevalence of a number of selected LTCs for Birmingham and the PCTs. These results are described in Chapter 6 to Chapter 13 of this report. The projections have been made either based on currently available predicting models (e.g. models developed by the Association of Public Health Observatories (APHO) based on data collected from the Health Survey for England) or simply by applying current age-specific prevalence rates of the conditions to the projected population for Birmingham and PCTs. Prevalence of all the LTCs covered by this report has been projected as likely to increase in 10 yearsâ&#x20AC;&#x2122; time, either due to the change in population or the change in the prevalence of related risk factors. More reliable predicting models for future prevalence of diseases locally have been highlighted as necessary in this study. The accuracy of the projections in this study have been highly limited by issues as (i) lacking of important predictors in the model (e.g. lacking of diabetes status in the CHD model); (ii) lacking of a model at all (e.g. CKD has been projected simply based on the age-specific rates); (iii) lacking of data for the predictors (e.g. lacking of obesity data for the CHD model) and (iv) lacking of application to local population of the models (e.g. the APHO diabetes model has been identified as not suitable for local use as Birmingham is an outlier in the national model). A key issue to build more reliable predicting models for future prevalence of LTCs has been identified as the availability of primary care and social care data on individual patients, both on the conditions that they have and related clinical and life style risk factors.

14.2. Future work This study has also identified a number of areas for further investigation, in terms of the prevalence of LTCs in Birmingham and the PCTs.

JSNA LTCs Final Version

185


Several further analyses on disease burdens of LTCs have been identified. Analysis on the emergency bed days, in terms of what conditions are accountable for the excess emergency bed days has been identified as worth doing. This will provide insights on areas to work on in order to meet the national target locally. In addition, estimation of the number of people at care homes who are with LTCs have also been identified as worth looking into, as this area will involve partnership working between health and social care services. This study has investigated the prevalence of multiple LTCs in Birmingham and the PCTs. Replication of the present study is worth doing with primary care data (once the data are available), as primary care data should reflect a better picture of prevalence the secondary care data. Further more, predicting models can be built based on these data, with data collected on life style predictors as well. These will be valuable for future areas of work such as targeting user groups for case management and developing personalised care. Finally, the area of multiple LTCs and comorbidities needs further investigation as these groups need our attention of both health and social services to enable us to provide more specific case management packages. A separate further needs assessment on diabetes has been identified as worth doing as high prevalence of diabetes is a highlighted local issue. Diabetes is also a clinical risk factor for many other LTCs (e.g. CHD and CKD) therefore an accurate estimate of the prevalence of diabetes can help the estimate of the related co-morbidities. In addition, further investigation on prevalence of the medical complications of diabetes (e.g. blindness) and amputation has been considered. It also has been identified that a further analysis on people who are on the renal replacement therapy (RRT) in Birmingham is worth doing. As the RRT costs add a significant proportion to total cost of delivery of care, this analysis will be helpful to target the group in the preventative interventions. Finally, learning disabilities have been identified as worth looking into, especially in relation with other LTCs such as diabetes and epilepsy. The coming JSNA on Learning Disabilities (in 2010) which has been commissioned is going to cover this area.

JSNA LTCs Final Version

186


15. Appendix A Table A.1

ICD codes used for LTCs

ICD-10 and ICD-9 codes used for LTCs

Conditions

ICD-10 codes (for year 2001 and onwards)

ICD-9 codes (for year 2000 and before)

Coronary heart disease

I20 to I25

410 to 414

Heart failure

I50

428

Stroke

I60 to I69

401 to 438

Hypertensive disease

I10 to I15

401 to 405

Diabetes mellitus

E10 to E14

250

COPD

J44

496

Epilepsy

G40 to G41

345

Cancers

C00 to C97

140 to 208

Mental illness

F00 â&#x20AC;&#x201C; F99

290 to 319

Asthma

J45 to J46

493

Renal failure

N17 to N19

5851 to 5856

Multiple sclerosis

G35

340

Parkinsonâ&#x20AC;&#x2122;s disease

G20 to G21

332

Osteoarthritis

M15 to M19 and M47

715

Rheumatoid arthritis

M05 to M06

714.0 to 714.2

Psoriasis

L40

696

Eczemasis

L20 to L30

692

Cerebral palsy

G80

343

Thyroid problems

E00 to E07

240 to 246

Lupus

L93 and M32

7100

Coeliac disease

K900

5790

Irritable Bowel Syndrome

K58

5641

Diverticulitis

K57

562

Chronic fatigue syndrome

G933

78071

JSNA LTCs Final Version

187


16. Appendix B Table B.1

Appraisal on the data sources

Data sources used in this study

Joint Strategic Needs Assessment

Data source

General Household Survey

Hospital Episode Statistics

Description

Use of the data source

The General Household Survey (GHS) is a multi-purpose continuous survey carried out by the Social Survey Division of the Office for National Statistics (ONS) which collects information on a range of topics from people living in private households in Great Britain.

Use of primary care services from people with LTCs in Birmingham

Hospital Episode Statistics (HES) is the national statistical data warehouse for England of the care provided by NHS hospitals and for NHS hospital patients treated elsewhere.

Use of secondary care from people with LTCs

Variables used: Long standing illness GP and practice nurse appointments attended

Suitable. As primary care data is not available, this is the only source for the purpose. A problem is the data is only available at Government Office level (i.e. West Midlands) Suitable.

Variables used: primary diagnosis

Multiple LTCs Variable used: primary

JSNA LTCs Final Version

suitability of purpose

accessibility

reliability of the data source

Raw data as well as survey reports available from the ONS website.

Very reliable. Well developed methodology in sampling and questionnaire design etc.

Latest year available 2007.

Available on annual basis from the DoH.

It is supplied by the DH and it is reliable data source

Latest year available 2006/07 (when the report was written)

timeliness of data

Hospital admissions data can only represent a portion of the prevalence

188


Table B.1

Data sources used in this study

Data source

Description

Use of the data source

suitability of purpose

and secondary diagnosis

of multiple LTCs. However, this is the only source available that can identify patients with multiple LTCs.

accessibility

reliability of the data source

timeliness of data

ONS death registrations

All death residents within the Birmingham PCTs, supplied by the Office of National Statistics (ONS).

Premature death from LTCs

Suitable

Supplied annually and monthly by ONS

Very reliable

Annual deaths 2007

Quality and Outcomes Framework (QOF) data

The QOF is a voluntary incentive scheme that rewards GP practices for implementing systematic improvements in quality of care for patients. It is part of the General Medical Services (GMS) contract. Quality Management and Analysis System (QMAS) is a national system for England that supports the quality and outcomes framework (QOF).

Current prevalence of diseases and trend

Suitable.

Data is available on the QOF website, in public domain.

Very reliable

QOF 2007/08

Census 2001

Census data supplied by the Office of National Statistics (ONS).

Available from the ONS website.

Very reliable

2001, data is a bit out of date.

JSNA LTCs Final Version

However, the prevalence is not broken down by demographics and not possible to relate to risk factors and calculate comorbidities.

Suitable. Prevalence of people with limiting long term illness

However limiting long term illness was only recorded for working age group (16

189


Table B.1

Data sources used in this study

Data source

Description

Use of the data source

suitability of purpose

accessibility

reliability of the data source

timeliness of data

– 74). In addition, it is not clear what LTCs are perceived by people as LLTIs. The Health Survey for England (HSE) comprises a series of annual surveys beginning in 1991. The series is part of an overall program of surveys commissioned the DH and designed to provide regular information on various aspects of the nation’s health. All surveys have covered the adult population aged 16 and over living in private households in England. Children were included in every year since 1995.

Current disease prevalence of long standing illness, CHD, diabetes, COPD and asthma

ONS Key Health Statistics from General Practice

A series of morbidity reports using data from General Practice. The data are contributed by over 400 Practices in England and Wales, covering 2.9 million patients registered at the end of 1998 – nearly 6 per cent of the population.

Primary care data

Suitable.

Prevalence of CHD and asthma

However, all the data are only available at England and Wales level.

Purcell et al.

A study on epilepsy prevalence in

Primary care data

Suitable.

Health Survey for England

JSNA LTCs Final Version

Prevalence of life style choices

Suitable. However, data is only available at Government Office level (i.e. West Midlands). For areas smaller than government office region, it is only an estimated prevalence.

190

Raw data as well as survey reports are available from NSH Information Centre’s website

Very reliable Well developed methodology in sampling and questionnaire design etc

Latest year 2007

Dataset available from the ONS website

Methodology described in the technical documents of the statistics on the ONS website

1994-1998

Paper

Methodology

1994 –

More than 10 years old.


Table B.1

Data sources used in this study

Data source

study

Stevens et al. study

UK renal registry

Description

Use of the data source

England and Wales based on data from the General Practice Research Database (GPRD) of 211 GP practices collected.

Epilepsy prevalence

A study on CKD prevalence in England as part of the NEOERICA project and it utilizes a dataset of 130, 226 adults in the regions of Kent, Manchester, and Surrey in the UK to study the risk factors of CKD.

CKD prevalence

The UK Renal Registry is a resource for the development of patient care in renal disease. It was established by the Renal Association with support from the Department of Health, the British Association of Paediatric Nephrologists, and the British Transplant Society.

Renal Replacement Therapy (RRT) prevalence

JSNA LTCs Final Version

reliability of the data source

timeliness of data

suitability of purpose

accessibility

Epilepsy is not covered by the HsfE and studies on the prevalence of epilepsy are very limited. This is the only study that is available for the purpose.

available from the ONS website. However raw data is not available.

described in the paper.

Paper available from the BMJ website.

Methodology described in the paper.

2003

Reports available from the UK renal registryâ&#x20AC;&#x2122;s website

Very reliable

2007

Suitable. CKD is not covered by the HsfE. There are a few studies on the incidents and prevalence of CKD. This study has a relatively large sample size and it covers different areas in the country too. Suitable. Demographic information of each patient is available.

191

1998 More than 10 years old.

More than five years old.


Table B.1

Data sources used in this study reliability of the data source

timeliness of data

Data available from the PCTs

Very reliable

May 2009

Suitable

Available from ONS website

Very reliable

2004 and 2007

Population

Suitable

Available from the ONS website

Reliable

2007

Primary care (GP practice) population

Suitable

Available on annual basis

Very reliable

2007

Data source

Description

Drug prescription data from primary care

Item, dosage and cost of prescriptions from GPs in Birmingham, collected by the Department of Medicine Management at Keele University on behalf of all PCTs in the West Midlands.

