Page 1

Laura Viester

Uitnodiging

Worksite health promotion in the construction industry Laura Viester

voor het bijwonen van de openbare verdediging van mijn proefschrift

Worksite health promotion in the construction industry

Worksite health promotion in the construction industry

op dinsdag 24 november 2015 om 13.45 uur in de aula van de Vrije Universiteit aan de Boelelaan 1105 te Amsterdam Na afloop bent u van harte welkom op de receptie

Laura Viester Ohmstraat 4-II 1098 SR Amsterdam 06-24472241 laura.viester@gmail.com

Paranimfen Linda Eijckelhof eijckelhof@hotmail.com Mirka Janssen mirka_janssen@hotmail.com

Body@Work


Worksite health promotion in the construction industry

Laura Viester


The study presented in this thesis was conducted at the EMGO+ Institute for Health and Care Research, Department of Public and Occupational Health of the VU University Medical Center. The EMGO+ Institute participates in the Netherlands School of Primary Care Research (CaRe), which was acknowledged in 2005 by the Royal Netherlands Academy of Arts and Sciences (KNAW). The study described in this thesis originated from Body@Work, Research Center on Physical Activity, Work, and Health, which is a joint initiative of the VU University Medical Center (Department of Public and Occupational Health, EMGO+ Institute for Health and Care Research), VU University Amsterdam, and the Netherlands Organisation of Applied Scientific Research (TNO). The study presented in this thesis is part of a research programme “Vitality in practice”, which is financed by Fonds Nuts Ohra (Nuts Ohra Foundation). Financial support for the printing of this thesis has kindly been provided by Body@Work, Research Center on Physical Activity, Work, and Health.

English title: Worksite health promotion in the construction industry Nederlandse titel: Gezondheidsbevordering voor werknemers in de bouwsector ISBN: 978-94-6233-109-9 Layout: Gildeprint– Enschede, the Netherlands Printed by: Gildeprint – Enschede, the Netherlands © Copyright 2015, Laura Viester All rights reserved. No part of this publication may be reproduced, stored or transmitted in any form or by any means without permission of the referenced journals or the author.


VRIJE UNIVERSITEIT

Worksite health promotion in the construction industry

ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, op gezag van de rector magnificus prof.dr. F.A. van der Duyn Schouten, in het openbaar te verdedigen ten overstaan van de promotiecommissie van de Faculteit der Geneeskunde op dinsdag 24 november 2015 om 13.45 uur in de aula van de universiteit, De Boelelaan 1105

door Laura Viester geboren te Amsterdam


promotoren:

prof.dr. A.J. van der Beek

prof.dr.ir. P.M. Bongers

copromotor:

dr. E.A.L.M. Verhagen


Contents Chapter 1

General introduction

Chapter 2

The relation between body mass index and musculoskeletal symptoms

in the working population

Chapter 3

VIP in construction: systematic development and evaluation of a

multifaceted health programme aiming to improve physical activity

levels and dietary patterns among construction workers

Chapter 4

Process evaluation of a multifaceted health programme aiming to

improve physical activity levels and dietary patterns among construction

7 17

35

65

workers Chapter 5

Improvements in dietary and physical activity behaviours and body mass

index as a result of a worksite intervention in construction workers:

results of a randomised controlled trial

Chapter 6

The effect of a health promotion intervention for construction workers

on work-related outcomes: results from a randomised controlled trial

Chapter 7

Cost-effectiveness and return-on-investment analysis of a worksite

intervention aimed at improving physical activity and nutrition among

construction workers

Chapter 8

General discussion

85

105

123

153

Summary

175

Samenvatting

179

Dankwoord

183


Chapter 1 General Introduction


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Developments in the construction sector

1

The labour market is changing dramatically. Between 1990 and 2011 the average age in the actively employed increased by 5 years, to over 41 years of age [1]. From 2013 on this will accelerate. According to the Statistics Netherlands (CBS) population’s prognosis, the number of people aged > 65 are projected to rise from 2.7 million in 2012 to 4.7 million in 2041 [2]. The ratio of economically active individuals to pensioners will become unfavourable, and as a result retirement age will be raised. Hence, the workforce is ageing and this also applies to the construction sector, where currently more workers are in their 50s than in their 30s. In the upcoming years, despite the counteracting consequences on employment as a result of the current economic recession, in several sectors a shortage in workers is expected. In the construction sector this shortage will also result from a decrease in the number of young workers entering the sector. An additional concern is that sickness absence is also more common in blue collar occupations [3]. The combination of ageing with high physical demands at work for this occupational group results in relatively high risk for increased sickness absence and work disability. Keeping ageing employees at work is a key goal of European labour policy, and from the perspective of employers it is essential to invest in the health of their employees. Another consequence of an ageing workforce is the increase in health risks. Body weight increases with age, and older workers suffer increasingly from musculoskeletal complaints, especially in physically demanding professions [4,5]. These developments, especially in combination with unfavourable health and lifestyle indicators, provide challenges for maintaining a healthy and productive workforce, and emphasise the need of interventions in the construction sector.

