Community Health Profiles 2020 Regional by Southern Plains Tribal Health Board

COMMUNITY HEALTH

Profile 2020

REGIONAL

Contents

Authors Moones Ackbaran Erin Spain

Executive Summary �� 1 Abstract �� 2 SPTHB Vision & Mission �� 2 Community Health Profile �� 3 Data Issues �� 4 Demographic Characteristics �� 5 Race �� 5 Age �� 7 Income �� 8 Unemployment �� 8 Educational Attainment �� 9-10 Poverty �� 11 Health Indicators �� 12 General Health �� 13 Tobacco Use �� 14 Depression �� 15 Alcohol Consumption �� 16 Influenza Immunizations �� 17 Access to Health Care �� 18 Heart Disease, Angina �� 19 Stroke �� 20 Asthma �� 21 Arthritis �� 22 Diabetes �� 23 Maternal and Child Health �� 24 Birth Weight �� 25-26 Gestational Age �� 27-28 Mother’s Age �� 29-30 Prenatal Care �� 31-32 Maternal Smoking Status �� 33-34 Infant Mortality �� 35-36 Mortality �� 37 Cancer �� 38-39 Diabetes �� 40-41 Major Cardiovascular Disease �� 42-43 Influenza and Pneumonia �� 44-45 Chronic Liver Disease and Cirrhosis �� 46-47 Accidents �� 48-49 Suicide �� 50-52 Data Resources �� 53-54 Behavioral Risk Factor Surveillance Survey �� 53 Centers for Disease Control and Prevention �� 53 Kansas Department of Health and Enviroment �� 53 March of Dimes �� 54 OK2SHARE �� 54 Oklahoma Vital Statistics �� 54 Texas Department of State Health Services �� 54 U.S. Census Bureau �� 54 Glossary �� 55-57 References �� 58-60

Executive Summary The SPTHB serves the largest Indian Health Service (IHS) user population area in the United States to serve the Oklahoma City area. The Southern Plains Tribal Health Board (SPTHB),

out certain functions on behalf

established in 1972, is a 501(c)(3) nonprofit

of the tribes they serve. The TECs’

organization. The SPTHB and the Oklahoma

seven core functions are to collect

Area Tribal Epidemiology Center (OKTEC) serve

data, evaluate data and programs,

44 federally recognized American Indian tribes

identify

in Kansas, Oklahoma, and Texas, as well as the

recommendations for health service

urban Indian health centers in Oklahoma City,

needs,

Tulsa, Wichita, Kansas City, and Dallas. The SPTHB

for improving health care delivery

serves the largest Indian Health Service (IHS) user

systems,

population area in the United States.

technical assistance to tribes and

health make

priorities,

make

recommendations

provide

epidemiologic

tribal organizations, and provide disease surveillance to tribes. These The OKTEC receives core funding from an IHS

core functions are performed in

Cooperative Agreement with the IHS Division of

consultation with and at the request

Epidemiology and Disease Prevention, which was

of the tribes we serve in our region.

established in 2004 to serve the Oklahoma City

The SPTHB and OKTEC strive to be

area. With the passage of the Affordable Care Act,

the most influential and proactive

including the Indian Health Care Improvement

public health advocates for positive

Act in 2010, TECs were designated public health

American Indian/Alaska Native (AI/

authorities for tribes and are mandated to carry

AN) health outcomes.

Abstract The

SPTHB

Vision and

OKTEC

developed

this

The SPTHB and OKTEC aim to be

Community Health Profile (CHP) to describe the

the most influential and energetic

current health status of AIs/ANs that reside within

public health advocates of AIs/ANs

tribal boundaries. The CHP provides basic health

in Kansas, Oklahoma, and Texas. The

information along with baseline data to compare

OKTEC is dedicated to the principle

the current health of the community to that

that all AI/AN people, regardless of

of the state. The profile includes demographic

geography, economics, or culture,

indicators, health indicators, general health, and

deserve the benefits of quality health

mortality statistics that can help identify health

care and good health.

issues and disparities that affect the community.

Mission The CHP can be used as a tool, informational guide,

and

resource

for

writing

grants

developing health initiatives. The information provided can be used to prioritize health issues, set goals, compare future trends, and monitor progress on improving health and eliminating health disparities in the community.

The mission of the SPTHB is to improve the health of AIs/ANs in Kansas, Oklahoma, and Texas by providing public health services in epidemiology, data management, analysis, training, health promotion/ disease prevention, and research through

outreach

partnerships.

and

creative

Community Health Profile 1. What is a CHP? A CHP describes the current health status of a community and provides an accurate picture of the health status of a specific region or community. It is a collection of data related to a specific population that describes all aspects of the community and identifies disparities between the selected community and a standard or comparison group. A CHP shows the background, health status, and risk factors of a group or population within a local area. 2. What does a CHP include? A CHP provides basic health information with baseline data to compare the current health of the community to that of a comparison population. It can include many variables, such as demographic characteristics (race, age, income, educational attainment, unemployment status, and location), health indicators, mortality statistics (death), natality (birth), mental health, and health disparities (differences in health among groups of people). 3. Who is included within AI/AN data? These data include any person who self-reported their race as AI/AN. The designation as the tribe or nation’s AI/AN population does not include members of the tribe or nation only, but also includes members of other tribes or nations and those not enrolled with a tribal nation. 4. What data sources are utilized? The data sources are the Oklahoma Behavioral Risk Factor Surveillance Survey (Oklahoma BRFSS); Centers for Disease Control and Prevention (CDC) Web Enabled Analysis Tool (WEAT); CDC Wide-ranging Online Data for Epidemiologic Research (WONDER); U.S. Census Bureau; and Oklahoma Prevention Needs Assessment (OPNA). 5. How can the CHP be used to beneﬁt the tribe or nation? The information can be used to prioritize health issues, for setting goals for policy development, as a resource for writing grants, and for public health decision-making. It may be utilized as a reference to compare future trends and to monitor progress on improving health and eliminating health disparities in the community.

Data Issues Data necessary to compile a community health profile come from federal, state, and local agencies. Natality (birth) and mortality (death) prevalence data for individual tribes and tribal nations were not available in most instances. • American Indian only, non-Hispanic data includes any person who self-reported their race in the CDC BRFSS. • The Behavioral Risk Factor Surveillance System (BRFSS) data is a cross-sectional telephone survey that state health departments conduct with technical and operational assistance from the CDC WEAT online tool and is also self-reported information.

Demographic Characteristics Demographic characteristics are descriptive data that refer to population characteristics, which provide information to assist in evaluation of community health status. Commonly used demographic data include race, age, income, educational attainment, unemployment status, and location. Distributions of values within a demographic variable and across households are both of interest, as well as trends over time. Demographic trends describe the changes in demographics in a population over time.

Race The majority of the distribution between the three states consisted of those identifying as white: 72.4% in Oklahoma, 84.6% in Kansas, and 74.3% in Texas. American Indians/Alaska Natives were a minority in all three states, specifically with 7.5% in Oklahoma, 0.8% in Kansas, and 0.5% in Texas.

Figure 1

2014–2018 Distribution of Race in Oklahoma Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Figure 2

2014–2018 Distribution of Race in Kansas Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Figure 3

2014–2018 Distribution of Race in Texas Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Figure 4

2014–2018 Distribution of Race in the United States of America Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Age According to many definitions, the elderly population is those who are older than 65 years old. The growing elderly population has many implications in planning for the future, including economic growth and public health. There are implications in planning for the younger population, while the elderly requires special attention that many are not prepared for individually or as a community.1 The AI/AN population for all three states had smaller percentages of elderly people compared to the white populations. The largest group for AI/AN people was ages 5–34. Whites were more evenly spread with a small increase in percentage in ages 65 years and older.

Table 1

Age Distribution by Gender (2014–2018) Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey Oklahoma White Total population Total male population <5

Count

Kansas AI/AN

Percent

2,837,772

Count

Texas

White

Percent

294,676

Count

AI/AN Percent

2,460,619

Count

Percent

24,050

White Count

AI/AN Percent

20,720,689

Count

Percent

136,061

1,402,880

49.4%

144,265

49.0%

1,220,138

49.6%

11,698

48.6%

10,309,847

49.8%

69,745

51.3%

85,766

3.0%

10,954

3.7%

78,983

3.2%

607

2.5%

738,270

3.6%

4,247

3.1%

5 to 14

175,537

6.2%

24,992

8.5%

163,875

6.7%

1,834

7.6%

1,501,430

7.2%

9947

7.3%

15 to 24

182,914

6.4%

25,948

8.8%

173,699

7.1%

1,935

8.0%

1,476,062

7.1%

11711

8.6%

25 to 34

191,757

6.8%

21,081

7.2%

160,398

6.5%

1,839

7.6%

1,497,534

7.2%

10,336

7.6%

35 to 44

175,633

6.2%

17,591

6.0%

148,408

6.0%

1,686

7.0%

1,372,438

6.6%

10,492

7.7%

45 to 54

179,907

6.3%

16,645

5.6%

151,994

6.2%

1,577

6.6%

1,305,559

6.3%

8,569

6.3%

55 to 64

187,871

6.6%

14,441

4.9%

161,938

6.6%

1,286

5.3%

1,177,661

5.7%

7,987

5.9%

65 +

223,495

7.9%

12,613

4.3%

180,843

7.3%

934

3.9%

1,240,893

6.0%

6,456

4.7%

1,434,892

50.6%

150,411

51.0%

1,240,481

50.4%

12,352

51.4%

10,410,842

50.2%

66,316

48.7%

80,981

2.9%

11,373

3.9%

75,722

3.1%

557

2.3%

701,497

3.4%

4,051

3.0%

5 to 14

167,274

5.9%

24,946

8.5%

157,483

6.4%

1,689

7.0%

1,442,972

7.0%

9,420

6.9%

15 to 24

171,103

6.0%

24,418

8.3%

160,881

6.5%

2,516

10.5%

1,397,264

6.7%

10,718

7.9%

25 to 34

186,939

6.6%

21,053

7.1%

154,370

6.3%

1,578

6.6%

1,440,075

6.9%

9,841

7.2%

35 to 44

171,869

6.1%

18,567

6.3%

145,323

5.9%

1,632

6.8%

1,350,521

6.5%

9,144

6.7%

45 to 54

180,883

6.4%

17,260

5.9%

152,903

6.2%

1,801

7.5%

1,315,051

6.3%

8,820

6.5%

55 to 64

198,772

7.0%

16,623

5.6%

169,404

6.9%

1,242

5.2%

1,239,202

6.0%

7,293

5.4%

65 +

277,071

9.8%

16,171

5.5%

224,395

9.1%

1,337

5.6%

1,524,260

7.4%

7,029

5.2%

Total female population <5

Income Although employment in general is a good indicator of whether a person has better access to health care, those who are below the poverty level are less likely to use or have health care. Cutting income inequality is likely to improve health outcomes and a population’s wellbeing. Measuring income will help plan what resources and programs a community might need.2 According to government guidelines, the poverty level for 2020 is $26,200.3 American Indians/Alaska Natives had lower median incomes across the nation and in all states. The national median income for AIs/ANs was the lowest ($41,879), along with the highest white median income ($63,917) when compared to the three-state region