Epilepsy and asthma prescription as proxy for prevalence

Suitable.

Indices of Deprivation

The Index of Multiple Deprivation combines a number of indicators, chosen to cover a range of economic, social and housing issues, into a single deprivation score for each small area in England. The Indices of Deprivation have been produced at Lower Super Output Area level.

Social deprivation scores and quintiles

ONS midyear population estimates

Mid-year estimates of the resident population are available for a range of geographies by age and sex.

NHS Strategic Tracing Service

The NSTS database covers every patient registered with the NHS in England and Wales.

JSNA LTCs Final Version

Use of the data source

suitability of purpose

However no future projections of GP registered population available

192

accessibility


17. Appendix C

Projection models

17.1. CHD model

Joint Strategic Needs Assessment

Table C.1

Relative risk ratios for local CHD model

Risk factor

RRR

Std Error

z

P>z

[95% Conf.

Interv al]

Age 25-34

1.000

Age 35-44

6.867

2.998

4.41

0

2.919

16.157

Age 45-54

19.514

8.217

7.06

0

8.549

44.541

Age 55-64

65.698

27.217

10.1

0

29.169

147.972

Age 65-74

122.864

50.719

11.65

0

54.707

275.936

Age 75+

191.252

79.128

12.7

0

85.003

430.307

Female sex

1.000

Male sex

1.849

0.139

8.16

0

1.595

2.143

Never smoker

1.000

Used to smoke occasionally

0.757

0.131

-1.61

0.107

0.539

1.062

Used to smoke regularly

1.484

0.119

4.91

0

1.267

1.737

Current smoker

1.072

0.109

0.68

0.495

0.878

1.308

Index of multiple deprivation 8.35

0.591.000

Index of multiple deprivation 8.3513.72

1.226

0.143

1.75

0.08

0.976

1.541

Index of multiple deprivation 13.7321.16

1.350

0.154

2.63

0.009

1.079

1.689

Index of multiple deprivation 21.1734.21

1.645

0.183

4.49

0

1.323

2.044

Index of multiple deprivation 34.2286.36

2.420

0.256

8.36

0

1.967

2.978

White

1.000

Mixed

1.264

0.851

0.35

0.727

0.338

4.726

Black/BB

0.763

0.168

-1.23

0.218

0.496

1.173

JSNA LTCs Final Version

193


Table C.1

Relative risk ratios for local CHD model

Risk factor

RRR

Std Error

z

P>z

[95% Conf.

Interv al]

Asian/AO

1.511

0.243

2.56

0.01

1.102

2.071

Other

0.168

0.170

-1.76

0.079

0.023

1.227

JSNA LTCs Final Version

194


18. Appendix D Projected CHD prevalence by demographical groups 18.1. Projected CHD by gender Table D.1

Projected CHD prevalence in Birmingham and PCTs up to 2020 â&#x20AC;&#x201C; females Birmingham Year

Scenario 1

Scenario 2

Scenario 3

N

SB PCT

HoB tPCT

%*

N

%*

N

%*

BEN PCT N

%

2008

24201

5.9%

6415

4.5%

4904

4.7%

10419

6.5%

2009

24188

5.9%

6398

4.4%

4896

4.7%

10407

6.5%

2010

24153

5.9%

6413

4.4%

4899

4.7%

10399

6.4%

2015

24656

5.8%

6512

4.4%

5020

4.7%

10581

6.4%

2020

25601

5.9%

6761

4.4%

5192

4.8%

10968

6.5%

2008

24201

5.9%

6415

4.5%

4904

4.7%

10419

6.5%

2009

24185

5.9%

6397

4.4%

4895

4.7%

10406

6.5%

2010

24147

5.9%

6411

4.4%

4897

4.7%

10397

6.4%

2015

24634

5.8%

6506

4.4%

5016

4.7%

10572

6.4%

2020

25563

5.9%

6751

4.4%

5184

4.8%

10951

6.5%

2008

24201

5.9%

6415

4.5%

4904

4.7%

10419

6.5%

2009

24177

5.9%

6395

4.4%

4893

4.7%

10402

6.5%

2010

24130

5.9%

6407

4.4%

4894

4.7%

10390

6.4%

2015

24594

5.8%

6496

4.4%

5007

4.7%

10555

6.4%

2020

25517

5.9%

6738

4.4%

5174

4.8%

10932

6.4%

* % out of persons aged 16+

JSNA LTCs Final Version

195


Table D.2

Projected CHD prevalence in Birmingham and PCTs up to 2020 â&#x20AC;&#x201C; males Birmingham Year

Scenario 1

Scenario 2

Scenario 3

N

SB PCT

HoB tPCT

%*

N

%*

N

%*

BEN PCT N

%

2008

32745

8.5%

8685

6.5%

7160

6.9%

13958

9.4%

2009

32929

8.5%

8695

6.5%

7185

6.9%

14032

9.4%

2010

33197

8.5%

8752

6.5%

7200

6.9%

14119

9.4%

2015

34734

8.7%

9211

6.6%

7576

7.1%

14742

9.6%

2020

36597

8.9%

9705

6.8%

7953

7.3%

15558

9.9%

2008

32745

8.5%

8685

6.5%

7160

6.9%

13958

9.4%

2009

32952

8.5%

8702

6.5%

7190

6.9%

14042

9.4%

2010

33243

8.5%

8764

6.5%

7210

6.9%

14138

9.4%

2015

34901

8.7%

9257

6.7%

7614

7.1%

14812

9.6%

2020

36896

9.0%

9787

6.9%

8021

7.3%

15683

9.9%

2008

32745

8.5%

8685

6.5%

7160

6.9%

13958

9.4%

2009

33015

8.5%

8719

6.5%

7204

7.0%

14068

9.5%

2010

33370

8.5%

8799

6.5%

7239

6.9%

14191

9.5%

2015

35211

8.8%

9342

6.7%

7684

7.2%

14941

9.7%

2020

37251

9.1%

9885

6.9%

8101

7.4%

15832

10.0%

* % out of persons aged 16+

JSNA LTCs Final Version

196


18.2. Projected CHD by age group Table D.3

Projected CHD prevalence in Birmingham and PCTs up to 2020 – Aged 16 – 44 Birmingham

Scenario 1

Scenario 2

Scenario 3

SB PCT

Year

N

%*

2008

2600

0.6%

581

0.4%

2009

2586

0.6%

579

2010

2603

0.6%

2015

2516

2020

BEN PCT

%*

N

720

0.5%

1036

0.6%

0.4%

717

0.5%

1027

0.6%

573

0.4%

710

0.5%

1018

0.6%

0.5%

553

0.4%

693

0.5%

982

0.6%

2718

0.6%

596

0.4%

749

0.5%

1058

0.6%

2008

2600

0.6%

581

0.4%

720

0.5%

1036

0.6%

2009

2589

0.6%

579

0.4%

718

0.5%

1028

0.6%

2010

2609

0.6%

575

0.4%

711

0.5%

1020

0.6%

2015

2535

0.5%

557

0.4%

699

0.5%

989

0.6%

2020

2754

0.6%

603

0.4%

760

0.5%

1072

0.6%

2008

2600

0.6%

581

0.4%

720

0.5%

1036

0.6%

2009

2597

0.6%

581

0.4%

720

0.5%

1031

0.6%

2010

2625

0.6%

578

0.4%

716

0.5%

1027

0.6%

2015

2572

0.6%

565

0.4%

709

0.5%

1003

0.6%

2020

2797

0.6%

613

0.4%

772

0.6%

1088

0.6%

JSNA LTCs Final Version

N

%*

HoB tPCT N

%

197


Table D.4

Projected CHD prevalence in Birmingham and PCTs up to 2020 – aged 45 – 64 Birmingham Year

Scenario 1

Scenario 2

Scenario 3

N

SB PCT

HoB tPCT

BEN PCT

%*

N

%*

N

%*

N

%

2008

17968

8.7%

4633

6.1%

3918

8.7%

7639

8.8%

2009

18064

8.7%

4654

6.1%

3923

8.7%

7573

8.8%

2010

18218

8.7%

4669

6.1%

3949

8.6%

7610

8.7%

2015

18784

8.6%

4823

6.0%

4074

8.5%

7845

8.6%

2020

19701

8.9%

5077

6.2%

4274

8.8%

8226

8.9%

2008

17968

8.7%

4633

6.1%

3918

8.7%

7639

8.8%

2009

18074

8.7%

4657

6.1%

3926

8.7%

7578

8.8%

2010

18240

8.7%

4675

6.1%

3953

8.6%

7619

8.7%

2015

18864

8.6%

4845

6.0%

4091

8.6%

7879

8.7%

2020

19843

8.9%

5116

6.3%

4305

8.9%

8286

8.9%

2008

17968

8.7%

4633

6.1%

3918

8.7%

7639

8.8%

2009

18105

8.7%

4665

6.1%

3932

8.7%

7591

8.8%

2010

18300

8.7%

4691

6.1%

3967

8.7%

7644

8.8%

2015

19013

8.7%

4885

6.1%

4123

8.6%

7942

8.7%

2020

20013

9.0%

5162

6.3%

4342

9.0%

8357

9.0%

JSNA LTCs Final Version

198


Table D.5

Projected CHD prevalence in Birmingham and PCTs up to 2020 – Aged 65 – 74 Birmingham Year

Scenario 1

Scenario 2

Scenario 3

N

%*

SB PCT N

%*

HoB tPCT N

%*

BEN PCT N

%

2008

15786

23.0%

4042

16.8%

3552

23.2%

6755

23.0%

2009

15896

23.0%

4054

16.8%

3552

23.2%

6801

23.0%

2010

15922

23.0%

4054

16.8%

3552

23.2%

6813

23.0%

2015

16560

23.1%

4235

16.9%

3722

23.3%

7064

23.0%

2020

17097

23.0%

4363

16.8%

3833

23.2%

7316

23.0%

2008

15786

23.0%

4042

16.8%

3552

23.2%

6755

23.0%

2009

15900

23.0%

4055

16.8%

3553

23.2%

6803

23.0%

2010

15930

23.1%

4056

16.8%

3554

23.2%

6817

23.0%

2015

16589

23.1%

4243

16.9%

3728

23.3%

7077

23.1%

2020

17148

23.1%

4378

16.9%

3845

23.3%

7337

23.1%

2008

15786

23.0%

4042

16.8%

3552

23.2%

6755

23.0%

2009

15911

23.0%

4058

16.8%

3555

23.2%

6808

23.0%

2010

15952

23.1%

4063

16.9%

3559

23.3%

6826

23.1%

2015

16643

23.2%

4259

17.0%

3741

23.4%

7099

23.1%

2020

17208

23.2%

4395

17.0%

3858

23.4%

7363

23.2%

JSNA LTCs Final Version

199


Table D.6

Projected CHD prevalence in Birmingham and PCTs up to 2020 â&#x20AC;&#x201C; aged 75 and above Birmingham Year