Overweight, lifestyle and musculoskeletal disorders Overweight becomes an ever greater public health problem. During the last decades the prevalence of obesity has increased worldwide, and the World Health Organization (WHO) lists overweight and obesity as one of the leading global risks for mortality [6]. Increased prevalence in overweight and obesity also applies to the Netherlands. In 2011, according to the Dutch Bureau of Statistics (CBS) over 50% of the male and 40% of the female population was overweight [7]. Of this population 10% of the men and 13% of the women were categorised as severely overweight, i.e. obese. Although the steep increase of the last three decades seems to be reaching a plateau, the obesity numbers are still rising. Overweight and obesity are associated with a series of secondary complications and serious comorbid diseases, such as elevated rates of diabetes, cardiovascular disease, cancer and musculoskeletal disorders (MSD) [8-10]. Along with these detrimental effects on a person’s health and well-being, there are substantial economic consequences to consider. The annual medical

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costs of overweight in the Netherlands have been estimated at â‚Ź500 million [11]. In addition to these direct health care costs, indirect costs of overweight for employers resulting from loss of productivity due to both sickness absenteism and presenteism, and work disability are even more substantial [12]. Among Dutch construction workers, the prevalence of overweight and obesity is even higher than in the general population. In this specific occupational group 64% of the workers is overweight, of which almost a quarter is obese [13]. Moreover, it seems that blue collar workers also have poorer scores when other lifestyle and health indicators are considered, including cardiovascular risk factors, leisure time physical activity and smoking [14-16]. Prevalence of overweight and obesity is lower among populations with healthier lifestyle behaviours [17]. A stable body weight requires a long-term balance between energy intake and energy expenditure. If energy intake exceeds expenditure, the excess of energy is stored as adipose tissue. The development of overweight and obesity is either the result of detrimental food intake behaviour, decreased physical activity behaviour, or a combination of both, with the consequence of an imbalance between energy uptake and expenditure. The effects of a positive energy balance can therefore be prevented and reversed by caloric restriction and increasing physical activity. Although blue collar workers might be more than average physically active at work, this is not accompanied by better health or improved physical capacity [18,19]. Recent research indicates that contrasting health associations of physical activity at work and leisure time physical activity exist [20]. Physical activity at work does not induce positive changes in aerobic capacity or muscular strength in workers [21]. Furthermore, being physically active at work might be compensated by more sedentary/inactive behaviour in leisure time. Although more likely to meet the weekly recommendations of overall physical activity [22], individuals from lower socioeconomic backgrounds and blue collar workers are less likely to engage in sports and leisure time activities [22-26]. Aiming at increasing leisure time physical activity in construction workers might therefore be a relevant strategy to improve both energy balance and general health. Another main cause of overweight is poor diet. Unhealthy eating is known to be more prevalent among individuals with lower socioeconomic status, with less fruit and vegetable consumption and higher consumption in refined products based on different household incomes, educational levels or occupational groups [27,28]. Apart from health problems most commonly related to overweight, such as diabetes or cardiovascular disease, overweight is also negatively associated with muscular strength [29,30] and increased risk for musculoskeletal pain [31,32]. Among blue collar workers in the construction sector, long-term sickness absence and work disability are primarily caused by MSD. When considering the high prevalence of MSD and overweight and the possible association between overweight/obesity and MSD, preventing and reducing excessive body weight among workers with a high physical work demand, might also be a strategy to decrease musculoskeletal

10 | Chapter 1


symptoms. Epidemiological studies have shown that some personal risk factors for MSD, such as high BMI, or lifestyle factors, such as smoking, are the same factors as those related to poor general health. Therefore, general health promotion might be an option to prevent MSD. In a systematic review of Proper et al. [33] it was concluded that there is strong evidence for positive effects of worksite physical activity programmes on physical activity and MSD. Since overweight and MSD are possibly associated, and (consequently) have joint risk factors, addressing these health related problems simultaneously should be considered. In order to prevent and reduce overweight and its related health and economic consequences, this thesis describes the systematic development and evaluation of a lifestyle and health-enhancing programme tailored to workers in the construction industry.

Worksite health promotion Although there is a variety of settings and contexts available to provide health promotion programmes, the WHO has described the workplace as one of the priority settings for health promotion into the 21st century [34]. Traditionally, worksite health promotion (WHP) has been concerned as a part of occupational safety and health, by influencing important health determinants at work, and as a strategy to reduce sickness absence. More recently, issues of productivity and sustainability, well-being and lifestyle choices have been addressed and WHP can be regarded even as a part of organisational development. The concept of WHP is becoming increasingly relevant as more employers recognise that (sustainably) realising organisational goals in the current competitive business environment, economic climate, with increasing pressure on the labour market, and in combination with an aging workforce, can only be achieved with a motivated and healthy workforce. WHP in the construction industry could contribute to a better balance between organisational targets on the one hand and employees’ health needs on the other. The worksite as setting for health promotion has several advantages. First, it provides the possibility to reach large groups, and the working population spends a large proportion of their waking hours at the workplace. These opportunities are of specific importance in construction workers who are often involved in shift work and spend a lot of time commuting to and from work. Second, there is the possibility to incorporate the programmes in existing organisational infrastructure and make use of existing communication and education channels. Third, the workplace provides the presence of a natural social network. In addition to efforts of worksite health programmes to increase health and vitality of the workforce, the worksite as setting provides opportunities to address health inequalities in the workforce. While for the population as a whole, and for all social classes, life expectancy has improved, social health inequalities remain. Generally, blue collar construction workers consist

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of a lower socioeconomic group than white collar workers. Physical working conditions explain part of the social gradient in health [35,36]. To improve health among lower socioeconomic status workers, workplace health promotion programmes need to focus on workers in blue collar occupations, especially since this group is harder to reach in general public health efforts. There is evidence that workplace programmes are both clinically effective and cost-effective in industries employing blue collar workers [37]. Thus, worksites are regarded as a promising context for health promotion while they provide many opportunities to reinforce health behaviours, especially in groups that are hard to reach outside this setting.