Figure 5

Median Household Income in the Past 12 Months (in 2018 InflationAdjusted Dollars) in 2014– 2018, by Geographical Area and Race Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Unemployment Knowing employment gives data on the “economic” aspect of socioeconomic characteristics. Socioeconomic data is important because it provides general data on a specific population. Employment also usually indicates a better means to spend on doctor visits and more healthy choices.4 The unemployment rate for AI/AN was highest when looking at the nation altogether (11.2%) and was the lowest for Texas (7.3%). White unemployment differences stayed within 1% even when looking between states and the nation as a whole.

Figure 6

Percent with Unemployment Status (16 Years and Older) in 2014–2018, by Geographical Area and Race Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Educational Attainment Educational attainment is a demographic measure influencing multiple aspects of a family or individual, including employment and income. Education also is associated with health and wellness. Public health efforts ultimately promote education and increase knowledge even if on just a single topic, but measuring what level of educational attainment a person has can also suggest reasoning ability, self-regulation, and interactional abilities.5, 6 Figures 7–9 represent people who may have a high school degree as well as a secondary education degree. The bar graphs will add up to over 100%. The individual bars represent the percentage of people who reported having the specific educational attainment, meaning there are some people who have both a high school degree and a secondary degree. Oklahoma had the highest percentage of AI/AN education attainment of a secondary degree (26.6%) as well as when looked at by gender: 26.3% for males and 26.9% for females. As a nation, whites had almost double the percentage of who had a bachelor’s degree or more (32.9%) than AI/AN (14.5%).

Figure 7

Percent of Overall Total Educational Attainment in 2014–2018, by Geographical Area and Race Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Figure 8

Percent of Male Educational Attainment in 2014–2018, by Geographical Area and Race Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Figure 9

Percent of Female Educational Attainment in 2014–2018, by Geographical Area and Race Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Poverty Many factors are linked to poor health and poverty is among them. Life expectancy increases as people are in higher income distribution brackets. Men at a higher income level live almost 15 years longer than men with a lower income. Low-income individuals also have a greater tendency to participate in behavioral risk factors, such as substance use, smoking, and poor nutrition choices. Many minorities are increasingly in households that live under the poverty line.7 The percent of AI/AN in poverty was higher for the whole nation (25.8%) than the three states. Texas had the lowest percent of AI/AN in poverty (17.9%). Poverty percentages for both races were different for each state as well.

Figure 10

Percent in Poverty Reported in the Past 12 Months in 2014–2018, by Geographical Area and Race Source: U.S. Census Bureau, 2014–2018 5-Year American Community Survey

Health Indicators Why are health indicators important? Healthy People 2020 Leading Health Indicators describe individual behaviors, physical and social environmental factors, and important health system issues that affect the health of individuals and communities. The health indicators evaluated in this CHP are the following: • General health • Tobacco use • Depression • Alcohol consumption • Immunization for influenza • Access to health care • Heart disease and agina • Stroke • Asthma • Arthritis • Diabetes

General Health The Behavioral Risk Factor Surveillance Survey (BRFSS) is an annual survey the CDC uses to measure the health risk behaviors among adult U.S. citizens through surveys. The responses are used to provide useful data for public health research and local health policy decisions. When looking at the combined data for Oklahoma, Kansas, and Texas, AIs/ANs had a higher percentage of people reporting fair or poor health (25.4%) than whites (16.7%). Texas had the highest percentage of AIs/ANs who reported having good or better health (76.1%). Kansas had the widest difference between AIs/ANs and whites in health status.

Figure 11

Percent of People Who Reported on Their General Health in 2015–2018, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Would you say that in general your health is: excellent, very good, good, fair, poor)

Figure 12

Percent of People Who Reported on Their General Health in 2015–2018, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Would you say that in general your health is: excellent, very good, good, fair, poor)

Tobacco Use Smoking and tobacco use are still prevalent. However, AIs/ANs are more likely than whites to use quitlines and take council to get help. Among those who received counseling, AIs/ ANs had greater odds than white smokers of attempting to quit.8 The CDC reports that commercial tobacco use remains the leading preventable cause of death in the United States. Commercial tobacco causes approximately 480,000 premature deaths each year and results in an annual cost for the United States of more than $300 billion USD (including medical bills and lost productivity).9 Combined or individually by state, AIs/ANs had a higher percentage of people report that they were current, everyday smokers than whites. Kansas had a greater percentage of AIs/ ANs who were former smokers (27.9%) than whites (25.8%), but the other states had a smaller percent of AIs/ANs who were former smokers.

Figure 13

Percent of People Who Reported on Their Smoking Status in 2015–2018, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Calculated smoking status, four-level status: every day smoker, some days smoker, former smoker, never smoked)

Figure 12

Percent of People Who Reported on Their Smoking Status in 2015–2018, by Geographical Area and Race * 0% indicates insufficient sample and/or statistically unreliable estimate. Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Calculated smoking status, four-level status: every day smoker, some days smoker, former smoker, never smoked).

Depression There is the phrase “mind over matter” for people who are struggling through hard times, but what happens if the mind is sick? The proportions of people with anxiety and depression have higher changes of having additional diseases, other mental health disorders as well as physical diseases. Anxiety might be a strong marker for the risk of major depressive disorder onset. Mental health is an important component of an individual’s overall wellness as well as a community’s health.10 In the combined region, 26.8% of AIs/ANs reported having been diagnosed with some depressive disorder. That is, over one in every four AI/AN individuals had some diagnosis of a depressive disorder. Kansas had the highest percentage with 30.2% and Texas had the lowest with 23.8%.

Figure 15

Percent of People in 2015–2018 Who Reported Having a Depressive Disorder Diagnosis, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you have a depressive disorder, including depression, major depression, dysthymia, or minor depression?)

Figure 16

Percent of People in 2015–2018 Who Reported Having a Depressive Disorder Diagnosis, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you have a depressive disorder, including depression, major depression, dysthymia, or minor depression?)

Alcohol Consumption There is a gap of culturally appropriate drug and alcohol prevention programs, especially for the AIs/ANs who reside in urban areas where a tribal organization is not close by to support individuals. Programs that have traditional practices such as traditional cooking, beading, and prayer ceremonies are helpful in reducing substance use problems. 11 If in one occasion men have five or more drinks, or women have four or more drinks, it is considered binge or heavy drinking. There were smaller percentages of AIs/ANs who reported large numbers of drinks in one occasion in every location or region, except for Texas, where 21.4% of AIs/ANs self-reported binge drinking compared to 17.0% of whites.

Figure 17

Percentage of People Who Reported Heavy Alcohol Use in 2015–2018, for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 201–2018 (Calculated variable for binge drinkers, men having +5 drinks on one occasion and women having +4 drinks on one occasion)

Figure 18

Percentage of People Who Reported Heavy Alcohol Use in 2015–2018, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Calculated variable for binge drinkers, men having +5 drinks on one occasion and women having +4 drinks on one occasion)

Influenza Immunizations Influenza and pneumonia greatly impact the world every year. The annual economic impact is between $6 and $11 billion USD in the United States.12 Most strategies include getting the vaccine to those who are most vulnerable before the flu season starts. Multiple cause-ofdeath tracking has shown that more deaths are contributed to the flu and pneumonia than are given credit as the cause of death. Many populations are at risk for becoming very ill or dying from flu and pneumonia.13 All locations and geographies had lower percentages of AIs/ANs who had received a flu shot compared to whites. Texas had the lowest percent of AIs/ANs who had received a flu shot (32.6%), while Oklahoma had the highest (42.6%).

Figure 19

Percent of People Older Than 18 Years Who Reported in 2015–2018 Getting the Flu Shot or Spray in the Last 12 Months, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Had a flu shot/spray in the past 12 months)

Figure 20

Percent of People Older Than 18 Years Who in 2015–2018 Reported Getting the Flu Shot or Spray in the Last 12 Months, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Had a flu shot/spray in the past 12 months)

Access to Health Care Health service access is important for everyone. However, many AIs/ANs are not eligible for Indian Health Services (HIS) for a variety of reasons, such as not being born to a federally recognized tribe or they live too far away from IHS services. IHS’s role in providing access to services is vital, but the large disparities that linger in socioeconomic conditions for AIs/ANs when compared to whites make it hard for individuals to get insurance.14 A majority of both white and AI/AN individuals had access to health care services in all locations and geographies. Oklahoma had the highest percentage of AI/AN people who reported having access to health care (94.0%). Kansas had the fewest AI/AN individuals who reported having access to health care (82.0%).