Scenario 1

Scenario 2

Scenario 3

N

%*

SB PCT N

%*

HoB tPCT N

%*

BEN PCT N

%

2008

20593

30.5%

5844

23.0%

3874

30.7%

9048

30.6%

2009

20572

30.6%

5807

23.0%

3888

30.9%

9037

30.6%

2010

20606

30.6%

5868

23.1%

3888

30.9%

9077

30.7%

2015

21530

30.8%

6112

23.3%

4108

31.1%

9432

30.9%

2020

22682

31.0%

6430

23.5%

4289

31.3%

9926

31.1%

2008

20593

30.5%

5844

23.0%

3874

30.7%

9048

30.6%

2009

20574

30.6%

5808

23.0%

3889

30.9%

9038

30.6%

2010

20610

30.6%

5869

23.1%

3889

30.9%

9079

30.7%

2015

21547

30.9%

6118

23.4%

4112

31.1%

9439

30.9%

2020

22713

31.1%

6441

23.5%

4295

31.4%

9939

31.2%

2008

20593

30.5%

5844

23.0%

3874

30.7%

9048

30.6%

2009

20580

30.6%

5810

23.1%

3890

30.9%

9041

30.6%

2010

20623

30.6%

5873

23.1%

3890

30.9%

9084

30.7%

2015

21578

30.9%

6128

23.4%

4118

31.2%

9453

31.0%

2020

22751

31.1%

6453

23.6%

4303

31.4%

9956

31.2%

JSNA LTCs Final Version

200


18.3. Projected CHD by ethnicity Table D.7

Projected CHD prevalence in Birmingham and PCTs up to 2020 â&#x20AC;&#x201C; White ethnic group Birmingham Year

Scenario 1

Scenario 2

Scenario 3

N

%*

SB PCT N

HoB tPCT

%*

N

%*

BEN PCT N

%

2008

47459

8.5%

13935

6.0%

6742

8.1%

21676

9.0%

2009

47594

8.4%

13926

6.0%

6746

8.1%

21725

8.9%

2010

46378

8.4%

13993

6.0%

6754

8.0%

21794

8.9%

2015

48043

8.5%

14509

6.0%

7030

8.1%

22507

9.0%

2020

50340

8.7%

15200

6.2%

7349

8.3%

23589

9.2%

2008

47459

8.5%

13935

6.0%

6742

8.1%

21676

9.0%

2009

47610

8.4%

13931

6.0%

6749

8.1%

21732

8.9%

2010

46408

8.4%

14002

6.0%

6758

8.0%

21808

8.9%

2015

48154

8.5%

14545

6.1%

7047

8.1%

22559

9.0%

2020

50540

8.7%

15264

6.2%

7379

8.3%

23583

9.2%

2008

47459

8.5%

13935

6.0%

6742

8.1%

21676

9.0%

2009

47653

8.4%

13945

6.0%

6755

8.1%

21752

8.9%

2010

46493

8.5%

14029

6.0%

6771

8.0%

21847

8.9%

2015

48361

8.6%

14611

6.1%

7078

8.2%

22656

9.0%

2020

50777

8.8%

15341

6.2%

7415

8.4%

23794

9.2%

JSNA LTCs Final Version

201


Table D.8

Projected CHD prevalence in Birmingham and PCTs up to 2020 â&#x20AC;&#x201C; Mixed race Birmingham Year

Scenario 1

Scenario 2

Scenario 3

N

%*

SB PCT %*

N

HoB tPCT %*

N

BEN PCT %

N

2008

189

1.2%

40

0.7%

78

1.3%

61

1.2%

2009

190

1.2%

40

0.7%

78

1.3%

61

1.2%

2010

236

1.2%

40

0.7%

78

1.3%

61

1.2%

2015

245

1.2%

41

0.7%

81

1.3%

63

1.2%

2020

254

1.2%

43

0.8%

85

1.4%

66

1.3%

2008

189

1.2%

40

0.7%

78

1.3%

61

1.2%

2009

190

1.2%

40

0.7%

78

1.3%

61

1.2%

2010

237

1.2%

40

0.7%

78

1.3%

61

1.2%

2015

246

1.2%

41

0.7%

81

1.3%

63

1.2%

2020

256

1.2%

43

0.8%

85

1.4%

66

1.3%

2008

189

1.2%

40

0.7%

78

1.3%

61

1.2%

2009

190

1.2%

40

0.7%

78

1.3%

61

1.2%

2010

237

1.2%

40

0.7%

78

1.3%

61

1.2%

2015

248

1.2%

42

0.8%

82

1.3%

64

1.2%

2020

258

1.2%

44

0.8%

86

1.4%

66

1.3%

JSNA LTCs Final Version

202


Table D.9

Projected CHD prevalence in Birmingham and PCTs up to 2020 â&#x20AC;&#x201C; Black ethnic group Birmingham

Scenario 1

Scenario 2

Scenario 3

Year

N

%*

2008

1893

3.6%

2009

1899

2010

SB PCT

HoB tPCT

BEN PCT

%*

N

%*

231

2.0%

1108

3.8%

459

3.6%

3.6%

232

2.0%

1111

3.8%

461

3.6%

2079

3.8%

233

2.0%

1112

3.8%

462

3.6%

2015

2150

3.8%

242

2.1%

1162

3.9%

478

3.7%

2020

2234

3.9%

252

2.1%

1210

3.9%

499

3.7%

2008

1893

3.6%

231

2.0%

1108

3.8%

459

3.6%

2009

1900

3.6%

232

2.0%

1111

3.8%

461

3.6%

2010

2080

3.8%

233

2.0%

1113

3.8%

462

3.6%

2015

2156

3.8%

243

2.1%

1165

3.9%

479

3.7%

2020

2245

4.0%

254

2.1%

1215

4.0%

501

3.7%

2008

1893

3.6%

231

2.0%

1108

3.8%

459

3.6%

2009

1902

3.6%

232

2.0%

1112

3.8%

461

3.6%

2010

2085

3.8%

234

2.0%

1115

3.8%

463

3.6%

2015

2167

3.8%

245

2.1%

1171

3.9%

481

3.7%

2020

2257

4.0%

256

2.1%

1221

4.0%

504

3.8%

JSNA LTCs Final Version

N

N

%

203


Table D.10 Projected CHD prevalence in Birmingham and PCTs up to 2020 â&#x20AC;&#x201C; Asian ethnic group Birmingham

Scenario 1

Scenario 2

Scenario 3

Year

N

%*

2008

7176

5.0%

2009

7205

2010

SB PCT

HoB tPCT

BEN PCT

%*

N

%*

N

842

3.9%

4022

5.0%

2129

4.8%

5.0%

844

3.9%

4032

5.0%

2139

4.8%

8373

5.3%

847

3.9%

4041

4.9%

2147

4.8%

2015

8659

5.4%

877

3.9%

4204

5.0%

2220

4.8%

2020

9064

5.5%

914

4.0%

4378

5.2%

2314

4.9%

2008

7176

5.0%

842

3.9%

4022

5.0%

2129

4.8%

2009

7209

5.0%

844

3.9%

4033

5.0%

2140

4.8%

2010

8380

5.3%

848

3.9%

4044

5.0%

2149

4.8%

2015

8685

5.4%

880

3.9%

4217

5.0%

2227

4.8%

2020

9111

5.5%

920

4.1%

4400

5.2%

2326

4.9%

2008

7176

5.0%

842

3.9%

4022

5.0%

2129

4.8%

2009

7217

5.0%

845

3.9%

4038

5.0%

2142

4.8%

2010

8400

5.3%

850

3.9%

4054

5.0%

2155

4.8%

2015

8733

5.4%

886

4.0%

4240

5.1%

2240

4.8%

2020

9167

5.6%

926

4.1%

4427

5.2%

2341

5.0%

JSNA LTCs Final Version

N

%

204


Table D.11 Other Ethnic communities Projected CHD prevalence in Birmingham and PCTs up to 2020 Birmingham Year Scenario 1

Scenario 2

Scenario 3

N

%*

SB PCT %*

N

HoB tPCT N

%*

BEN PCT %

N

2008

229

1.2%

51

0.6%

114

1.5%

53

1.4%

2009

230

1.2%

52

0.6%

114

1.5%

54

1.4%

2010

284

1.5%

52

0.6%

114

1.5%

54

1.4%

2015

294

1.5%

54

0.6%

119

1.5%

55

1.3%

2020

306

1.5%

56

0.6%

124

1.6%

58

1.4%

2008

229

1.2%

51

0.6%

114

1.5%

53

1.4%

2009

230

1.2%

52

0.6%

114

1.5%

54

1.4%

2010

284

1.5%

52

0.6%

114

1.5%

54

1.4%

2015

295

1.5%

54

0.6%

119

1.5%

56

1.4%

2020

308

1.6%

56

0.7%

125

1.6%

58

1.4%

2008

229

1.2%

51

0.6%

114

1.5%

53

1.4%

2009

230

1.2%

52

0.6%

114

1.5%

54

1.4%

2010

285

1.6%

52

0.6%

115

1.5%

54

1.4%

2015

297

1.5%

54

0.6%

120

1.5%

56

1.4%

2020

310

1.6%

57

0.7%

126

1.6%

59

1.4%

JSNA LTCs Final Version

205


19. Appendix E Projected population for Birmingham and the PCTs Table E.1

Projected population by gender and aged group, Birmingham and PCTs, 2010, 2015 and 2020 Birmingham