Context and project setting The project is part of a larger research programme ‘Vitality in Practice’ aiming at enhancing vitality of companies and their employees by developing and evaluating tailored worksite health promotion programmes. The study described in this thesis was developed and evaluated among blue collar construction workers employed by a large construction company. Investing in health and vitality of their workers is essential for the company to realise its ambitious goals, along with an aging and shrinking workforce. As other employers in the construction industry, the company was already engaged in WHP activities for their employees. WHP consists of various components and activities, such as for example periodic health screenings (PHS), company fitness programmes, and courses in smoking cessation. However, the health benefits, and effects on work-related outcomes, such as sickness absence and work ability, of these activities have not been identified. Moreover, it is not established whether these efforts reach the target population. Participation in these activities is on voluntary basis. As a result it is not clear if those most at risk are being reached. Based on studies on participation in health promotion programmes, it is hypothesised that low risk and healthier employees are more likely to enrol in worksite health programmes, and not necessarily those most in need [38,39]. As a result it is crucial to develop strategies to include all workers starting by investigating reasons for non-participation. In the previous paragraphs it was concluded that lifestyle behaviour is an important factor for the existence and increase in unhealthy body weight with health-impairing consequences. Since several risk factors are present in this particular group of workers, and potentially large health benefits can be obtained it seems justified to develop a sector specific approach. To increase likelihood of effectiveness, interventions should be developed systematically, need a theoretical basis, and should match the context and the target population [40,41]. Interventions designed for other target groups might not be suitable for this specific occupational group. Tailoring of WHP is relevant to address specific health concerns and health behaviours in construction workers, the specific work conditions and characteristics of the work setting. 12 | Chapter 1


Organisational factors that are involved in adoption of evidence-based interventions should also be included in the evaluation of the programme. Providing employers with information on the potential benefits of WHP, for example by including financial return data in the evaluation of programmes, might be an incentive for employers to invest in these activities [42,43]. This might also lead to increased implementation of research results into practice. Therefore, research is needed to gain more insight into the feasibility and (cost-)effectiveness of preventive measures in evidence-based intervention programmes, and to support organisational decision making.

Aims and outline of this thesis Following the rationale in the previous paragraphs, the primary aim of this thesis is to examine the effect of a tailored intervention developed in consultation with the target population and management of a construction company. To gain insight into prevention possibilities for overweight/obesity and musculoskeletal symptoms in blue collar workers it is important to further explore the relation between these major health concerns. Therefore, the current thesis addresses the following objectives: 1) To provide insight into the association of overweight/obesity and musculoskeletal symptoms, 2) To describe the systematic development of a worksite intervention tailored to a specific

group of workers,

3) To evaluate this newly developed intervention on its (cost-)effectiveness and evaluate the

process of implementation.

First, chapter 2 addresses the association between the central health problems in this thesis, overweight and musculoskeletal symptoms. It additionally examines the hypothesised interaction with work-related physical exposure. The second objective is introduced in chapter 3, describing the process of systematic development of the intervention and its evaluation plan. Chapters 4 to 7 describe the evaluation of the programme, and the trial results are presented in these chapters. Chapter 4 describes the results of the process evaluation following the RE-AIM framework. In chapter 5 the effects on physiological and behavioural outcomes are evaluated, and chapter 6 investigates the effects on musculoskeletal symptoms and several work-related outcomes. The purpose of chapter 7 is to explore the cost-effectiveness and return-on-investment of the VIP in Construction intervention from a societal as well as employer’s perspective. Finally, this thesis concludes with a general discussion in chapter 8, where the findings of this thesis are summarised and discussed. After discussing the applied theoretical model, methods, and results, future directions for research as well as practice are given.

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Chapter 2 The relation between body mass index and musculoskeletal symptoms in the working population

Laura Viester, Evert A. L. M. Verhagen, Karen M. Oude Hengel, Lando L.J. Koppes, Allard J. van der Beek, Paulien M. Bongers

BMC Musculoskeletal Disorders. 2013 12;14-238


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Abstract Background: The primary aim of this study was to investigate the association between BMI and musculoskeletal symptoms in interaction with physical workload. In addition, it was aimed to obtain insight into whether overweight and obesity are associated with an increase in occurrence of symptoms and/or decrease in recovery from symptoms. Methods: Based on a large working population sample (n = 44,793), using the data from The Netherlands Working Conditions Survey (NWCS), logistic regression analyses were carried out to investigate the association between BMI and musculoskeletal symptoms, with adjustment for potential confounders. Longitudinal data from the Netherlands Working Conditions Cohort Study (NWCCS) of 7,909 respondents was used for the second research aim (i.e., to investigate the transition in musculoskeletal symptoms). Results: For high BMI an increased 12-month prevalence of musculoskeletal symptoms was found (overweight: OR 1.13, 95% CI: 1.08-1.19 and obesity: OR 1.28, 95% CI: 1.19-1.39). The association was modified by physical workload, with a stronger association for employees with low physical workload than for those with high physical workload. Obesity was related to developing musculoskeletal symptoms (OR 1.37, 95% CI: 1.05-1.79) and inversely related to recovery from symptoms (OR 0.76, 95% CI: 0.59-0.97). Conclusion: BMI was associated with musculoskeletal symptoms, in particular symptoms of the lower extremity. Furthermore, the association differed for employees with high or low physical workload. Compared to employees with normal weight, obese employees had higher risk for developing symptoms as well as less recovery from symptoms. This study supports the role of biomechanical factors for the relationship between BMI and symptoms in the lower extremity.