Figure 21

Percent of People Ages 18–64 Who, in 2015–2018, Reported Any Type of Health Care Coverage, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015-2018 (Calculated variable for adults aged 18–64 who had any form of health care coverage)

Figure 22

Percent of People Ages 18–64 Who, in 2015–2018, Reported Any Type of Health Care Coverage, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Calculated variable for adults aged 18–64 who had any form of health care coverage)

High Cholesterol Heart Disease, Angina Angina is a type of heart disease that causes pain in the chest due to reduced blood flow to the heart. This reduced blood flow can result from plaque buildup. During times of rest, the heart muscle may be able to work with the reduced blood flow without starting any symptoms, but as demand for blood increases, such as during times of exercise, angina can result. There are risks that increase a person’s chance of getting angina. Some of those risks include smoking, diabetes, high blood pressure, a family history of heart disease, and lack of exercise. Preventing or reducing risk includes quitting smoking, eating well, maintaining a healthy weight, reducing stress levels, and getting an annual flu shot to avoid heart complications from the virus.15 When comparing AIs/ANs and whites for angina cases, the percentage of people who reported having it were very similar. Texas ‘s sample size was too small to have representative data for AI/AN. For the combined three states, the white population had 5.0% and the AI/ AN population had 5.1%. Angina is fairly similar between races.

Figure 23

Percent of People Who Reported Ever Having Angina in 2015–2018, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you had angina or coronary heart disease?)

Figure 24

Percent of People Who Reported Ever Having Angina in 2015–2018, by Geographical Area and Race * 0% indicates insufficient sample and/or statistically unreliable estimate. Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you had angina or coronary heart disease?)

High Blood Pressure Stroke Stroke is a disease that affects the arteries in and around the brain. A stroke occurs when a blood clot causes blood loss in the brain or a part of the brain. Long-term disability from these stroke events can incite a multitude of issues beyond the initial event. There are persistent consequences with some individuals who never fully gain all functioning again. Avoiding behaviors that increase the risk of stroke is the best course of action. Like most other health situations, behaviors that prevent the risk of stroke include quitting smoking, regular physical activity, and eating a healthy diet.16 Stroke occurrences in Oklahoma were similar between the two races (4.5% and 4.7%), but Kansas and Texas had a larger difference. The combined three states also had similar percentages between races (5.0% and 5.1%). Texas had the highest percentage of AIs/ANs who had a stroke (7.1%), while Oklahoma had the smallest (4.7%).

Figure 25

Percentage of People Who Reported Ever Having a Stroke in 2015–2018, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you had a stroke?)

Figure 26

Percentage of People Who Reported Ever Having a Stroke in 2015–2018, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you had a stroke?)

High Cholesterol Asthma Asthma is often a childhood condition, but can just as often persist into adulthood. Children with asthma are often in a lower socioeconomic status and have many environmental influences, especially in AI/AN children. There is an opportunity for research to explore efforts that lessen environmental pollutants, including indoor and outdoor pollutants, for reducing asthma cases. Reducing the severity of childhood asthma will also help reduce the number of adults with asthma.17, 18 In Oklahoma, 12.2% of AIs/ANs had asthma at the time of the interview. Kansas and Texas had higher percentages of current asthma among the AI/AN population than Oklahoma, though they were similar to each other (18.1% and 18.2%, respectively). In the combined states area, 14.7% of AIs/ANs had asthma compared to the 9.1% of whites who had asthma.

Figure 27

Percent of People Who Reported Currently Having Asthma in 2015–2018, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Do you still have asthma?)

Figure 28

Percent of People Who Reported Currently Having Asthma in 2015–2018, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Do you still have asthma?)

High Blood Pressure Arthritis Arthritis refers to joint inflammation and cartilage breakdown. When the amount of cartilage is reduced, the joint bones rub together, which causes pain, swelling, and stiffness. There are many forms of arthritis and they can occur at all ages. The most common form of arthritis is osteoarthritis, or degenerative joint disease. Risk factors for arthritis include being overweight or obese, previous injury to the joint, and repetitive action that stresses the joint.19 Programs for addressing arthritis should include cultural values and emphasize holistic wellness and social interconnectedness. AI/AN elders have better response to programs that include indigenous values promoting active handling of arthritis symptoms. 20 For the combined area of the three states, 32.0% of AIs/ANs had ever been told they had some form of arthritis. Texas had the greatest percentage of AIs/ANs with arthritis (37.3%), while Oklahoma had the smallest (28.6%). Oklahoma was also the only state where whites had a greater percentage (30.6%) than AIs/ANs (28.6%).

Figure 29

Percent of People Who Reported Ever Being Diagnosed with Arthritis in 2015–2018, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you have some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia?)

Figure 30

Percent of People Who Reported Ever Being Diagnosed with Arthritis in 2015–2018, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you have some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia?)

High Cholesterol Diabetes Most AIs/ANs have had some type of diabetes education, but that has not always adapted into self-care behaviors. Alongside more western medicine practices, there are many traditional healing methods that can help. Programs need to emphasize or at least incorporate traditional methods to reach the greatest effectiveness. Preventing diabetes is the best goal for individuals, but there are ways to manage diabetes and still live a comfortable life. Preventative actions for diabetes include checking blood glucose levels, daily foot checks, eye doctor appointments to have the eyes dilated, and to have five daily servings or more of fruits and vegetables.21 AIs/ANs had greater percentages of people who had been told they had diabetes than whites in every geographical area of comparison. Kansas had the smallest percentage of AIs/ANs who had diabetes (12.2%). Oklahoma and Texas had similar percentages of AIs/ ANs that had diabetes (17.0% and 17.4%, respectively).

Figure 31

Percentage of People Reporting Having Been Told They Have Diabetes in 2015–2018, by Race for OK, KS, and TX Combined and the United States of America Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you have diabetes?)

Figure 32

Percentage of People Reporting Having Been Told They Have Diabetes in 2015–2018, by Geographical Area and Race Source: Behavioral Risk Factor Surveillance System, CDC WEAT 2015–2018 (Have you ever been told you have diabetes?)

Maternal and Child Health A mother’s health greatly affects the health of her children. Women who start prenatal care soon after they become pregnant, and continue until they have their baby, usually have fewer problems and healthier babies. Topics associated with maternal and child health are included in this profile: • birth weight • gestational age at time of birth • mother’s age • prenatal care • maternal smoking • infant mortality

High Cholesterol Birth Weight There are many health effects and factors that are linked to low birth weight. Some of the most concerning maternal influences on the infant’s weight are smoking during pregnancy, gestational diabetes, and age. Even though there are many medical advancements that could prevent lasting damage, there are still many severe morbidity and mortality outcomes. Severe outcomes can include sudden infant death syndrome (SIDS), slow development, high infection rates, and higher likelihood of injury.22 There were similarities between whites and AIs/ANs in terms of birth weight. Most births were at the normal weight for both races. In the combined states area, there were more infants being born at a high birth weight (9.8%) than whites (7.4%).

Table 2

Birth Weight Distribution for OK, KS, and TX Combined and the United States of America (2015–2018) Source: CDC WONDER, 2015–2018 Combined three states Mother's race

AI/AN

White

Birth weight Very low (< 1500 grams) Low (1500– 2499 grams) Normal (2500– 3999 grams) High (≥ 4000 grams) Very low (< 1500 grams) Low (1500– 2499 grams) Normal (2500– 3999 grams) High (≥ 4000 grams)

United States of America

Live births

% Live births

Live births

% Live births

249

1.3%

2,322

1.4%

1,096

5.7%

11,277

6.6%

16,031

83.1%

141,203

82.1%

1,894

9.8%

16,962

9.9%

13,524

1.2%

129,358

1.1%

69,548

6.2%

693,418

6.0%

947,778

85.0%

9,783,982

84.0%

82,991

7.4%

1,034,926

8.9%

Table 3

Birth Weight Distribution for OK, KS, and TX Combined and the United States of America (2015–2018) *Calculations may be suppressed due to small sample size. Source: CDC WONDER, 2015–2018

Mother's race

AI/AN

White

Birth weight Very low (< 1500 grams) Low (1500–2499 grams) Normal (2500 3999 grams) High (≥ 4000 grams) Very low (< 1500 grams) Low (1500–2499 grams) Normal (2500– 3999 grams) High (≥ 4000 grams)

Oklahoma % Live Live births births

Kansas

Texas

Live births

% Live births

Live births

% Live births

181

1.2%

893

5.8%

6.2%

12,768

83.1%

169

84.9%

932

83.4%

1,511

9.8%

102

9.1%

1,367

1.3%

355

1.1%

3,570

1.2%

6,559

6.1%

1,756

5.7%

18,991

6.3%

90,504

84.3%

26,037

84.1%

255,897

85.3%

8,899

8.3%

2,781

9.0%

21,424

7.1%

High Blood Pressure Gestational Age Being born too early is another risk factor for health problems immediately at birth and later in life. Regular gestation is between 39 and 41 weeks. Births before 36 weeks have especially high risks of having complications and illness. Even births postterm (42 weeks or longer) have complications that put mother and infant at risk. Maintaining healthy habits during pregnancy help reduces the chance of a preterm birth, such as healthy diet and weight, exercise, avoiding all alcohol, and quitting smoking before getting pregnant. Low birth weight is usually an indicator of not being fully developed and the most common issues after birth are respiratory disorders.23 The majority of births happened at a healthy time for both races. There wasn’t any distinct difference between AIs/ANs and whites when it came to gestational age. Kansas and Texas had such a small sample of AI/AN births that the calculation was not reliable for many categories of gestation time.