Age group

2010

BEN

HOB

SB

2015

2020

2010

2015

2020

2010

2015

2020

2010

2015

2020

Males (thousand) 0-4

42.7

46

46.7

17.2

18.5

18.8

13.9

15.0

15.2

11.6

12.5

12.7

5-9

35.0

40.6

43.6

14.4

16.7

17.9

10.4

12.1

13.0

10.2

11.8

12.7

10-14

33.1

33.4

38.6

13.9

14.0

16.3

9.2

9.3

10.7

10.0

10.1

11.6

15-19

35.8

33.6

33.7

13.6

12.8

12.9

11.1

10.4

10.4

11.1

10.4

10.4

20-24

48.0

45.9

43.5

14.7

14.1

13.3

15.6

14.9

14.1

17.7

16.9

16.1

25-29

46.8

49.5

47.7

15.5

16.4

15.8

15.7

16.6

16.0

15.6

16.5

15.9

30-34

34.7

43.2

45.8

12.5

15.6

16.5

11.0

13.7

14.5

11.2

13.9

14.8

35-39

33.6

32.1

39.3

13.3

12.7

15.5

9.2

8.8

10.8

11.1

10.6

13.0

40-44

35.5

31.8

30.1

14.3

12.8

12.1

8.9

8.0

7.6

12.3

11.0

10.4

45-49

31.0

33.3

29.9

12.9

13.8

12.4

7.3

7.9

7.1

10.8

11.6

10.4

50-54

27.1

29.1

31.1

10.9

11.7

12.5

6.1

6.5

7.0

10.1

10.9

11.6

55-59

23.1

24.7

26.7

10.0

10.7

11.5

4.3

4.6

5.0

8.8

9.4

10.2

60-64

21.5

20.6

22.3

9.1

8.7

9.4

4.6

4.4

4.8

7.8

7.5

8.1

65-69

17.2

19.1

18.3

7.1

7.8

7.5

4.0

4.5

4.3

6.1

6.8

6.5

70-74

15.3

14.9

16.7

6.8

6.6

7.4

3.4

3.3

3.7

5.1

5.0

5.6

75-79

12.0

12.5

12.5

5.1

5.3

5.3

2.5

2.6

2.6

4.4

4.6

4.6

80-84

8.4

8.8

9.7

3.7

3.9

4.3

1.8

1.9

2.1

2.9

3.0

3.3

85+

6.5

7.8

9.1

2.9

3.4

4

1.1

1.4

1.6

2.5

3.0

3.5

JSNA LTCs Final Version

206


Table E.1

Projected population by gender and aged group, Birmingham and PCTs, 2010, 2015 and 2020 Birmingham

BEN

HOB

SB

Age group

2010

2015

2020

2010

2015

2020

2010

2015

2020

2010

2015

2020

All ages

507.3

526.8

545.4

197.8

205.5

213.6

140.2

145.8

150.4

169.3

175.5

181.4

Females (thousand) 0-4

41.1

44.3

44.9

16.4

17.7

18

13.7

14.8

15.0

11.0

11.8

11.9

5-9

33.6

39.2

42.1

13.8

16.1

17.3

10.2

11.9

12.8

9.6

11.2

12.0

10-14

31.7

32.1

37.3

13.1

13.3

15.4

8.8

8.9

10.4

9.8

9.9

11.5

15-19

36.3

33.7

33.9

13.7

12.8

12.9

11.0

10.2

10.2

11.6

10.7

10.8

20-24

48.9

47.4

44.5

14.8

14.4

13.5

16.4

15.9

14.9

17.7

17.1

16.1

25-29

45.7

48.4

47

15.9

16.9

16.4

13.9

14.7

14.3

15.9

16.8

16.3

30-34

36.0

43.5

46

13.9

16.8

17.8

10.0

12.1

12.8

12.1

14.6

15.4

35-39

33.5

34.1

40.7

13.6

13.8

16.5

8.6

8.8

10.5

11.3

11.5

13.7

40-44

34.7

31.6

31.9

14.4

13.1

13.2

8.3

7.6

7.7

12.0

10.9

11.0

45-49

32.7

32.7

29.9

13.4

13.4

12.3

7.8

7.8

7.1

11.5

11.5

10.5

50-54

27.7

30.8

30.9

11.2

12.5

12.5

6.1

6.8

6.8

10.4

11.5

11.6

55-59

24.1

25.7

28.6

10.1

10.8

12

4.8

5.1

5.7

9.2

9.8

10.9

60-64

22.7

22.1

23.5

9.7

9.4

10

4.8

4.7

5.0

8.2

8.0

8.5

65-69

18.8

20.8

20.2

8.1

9.0

8.7

4.2

4.6

4.5

6.5

7.2

7.0

70-74

17.7

17

19

7.6

7.3

8.2

3.7

3.6

4.0

6.4

6.1

6.8

75-79

15.1

15.4

14.9

6.7

6.8

6.6

2.9

3.0

2.9

5.5

5.6

5.4

80-84

12.2

11.7

12.4

5.5

5.3

5.6

1.9

1.8

1.9

4.8

4.6

4.9

85+

13.4

13.7

14.4

5.7

5.8

6.1

2.4

2.5

2.6

5.3

5.4

5.7

526.0

544.1

562

207.8

215.2

223

139.7

144.8

149.0

178.5

184.1

190.0

All ages

JSNA LTCs Final Version

207


20. Appendix F Projected epilepsy prevalence by demographics Table F.1

Projected number of people with epilepsy by gender and age group, Birmingham and PCTs, 2010, 2015 and 2020 Birmingham

BEN

HOB

SB

2010

2015

2020

2010

2015

2020

2010

2015

2020

2010

2015

2020

0-4

155

167

170

62

67

68

51

55

56

42

45

46

5-9

292

339

364

120

139

150

88

102

110

84

98

105

10-14

276

279

323

115

116

135

77

77

90

84

85

98

15-19

487

454

456

184

173

174

149

139

139

153

142

143

20-24

654

630

594

199

192

181

216

208

196

239

230

217

25-29

731

773

748

248

263

254

234

247

239

249

263

254

30-34

559

685

725

209

256

271

166

204

216

184

225

239

35-39

530

523

632

212

209

253

141

139

168

177

175

211

40-44

555

501

490

227

205

200

136

123

121

192

173

169

45-49

545

564

511

225

233

211

129

134

121

191

197

179

50-54

469

512

530

189

207

214

104

114

118

175

192

198

55-59

436

466

511

186

199

217

84

90

99

166

178

195

60-64

409

395

423

174

167

179

87

84

91

148

143

153

65-69

379

420

406

160

177

170

86

96

93

133

148

142

70-74

347

336

376

152

146

164

75

73

81

121

117

130

75-79

316

326

321

137

141

139

63

66

65

116

119

117

80-84

238

238

258

106

107

115

44

44

48

88

87

94

85+

246

268

296

106

115

128

43

49

53

96

105

116

7904

8192

8471

3102

3218

3340

2141

2223

2290

2660

2751

2841

JSNA LTCs Final Version

208


Table F.1

Projected number of people with epilepsy by gender and age group, Birmingham and PCTs, 2010, 2015 and 2020 Birmingham

BEN

HOB

SB

2010

2015

2020

2010

2015

2020

2010

2015

2020

2010

2015

2020

0-4

81

87

89

33

35

36

26

29

29

22

24

24

5-9

154

179

192

63

73

79

46

53

57

45

52

56

10-14

146

147

170

61

62

72

40

41

47

44

44

51

15-19

236

222

222

90

84

85

73

69

69

73

69

69

20-24

317

303

287

97

93

88

103

98

93

117

112

106

25-29

370

391

377

122

130

125

124

131

126

123

130

126

30-34

274

341

362

99

123

130

87

108

115

88

110

117

35-39

269

257

314

106

102

124

74

70

86

89

85

104

40-44

284

254

241

114

102

97

71

64

61

98

88

83

45-49

260

280

251

108

116

104

61

66

60

91

97

87

50-54

228

244

261

92

98

105

51

55

59

85

92

97

55-59

219

235

254

95

102

109

41

44

48

84

89

97

60-64

204

196

212

86

83

89

44

42

46

74

71

77

65-69

187

208

199

77

85

82

44

49

47

66

74

71

70-74

167

162

182

74

72

81

37

36

40

56

55

61

75-79

167

174

174

71

74

74

35

36

36

61

64

64

80-84

117

122

135

51

54

60

25

26

29

40

42

46

98

118

137

44

51

60

17

21

24

38

45

53

3906

4056

4200

1523

1582

1645

1080

1123

1158

1304

1351

1397

Males

85+ ALL AGES

JSNA LTCs Final Version

209


Table F.1

Projected number of people with epilepsy by gender and age group, Birmingham and PCTs, 2010, 2015 and 2020 Birmingham

BEN

HOB

SB

2010

2015

2020

2010

2015

2020

2010

2015

2020

2010

2015

2020

0-4

74

80

81

30

32

32

25

27

27

20

21

21

5-9

138

161

173

57

66

71

42

49

52

39

46

49

10-14

130

132

153

54

55

63

36

36

43

40

41

47

15-19

250

233

234

95

88

89

76

70

70

80

74

75

20-24

337

327

307

102

99

93

113

110

103

122

118

111

25-29

361

382

371

126

134

130

110

116

113

126

133

129

30-34

284

344

363

110

133

141

79

96

101

96

115

122

35-39

261

266

317

106

108

129

67

69

82

88

90

107

40-44

271

246

249

112

102

103

65

59

60

94

85

86

45-49

284

284

260

117

117

107

68

68

62

100

100

91

50-54

241

268

269

97

109

109

53

59

59

90

100

101

55-59

217

231

257

91

97

108

43

46

51

83

88

98

60-64

204

199

212

87

85

90

43

42

45

74

72

77

65-69

192

212

206

83

92

89

43

47

46

66

73

71

70-74

181

173

194

78

74

84

38

37

41

65

62

69

75-79

149

152

148

66

67

65

29

30

29

54

55

53

80-84

121

116

123

54

52

55

19

18

19

48

46

49

85+

147

151

158

63

64

67

26

28

29

58

59

63

3998

4135

4271

1579

1636

1695

1062

1100

1132

1357

1399

1444

Females

ALL AGES

JSNA LTCs Final Version

210


21. Appendix G Projected prevalence of CKD by demographical groups Table G.1

Projected number of people with CKD (stage 3 to 5) by gender and age group (aged 18 and above), Birmingham and PCTs, 2010, 2015 and 2020 Birmingham