18 | Chapter 2


Background Musculoskeletal disorders (MSDs) represent a considerable health problem in the working population, with low back pain (LBP) as one of the most common MSDs [1]. MSDs have a high impact on the individual worker, due to problems such as pain and limitations in daily activities. Moreover, it has consequences at society level, including employers, as MSDs have been identified as the most common cause of absenteeism from work and work disability [2] and generate high impact on healthcare costs and on costs due to productivity loss in particular [3-5]. As MSDs have a high impact for the individual as well as for society, it is important to gain insight in the risk factors of such disorders in order to find opportunities for prevention. The origin of MSDs is complex and multi-factorial. Amongst various risk factors, such as heavy lifting [6] and high job demands [7-9], it has been suggested that high body mass index (BMI) (overweight and obesity) might be an independent risk factor for MSDs. To date, the relationship between BMI and MSDs has mainly been investigated in studies on LBP [10]. These cross-sectional and cohort studies showed that overweight and obesity were associated with LBP [10]. While this relationship has been suggested, it could also be argued that BMI is associated with MSDs in other body regions. For symptoms of neck/shoulder, upper and lower limbs, evidence was also found that high BMI is an independent risk factor for the development of (symptoms of) MSDs [11-18]. Multiple hypotheses might explain the link between overweight and obesity and musculoskeletal symptoms including, amongst others, increased mechanical demands [19,20] and metabolic factors associated with obesity [19,21]. Increased forces across the joints are likely to play a larger role in the relationship between a high BMI and weight-bearing joints (back and lower extremities), compared to symptoms in non-weight-bearing joints (in the shoulder/neck and upper extremities). For carpal tunnel syndrome (CTS) an increase in upper extremity musculoskeletal symptoms associated with obesity has been attributed to increased adipose tissue in the carpal tunnel, causing median nerve compression [22,23]. Therefore, it seems relevant to make a distinction in different body regions because of potentially different (importance of) risk factors, underlying mechanisms, and natural course of the symptoms. Weight reduction in overweight and obese workers is assumed to reduce the incidence of musculoskeletal pain [24]. Since overweight and obesity are a growing public health problem, interventions reducing BMI could - if the hypothesised relationship exists - also be an effective primary and secondary prevention strategy for musculoskeletal symptoms. Epidemiological studies that have demonstrated that high BMI is linked to MSD have not revealed factors that explain this link. Among mechanical factors, adjustment for physical workload could affect the relationship between BMI and MSDs. Occupational physical workload has found to be associated with MSD [25,26]. In a working population, work-related physical load could modify the effect of high BMI on the prevalence of MSD. Our hypothesis is that in workers with high

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physical workload, the association in weight bearing joints will be increased, through additional physical strain, since overweight and obese individuals experience greater loads on their joints than normal-weight individuals. Analysis of the possible difference in the relationship between high BMI and musculoskeletal symptoms among workers by work-related physical exposure would provide directions for prevention strategies. The primary research aim of this study was therefore to cross-sectionally investigate the association between BMI and musculoskeletal symptoms in interaction with physical workload. Secondly, since MSDs are of episodic nature, it is of interest to obtain insight into whether high BMI is associated with an increase in occurrence of symptoms in a symptom-free population, or whether high BMI is associated with less recovery from symptoms in a population with symptoms at baseline occurs (or a combination of these options).

Methods Sample / Study population Based on a large working population cohort, we examined BMI in association with prevalence of musculoskeletal symptoms in employees, with adjustment for potential confounders. Additionally, within a subcohort, transitions in musculoskeletal symptoms were longitudinally investigated in relation to BMI. Data were obtained from The Netherlands Working Conditions Survey (NWCS) [27]. This dataset constitutes of a representative sample of the Dutch workforce in the 15–64 years age group, but excluded self-employed individuals. Each year, 80,000 individuals were sampled from the Dutch working population database by Statistics Netherlands. This database contains information on all jobs that fall under the worker national insurance schemes and are liable to income tax. Sampling was random, except for a 50% over-sampling of employees with lower response rates, namely employees under the age of 25 years and employees with a non-western background. Individuals in the sample received the questionnaire mailed to their home address. After three to four weeks, reminders were sent to those who had not yet responded. Data collection was stopped after two months. To be representative for employees in the Netherlands, the response was weighted for gender, age, sector, ethnic origin, level of urbanization, geographical region and level of education. The sample was extensively informed about the study in a letter that accompanied the questionnaire. The burden for respondents was low given the topics covered in the questionnaire. Consequently, and in accordance with ethics regulations in the Netherlands, ethical approval was not required for this study. A total of 44,793 employees completed the NWCS questionnaire in 2008 or 2009 (2008: n = 22,025, 2009: n = 22,768; overall response rate: 28%) and these employees were eligible for