Table 4

Gestational Age Distribution for OK, KS, and TX Combined and the United States of America (2015–2018) Source: CDC WONDER, 2015–2018 Combined three states Mother's race

AI/AN

White

United States of America

Gestation age

Live births

% Live births

Live births

% Live births

< 32 weeks

293

1.5%

1,875

1.7%

32–36 weeks

1,758

9.1%

10,650

9.6%

37–39 weeks

13,354

69.3%

70,673

64.0%

40–41 weeks

3,816

19.8%

26,826

24.3%

42+ weeks

0.2%

347

0.3%

< 32 weeks

16,075

1.4%

110,148

1.3%

32–36 weeks

96,252

8.6%

672,521

7.9%

37–39 weeks

763,896

68.5%

5,355,668

63.0%

40–41 weeks

234,199

21.0%

2,327,146

27.4%

42+ weeks

3,484

0.3%

30,027

0.4%

Table 5

Gestational Age Distribution (2015–2018) *Calculations may be suppressed due to small sample size. Source: CDC WONDER, 2015–2018

Mother's race

Gestation age < 32 weeks

AI/AN

White

Oklahoma Live % Live births births 224 1.5%

Live births *

Kansas % Live births *

Live births *

Texas

% Live births *

32–36 weeks

1,417

9.2%

7.9%

37–39 weeks

10,715

69.8%

138

69.3%

772

69.1%

40–41 weeks

2,960

19.3%

240

21.5%

42+ weeks

0.2%

< 32 weeks

1,577

1.5%

394

1.3%

4,243

1.4%

32–36 weeks

9,853

9.2%

2,451

7.9%

26,565

8.9%

37–39 weeks

75,324

70.1%

20,655

66.7%

208,777

69.6%

40–41 weeks

20,317

18.9%

7,339

23.7%

59,432

19.8%

42+ weeks

264

0.2%

0.3%

884

0.3%

High Cholesterol Mother’s Age The age of not only the infant at birth matters, but also the mother’s age can make a difference. Extreme age, both young and old, increases the chances of health complications for the infants and mothers. There are compounding factors with maternal age, such as education and socioeconomic status, that influence the infants’ health outcome. Study results showed that younger mothers under 18 years old had worse health outcomes than those parents who waited a couple of years.24 The majority of births happen between ages 20–35 for both races. AIs/ANs have the most births at a slightly younger age than whites in all geographies, except when looking at the nation as a whole.

Table 6

Birth Distribution by Maternal Age for OK, KS, and TX Combined and the United States of America (2015–2018) *Calculations may be suppressed due to small sample size. Source: CDC WONDER, 2015–2018 Combined states Live births % Live births

Mother’s race Under 15 years

AI/AN

White

United States of America Live births % Live births

0.1%

132

0.1%

1,919 6,103 5,892 3,680 1,412 245

10.0% 31.6% 30.6% 19.1% 7.3% 1.3%

10,675 31,086 33,467 22,399 10,554 2,183

9.7% 28.1% 30.3% 20.3% 9.5% 2.0%

45–49 years

0.1%

106

0.1%

50 years and over Under 15 years 15–19 years 20–24 years 25–29 years 30–34 years 35–39 years 40–44 years

* 888 79,433 258,660 331,022 284,028 132,120 26,673

* 0.1% 7.1% 23.2% 29.7% 25.5% 11.9% 2.4%

6 3,339 402,842 1,629,987 2,493,413 2,481,926 1,226,064 245,324

0.0% 0.0% 4.7% 19.2% 29.3% 29.2% 14.4% 2.9%

45–49 years

1,578

0.1%

17,117

0.2%

50 years and over

0.0%

1,627

0.0%

15–19 20–24 25–29 30–34 35–39 40–44

years years years years years years

Table 7

Birth Distribution by Maternal Age (2015–2018)*Calculations may be suppressed due to small sample size. Source: CDC WONDER, 2015–2018

Mother's race

Mother's age Under 15 years

AI/AN

White

Oklahoma % Live Live births births 16 0.1%

Kansas

% Live births *

Live births *

Live births

Texas

% Live births *

15–19 years

1,609

10.5%

5.0%

7.4%

20–24 years

5,064

33.0%

31.2%

286

25.6%

25–29 years

4,758

31.0%

29.6%

334

29.9%

30–34 years

2,771

18.0%

23.6%

258

23.1%

35–39 years

976

6.4%

7.0%

129

11.5%

40–44 years

165

1.1%

2.1%

45–49 years 50 years and over Under 15 years

0.1%

242

0.1%

15–19 years

7,183

6.7%

1,526

4.9%

20,795

6.9%

20–24 years

26,881

25.1%

6,525

21.1%

67,624

22.5%

25–29 years

34,284

32.0%

9,833

31.8%

88,431

29.5%

30–34 years

26,629

24.8%

8,724

28.2%

76,729

25.6%

35–39 years

10,394

9.7%

3,675

11.9%

37,733

12.6%

40–44 years

1,828

1.7%

616

2.0%

7,885

2.6%

45–49 years 50 years and over

0.0%

0.1%

494

0.2%

0.0%

High Blood Prenatal Care Pressure Prenatal care is important to the mother’s and the infant’s health. The child’s development can be enhanced by the attention and medicine provided through that care. Women who don’t get prenatal care or those who delay getting attention are more likely to have adverse outcomes in pregnancy and birth, such as preterm birth, low birthweight, or birth defects. Prenatal care is another way to address problems that initially may not be obvious. AIs/ ANs are more likely to have birth defects than whites, namely underdeveloped ears (anotia or microtia). Although not always detectable before birth, care while still in the womb encourages more complete development.25, 26 Most mothers for both races received prenatal care in the first trimester, for all geographies. There were more AI/AN mothers who waited until the second trimester (22.3%) than whites (19.6%) in the combined states area. Texas had the most who had no prenatal care during pregnancy for both races (4.2% and 3.0%, respectively). Oklahoma had the highest percentages of AI/AN live births that had prenatal care only in the third trimester (7.0%) out of the three states.

Table 8

Prenatal Care Distribution for OK, KS, and TX Combined and the United States of America (2015–2018) Source: CDC WONDER, 2015–2018

Combined three states Mother's race

AI/AN

White

United States of America

Prenatal care

Live births

% Live births

Live births

% Live births

No prenatal care

167

2.7%

3,760

3.5%

1st trimester

4,232

69.7%

68,321

63.6%

2nd trimester

1,352

22.3%

25,978

24.2%

3rd trimester

403

6.6%

9,394

8.7%

No prenatal care

9,747

2.7%

118,909

1.4%

1st trimester

261,504

73.4%

6,609,099

79.6%

2nd trimester

69,856

19.6%

1,251,348

15.1%

3rd trimester

19,261

5.4%

325,538

3.9%

Table 9

Prenatal Care Distribution (2015–2018) *Calculations may be suppressed due to small sample size. Source: CDC WONDER, 2015–2018

Mother's race

Prenatal care No prenatal care

AI/AN

White

Oklahoma % Live Live births births 348 2.3%

Kansas % Live Live births births * *

Texas Live % Live births births 47 4.2%

1st trimester

10,570

68.8%

136

68.3%

696

62.3%

2nd trimester

3,123

20.3%

24.1%

284

25.4%

3rd trimester

1,072

7.0%

6.8%

No prenatal care

1,694

1.6%

294

1.0%

8,957

3.0%

1st trimester

80,168

74.7%

26,007

84.0%

208,943

69.7%

2nd trimester

18,352

17.1%

3,623

11.7%

60,509

20.2%

3rd trimester

4,773

4.4%

821

2.7%

16,866

5.6%

High Cholesterol Maternal Smoking Status Smoking while pregnant can have devastating impacts on the infant’s and mother’s health. Even secondhand smoke influences health. There are many effects of smoking and especially smoking while pregnant. The impacts of maternal smoking can be immediate and glaring to delayed and subtle. For example, childhood obesity is a slightly delayed effect of smoking while pregnant. An immediate problem of maternal smoking might be the infant’s underdeveloped lungs and brain, which can cause critical complications at birth. According to a National Center for Health Statistics data brief published in 2018, AIs/ ANs have the highest prevalence out of any race of smoking while pregnant. This very likely has contributed to the AI/AN high infant mortality. 27, 28 In some areas, AI/AN mothers reported almost double the percentage of maternal smoking. In the combined three states, AIs/ANs had 12.4% of mothers who smoked while pregnant, while whites only had 4.2%. Kansas had the highest percent of AI/AN mothers who smoked (18.6%) and Texas had the smallest (4.5%).

Table 10

Maternal Smoking Status for OK, KS, and TX Combined and the United States of America (2015–2018) Source: CDC WONDER, 2015–2018 Combined three states

United States of America

Mother's race

Smoking status

Live births

% Live births

Live births

% Live births

AI/AN

Mom smoked while pregnant

774

12.4%

15,785

14.4%

Mom did not smoke

5,437

87.1%

93,458

85.6%

Mom smoked while pregnant

15,241

4.2%

641,059

7.6%

Mom did not smoke

350,601

95.8%

7,823,055

92.4%

White

Table 11

Maternal Smoking Status (2015–2018) Source: CDC WONDER, 2015–2018

Mother's race

Smoking status

AI/AN

Mom smoked while pregnant

White

Oklahoma Live % Live births births

Kansas Live % Live births births

Texas Live % Live births births

2,188

14.2%

18.6%

4.5%

Mom did not smoke

13,099

85.3%

161

80.9%

1,068

95.5%

Mom smoked while pregnant

11,877

11.1%

2,954

9.5%

8,603

2.9%

Mom did not smoke

95,444

88.9%

27,904

90.2%

291,299

97.1%

Prenatal High Infant Blood Mortality Care Pressure Infant mortality is a standard health measurement that assists in evaluating the overall health of a community, population, or nation. Usually high infant mortality indicates poor health within that measured population or community. AIs/ANs have higher risks of SIDS and accidental death before the age of 1, particularly when compared to whites. Congenital malformations (birth defects developed in the womb) are the most common infant death for all races.29 Infant mortality rates can be improved by addressing maternal behaviors during pregnancy, getting prenatal care early in pregnancy, creating safe sleep and living areas for the infant, as well as changing societal challenges. Infant mortality can be reduced and even prevented with purposeful intervention.30 Infant death rates for the combined three states were higher for AIs/ANs (8.6 per 1,000) than whites (5.4 per 1,000). Kansas and Texas had too few AI/AN infant deaths to make reliable mortality rates.