BEN

HOB

SB

2010

2015

2020

2010

2015

2020

2010

2015

2020

2010

2015

2020

18-24

120

116

110

39

37

35

39

38

36

42

41

39

25-34

784

884

894

283

321

325

234

263

266

267

300

303

35-44

2325

2221

2446

949

905

995

583

560

620

793

756

831

45-54

3475

3694

3575

1419

1508

1459

801

851

822

1255

1335

1294

55-64

9199

9378

10196

3908

3981

4320

1870

1903

2076

3421

3494

3800

65-74

15905

16532

17099

6827

7083

7338

3507

3661

3780

5571

5788

5980

75-84

18143

18358

18740

8003

8094

8268

3427

3493

3559

6714

6772

6913

9422

10150

11072

4069

4341

4755

1659

1842

1980

3695

3967

4337

18-24

6

6

6

2

2

2

2

2

2

2

2

2

25-34

139

158

159

48

54

55

45

52

52

46

52

52

35-44

491

454

493

196

181

196

129

119

131

166

153

166

45-54

1789

1922

1879

733

785

767

413

444

434

644

693

678

55-64

3073

3121

3376

1316

1337

1440

613

620

675

1144

1164

1261

65-74

5736

6001

6178

2453

2542

2630

1306

1377

1412

1977

2083

2136

75-84

6765

7063

7362

2918

3051

3183

1426

1492

1559

2421

2520

2620

85+

2909

3491

4072

1298

1522

1790

492

627

716

1119

1343

1566

114

110

105

37

35

34

37

36

34

40

38

37

85+ Males

Females 18-24

JSNA LTCs Final Version

211


Table G.1

Projected number of people with CKD (stage 3 to 5) by gender and age group (aged 18 and above), Birmingham and PCTs, 2010, 2015 and 2020 Birmingham

BEN

HOB

SB

2010

2015

2020

2010

2015

2020

2010

2015

2020

2010

2015

2020

25-34

645

726

735

235

266

270

189

212

214

221

248

250

35-44

1835

1767

1953

753

724

799

455

441

490

627

603

664

45-54

1685

1772

1696

686

723

692

388

407

388

611

642

617

55-64

6126

6257

6820

2592

2644

2880

1257

1283

1401

2278

2330

2539

65-74

10169

10531

10921

4374

4541

4708

2201

2285

2368

3594

3705

3845

75-84

11379

11295

11379

5085

5043

5085

2001

2001

2001

4293

4251

4293

6514

6660

7000

2771

2819

2965

1167

1215

1264

2576

2625

2771

85+

JSNA LTCs Final Version

212


22. Appendix H

Top 20 co morbidities of common LTCs

22.1. CHD Table H.1

Prevalence of top 20 co-morbidities with CHD

Diseases

SB PCT M

F

HOB tPCT

BEN PCT

M

M

F

F

Birmingham M

F

CHD + [Asthma]

31

40

27

17

49

53

107

110

CHD + [Osteoarthritis]

27

41

14

15

23

31

64

87

CHD + [Heart failure]

43

31

32

11

56

46

131

88

CHD + [Heart failure] + [Hypertensive disease]

28

17

23

14

45

28

96

59

CHD + [Heart failure] + [Hypertensive disease] + [Diabetes mellitus]

12

11

32

21

16

16

60

48

CHD + [Stroke]

15

15

12

5

32

26

59

46

CHD + [Stroke] + [Hypertensive disease]

23

24

31

13

26

24

80

61

CHD + [Hypertensive disease]

400

260

338

197

421

303

1159

760

CHD + [Hypertensive disease] + [Asthma]

36

32

30

34

25

31

91

97

CHD + [Hypertensive disease] + [Osteoarthritis]

32

58

20

21

20

34

72

113

CHD + [Hypertensive disease] + [Thyroid Problems]

10

38

11

24

7

27

28

89

CHD + [Hypertensive disease] + [Diabetes mellitus]

137

83

184

122

164

118

485

323

CHD + [Hypertensive disease] + [Diabetes mellitus] + [Asthma]

8

12

20

29

12

23

40

64

JSNA LTCs Final Version

213


Table H.1

Prevalence of top 20 co-morbidities with CHD

Diseases

SB PCT M

F

HOB tPCT

BEN PCT

M

M

F

F

Birmingham M

F

CHD + [Hypertensive disease] + [COPD]

21

27

22

14

31

23

74

64

CHD + [Hypertensive disease] + [Cancer]

30

16

17

10

29

20

76

46

CHD + [Hypertensive disease] + [Mental Illness]

28

21

17

12

19

17

64

50

102

47

90

40

140

70

332

157

CHD + [COPD]

44

26

30

11

50

32

124

69

CHD + [Cancer]

58

19

20

11

56

28

134

58

CHD + [Mental Illness]

52

31

31

15

51

31

134

77

CHD + [Diabetes mellitus]

JSNA LTCs Final Version

214


Table H.2

Prevalence rate (per 100,000) of top 20 co-morbidities with CHD

Diseases

SB

HOB

BEN

BHAM

M

F

M

F

M

F

M

F

CHD + [Asthma]

19.1

23.0

19.9

12.6

54.7

25.9

21.7

21.4

CHD + [Osteoarthritis]

16.6

23.6

10.3

11.1

32.7

15.1

13.0

17.0

CHD + [Heart failure]

26.5

17.9

23.6

8.2

67.0

22.5

26.5

17.2

CHD + [Heart failure] + [Hypertensive disease]

17.2

9.8

17.0

10.4

49.1

13.7

19.5

11.5

CHD + [Heart failure] + [Hypertensive disease] + [Diabetes mellitus]

7.4

6.3

23.6

15.6

30.7

7.8

12.2

9.4

CHD + [Stroke]

9.2

8.6

8.9

3.7

30.2

12.7

12.0

9.0

14.2

13.8

22.9

9.7

40.9

11.7

16.2

11.9

CHD + [Hypertensive disease]

246.1

149.8

249.6

146.3

592.7

147.9

234.9

148.1

CHD + [Hypertensive disease] + [Asthma]

22.2

18.4

22.2

25.2

46.5

15.1

18.4

18.9

CHD + [Hypertensive disease] + [Osteoarthritis]

19.7

33.4

14.8

15.6

36.8

16.6

14.6

22.0

CHD + [Hypertensive disease] + [Thyroid Problems]

6.2

21.9

8.1

17.8

14.3

13.2

5.7

17.3

CHD + [Hypertensive disease] + [Diabetes mellitus]

84.3

47.8

135.9

90.6

248.0

57.6

98.3

63.0

CHD + [Hypertensive disease] + [Diabetes mellitus] + [Asthma]

4.9

6.9

14.8

21.5

20.5

11.2

8.1

12.5

CHD + [Hypertensive disease] + [COPD]

12.9

15.6

16.2

10.4

37.8

11.2

15.0

12.5

CHD + [Stroke] + [Hypertensive disease]

JSNA LTCs Final Version

215


Table H.2

Prevalence rate (per 100,000) of top 20 co-morbidities with CHD

Diseases

SB

HOB

BEN

BHAM

M

F

M

F

M

F

M

F

CHD + [Hypertensive disease] + [Cancer]

18.5

9.2

12.6

7.4

38.9

9.8

15.4

9.0

CHD + [Hypertensive disease] + [Mental Illness]

17.2

12.1

12.6

8.9

32.7

8.3

13.0

9.7

CHD + [Diabetes mellitus]

62.8

27.1

66.5

29.7

169.8

34.2

67.3

30.6

CHD + [COPD]

27.1

15.0

22.2

8.2

63.4

15.6

25.1

13.4

CHD + [Cancer]

35.7

10.9

14.8

8.2

68.5

13.7

27.2

11.3

CHD + [Mental Illness]