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the cross-sectional analysis. In addition to the regular annual survey, respondents of the NWCS questionnaire in 2007, who gave consent for being contacted in the future, were invited to respond to follow-up questionnaires in 2008 and 2009 (Netherlands Working Conditions Cohort Study (NWCCS)). In this cohort, a total of 7,909 completed the NWCCS questionnaire in 2009 (response rate: 35%). Respondents who participated at follow-up were more often higher educated and slightly older than expected based on the NWCS sample. No selective differences were found for the dependent variables BMI and musculoskeletal symptoms. Data retrieved from the NWCCS of these 7,909 respondents were used for the second research aim (i.e., to investigate the transition in musculoskeletal symptoms). Measurement of BMI Self-reported body weight in kilogrammes (kg) and body height in centimetres (cm) were used to determine BMI. BMI was computed as weight (kg)/height (m)2. Subsequently, BMI was classified into three categories (normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25.0-29.9 kg/m2), and obese (BMI ≥ 30 kg/m2)), which is in accordance with the international classification system of the WHO [28]. Measurement of musculoskeletal symptoms The questions on musculoskeletal symptoms were based on the Dutch Musculoskeletal Questionnaire [29,30]. Employees were asked to rate the occurrence of pain or discomfort in the neck, shoulders, back, arms/elbows, hands/wrists, and lower extremity, in the previous 12 months using 6 questions with five answering categories (‘never’, ‘only once, of short duration’, ‘only once, prolonged’, ‘frequently, of short duration’, ‘frequently and prolonged’). Employees who answered ‘never’ or ‘only once, of short duration’ on all questions were classified as having no musculoskeletal symptoms. Those who answered ‘prolonged’ or ‘frequently’ for one or more locations were classified as having musculoskeletal symptoms overall. Hence, this overall prevalence is reported for any location, in addition to location-specific prevalences for which the responses on neck and shoulders were combined (neck/shoulder), as were those on arms/elbows and hands/wrists (upper extremity). Potential confounders and effect modifiers Employees were asked questions on current use of force, work in awkward positions, use of vibrating tools (tools, machines or vehicles), and repetitive motions on a 3-point scale (‘never’, ‘yes, occasionally’, yes, regularly’). Employees who answered ‘yes, regularly’ on use of force or work in awkward positions were classified as having high physical workload. Those who answered ‘no, never’ or ‘yes, occasionally’ on both questions were classified as having low physical workload.

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Additional potential confounders were gender, age, education (categorised into low, intermediate, and high educational level), contractual working hours (part time/full time), current smoking (yes/ no), and physical activity (days a week physically active for at least 30 minutes and of at least moderate intensity). Physical activity was dichotomized as physically active (yes/no) according to the Dutch public health recommendation for moderate intensity physical activity [31]. Analysis For the first research aim, using the weighted cross-sectional data, logistic regression analyses were carried out to investigate the association between BMI and musculoskeletal symptoms. The measure of association was expressed by the Odds Ratio (OR) and its 95% confidence interval (CI). In the categorical analyses involving BMI, the interval 18.5-24.9 was considered as the reference group. In adjusted analysis potential confounders were added to the regression model (full model). Effect modification was defined as a significant interaction term (p < 0.05) between potential effect modifiers (age, gender, physical workload) and BMI. Analyses were presented stratified for age, gender, or physical workload if the associations between BMI and musculoskeletal symptoms differed based on significant interaction terms. For the second research aim, using the cohort data (no weighting), the analyses were stratified for respondents without symptoms and those with symptoms in the baseline survey. To determine the difference in the risk of developing symptoms (occurrence) between employees who are overweight and those who are not, outcome was the 12-month incidence of musculoskeletal symptoms. Cases of musculoskeletal symptoms were identified as those who reported frequent or prolonged symptoms at follow-up. To study the influence of BMI on recovery from symptoms, a separate analysis for employees who reported frequent or prolonged symptoms in the last 12 months was performed. Hence, the OR expressed the association between the risk factor at baseline (high BMI) and transition from symptoms to no symptoms, or the reverse, at follow-up.

Results Characteristics and prevalence of symptoms Table 1 presents the characteristics of the cross-sectional sample. After excluding 865 employees with missing data on BMI (1.9%), and underweight employees (BMI < 18.5; 1.6%), in total 43,221 employees were included in the analysis. Of the employees with normal weight, 50% reported musculoskeletal symptoms within the past 12 months. Musculoskeletal symptoms were reported by 52.3% and 57.6% of the overweight and obese employees, respectively.

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Table 1. Sample characteristics of musculoskeletal symptoms, demographic, work, and lifestylerelated factors across BMI categories N Symptoms (overall) % Neck/Shoulder Upper Extremity Back Lower Extremity Gender Male Female Age (in years (sd)) Employment Full time (> = 36 hrs/wk) Part time (<36 hrs/wk) Physical workload: Repetitive motions Regular Occasional None Physical workload: Use of vibrating tools Regular Occasional None Physical workload: Use of force Regular Occasional None Physical workload: Awkward position Regular Occasional None Combined physical workload High Low Lifestyle-related factors Physically acive (yes) Smoking (yes)

Total 43,221 51.6 30.2 20.0 24.0 24.5

â&#x20AC;&#x2DC;Normalâ&#x20AC;&#x2122; weight 24,025 50.0 30.0 18.3 24.2 21.4

Overweight 14,905 52.3 29.7 21.0 23.3 26.7

Obese 4,291 57.6 33.0 26.2 26.0 34.3

54.2 45.8 40.3(12.1)

48.0 52.0 37.9(12.3)

64.4 35.6 43.1(11.2)

53.4 46.6 43.7(10.9)

56.5 43.5

51.8 48.2

63.7 36.3

57.0 43.0

33.8 22.1 44.2

33.1 22.3 44.6

33.4 22.0 44.7

38.8 21.2 40.0

9.5 9.0 81.5

8.0 8.2 83.8

11.0 10.1 78.9

12.0 9.9 78.1

19.2 22.5 58.3

18.9 21.6 59.5

19.1 23.0 57.9

20.6 24.9 54.4

10.6 25.9 63.5

10.0 25.6 64.4

11.3 25.9 62.8

11.9 27.3 60.9

22.0 78.0

21.7 78.3

21.9 78.1

23.6 76.4

52.5 27.6

54.8 28.1

50.3 26.9

47.5 27.0

Variables are presented as proportions, with the exception of age (mean (standard deviation)).