Table 12

Infant Mortality Rates for OK, KS, and TX Combined and the United States of America (2015–2017) **Per 1,000 Source: CDC WONDER, 2015–2017 United States of America

Combined three states Mother's race

Infant death

Births

Death rate*

Infant death

Births

Death rate*

AI/AN

6,313

8.6

1,089

129,770

8.4

White

1,974

364,948

5.4

43,287

8,816,670

4.9

Table 13

Infant Mortality Rates by Race in Oklahoma (2015–2017) **Per 1,000 Source: CDC WONDER, 2015–2017 Kansas Mother’s race

Deaths

Death rate**

AI/AN

14.4

White

777

5.0

Table 14

Infant Mortality Rates by Race in Kansas (2014 –2018) **Per 1,000 Source: Kansas Vital Statistics, Kansas Health Department, 2014–2018 Kansas Mother’s race

Deaths

Death rate**

AI/AN

14.4

White

777

5.0

Table 15

Infant Mortality Rates by Race in Texas (2015–2017) *Calculations may be suppressed due to small sample size **Per 1,000 Source: CDC WONDER, 2015–2017

Texas Mother's race

Infant death

Births

Death rate**

AI/AN

1,010

White

1,557

298,596

5.2

Mortality Mortality rate refers to the number of deaths in a certain population over a given period. A mortality rate can be expressed as the number of deaths for a certain disease, a specific region, or a specific population, such as an age group or racial group.

Top 10 Causes of Death for Male AIs/ANs and White Male U.S. Citizens for 201731 *Percentages displayed represent total deaths in the age group due to the cause indicated.

AI/AN

White

1. Heart disease (19.4%)

1. Heart disease (24.7%)

2. Cancer (16.4%)

2. Cancer (22.4%)

3. Unintentional injuries (13.8%)

3. Unintentional injuries (7.2%)

4. Diabetes (5.9%)

4. Chronic lower respiratory diseases (5.9%)

5. Chronic liver disease and cirrhosis (5.3%)

5. Cerebrovascular diseases (4.1%)

6. Suicide (4.3%)

6. Alzheimer’s disease (2.9%)

7. Chronic lower respiratory diseases (4.2%)

7. Diabetes (2.8%)

8. Cerebrovascular diseases (3.1%)

8. Suicide (2.7%)

9. Homicide (1.9%)

9. Influenza and pneumonia (1.9%)

10. Influenza and pneumonia (1.8%)

10. Chronic liver disease and cirrhosis (1.7%)

Causes of Death for Female AIs/ANs and White Female U. Top 10 S. Citizens for 201731 *Percentages displayed represent total deaths in the age group due to the cause indicated.

AI/AN

White

1. Cancer (17.9%)

1. Heart disease (21.9%)

2. Heart disease (16.5%)

2. Cancer (20.3%)

3. Unintentional injuries (9.0%)

3. Chronic lower respiratory diseases (7.0%)

4. Chronic lower respiratory diseases (5.7%)

4. Alzheimer’s disease (6.5%)

5. Diabetes (5.6%)

5. Cerebrovascular diseases (6.0%)

6. Chronic liver disease and cirrhosis (5.6%)

6. Unintentional injuries (4.4%)

7. Cerebrovascular diseases (4.8%)

7. Diabetes (2.2%)

8. Alzheimer’s disease (2.9%)

8. Influenza and pneumonia (2.1%)

9. Influenza and pneumonia (2.4%)

9. Kidney diseases (1.6%)

10. Kidney diseases (2.1%) Kidney diseases (2.1%)

10. Septicemia (1.5%)

InfantBlood Prenatal High Cancer Mortality Care Pressure Cancer is complicated and has many causes, with many outcomes. There are two basic categories that a cancer diagnosis can fall under: benign and malignant. If something the cancer is benign, then it is considered not harmful, whereas malignant cancer is a type that tends to invade healthy tissue and possibly recurs after removal. American Indian/Alaska Native cancer rates have been increasing with the years. The disparity between the rates of AI/AN and white cancer deaths has widened instead of closed. Cancer survivorship has also been decreasing from comorbidities, meaning there are many health issues happening simultaneously for an individual. Breast and prostate cancer especially had significantly higher mortality rates for AIs/ANs compared to whites, according to Emerson et al.’s 2017 study.32

Table 16

Cancer Age-Adjusted Death Rates for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

AI/AN

Combined three states Age-adjusted Deaths death rate** 2,916 129.3

White

185,434

Race

152.3

United States of America Age-adjusted Deaths death rate** 13,727 101.7 2,023,801

154.9

Table 17

Cancer Age-Adjusted Death Rates by Gender for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Combined three states Age-adjusted Deaths death rate** 1,321 108.6

United States of America Age-adjusted Deaths death rate** 6,419 87.6

Male

1,595

155.6

7,308

119.8

Female

85,514

129.2

951,391

133.4

Male

99,920

182.7

1,072,410

183.7

InfantBlood Prenatal High Cancer Mortality (cont) Care Pressure Deaths from cancer were higher per 100,000 in whites than AIs/ANs, other than Kansas and Oklahoma. Oklahoma had the highest rate for AI/AN cancer deaths (198.6 per 100,000). Texas had the lowest rate for AI/AN cancer deaths (29.8 per 100,000). For both races, the male mortality rates were higher than the female rates.

Table 18

Cancer Age-Adjusted Death Rates **Per 100,000 Source: CDC WONDER, 2015–2018

Deaths

AI/AN

Oklahoma Age-adjusted Deaths death rate** 1,843 198.6

White

20,999

20,591

Race

178.1

222

Kansas Age-adjusted death rate** 197.8 158.7

Deaths 258

Texas Age-adjusted death rate** 29.8

136,624

147.1

Table 19

Cancer Age-Adjusted Death Rates by Gender (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Oklahoma Race AI/AN

White

Kansas

Texas

Gender

Deaths

Age-adjusted death rate**

Deaths

Age-adjusted death rate**

Deaths

Age-adjusted death rate**

Female

1,103

158.9

151.7

126

29.2

Male

1,333

243.0

130

254.4

132

30.2

Female

12,910

150.6

9,755

137.8

62,849

124.4

Male

15,309

213.9

10,836

186.7

73,775

176.9

Maternal High Diabetes Cholesterol Smoking Status Diabetes-related death is usually from complications resulting from this disease, for example nerve damage in limbs can increase the chance of injuries and amputation. There are many complications from diabetes and most of them can lead to death if untreated. Diabetes patients’ health conditions also influence hospital stays.33

Table 20

Diabetes Age-Adjusted Death Rates for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

AI/AN

Combined three states Age-adjusted Deaths death rate** 782 34.7

United States of America Age-adjusted death Deaths rate** 4,520 33.4

White

25,495

253,237

Race

21.1

19.5

Table 21

Diabetes Age-Adjusted Death Rates by Gender for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018. Combined three states Race AI/AN White

United States of America

Gender

Deaths

Age-adjusted death rate**

Deaths

Age-adjusted death rate**

Female

386

32.6

2,057

29.0

Male

396

36.9

2,463

38.2

Female

11,536

17.3

110,654

15.2

Male

13,959

25.6

142,583

24.7

Maternal High Diabetes Cholesterol (cont) Smoking Status Texas was the only geography that had lower death rates from diabetes (5.4 per 100,000) for AIs/ANs than whites. All other areas had increased deaths for AIs/ANs compared to whites. The combined three states had an AI/AN age-adjusted rate of 34.7 per 100,000, while whites only had 21.1 per 100,000. For both races, women had lower rates of mortality than men.

Table 22

Diabetes Age-Adjusted Death Rates (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Oklahoma Age-adjusted Deaths death rate** 533 58.3

Race AI/AN White

3,213

27.5

Deaths 41

Kansas Age-adjusted death rate** 38.6

2,721

21.0

Deaths 47

Texas Age-adjusted death rate** 5.4

18,548

20.0

Table 23

Diabetes Age-Adjusted Death Rates by Gender (2015–2018) *Calculations may be suppressed due to small sample size. **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Oklahoma Age-adjusted Deaths death rate** 341 50.9

Deaths 15

Kansas Age-adjusted death rate** *

Male

353

61.0

50.4

Female

1,997

23.0

1,172

Male

2,229

31.8

1,549

Texas Age-adjusted Deaths death rate** 30 6.3 17

16.1

8,367

16.5

27.1

10,181

24.4

High Blood Major Cardiovascular Pressure Disease Any disease that has to do with the heart and heart tissues is serious. There are many types of diseases and conditions that may cause a range of effects from an irregular heartbeat to death. Overall, heart disease is the major cause of death across the nation and all races. However, there are signs that within the AI/AN community, the incidence rate is stabilizing or declining in some areas. Reducing the risk of heart disease will be the best way to reduce overall death from heart disease.34, 35

Table 24

Major Cardiovascular Disease Age-Adjusted Death Rates for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018 Combined three states Age-adjusted Deaths death rate** 4,254 207.2

Race AI/AN White

4,972

119.2

United States of America Age-adjusted death Deaths rate** 18,824 151.9 2,865,135

216.6

Table 25

Major Cardiovascular Disease Age-Adjusted Death Rates by Gender for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Combined three states Age-adjusted Deaths death rate** 1,867 171.7

United States of America Age-adjusted Deaths death rate** 8,344 125.4

Male

2,387

247.5

10,480

183.2

Female

131,604

190.5

1,402,105

178.6

Male

144,424

278.7

1,463,030

261.8

High Blood Major Cardiovascular Pressure Disease (cont) The AN/AI age-adjusted death rate for cardiovascular disease in the combined states area was higher (207.2 per 100,000) than whites (119.2 per 100,000). In the nation as a whole, the death rate was lower for AIs/ANs (151.9 per 100,000) than whites (216.6 per 100,000). The rate for AIs/ANs in Oklahoma was higher than any other area (329.9 per 100,00).