32.0

17.9

22.9

11.1

68.5

15.1

27.2

15.0

JSNA LTCs Final Version

216


22.2. Diabetes Table H.3

Prevalence rate (per 100,000) of top 20 co-morbidities with Diabetes

Diseases

SB

HOB

BEN

M

F

M

F

F

M

F

62.8

27.1

66.5

29.7

169.8

34.2

67.3

30.6

Diabetes + CHD + Heart Failure + Hypertensive disease

7.4

6.3

23.6

15.6

30.7

7.8

12.2

9.4

Diabetes + CHD + Hypertensive disease

84.3

47.8

135.9

90.6

248.0

57.6

98.3

63.0

Diabetes + CHD + Hypertensive disease + Asthma

4.9

6.9

14.8

21.5

20.5

11.2

8.1

12.5

Diabetes + Asthma

14.8

23.6

25.9

37.1

43.0

22.0

17.0

26.5

Diabetes + CKD + Osteoarthritis

13.5

9.2

14.0

8.2

35.8

15.1

14.2

11.3

Diabetes + Osteoarthritis

16.6

15.6

5.2

11.9

29.2

11.7

11.6

13.1

Diabetes + Thyroid problems

6.2

15.0

3.7

20.8

12.8

11.7

5.1

15.2

Diabetes + Heart Failure + hypertensive disease

4.9

4.0

17.0

15.6

24.0

7.3

9.5

8.4

Diabetes + Stroke

9.8

7.5

11.1

6.7

26.1

10.3

10.3

8.4

Diabetes + Stroke + Hypertensive disease

10.5

5.8

29.5

33.4

40.9

10.7

16.2

15.0

Diabetes + Hypertensive disease

193.8

160.8

291.0

287.4

528.3

170.4

209.4

197.8

Diabetes + Hypertensive disease + Asthma

12.3

20.7

23.6

39.4

36.8

19.5

14.6

25.1

Diabetes + Hypertensive disease + CKD

12.9

8.1

21.4

14.1

35.8

4.4

14.2

8.2

Diabetes + Hypertensive disease + Osteoarthritis

26.5

31.7

19.9

27.5

47.1

17.1

18.6

24.8

Diabetes + CHD

JSNA LTCs Final Version

M

BHAM

217


Table H.3

Prevalence rate (per 100,000) of top 20 co-morbidities with Diabetes

Diseases

SB M

HOB F

M

BEN F

M

BHAM F

M

F

Diabetes + Hypertensive disease + Thyroid problems

3.1

18.4

5.9

14.1

8.7

13.2

3.4

15.2

Diabetes + Hypertensive disease + Cancer

22.2

16.7

25.9

17.8

52.2

9.3

20.7

14.0

Diabetes + Hypertensive disease + Mental Illness

16.0

10.4

21.4

20.8

44.0

7.8

17.4

12.1

Diabetes + Cancer

28.3

10.4

18.5

16.3

68.0

16.1

27.0

14.2

Diabetes + Mental Illness

31.4

32.3

29.5

17.1

65.5

18.1

25.9

22.6

JSNA LTCs Final Version

218


22.3. CKD Table H.4

Prevalence rate (per 100,000) of top 20 co-morbidities with CKD

Diseases

SB

HOB

BEN

BHAM

M

F

M

F

M

F

M

F

16.6

7.5

10.3

2.2

31.7

5.9

12.6

5.5

CKD + Heart Failure

9.2

4.6

3.7

2.2

17.4

2.4

6.9

3.1

CKD + Heart Failure + Diabetes

3.1

0.6

0.7

0.7

7.7

2.4

3.0

1.4

CKD + CHD + Hypertensive disease

10.5

3.5

5.9

2.2

19.9

4.4

7.9

3.5

3.7

2.9

4.4

4.5

9.7

1.0

3.9

2.5

CKD + CHD + Diabetes

5.5

2.9

5.2

2.2

15.3

1.0

6.1

1.9

CKD + Asthma

0.6

0.7

3.0

3.6

4.9

1.4

3.9

CKD + Osteoarthritis

3.1

2.9

1.5

1.5

4.1

2.0

1.6

2.1

CKD + Thyroid Problems

1.2

3.5

0.7

3.7

4.1

2.4

1.6

3.1

CKD + Heart Failure

4.3

8.6

5.2

2.2

15.9

6.3

6.3

6.0

CKD + Stroke

1.8

1.2

3.7

0.7

9.2

3.4

3.6

1.9

CKD + Hypertensive Disease

24.0

20.7

24.4

23.0

58.3

16.6

23.1

19.7

CKD + Hypertensive Disease + Diabetes

13.5

8.6

22.2

14.1

36.8

4.4

14.6

8.4

CKD + Hypertensive Disease + Cancer

3.1

3.5

6.6

2.2

8.7

1.5

3.4

2.3

14.2

10.4

14.0

7.4

36.8

14.6

14.6

11.3

CKD + Diabetes + COPD

1.8

2.9

0.7

0.7

3.6

1.5

1.4

1.8

CKD + Diabetes + Mental Health

1.2

2.3

3.7

4.5

4.1

1.0

1.6

2.3

CKD + COPD

4.9

1.7

2.2

0.7

14.3

2.4

5.7

1.8

CKD + CHD

CKD + CHD + Hypertensive disease + Diabetes

CKD + Diabetes

JSNA LTCs Final Version

3.5

219


Table H.4

Prevalence rate (per 100,000) of top 20 co-morbidities with CKD

Diseases

SB

HOB

M

F

CKD + Cancer

17.2

4.0

CKD + Mental Health

10.5

12.1

JSNA LTCs Final Version

M

BEN

BHAM

F

M

F

M

F

7.4

6.7

32.2

11.2

12.8

7.6

8.9

7.4

21.0

9.8

8.3

9.9

220


22.4. COPD Table H.5

Prevalence rate (per 100,000) of top 20 co-morbidities with COPD

Diseases

SB PCT

HOB tPCT

BEN PCT

Birmingham

M

F

M

F

M

F

M

F

26.5

14.4

22.9

8.2

63.9

14.6

25.3

12.9

0.0

2.9

6.6

0.7

9.7

3.4

3.9

2.5

18.5

15.6

15.5

10.4

40.9

12.2

16.2

12.9

2.5

2.3

3.7

3.0

9.2

2.9

3.6

2.7

COPD + CHD + Diabetes

6.8

8.6

0.7

2.2

13.8

2.9

5.5

4.7

COPD + CHD + Mental Illness

5.5

3.5

4.4

0.0

9.7

1.0

3.9

1.6

COPD + Asthma

3.7

6.3

2.2

2.2

21.0

10.7

8.3

7.0

COPD + CKD

4.9

2.3

3.0

0.7

14.8

2.4

5.9

1.9

COPD + Osteoarthritis

6.2

9.2

4.4

7.4

9.2

5.9

3.6

7.4

COPD + Thyroid Problems

2.5

7.5

2.2

4.5

5.6

4.4

2.2

5.5

COPD + Heart Failure

6.2

5.2

3.0

5.2

16.9

11.2

6.7

7.6

COPD + Heart Failure + Hypertensive disease

1.2

3.5

5.2

4.5

8.2

3.4

3.2

3.7

COPD + Stroke

3.7

1.7

7.4

2.2

14.3

4.9

5.7

3.1

COPD + Hypertensive disease

32.6

33.4

30.3

20.0

77.7

22.9

30.8

25.7

COPD + Hypertensive disease + Diabetes

6.2

5.2

11.1

5.9

20.5

6.3

8.1

5.8

COPD + Hypertensive disease + Cancer

1.2

3.5

5.2

1.5

8.2

2.9

3.2

2.7

COPD + CHD COPD + CHD + Heart Failure COPD + CHD + Hypertensive disease COPD + CHD + Hypertensive disease + Diabetes

JSNA LTCs Final Version

221


Table H.5

Prevalence rate (per 100,000) of top 20 co-morbidities with COPD

Diseases

SB PCT M

F

HOB tPCT

BEN PCT

M

F

M

F

Birmingham M

F

COPD + Hypertensive disease + Mental Illness

8.6

5.8

5.9

3.7

13.3

3.9

5.3

4.5

COPD + Diabetes

6.8

8.1

7.4

1.5

21.0

5.4

8.3

5.3

COPD + Cancer

27.7

9.8

11.1

5.2

50.1

11.2

19.9

9.2

COPD + Mental Illness

33.2

23.0

19.9

11.9

61.4

18.1

24.3

18.1

JSNA LTCs Final Version

222


22.5. Asthma Table H.6

Prevalence rate (per 100,000) of top 20 co-morbidities with Asthma

Diseases

SB PCT

HOB tPCT

BEN PCT

Birmingham

M

F

M

F

M

F

M

F

Asthma + CHD

19.1

22.5

21.4

13.4

55.2

25.4

21.9

21.2

Asthma + CHD + Hypertensive Disease

22.2

18.4

22.2

26.0

46.5

15.6

18.4

19.3

Asthma + CHD + Hypertensive Disease + Diabetes

4.9

6.9

14.0

21.5

20.5

11.2

8.1

12.5

Asthma + CHD + Diabetes

4.3

3.5

5.9

8.2

12.8

6.8

5.1

6.0

Asthma + Osteoarthritis

18.5

46.7

9.6

37.1

29.7

23.4

11.8

34.9

Asthma + Eczemasis

14.8

15.6

28.1

17.8

41.9

11.2

16.6

14.4

Asthma + Thyroid problems

3.1

17.3

4.4

19.3

8.2

17.1

3.2

17.7

Asthma + Diverticulitis

5.5

10.4

1.5

3.0

8.7

4.4

3.4

6.0

Asthma + Stroke

1.8

4.0

4.4

3.0

6.6

3.9

2.6

3.7

Asthma + Hypertensive disease

59.7

100.3

68.7

98.0

129.9

66.4

51.5

86.1

Asthma + Hypertensive disease + Osteoarthritis

8.0

24.2

7.4

24.5

15.3

14.2

6.1

20.3

Asthma + Hypertensive disease + Thyroid problems

1.8

8.1

1.5

12.6

2.6

2.4

1.0

7.0

Asthma + Hypertensive disease + Diabetes

12.3

21.9

22.9

40.1

35.8

4.9

14.2

19.9

Asthma + Hypertensive disease + Cancer

7.4

10.4

4.4

6.7

11.3

4.9

4.5

7.2

Asthma + Hypertensive disease + Mental Illness

6.2

4.0

4.4

7.4

10.2

7.3

4.1

6.2

JSNA LTCs Final Version

223


Table H.6

Prevalence rate (per 100,000) of top 20 co-morbidities with Asthma

Diseases

SB PCT

HOB tPCT

BEN PCT

Birmingham

M

F

M

F

M

F

M

F

14.8

23.6

27.3

36.4

44.0

22.5

17.4

26.5

Asthma + COPD

4.3

6.3

2.2

2.2

21.0

10.3

8.3

6.8

Asthma + Epilepsy

6.8

12.7

7.4

9.7

17.9

10.3

7.1

10.9

Asthma + Cancer

17.2

13.3

9.6

13.4

30.7

14.6

12.2

13.8

Asthma + Mental Illness

46.8

67.4

48.7

55.0

102.8

43.0

40.7

54.4

Asthma + Diabetes

JSNA LTCs Final Version

224


22.6. Epilepsy Table H.7

Prevalence rate (per 100,000) of top 20 co-morbidities with Epilepsy

Diseases

SB PCT M

F

HOB tPCT

BEN PCT

M

M

F

F

Birmingham M

F

Epilepsy + CHD

3.7

4.0

3.7

0.7

9.7

1.0

3.9

1.9

Epilepsy + CHD + Hypertensive disease

3.1

1.7

2.2

2.2

6.1

2.4

2.4

2.1

Epilepsy + CHD + Mental Illness

0.1

0.6

3.0

0.0

3.6

1.5

1.4

0.8

Epilepsy + Asthma

6.8

12.7

7.4

9.7

17.9

10.3

7.1

10.9

Epilepsy + Osteoarthritis

1.8

0.6

4.4

0.7

6.1

2.4

2.4

1.4

Epilepsy + Cerebral Palsy

8.6

5.2

8.1

5.9

16.9

8.8

6.7

6.8

Epilepsy + Thyroid Problems

0.6

1.7

0.0

3.7

1.0

2.4

0.4

2.5

Epilepsy + Stroke

6.8

2.3

3.0

3.7

12.8

6.3

5.1

4.3

Epilepsy + Stroke + Hypertensive disease

2.5

2.9

1.5

1.5

4.6

2.4

1.8

2.3

Epilepsy + Stroke + Mental Illness

1.8

1.7

0.7

1.5

3.6

0.0

1.4

1.0

Epilepsy + Hypertensive disease

11.7

9.8

10.3

4.5

22.0

9.3

8.7

8.2

Epilepsy + Hypertensive disease + Asthma

0.6

0.6

1.5

2.2

2.6

2.0

1.0

1.6

Epilepsy + Hypertensive disease + Diabetes

2.5

1.2

3.0

3.7

6.1

1.5

2.4

1.9

Epilepsy + Hypertensive disease + mental illness

3.1

1.2

5.9

1.5

8.7

0.5

3.4

1.0

Epilepsy + Diabetes

2.5

1.7

4.4

3.7

8.7

1.0

3.4

1.9

Epilepsy + COPD

0.6

1.2

0.7

1.5

1.5

2.0

0.6

1.6

Epilepsy + Cancer

1.8

1.7

3.0

1.5

6.1

2.4

2.4

1.9

JSNA LTCs Final Version

225


Epilepsy + Mental Illness

36.9

29.4

59.1

20.0

102.8

18.5

40.7

22.6

Epilepsy + Mental Illness + Asthma

3.1

2.9

3.0

2.2

7.7

2.0

3.0

2.3

Epilepsy + Mental Illness + Cerebral Palsy

1.2

2.9

2.2

1.5

3.1

1.5

1.2

1.9

JSNA LTCs Final Version

226


Table H.8

Prevalence rate (per 100,000) of top 20 co-morbidities with Epilepsy + Learning Disabilities