Associations between categories BMI and musculoskeletal symptoms Table 2 shows the ORs adjusted for age and gender, as well as the ORs after adjustment for all potential confounders (full model). Overall, high BMI (overweight and obesity) was associated with an increased 12-month prevalence of musculoskeletal symptoms. This association was significant for both overweight (OR 1.13, 95% CI: 1.08-1.19) and obesity (OR 1.28, 95% CI:

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1.19-1.39) regarding overall musculoskeletal symptoms. Regarding the specific body regions, overweight as well as obesity were associated with increased odds for symptoms. Overweight was associated with upper and lower extremity symptoms (OR 1.10, 95% CI: 1.03-1.17; OR 1.29, 95% CI: 1.21-1.36). Obesity was associated with neck/shoulder (OR 1.12; 95% CI: 1.031.21), upper extremity (OR 1.37, 95% CI: 1.25-1.50), back (OR 1.10, 95% CI: 1.01-1.20), and lower extremity symptoms (OR 1.68, 95% CI: 1.55-1.83). Additional (full model) adjustment for employment status (working full time/ part time), level of education, smoking status, physical workload factors, and physical activity level, did not affect the associations. Table 2 Cross-sectional associations between BMI and musculoskeletal symptoms Adjusted for age and gender Overall Neck/shoulder Upper extremity Back Lower extremity Normal weight 1.00 1.00 1.00 1.00 1.00 Overweight 1.14 1.04 1.14 1.03 1.31 (1.09-1.19) (0.99-1.09) (1.08-1.21) (0.98-1.08) (1.24-1.37) Obese 1.35 1.13 1.45 1.10 1.82 (1.26-1.44) (1.06-1.22) (1.34-1.57) (1.02-1.19) (1.69-1.96) Adjusted for age, gender, smoking, education, contractual working hours(part-time/full-time), use of force, work in awkward positions, use of vibrating tools, repetitive motions, and physical activity Normal weight Overweight Obese

1.00 1.13 (1.08-1.19) 1.28 (1.19-1.39)

1.00 1.03 (0.98-1.09) 1.12 (1.03-1.21)

1.00 1.10 (1.03-1.17) 1.37 (1.25-1.50)

1.00 1.02 (0.96-1.08) 1.10 (1.01-1.20)

1.00 1.29 (1.21-1.36) 1.68 (1.55-1.83)

Data are presented as Odds Ratios (95% confidence interval), with normal weight as reference category. Significant associations are printed in bold.

No effect modification on the association between BMI and musculoskeletal symptoms was found for age or gender. For physical workload, effect modification was found, meaning that the association between BMI and both overall musculoskeletal symptoms and lower extremity symptoms differed between employees with low and high physical workload. This effect modification was not found for neck/shoulder, upper extremity, and back symptoms. Tables 3 and 4 present the model for musculoskeletal symptoms overall and lower extremity symptoms among employees with high as well as low physical workload. Musculoskeletal symptoms overall and lower extremities were reported significantly more often by obese and overweight employees with low physical workload compared to normal weight employees with low physical workload. For high physical workload, only an association was found for obesity and lower extremity symptoms.

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Table 3 Prevalence of musculoskeletal symptoms across BMI categories presented separately for high and low combined physical workload Physical workload = low Overall Neck/Shoulder Upper Extremity Back Lower Extremity Physical workload = high Overall Neck/Shoulder Upper Extremity Back Lower Extremity

Total N = 31,622 15,135 8,621 5,349 6,935 6,317 N = 8,897 5,713 3,231 2,355 2,424 3,220

â&#x20AC;&#x2DC;Normalâ&#x20AC;&#x2122; weight N = 17,709 8,156 4,839 2,754 3,944 2,982 N = 4,905 3,141 1,778 1,202 1,347 1,678

Overweight N = 10,873 5,323 2,869 1,905 2,276 2,422 N = 3,052 1,940 1,101 858 809 1,137

Obese N = 3,040 1,656 913 690 715 913 N = 940 632 352 295 268 405

Table 4 Associations between BMI and Overall musculoskeletal symptoms and Lower Extremity symptoms stratified for physical workload Physical workload = high (n = 8,897) Normal weight Overweight Obese Physical workload = low (n = 31,623) Normal weight Overweight Obese

Overall 1.00 0.98 (0.88-1.09) 1.08 (0.92-1.28)

Lower extremity 1.00 1.07 (0.96-1.19) 1.28 (1.09-1.50)

1.00 1.17 (1.11-1.24) 1.34 (1.23-1.46)

1.00 1.38 (1.29-1.48) 1.86 (1.69-2.05)

*Neck/shoulder, upper extremity and back ORs are not presented separately, since no effect modification was found for these body regions. The complete model is presented in Additional files 1 and 2. Data are presented as Odds Ratios (95% confidence interval), with normal weight as reference category, adjusted for age, gender, smoking, education, contractual working hours(part-time/full-time), use of vibrating tools, repetitive motions, and physical activity (full model). Significant associations are printed in bold.