Table 26

Major Cardiovascular Disease Age-Adjusted Death Rates (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Deaths

AI/AN

Oklahoma Age-adjusted Deaths death rate** 2,743 329.9

White

33,926

29,605

Race

289.6

256

Kansas Age-adjusted death rate** 274.0 218.4

Deaths 356 201,079

Texas Age-adjusted death rate** 43.8 223.0

Table 27

Major Cardiovascular Disease Age-Adjusted Death Rates by Gender (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Oklahoma Age-adjusted Deaths death rate** 1,589 257.0

Kansas Age-adjusted Deaths death rate** 116 236.3

Male

2,053

399.6

140

319.0

Female

22,366

245.7

14,889

Male

22,978

336.1

14,716

Deaths 162

Texas Age-adjusted death rate** 39.0

194

49.0

182.2

94,349

182.2

261.6

106,730

271.3

Maternal High Influenza Cholesterol Smoking and Pneumonia Status Influenza(the flu) is a contagious respiratory illness. The flu can cause mild to severe symptoms and sometimes even death. Each year, about 200,000 people are hospitalized due to the flu and 36,000 people die from flu-related complications. Young children, people with certain health conditions, and the elderly are at a higher risk of complications related to the flu. Pneumonia is inflammation of the lungs that usually an infection causes and is a complication of the flu.36

Table 28

Influenza and Pneumonia Age-Adjusted Death Rates for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

AI/AN

Combined three states Age-adjusted Deaths death rate** 262 13.0

United States of America Age-adjusted Deaths death rate** 1,586 13.0

White

15,367

189,616

Race

13.0

14.4

Table 29

Influenza and Pneumonia Age-Adjusted Death Rates by Gender for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Combined three states Age-adjusted death Deaths rate** 124 11.1

United States of America Age-adjusted death Deaths rate** 771 11.6

Male

138

15.6

815

14.6

Female

7,882

11.5

99,249

12.8

Male

7,485

15.0

90,367

16.6

Maternal High Influenza Cholesterol Smoking and Pneumonia Status (cont) Deaths from the flu or pneumonia are less varied between races than other causes of death. In the combined three states region, the rates for AIs/ANs and whites were 13 per 100,000. The sample sizes of AIs/ANs in Kansas and Texas were too small to obtain reliable age-adjusted rates. Men for both races had higher death rates than women for flu and pneumonia.

Table 30

Influenza and Pneumonia Age-Adjusted Death Rates for OK, KS, and TX Combined and the United States of America (2015–2018) *Calculations may be suppressed due to small sample size. **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Oklahoma Age-adjusted Deaths death rate** 161 20.1 1,612

13.9

Deaths 19

Kansas Age-adjusted death rate** *

2,267

Texas Age-adjusted death rrate** *

Deaths 18

16.4

10,803

12.1

Table 31

Influenza and Pneumonia Age-Adjusted Death Rates by Gender (2015–2018) *Calculations may be suppressed due to small sample size. **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Oklahoma Age-adjusted Deaths death rate** 101 16.2

Kansas Age-adjusted Deaths death rate** 11 *

Deaths 12

Texas Age-adjusted death rate** *

Male

124

26.6

Female

1,191

13.4

1,252

15.1

5,439

10.6

Male

1,106

16.6

1,015

18.2

5,364

14.2

Chronic Liver Disease and Cirrhosis The liver is a vital organ that is both expensive and difficult to help recover if it is damaged or sick. Chronic liver disease and cirrhosis are general conditions that commonly result from alcohol abuse, forms of hepatitis, and other nonalcoholic fatty liver diseases. Liver disease is an increasing cause of death for most developed nations. Among AIs/ANs, there is a large gap comparing rates to other races in all parts of the United States. Death from liver disease is already in the top five causes of death and will soon be in the top three if trends are not halted.37, 38

Table 32

Chronic Liver Disease and Cirrhosis Age-Adjusted Death Rates for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

AI/AN

Combined three states Age-adjusted death Deaths rate** 671 25.1

United States of American Age-adjusted death Deaths rate** 5,351 32.6

White

22,702

188,948

Race

18.5

15.2

Table 33

Chronic Liver Disease and Cirrhosis Age-Adjusted Death Rates by Gender for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Combined three states Age-adjusted death Deaths rate** 282 20.6

United States of American Age-adjusted death Deaths rate** 2,484 30.1

Male

389

29.9

2,867

35.1

Female

8,501

13.2

73,274

11.2

Male

14,201

24.0

115,674

19.4

Chronic Liver Disease and Cirrhosis (cont) The age-adjusted death rate for AIs/ANs in the combined states region was 25.1 per 100,000. When broken down by gender, male AIs/ANs had a higher rate (29.9 per 100,000) than female AIs/ANs (20.6 per 100,000), or white males or females (24.0 and 13.2 per 100,000). Table 34

Chronic Liver Disease and Cirrhosis Age-Adjusted Death Rates (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Oklahoma Age-adjusted Deaths death rate** 406 39.0 1,905

17.1

Deaths 43

Kansas Age-adjusted death rate** 30.6

1,737

14.4

Deaths 66

Texas Age-adjusted death rate** 6.0

18,392

19.2

Table 35

Chronic Liver Disease and Cirrhosis Age-Adjusted Death Rates by Gender (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Oklahoma Age-adjusted Deaths death rate** 230 30.6

Deaths 20

Kansas Age-adjusted death rate** 27.6

Deaths 32

Texas Age-adjusted death rate** 5.8

Male

332

49.6

34.2

6.2

Female

1,073

14.0

642

10.3

6,786

13.6

Male

1,500

20.8

1,095

18.9

11,606

25.2

Maternal High Accidents Cholesterol Smoking Status Accidental death is a problem for all races. When other causes of death decrease through medical advancement, there are certain causes of death, such as accidents, that will remain. Effective progress will be a matter of reducing the circumstances around accidental deaths to reduce the rate. There are many accidental deaths, but some of the most frequent are motor vehicle accidents, poisoning, and falling. All injuries the IHS paid for in 2016 totaled up to 14% of the full expenses paid in that year.39 The IHS planned purposeful interventions that did show to have some impact on lowering rates. However, there are many other factors to injury and accidental death. Thus, continually reducing injury rates need to be a continuous investment.40

Table 36

Accidental Injury Age-Adjusted Death Rates for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

AI/AN

Combined three states Age-adjusted Deaths death rate** 1,212 44.6

United States of American Age-adjusted death Deaths rate** 8,913 52.6

White

49,177

540,650

Race

43.0

49.3

Table 37

Accidental Injury Age-Adjusted Death Rates by Gender for OK, KS, and TX Combined and the United States of America (2015–2018) Note. **Per 100,000. From OK2SHARE, 2015-2018.

Race AI/AN White

Gender Female

Combined three states Age-adjusted Deaths death rate** 416 30.8

United States of American Age-adjusted death Deaths rate** 2,998 35.7

Male

796

59.0

5,915

70.0

Female

17,568

28.6

197,536

32.6

Male

31,609

58.0

343,114

66.6

Maternal High Accidents Cholesterol Smoking (cont) Status Accidental death between AIs/ANs and whites were similar in the region (44.6 and 43.0 per 100,000, respectively). When looking at gender, both races’ male population had almost double the rate of death from accidents. Oklahoma had the highest overall death rate for AIs/ ANs (71.5 per 100,000), while Kansas had the highest AI/AN male death rate (99.5 per 100,000).

Table 38

Accidental Injury Age-Adjusted Death Rates (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018 Oklahoma Age-adjusted Deaths death rate** 765 71.5

Race AI/AN White

6,138

61.6

Kansas Age-adjusted Deaths death rate** 88 66.8 5,435

47.4

100

Texas Age-adjusted death rate** 8.4

35,489

39.5

Deaths

Table 39

Accidental Injury Age-Adjusted Death Rates by Gender (2015–2018) Note. **Per 100,000. From OK2SHARE, 2015-2018.

Race AI/AN White

Gender Female

Oklahoma Age-adjusted Deaths death rate** 357 49.4

Deaths 27

Kansas Age-adjusted death rate** 37.8

Deaths 32

Texas Age-adjusted death rate** 5.6

Male

667

95.2

99.5

11.1

Female

3,249

44.2

2,202

33.9

12,117

25.5

Male

5,004

80.0

3,233

61.8

23,372

54.0

InfantBlood Prenatal High Mortality Care Pressure Suicide Suicide is a complicated public health situation and especially so for the AI/AN population. Socioeconomic characteristics, access or lack thereof to mental health services, and substance use are contributing factors to suicide rates. There are differences between urban and rural suicide rates with many theories as to what is occurring in each populace. Projects and initiatives are in place all over the county with specific interventions for AI/AN communities. Many have shown some success, but there is room for improvement. 41, 42

Table 40

Suicide Age-Adjusted Death Rates for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

AI/AN

Combined three states Age-adjusted Deaths death rate** 393 12.9

United States of America Age-adjusted death Deaths rate** 2,513 13.4

White

17,751

164,645

Race

15.7

15.5

Table 41

Suicide Age-Adjusted Death Rates by Gender for OK, KS, and TX Combined and the United States of America (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Race AI/AN White

Gender Female

Combined three states Age-adjusted Deaths death rate** 88 5.8

United States of America Age-adjusted death Deaths rate** 617 6.5

Male

305

20.2

1,896

20.2

Female

3,864

6.8

36,677

6.9

Male

13,887

24.9

127,968

24.5

Infant Mortality Prenatal Care Suicide (cont) AI/AN suicide age-adjusted rates for the combined region was lower (12.9 per 100,000) than whites (15.7 per 100,000). When looking at the states individually, Kansas’s AI/AN rate was higher (20.0 per 100,000) than the white rate (18.7 per 100,000). Suicide rates by gender showed that for both races, male rates of suicide were higher and in some areas were more than 3 times higher than that of females. The female rates in Kansas and Texas were unreliable since the sample sizes were too small.