Diseases

SB PCT M

F

HOB tPCT

BEN PCT

M

M

F

F

Birmingham M

F

Epilepsy + CHD

3.7

4.0

3.7

0.7

9.7

1.0

3.9

1.9

Epilepsy + CHD + Hypertensive disease

3.1

1.7

2.2

2.2

6.1

2.4

2.4

2.1

Epilepsy + CHD + Mental Illness

0.0

0.6

3.0

0.0

3.6

1.5

1.4

0.8

Epilepsy + Asthma

6.8

12.7

7.4

9.7

17.9

9.8

7.1

10.7

Epilepsy + Osteoarthritis

1.8

0.6

4.4

0.7

6.1

2.4

2.4

1.4

Epilepsy + Cerebral Palsy

8.6

5.2

8.1

5.9

16.9

8.8

6.7

6.8

Epilepsy + Thyroid Problems

0.6

1.7

0.0

3.7

1.0

2.4

0.4

2.5

Epilepsy + Stroke

6.8

2.3

3.0

3.7

12.8

6.3

5.1

4.3

Epilepsy + Stroke + Hypertensive disease

2.5

2.9

1.5

1.5

4.6

2.4

1.8

2.3

Epilepsy + Stroke + Mental Illness

1.8

1.7

0.7

1.5

3.6

0.0

1.4

1.0

Epilepsy + Hypertensive disease

11.7

9.8

10.3

4.5

22.5

9.3

8.9

8.2

Epilepsy + Hypertensive disease + Asthma

0.6

0.6

1.5

2.2

2.6

2.0

1.0

1.6

Epilepsy + Hypertensive disease + Diabetes

2.5

1.2

3.0

3.7

6.1

1.5

2.4

1.9

Epilepsy + Hypertensive disease + mental illness

2.5

1.2

4.4

1.5

7.2

0.5

2.8

1.0

Epilepsy + Diabetes

2.5

1.7

4.4

3.7

8.7

1.0

3.4

1.9

Epilepsy + COPD

0.6

1.2

0.7

1.5

1.5

2.0

0.6

1.6

Epilepsy + Cancer

1.8

1.7

3.0

1.5

6.1

2.4

2.4

1.9

JSNA LTCs Final Version

227


Table H.8

Prevalence rate (per 100,000) of top 20 co-morbidities with Epilepsy + Learning Disabilities

Diseases

SB PCT

HOB tPCT

BEN PCT

Birmingham

M

F

M

F

M

F

M

F

Epilepsy + Mental Illness

34.5

24.8

44.3

11.9

84.9

14.6

33.6

17.3

Epilepsy + Mental Illness + Asthma

2.5

2.9

2.2

2.2

5.1

2.0

2.0

2.3

Epilepsy + Learning Disabilities (Mental Illness)

1.2

4.0

14.8

6.7

15.9

3.9

6.3

4.7

JSNA LTCs Final Version

228


23. Appendix I Estimated prevalence of diabetes Table I.1

Estimated number of people with diagnosed or undiagnosed diabetes, by type, sex and ten-year age groups, Birmingham, 2006

Birmingham

Sex

All ages

0-15

16-24

25-34

Joint Strategic Needs Assessment Indicator

35-44

45-54

55-64

65-74

75+

Number of T1DM and T2DM patients by sex and age, and eligible populations

Eligible Population with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 Eligible Population

Both sexes Both sexes Both sexes Both sexes Males

with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 Eligible Population

Males Males Males Females

with diabetes, type 1 with diabetes, type 2

Females Females

1,006,503 4,039 52,816 56,855 493,432 2,773 29,434 32,206 513,071 1,266 23,382

with diabetes type 1 & 2

Females

24,648

Indicator

223,461 410 0 410 113,742

154,661 857 716 1,573 76,998

146,336 1,106 1,083 2,189 73,364

142,649 701 3,322 4,023 71,137

111,593 522 7,897 8,419 55,025

90,388 270 10,863 11,133 44,462

69,737 85 15,534 15,619 32,806

67,678 87 13,401 13,488 25,898

298 0 298 109,719

605 282 886 77,663

870 407 1,277 72,972

551 2,290 2,841 71,512

140 5,582 5,722 56,568

223 6,148 6,370 45,926

83 8,762 8,845 36,931

3 5,964 5,967 41,780

112 0 112

253 434

236 676

150 1,031

382 2,316

47 4,716

2 6,772

84 7,437

687

912

1,182

2,698

4,763

6,774

7,521

T1DM and T2DM prevalence rates by sex and age

with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 with diabetes, type 1 with diabetes, type 2

Both sexes Both sexes Both sexes Males Males Males Females Females

0.40% 5.25% 5.65% 0.56% 5.97% 6.53% 0.25% 4.56%

0.18% 0.00% 0.18% 0.26% 0.00% 0.26% 0.10% 0.00%

0.55% 0.46% 1.02% 0.79% 0.37% 1.15% 0.33% 0.56%

0.76% 0.74% 1.50% 1.19% 0.55% 1.74% 0.32% 0.93%

0.49% 2.33% 2.82% 0.77% 3.22% 3.99% 0.21% 1.44%

0.47% 7.08% 7.54% 0.25% 10.14% 10.40% 0.68% 4.09%

0.30% 12.02% 12.32% 0.50% 13.83% 14.33% 0.10% 10.27%

0.12% 22.27% 22.40% 0.25% 26.71% 26.96% 0.01% 18.34%

0.13% 19.80% 19.93% 0.01% 23.03% 23.04% 0.20% 17.80%

with diabetes type 1 & 2

Females

4.80%

0.10%

0.88%

1.25%

1.65%

4.77%

10.37%

18.34%

18.00%

JSNA LTCs Final Version

229


Table I.2

Estimated number of people with diagnosed or undiagnosed diabetes, by type, sex and ten-year age groups, BEN PCT, 2006

BEN PCT

Sex

Indicator

All ages

0-15

16-24

25-34

35-44

45-54

55-64

65-74

75+

Number of T1DM and T2DM patients by sex and age, and eligible populations

Eligible Population

Both sexes

with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 Eligible Population with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 Eligible Population

Both sexes Both sexes Both sexes Males Males Males Males Females

with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2

Females Females Females

400,399 1,432 20,781 22,214 195,530 981 11,458 12,439 204,869 451 9,324 9,775

Indicator

91,792

52,988

52,699

58,102

46,316

38,425

30,013

30,064

157 0 157 46,827 114 0 114 44,965

270 213 483 26,704 195 84 279 26,284

359 342 701 25,735 281 122 403 26,964

264 1,196 1,461 28,477 208 809 1,017 29,625

200 2,987 3,187 23,081 56 2,114 2,170 23,235

111 4,303 4,414 19,041 92 2,435 2,528 19,384

35 6,131 6,166 14,092 34 3,426 3,461 15,921

37 5,608 5,645 11,573 1 2,467 2,468 18,491

75 129 204

77 220 298

144 873 1,017

19 1,868 1,887

1 2,705 2,706

35 3,141 3,177

43 0 43

57 387 444

T1DM and T2DM prevalence rates by sex and age

with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 with diabetes, type 1 with diabetes, type 2

Both sexes Both sexes Both sexes Males Males Males Females Females

0.36% 5.19% 5.55% 0.50% 5.86% 6.36% 0.22% 4.55%

0.17% 0.00% 0.17% 0.24% 0.00% 0.24% 0.10% 0.00%

0.51% 0.40% 0.91% 0.73% 0.32% 1.04% 0.29% 0.49%

0.68% 0.65% 1.33% 1.09% 0.47% 1.57% 0.29% 0.82%

0.45% 2.06% 2.51% 0.73% 2.84% 3.57% 0.19% 1.31%

0.43% 6.45% 6.88% 0.24% 9.16% 9.40% 0.62% 3.76%

0.29% 11.20% 11.49% 0.49% 12.79% 13.27% 0.10% 9.64%

0.12% 20.43% 20.55% 0.24% 24.31% 24.56% 0.00% 16.99%

0.12% 18.65% 18.78% 0.01% 21.31% 21.33% 0.19% 16.99%

with diabetes type 1 & 2

Females

4.77%

0.10%

0.78%

1.10%

1.50%

4.38%

9.73%

16.99%

17.18%

JSNA LTCs Final Version

230


Table I.3

Estimated number of people with diagnosed or undiagnosed diabetes, by type, sex and ten-year age groups, HoB tPCT, 2006

HOB tPCT

Sex

All ages

Indicator

0-15

Eligible Population with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 Eligible Population with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 Eligible Population with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2

Both sexes Both sexes Both sexes Males Males Males Males Females Females Females Females

270,058 1,493 16,465 17,958 135,394 1,018 9,268 10,285 134,664 475 7,197 7,672

35-44

45-54

55-64

65-74

75+

68,150

48,393

45,998

37,021

25,820

17,633

15,022

12,021

164 0 164 34,579 113 0 113 33,571 50 0 50

347 315 661 24,166 237 123 360 24,227 109 192 301

455 472 927 24,220 357 185 541 21,778 98 287 386

242 1,253 1,495 19,175 188 876 1,065 17,846 54 377 430

170 2,668 2,838 12,719 42 1,873 1,915 13,101 128 795 923

70 3,173 3,242 8,544 56 1,757 1,813 9,089 14 1,415 1,429

24 4,951 4,975 7,107 23 2,779 2,803 7,915 1 2,172 2,173

22 3,633 3,655 4,884 1 1,674 1,675 7,137 21 1,959 1,980

Indicator

JSNA LTCs Final Version

25-34

Number of T1DM and T2DM patients by sex and age, and eligible populations Both sexes

with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2

16-24

T1DM and T2DM prevalence rates by sex and age Both sexes Both sexes Both sexes Males Males Males Females Females Females

0.55% 6.10% 6.65% 0.75% 6.85% 7.60% 0.35% 5.34% 5.70%

0.24% 0.00% 0.24% 0.33% 0.00% 0.33% 0.15% 0.00% 0.15%

0.72% 0.65% 1.37% 0.98% 0.51% 1.49% 0.45% 0.79% 1.24%

0.99% 1.03% 2.02% 1.47% 0.76% 2.24% 0.45% 1.32% 1.77%

231

0.65% 3.39% 4.04% 0.98% 4.57% 5.55% 0.30% 2.11% 2.41%

0.66% 10.33% 10.99% 0.33% 14.73% 15.06% 0.98% 6.07% 7.05%

0.39% 17.99% 18.39% 0.65% 20.57% 21.22% 0.15% 15.57% 15.72%

0.16% 32.96% 33.12% 0.33% 39.11% 39.43% 0.01% 27.44% 27.45%

0.19% 30.22% 30.41% 0.02% 34.28% 34.30% 0.30% 27.44% 27.75%


Table I.4

Estimated number of people with diagnosed or undiagnosed diabetes, by type, sex and ten-year age groups, SB PCT, 2006 SB PCT