Effects on the development and recovery of musculoskeletal symptoms Table 5 presents the effects of BMI on developing musculoskeletal symptoms for employees without symptoms at baseline. The findings on overall symptoms indicated that being obese statistically significantly increased the risk of developing musculoskeletal symptoms during 12-month follow-up (OR 1.37, 95% CI: 1.05- 1.78). Regarding the different body regions, the relationship also existed for lower extremity symptoms for overweight employees (OR 1.35, 95% CI: 1.13-1.61), and for obese employees (OR 2.12, 95% CI: 1.64-2.73). For the upper extremity

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there was an effect of BMI on occurrence of symptoms for overweight employees (OR 1.22, 95% CI: 1.01-1.46) and for obese employees (OR 1.51, 95% CI: 1.14-1.98). In obese employees the OR was higher than in overweight employees, suggesting a doseâ&#x20AC;&#x201C;response relationship. Table 5 Occurrence and recovery of musculoskeletal symptoms after 12 months for categories of BMI (overweight and obese), adjusted for age and gender Occurrence (from no symptoms to symptoms) Overall Neck/shoulder N = 3,663 N = 5,071 Normal weight 1.00 1.00 1.17 1.07 Overweight (0.99-1.37) (0.90-1.28) 1.37 1.00 Obese (1.05-1.79) (0.76-1.33) Recovery (from symptoms to no symptoms) Overall Neck/shoulder N = 3,841 N = 2,086 Normal weight 1.00 1.00 0.97 0.99 Overweight (0.82-1.13) (0.82-1.22) 0.76 0.95 Obese (0.59-0.97) (0.70-1.30)

Upper extremity N = 5,591 1.00 1.23 (1.01-1.47) 1.51 (1.14-1.98)

Back N = 5,085 1.00 1.13 (0.95-1.35) 0.94 (0.69-1.28)

Lower extremity N = 5,410 1.00 1.34 (1.13-1.60) 2.11 (1.64-2.72)

Upper extremity N = 1,378 1.00 0.95 (0.75-1.21) 0.84 (0.59-1.18)

Back N = 2,005 1.00 1.06 (0.86-1.30) 0.99 (0.73-1.33)

Lower extremity N = 1,667 1.00 0.80 (0.65-1.00) 0.57 (0.42-0.78)

Data are presented as Odds Ratios (95% confidence interval), with normal weight as reference category.

Table 6 Associations between BMI and Overall musculoskeletal symptoms and Lower Extremity symptoms Normal weight and low workload Normal weight and high workload Overweight and low workload Overweight and high workload Obese and low workload Obese and high workload

Overall 1.00 2.22 (2.06 - 2.39) 1.18 (1.11 - 1.24) 2.21 (2.02 - 2.42) 1.36 (1.25 - 1.48) 2.47 (2.12 - 2.89)

Lower extremity 1.00 2.50 (2.31 - 2.71) 1.37 (1.29 - 1.47) 2.78 (2.53 - 3.06) 1.88 (1.70 - 2.07) 3.29 (2.82 - 3.82)

Data are presented as Odds Ratios (95% confidence interval), with normal weight and low workload as reference category, adjusted for age, gender, smoking, education, contractual working hours(full-time/parttime), and physical activity.

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Table 7 Univariable and multivariable associations between BMI, workload, and BMI*workload and musculoskeletal symptoms Univariable model

BMI Normal weight Overweight Obese Combined workload Low physical workload High physical workload Multivariable model BMI Overweight Obese High physical workload BMI*combined workload Overweight*workload Obese*workload

Overall

Neck/ shoulder

Upper extremity

Back

Lower extremity

1.00 1.13 (1.08-1.19) 1.28 (1.19-1.39)

1.00 1.03 (0.98-1.09) 1.12 (1.03-1.21)

1.00 1.10 (1.03-1.17) 1.37 (1.25-1.50)

1.00 1.02 (0.96-1.08) 1.10 (1.01-1.20)

1.00 1.29 (1.21-1.36) 1.68 (1.55-1.83)

1.00 1.77 (1.66-1.88)

1.00 1.48 (1.39-1.58)

1.00 1.46 (1.36-1.57)

1.00 1.37 (1.28-1.47)

1.00 1.84 (1.72-1.97)

1.18 (1.12-1.24) 1.34 (1.23-1.46) 1.92 (1.77-2.08) P = 0.003 0.84 (0.74-0.94) 0.81 (0.67-0.98)

1.04 (0.98-1.11) 1.14 (1.04-1.25) 1.52 (1.40-1.65) P = 0.610 0.97 (0.85-1.09) 0.91 (0.76-1.11)

1.10 (1.02-1.18) 1.41 (1.27-1.56) 1.49 (1.36-1.64) P = 0.600 0.98 (0.85-1.12) 0.90 (0.73-1.10)

1.03 (0.96-1.10) 1.11 (1.00-1.23) 1.39 (1.27-1.51) P = 0.950 0.98 (0.86-1.12) 0.98 (0.80-1.20)

1.39 (1.30-1.48) 1.86 (1.69-2.05) 2.11 (1.93-2.30) P <0.00001 0.77 (0.68-0.88) 0.69 (0.57-0.83)

Data are presented as Odds Ratios (95% confidence interval), mutually adjusted, and adjusted for age, gender, smoking, education, contractual working hours(part-time/full-time), use of vibrating tools, repetitive motions, and physical activity. Significant associations are printed in bold. The effect of BMI on the recovery from musculoskeletal symptoms after 12 months of follow-up is also presented in Table 5. Employees with obesity recovered less often from musculoskeletal symptoms than employees with normal weight (OR 0.75, 95% CI: 0.59 0.96). This relationship was also found for symptoms in the lower extremity (OR 0.57, 95% CI: 0.42-0.78).