Table 42

Suicide Age-Adjusted Death Rates (2015–2018) **Per 100,000 Source: CDC WONDER, 2015–2018

Oklahoma Deaths

Age-adjusted death rate**

AI/AN

231

White

2,021

Race

Kansas

Texas

Deaths

Age-adjusted death rate**

19.5

20.0

3.7

21.7

1,916

18.7

13,149

14.6

Deaths

Age-adjusted death rate**

Table 43

Suicide Age-Adjusted Death Rates by Gender (2015–2018) *Calculations may be suppressed due to small sample size. **Per 100,000 Source: CDC WONDER, 2015–2018 Oklahoma Race AI/AN White

Gender

Deaths

Age-adjusted death rate**

Kansas Deaths

Texas

Age-adjusted death rate**

Deaths

Age-adjusted death rate**

Female

8.4

Male

244

31.8

36.2

4.6

Female

577

9.5

414

8.2

2,873

6.4

Male

2,109

34.1

1,502

29.5

10,276

23.1

Data Resources Behavioral Risk Factor Surveillance Survey

Centers for Disease Control and Prevention

Established in 1984 by the CDC, the BRFSS is a state-based system of health survey that collects information on health-risk behaviors, preventive health practices, and health care access, primarily related to chronic disease and injury. For many states, the BRFSS is the only available source of timely, accurate data on health-related behaviors. Currently, data are collected monthly in all 50 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, and Guam. The BRFSS completes more than 400,000 adult interviews each year, making it the largest continuously conducted health survey system in the world. By collecting behavioral health risk data at the state and local level, the BRFSS has become a powerful tool for targeting and building health promotion activities. As a result, BRFSS users have increasingly demanded more data and asked for more questions on the survey. Currently, there is a wide sponsorship of the BRFSS survey, including most divisions in the CDC National Center for Chronic Disease Prevention and Health Promotion; other CDC centers; and federal agencies, such as the Health Resources and Services Administration, Administration on Aging, Department of Veterans Affairs, and Substance Abuse and Mental Health Services Administration. States use BRFSS data to identify emerging health problems, establish and track health objectives, and develop and evaluate public health policies and programs. Many states also use BRFSS data to support health-related legislative efforts. More information can be found at www.cdc. gov/brfss

The CDC, a part of the U.S. Department of Health and Human Services, is the primary federal agency for conducting and supporting public health activities in the United States. The CDC works 24/7 to protect America from health, safety, and security threats, both foreign and in the U.S. Whether diseases start at home or abroad, are chronic or acute, are curable or preventable, are due to human error or deliberate attack, the CDC fights disease and supports communities and citizens to do the same. More information can be found at www.cdc.gov

Kansas Department of Health and Environment The Kansas Department of Health and Environment consists of three divisions: Environment, Health Care Finance, and Public Health. The Office of Vital Statistics, which is within the Bureau of Epidemiology and Public Health Informatics, manages vital statistics data. This includes statistics from live births, stillbirths, abortions, deaths, marriages, and marriage dissolutions based on certificates and reports. The Annual Summary of Vital Statistics provides an overview of the events contributing to Kansans’ health status: http://www.kdheks.gov/hci/annsumm. html. The Kansas Behavioral Risk Factor Surveillance System conducts health-related telephone surveys with adult Kansans on a wide range of health-related risk behaviors, chronic health conditions, and using preventive services. Survey data are available for the state, multiple regions within Kansas, and several counties through partnerships with Kansas-based public health programs, the CDC, Health Forward Foundation, Kansas Health Foundation, REACH Healthcare Foundation, and Sunflower Foundation. See the Kansas BRFSS website for access to data and reports: https://www.kdheks.gov/brfss/about.html.

March of Dimes

Oklahoma Vital Statistics

For 80 years, March of Dimes has helped millions of infants survive and thrive. Now the organization is building on that legacy to level the playing field for all mothers and children, no matter their age, socioeconomic background, or demographics. March of Dimes supports mothers throughout their pregnancy, even when everything does not go according to plan. March of Dimes advocates for policies that prioritize mothers’ health. It supports radical improvements to the care mothers and children receive. The organization pioneers research to find solutions to the biggest health threats to mothers and children. It believes that every child deserves the best possible start. Unfortunately, not all children had one. March of Dimes is working to change that. Today, programs educate medical professionals and the public about best practices; support lifesaving research; provide comfort and support to families in NICUs; and advocate for those who need March of Dimes’ programs the most, mothers and children. March of Dimes is stronger and more committed than ever to guiding mothers through every stage of the pregnancy journey. The organization is fighting for the smallest among us and advocating for their health each and every day.

Vital statistics are considered the foundation of public health. Oklahoma began collecting information related to births and deaths in 1917. These records are used by multiple organizations for a variety of purposes. In Oklahoma, these data are evaluated to address health issues such as improving birth outcomes, causes of death (leading, infant deaths, stillbirth, and childhood deaths), and identifying areas of high risk for teenage pregnancies. More information can be found at www.ok.gov/health.

OK2SHARE

U.S. Census Bureau

The purpose of the interactive Oklahoma State Department of Health OK2SHARE Service databases is to support the information needs of the Oklahoma State Department of Health and other users, such as health officials, educators, and students in improving service delivery, evaluating health care systems, and monitoring the health of the people of Oklahoma. These databases may be used only for the purpose for which they are provided. Any effort to determine the identity of any reported cases, or to use the information for any purpose other than for statistical reporting and analysis, is prohibited. More information can be found at www.health.state.ok.us/ok2share.

The Census Bureau is the federal government’s largest statistical agency. The bureau provides current facts and figures about America’s people, places, and economy. Federal law protects the confidentiality of all the information the Census Bureau collects. Guidelines for the Census Bureau are led by scientific objectivity, a strong and capable workforce, devotion to research-based innovation, and an abiding commitment to customers. More information can be found at www.census.gov

Texas Department of State Health Services The Department of State Health Services Center for Health Statistics was established to provide a convenient access point for health-related data for Texas. The Center aims to be a source of information for assessing community health and for public health planning. Texas data are used to support research, grant applications, and policy development, and to provide the rapid-needs response to health emergencies.

Glossary Age Adjustment is a method used to better

Cardiovascular Disease refers to the condition(s)

ensure comparability of estimates (e.g., rates) with

that generally involve narrow or blocked blood

respect to age. The age distribution of a population

vessels. Cardiovascular diseases can lead to heart

might change over time and differ from place to

attacks, strokes, and chest pain.

place. Because some health conditions or diseases are more common in certain age groups, it can be misleading to compare rates or prevalence

Community Health Proﬁle is a collection of data related to a specific population that describes

estimates of populations if the age distribution

all aspects of the community and identifies

of the populations compared are different. A rate

disparities between a selected community and a

is age adjusted by applying age-specific rates in

standard comparison group. A community health

the population of interest to the U.S. 2000 Census

profile shows the background, health status, and

standard population. Age-adjusted rates are

risk factors of a group or population in a local

relative and should not be considered exact rates

area.

that necessarily represent the true underlying burden of disease in the population.

Cholesterol is a waxy, fat-like substance that

Angina or Coronary Heart Disease is a condition marked by severe pain in the chest, often also spreading to the shoulders, arms, and neck. It is caused by too little blood going to the heart. Asthma is an inflammatory disorder of the airways, marked by periodic attacks of wheezing, shortness

breath,

coughing,

and

chest

tightening. Birth Rates are calculated as the number of births divided by total population in the given year(s). The Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based random digitdialed phone survey of adults 18+ years of age.

occurs naturally in all parts of the body. Cirrhosis of the Liver is a disease caused by a variety of liver diseases and conditions, such as chronic alcoholism and hepatitis, which lead to scarring and liver failure. Data refers to information collected from a survey or administrative source used to produce statistics. Death Rate is calculated by dividing the number of deaths in a population in a year by the midyear resident population.

Demographic Characteristics are descriptive

Influenza (the flu) is a respiratory illness that is

data that refer to a population’s characteristics.

spread mainly through coughing and sneezing. It

They provide information to assist in evaluation of

can cause mild to severe illness and at times lead

community health.

to death.

Depression is a mental disorder characterized by

Life Expectancy is the average number of years

depressed mood, loss of interest or pleasure, or

of life remaining for a person at a particular age.

feelings of low self-worth or guilt. Mental Health is a state of mental functioning, Diabetes is a chronic health condition where the

resulting

body is unable to produce insulin and properly

relationships, and the ability to change and cope

break down sugar (glucose) in the blood.

with diversity.

Disease is a sickness, illness, or loss of health.

Pneumonia is an infection of the lung. Bacterial

productive

activities,

fulfilling

pneumonia is the deadliest type. Health is a state of complete physical, mental, and social well-being and not merely the absence

Population Census is the total process of

of disease or infirmity.

collecting, and

High Blood Pressure (hypertension) is when the

compiling,

publishing

demographic,

evaluating,

otherwise

economic,

and

analyzing,

disseminating social

data

pressure against the arterial walls is consistently

pertaining, at a specified time, to all persons in a

higher than normal. In this document, 140/90 or

country or in a well-delimited part of a country.

higher is considered high. Poverty refers to a lack of resources. Families Infant Mortality Rate is based on a period

with incomes below the federal poverty level of

calculated by dividing the number of infant

$26,200 for a family of four in 2020 for the 48

deaths during a calendar year by the number

contiguous states and the District of Columbia

of live births reported in the same year. It is

are considered poor. A family of four living with

expressed as the number of infant deaths per

an income below $48,678 in 2016 was referred to

1,000 live births.

as low income.