Sex

Indicator

All ages

0-15

Eligible Population with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 Eligible Population with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 Eligible Population with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2

Both sexes Both sexes Both sexes Males Males Males Males Females Females Females Females

336,046 1,114 15,569 16,683 162,508 774 8,708 9,482 164,551 340 6,861 7,201

35-44

45-54

55-64

65-74

75+

63,519

53,280

47,639

47,526

39,457

34,330

24,702

25,593

90 0 90 32,336 71 0 71 22,197 19 0 19

241 188 429 26,128 173 75 247 27,151 68 113 181

293 269 562 23,409 232 100 332 24,230 61 169 229

195 872 1,067 23,485 155 605 760 24,041 40 268 308

152 2,242 2,394 19,225 42 1,595 1,637 20,232 110 647 757

89 3,388 3,476 16,877 74 1,955 2,029 17,453 15 1,433 1,447

26 4,451 4,477 11,607 26 2,556 2,582 13,095 1 1,895 1,895

28 4,160 4,188 9,441 1 1,823 1,824 16,152 27 2,337 2,364

Indicator

JSNA LTCs Final Version

25-34

Number of T1DM and T2DM patients by sex and age, and eligible populations Both sexes

with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2 with diabetes, type 1 with diabetes, type 2 with diabetes type 1 & 2

16-24

T1DM and T2DM prevalence rates by sex and age Both sexes Both sexes Both sexes Males Males Males Females Females Females

0.33% 4.63% 4.96% 0.48% 5.36% 5.83% 0.21% 4.17% 4.38%

0.14% 0.00% 0.14% 0.22% 0.00% 0.22% 0.08% 0.00% 0.08%

0.45% 0.35% 0.80% 0.66% 0.29% 0.95% 0.25% 0.42% 0.67%

0.61% 0.56% 1.18% 0.99% 0.43% 1.42% 0.25% 0.70% 0.95%

232

0.41% 1.84% 2.25% 0.66% 2.57% 3.23% 0.17% 1.11% 1.28%

0.39% 5.68% 6.07% 0.22% 8.29% 8.51% 0.54% 3.20% 3.74%

0.26% 9.87% 10.13% 0.44% 11.58% 12.02% 0.08% 8.21% 8.29%

0.11% 18.02% 18.12% 0.22% 22.02% 22.24% 0.00% 14.47% 14.47%

0.11% 16.25% 16.36% 0.01% 19.31% 19.32% 0.17% 14.47% 14.64%


24. References Anderson HR (2005); Prevalence of asthma, British Medical Journal (2005), 330(7499), 1037-1038 Anderson HR, Butland BK, Strachan DP (1994); Trends in prevalence and severity of childhood asthma, British Medical Journal 1994, 308(6944): 1600–1604

Joint Strategic Needs Assessment

Asher MI, Montefort S, Björkstén B, Lai CK, Strachan DP, Weiland SK, Williams H (2006); Worldwide trends in the prevalence of symptoms of asthma, allergic rhineconjunctivitis, and eczema in childhood: ISAAC Phases One and Three, Lancet (2006), 368: 733-43 Asthma UK (2006) Where do we stand, 2006 Basagaña X, Sunyer J, Kogevinas M, Zock J, Duran- Tauleria E, Jarvis D, Burney P, Anto JM (2004); Socio economic status and asthma prevalence in young adults, American Journal of Epidemiology (2004), 160:178-88 Bello, A., Peters, J., Rigby, I., Rahman, A and Nahas, M. (2008); Socioeconomic Status and Chronic Kidney Disease at Presentation to a Renal Service in the United Kingdom. Clinical Nephrology. Clin J Am Soc Nephrol 3: 1316-1323, 2008 Bouyateb A., EH Twizell, K Achouayb and A Chetouani (2004); A mathematical model for the burden of diabetes and its complications;Biomedical Engineering Online 2004, 3: 20 British Medical Association (2004), Board of Science and Education, Diabetes mellitus, an update for healthcare professionals, BMA 2004 British Occupational Health Research Foundation (2004); Occupational Asthma: A guide for Employers, Workers and their Representatives, British Thoracic Society (2009); Guidelines on the Management of Asthma, British Thoracic Society 2009 Charlotte Jones-Burton, Stephen L. Seliger, Roberta W. Scherer, Shiraz I. Mishra, Ghazal Vessal, Jeanine Brown, Matthew R. Weir, Jeffrey C. Fink (2007); Cigarette Smoking and Incident Chronic Kidney Disease: A Systematic Review, Am J Nephrol 2007;27:342-351 Cohan.G, Forbes.J, Garraway.M (1995), Interpreting self reported limiting long term illness, BMJ 1995; 311:722-724 Darzi, Lord (2008) High Quality Care for All. DOH 2008 David Ansell, Terry Feest, Andrew Williams, Chris Winearls (2008). UK Renal Registry Report 2008 Department for Communities and Local Government (2008); National Indicators for Local Authorities and Local Authority Partnerships: Hand book of Definitions. London, 2008 OH Department of Health (2002); Report on Asthma and Outdoor Air Pollution, http://www.advisorybodies.doh.gov.uk/COMEAP/statementsreports/airpol2.htm

JSNA LTCs Final Version

233


Department of Medicines Management, Keele University (2009); Asthma & COPD â&#x20AC;&#x201C; An Update Diabetes UK (2006); Position Statement Early Identification of people with type 2 diabetes, London, June 2006 DOH (2005); Supporting people with long term conditions, Department of Health, 2005 DOH (2007a); Raising the profile of Long Term conditions Care, Department of Health, 2007 DOH (2007b); Guidance on Joint Strategic Needs Assessment, Department of Health, 2007 Doll, R., Peto, R., Boreham, J. and Sutherland I. (2004); Mortality in relation to smoking: 50 years' observations on male British doctors. BMJ. 2004 Jun 26;328(7455):1519. Ehtisham W, Hattersley AT, Dunger DB, Barrett TG (2004), for the British Society for Paediatric Endocrinology and Diabetes Clinical Trials Group. First UK survey of paediatric type 2 diabetes and MODY. Arch Dis Child. 2004; 89: 526-529. Feltbower RG, McKinney PA, Campbell FM, Stephenson CR & Bodansky (2003). Type 2 and other forms of diabetes in 0-30 year olds: a hospital based study in Leeds, UK. Arch Dis Child, 2003;88:676-679 Haines L, Wan KC, Lynn R, Barrett TG, Shield JPH. (2007); Rising Incidence of Type 2 Diabetes in Children in the UK. Diabetes Care,2007;30:1097-1101 International Diabetes Federation (2003); IDF report, 2003 at www.idf.org/home/index.cfm Key Facts & Statistics, Asthma UK (Accessed 09/2009), http://www.asthma.org.uk Lambie M., N. Richards, and S. Smith. (2002) Ethnicity, age and incidence rates for renal replacement therapy. International Comparison of the Relationship of Chronic Kidney Disease Last.John.M. (2001) A Dictionary of Epidemiology, Oxford University Press 2001 Meyer JD, Holt DL, Chen DY, Cherry NM, MacDonald JC; SWORD (1999); Surveillance of work-related and occupation respiratory disease in the UK, Occupational Medicine (2001), 51(3): 204-8 NHS Clinical Knowledge Summaries: Asthma, Department of Health (Accessed 09/2009), http://www.cks.nhs.uk/asthma/evidence NICE (2004). The epilepsies: the diagnosis and management of the epilepsies in adults and children in primary and secondary care, 2004 Panico L, Bartley M, Marmot M, Nazroo JY, Sacker A, Kelly YJ (2007); Ethnic variation in childhood asthma and wheezing illnesses: findings from the Millennium Cohort Study, International Journal of Epidemiology (2007) Purcell.B, Gaitatzis.A, Sander.JW, Majeed A. (2002); Epilepsy Prevalence and

JSNA LTCs Final Version

234


prescribing patterns in England and Wales. ONS Health Statistics 2002 (24-31) Quality Outcomes Framework 2007/08: Data Tables, NHS Information Centre (Accessed 09/2009) Rasmussen F, Siersted HC, Lambrechtsen J, Hansen H, Hansen NG (2000); Impact of airway lability, atopy, and tobacco smoking on the development of asthma-like symptoms in asymptomatic teenagers, Chest (2000), 117(5): 1330-5 Rhys Williams and H Farrar (2007); University of Birmingham, Chapter 1 Diabetes Mellitus in University of Birmingham series of chapters resulting from the Health Care Needs Assessment project. Simpson. Ludi (2007); Projection on limiting long term illnesses in Birmingham, Manchester university, 2007 Stevens.PE, O’Donoghue.DJ, DeLusignan.S, Vlymen. J, Klebe.B, Middleton.R, Hague. N, New.J, Farmer.CKT. (2007); Chronic Kidney disease management in the United Kingdom: NEOERICA project results. Kidney Int. 2007 Jul;72(1):3-5. Upton MN, McConnachie A, McSharry C, Hart CL, Smith GD, Gillis CR, Watt GCM (2000); Intergenerational 20 year trends in the prevalence of asthma and hay fever in adults: the Midspan family study surveys of parents and offspring, British Medical Journal (2000), 321: 88-92 WHO (2002); Reducing Risks, Promoting Health Life. 2002 WHO (2003); Diet, nutrition and the prevention of chronic disease 2003 WHO (2003); The World Health Report, Today’s challenges, Geneva, WHO: www.who.int/whr/2003/en www.jointepilepsycouncil.org.uk YHPHO (2009); Statement on the PBS Diabetes Prevalence model – February 2009 Yorkshire and Humber Public Health Observatory (2008); PBS diabetes Model Phase 3 Technical Briefing document, accompanying release of the model in May 2008.

JSNA LTCs Final Version

235

PrevalenceStudyOnLongTermConditions_inBirmingham_Oct2009  

Yang Tian, Eric Jager, Chris Stephen, Hashum Mahmood, Jeanette Davis and Mohan Singh Date 30/10/09 File location (public) http://www.bhwp.nh...