Prevention has three levels: primary—stopping or

delaying

onset

disease;

secondary—early

identification and stopping or delaying onset of complications; and tertiary—stopping disability from disease and its complications. Race/Ethnic and Age Distributions are used to describe characteristics of the population and to examine differences in the prevalence of health indicators across populations or over time. Rheumatoid Arthritis is a chronic progressive disease causing painful inflammation in the joints. The joints most affected are fingers, wrists, feet, and ankles. Risk has two definitions: (a) the chance of being exposed to an infectious agent by its specific transmission mechanism; b) the chance of becoming infected if exposed to an infectious agent by its specific transmission mechanism. A Risk Factor is any influence increasing a person’s chance of developing a disease. Socioeconomic Status Indicators are education level, poverty level, and migrant status that are associated with prevalence rates. Infant mortality rate is based on a period calculated by dividing the number of infant deaths during a calendar year by the number of live births reported in the same year. It is expressed as the number of infant deaths per 1,000 live births.

References 1.

Organization for Economic Co-operation and Development (2019), Elderly population (indicator). doi: 10.1787/8d805ea1-en (Accessed on 31 October 2019)

Wilkinson, R. G., & Pickett, K. E. (2006). Income inequality and population health: a review and explanation of the evidence. Social science & medicine, 62(7), 1768-1784.

Poverty Guidelines. (2020, March 5). Retrieved from https://aspe.hhs.gov/poverty-guidelines

Chappelow, J. I. (2019, October 9). Demographics Definition. Retrieved from https://www.investopedia.com/ terms/d/demographics.asp

Hahn, R. A., & Truman, B. I. (2015). Education Improves Public Health and Promotes Health Equity. International Journal of Health Services, 45(4), 657–678. doi: 10.1177/0020731415585986

Ryan, C. L., & Siebens, J. (2012). Educational attainment in the United States: 2009. Washington, DC: US Census Bureau, P20-566.

Khullar, D., & Chokshi, D. A. (2018). Health, income, & poverty: Where we are & what could help. Health affairs, 4.doi:10.1377/hpb20180817.901935

Lienemann, B. A., Cummins, S. E., Tedeschi, G. J., Wong, S., & Zhu, S. H. (2019). American Indian/Alaska Native Smokers’ Utilization of a Statewide Tobacco Quitline: Engagement and Quitting Behaviors from 20082018. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco.

U.S. Department of Health and Human Services. (2015, August). Tobacco-Related Mortality. National Center for Chronic Disease Prevention and Health Promotion. http://www.cdc.gov/tobacco/data_statistics/fact_ sheets/health_effects/tobacco_related_mortality/

10. Kessler, R., Sampson, N., Berglund, P., Gruber, M., Al-Hamzawi, A., Andrade, L., Wilcox, M. (2015). Anxious and non-anxious major depressive disorder in the World Health Organization World Mental Health Surveys. Epidemiology and Psychiatric Sciences, 24(3), 210-226. doi:10.1017/S2045796015000189 11. Dickerson, D. L., Brown, R. A., Johnson, C. L., Schweigman, K., & D’Amico, E. J. (2016). Integrating Motivational Interviewing and Traditional Practices to Address Alcohol and Drug Use Among Urban American Indian/ Alaska Native Youth. Journal of Substance Abuse Treatment, 65, 26–35. doi: 10.1016/j.jsat.2015.06.023 12. Schoenbaum, S. C. (1987). Economic impact of influenza. The American Journal of Medicine, 82(6), 26–30. doi: 10.1016/0002-9343(87)90557-2 13. Fedson, D. S. (1987). Influenza and Pneumococcal Immunization Strategies for Physicians. Chest, 91(3), 436–443. doi: 10.1378/chest.91.3.436 14. Zuckerman, S., Haley, J., Roubideaux, Y., & Lillie-Blanton, M. (2004). Health service access, use, and insurance coverage among American Indians/Alaska Natives and Whites: what role does the Indian Health Service play?. American Journal of Public Health, 94(1), 53-59. 15. Angina. (2020, March 25). Retrieved from https://www.mayoclinic.org/diseases-conditions/angina/symptomscauses/syc-20369373 16. Lai, S. M., Studenski, S., Duncan, P. W., & Perera, S. (2002). Persisting consequences of stroke measured by the Stroke Impact Scale. Stroke, 33(7), 1840-1844. 17. Kinghorn, B., Fretts, A. M., O’Leary, R. A., Karr, C. J., Rosenfeld, M., & Best, L. G. (2019). Socioeconomic and environmental risk factors for pediatric asthma in an American Indian community. Academic pediatrics, 19(6), 631-637.

18. Lowe, A. A., Bender, B., Liu, A. H., Solomon, T., Kobernick, A., Morgan, W., & Gerald, L. B. (2018). Environmental concerns for children with asthma on the Navajo Nation. Annals of the American Thoracic Society, 15(6), 745-753. 19. Arthritis. National Statistics 2010-2012. Center for Disease Control and Prevention. http://www.cdc.gov/arthritis/ data_statistics/national-statistics.html 20. Conte, K. P., Schure, M. B., & Goins, R. T. (2017). Older American Indians’ perspectives on health, arthritis, and physical activity: implications for adapting evidence-based interventions, Oregon, 2013. Preventing chronic disease, 13. 21. Daley, C. M., Hale, J. W., Berryhill, K., Bointy, S., Clark, L., Chase, B., & He, J. (2017). Diabetes Self-Management Behaviors among American Indians in the Midwestern United States. ARC journal of diabetes and endocrinology, 3(1), 34. 22. Dennis, J. A. (2019). Birth weight and maternal age among American Indian/Alaska Native mothers: A test of the weathering hypothesis. SSM-population health, 7, 100304. 23. Boyle EM, Poulsen G, Field DJ, et al. Effects of gestational age at birth on health outcomes at 3 and 5 years of age: population based cohort study. BMJ. 2012;344:e896. Published 2012 Mar 1. doi:10.1136/bmj.e896 24. Myrskylä, M., & Fenelon, A. (2012). Maternal age and offspring adult health: evidence from the health and retirement study. Demography, 49(4), 1231-1257. 25. Abshire, C., Mcdowell, M., Crockett, A. H., & Fleischer, N. L. (2019). The Impact of Centering Pregnancy Group Prenatal Care on Birth Outcomes in Medicaid Eligible Women. Journal of Women’s Health, 28(7), 919-928. 26. Marengo, LK, Flood, TJ, Ethen, MK, et al. Study of selected birth defects among American Indian/ Alaska Native population: A multi‐state population‐based retrospective study, 1999–2007. Birth Defects Research. 2018; 110: 1412– 1418. https://doi.org/10.1002/bdr2.1397 27. Drake, P., Driscoll, A. K., & Mathews, T. J. (2018). Cigarette smoking during pregnancy: United States, 2016. 28. Von Kries, R., Toschke, A. M., Koletzko, B., & Slikker Jr, W. (2002). Maternal smoking during pregnancy and childhood obesity. American journal of epidemiology, 156(10), 954-961. 29. Office of Minority Health. (2019, November 8). Retrieved from https://minorityhealth.hhs.gov/omh/browse. aspx?lvl=4&lvlid=38 30. National Institute of Child Health and Human Development. Are there ways to reduce the risk of infant mortality? (2016, December 1). Retrieved from https://www.nichd.nih.gov/health/topics/infant-mortality/topicinfo/reducerisk 31. Heron, M. (2019, June 24). National Vital Statistics Reports Volume 68, Number 6, June 24, 2019, Deaths: Leading Causes for 2017. Retrieved April 4, 2020, from https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_06-508.pdf 32. Emerson, M. A., Banegas, M. P., Chawla, N., Achacoso, N., Alexeeff, S. E., Adams, A. S., & Habel, L. A. (2017). Disparities in prostate, lung, breast, and colorectal cancer survival and comorbidity status among urban American Indians and Alaskan natives. Cancer research, 77(23), 6770-6776. 33. Clements, J. M., & Rhynard, S. J. (2018). In-hospital Mortality, Length of Stay, and Discharge Disposition in a Cohort of Rural and Urban American Indians and Alaska Natives. Am Indian Alsk Native Ment Health Res [Internet], 25(3), 78-91. 34. (2013-2014). Heart Disease. Centers for Disease Control and Prevention. disease.htm

http://www.cdc.gov/nchs/fastats/heart-

35. Muller, C. J., Noonan, C. J., MacLehose, R. F., Stoner, J. A., Lee, E. T., Best, L. G., & Howard, B. V. (2019). Trends in Cardiovascular Disease Morbidity and Mortality in American Indians Over 25 Years: The Strong Heart Study. Journal of the American Heart Association, 8(21), e012289. 36. U.S. Department of Health and Human Services. (2013). Key Facts about Influenza and Flu Vaccine. Centers for Disease Control and Prevention. http://www.cdc.gov/flu/keyfacts.htm 37. Allen, A. M., & Kim, W. R. (2016, May). Epidemiology and healthcare burden of acute-on-chronic liver failure. In Seminars in liver disease (Vol. 36, No. 02, pp. 123-126). Thieme Medical Publishers. 38. Jacobs-Wingo, J. L., Espey, D. K., Groom, A. V., Phillips, L. E., Haverkamp, D. S., & Sandte, L. (2016). Causes and disparities in death rates among urban American Indian and Alaska Native populations, 1999–2009. American journal of public health, 106(5), 906-914. 39. Indian Health Service. Indian health focus: injuries 2017 edition. Maryland: Indian Health Service; 2017 Oct. Page 116. https://www.ihs.gov/sites/dps/themes/responsive2017/display_objects/documents/Indian_ Health_Focus_%20Injuries_2017_Edition_508.pdf 40. Honeycutt, A. A., Khavjou, O., Neuwahl, S. J., King, G. A., Anderson, M., Lorden, A., & Reed, M. (2019). Incidence, deaths, and lifetime costs of injury among American Indians and Alaska Natives. Injury epidemiology, 6(1), 44. 41. Hamilton, S. M., & Rolf, K. A. (2010). Suicide in adolescent American Indians: Preventative social work programs. Child and Adolescent Social Work Journal, 27(4), 283-290. 42. LeMaster, P. L., Beals, J., Novins, D. K., & Manson, S. M. (2004). The prevalence of suicidal behaviors among Northern Plains American Indians. Suicide and Life-Threatening Behavior, 34(3), 242-254.

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