Discussion The primary aim of this study was to examine the association between BMI and musculoskeletal symptoms in interaction with physical workload. Overall, high BMI (overweight and obesity) was moderately associated with an increased prevalence of musculoskeletal symptoms in the past 12 months. This association was modified by physical workload. Regarding the second research aim, our longitudinal results showed that for obese employees the association was caused by an increased risk of developing musculoskeletal symptoms during 12-month follow-up as well as less recovery from musculoskeletal symptoms compared to employees with normal weight. The relation between body mass index and musculoskeletal symptoms in the working population | 27

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Lower extremity Consistent with findings from other studies [31,32] we found the association to be strongest for lower extremity symptoms. The most common joint diseases that cause lower extremity symptoms are osteoarthritis (OA) and rheumatoid arthritis (RA), whereas other causes include musculoskeletal injuries. In the literature it is also suggested that knee pain is a more persistent type of pain, supporting the hypothesis for OA as the cause for symptoms. However, in this cohort lower extremity symptoms were not found to be more persistent than other symptoms in normal weight individuals (data not shown). Obesity had a significant negative effect on recovery from lower extremity symptoms (OR 0.57). Obesity has also, among those with OA as well as in the general population, been found to be associated with disability in mobility [32]. Therefore, biomechanics may explain part of the contribution of the effect of excessive weight on lower extremity symptoms. Upper extremity, and neck/shoulder The association between high BMI and upper extremity as well as neck/shoulder symptoms could be supporting a non-mechanical hypothesis. This hypothesis is supported by studies showing the association between BMI and the development of OA in non-weight bearing joints, such as the hands [15,33], as well as the link between high BMI and other rheumatic diseases, such as fibromyalgia [34-36]. In a study aimed at weight loss among an obese working population [37] upper extremity symptoms (except for shoulder complaints) decreased with weight loss. In this study it was suggested that many obese subjects use their upper extremities as weight bearing limbs when arising from a seated position, which may account for the increased upper extremity symptoms in obese subjects. However, this explanation is less likely for overweight (non-obese) individuals, for whom in the present study also an association was found. For the upper extremity, an effect of BMI on occurrence of symptoms was found, but not on recovery from symptoms. Overall, the results on upper extremity and neck/shoulder symptoms indicate that most likely metabolic factors are part of the underlying mechanism in the association with high BMI. Back Yet, in contrast to studies included in a recent meta-analysis [10] no association for overweight and back symptoms in the past 12 months was found. The strength of the association with obesity was modest comparable to the pooled OR from the meta-analysis (1.10 vs. 1.33). Additionally, neither for occurrence nor recovery of back symptoms, overweight or obesity was found to be a risk factor. The finding that workers with high BMI are not at higher risk for developing back symptoms than workers with a normal BMI is in line with a prospective cohort study among health care workers [38].

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Physical workload It has been argued that for MSD, physical workload as a risk factor itself is more important than BMI [38]. In a study on risk factors for LBP the strength of the association with workload and health behavior (sum of BMI, physical exercise, and smoking) was found to be age-related; workload predicted LBP among those younger than 50 years while health behavior increased the risk among those 50 years or older [39]. In the present study, the association between BMI and MSD differed between employees with low and high physical workload. For musculoskeletal symptoms overall and lower extremity symptoms the association was stronger in those with low physical workload compared to those with high physical workload. No effect modification was found for upper extremity, neck/shoulder, or back symptoms. Contradictory to our hypothesis, the association of BMI and lower extremity symptoms was found to be weaker for employees with higher physical workload. This implies that the association may not be simply due to weight related increased excessive loading of the joint. Based on these results, it is possible that for employees with high BMI and high physical workload, muscle mass around the knee joint is protective for the development of MSD. Weakness of the quadriceps have been considered a primary risk factor for knee pain and disability in persons with OA [40]. There is evidence to hypothesise that muscle mass protects the knee joint, with increased muscle strength protecting against incidence knee OA (greater joint stability and cartilage volume) [41]. Further support for this explanation comes from research on functional limitations as a consequence of obesity. Increased body mass can have negative influences on the control of postural stability and locomotion [42]. Poorer balance was found to be associated with higher pain in the presence of less muscle strength [43]. Support for this notion also comes from literature that shows that muscle strengthening, as a part of treatment, reduces disability from MSD [44-46]. In addition, loss of muscle mass as well as central obesity (not BMI) were found to be possible risk factors for LBP [47]. Methodological strengths, and limitations The main strength of this study is the large sample that included a nationally representative sample of the Dutch workforce. This provided sufficient statistical power to examine overweight and obesity in association with musculoskeletal symptoms in employees for physical workload categories, as well as different locations of symptoms. Some limitations should be considered as well. The study is conducted in a worker population, and when translating the results to the general population, the healthy worker (survival) effect should be taken into account. By exploring the association in a working population it is possible that workers, who have severe MSD, are no longer employed or change to work with lower exposure. In the analysis the association was controlled for several potential confounding factors, however some potential psychosocial confounders, for instance stress, anxiety or depression disorders, were not measured, and consequently could not be controlled for.

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The use of self-reported measures could be considered a limitation as they are susceptible to possible bias. Self-reported workload might be biased by the presence of symptoms. In workers performing the same job, workers with MSD reported higher exposure rates than workers without MSD [48]. However, in the present study self-reported workload was used to identify high exposure from low exposure, with highly contrasting jobs and working conditions. Misclassification in categories BMI, as a result of underreporting of body weight, could hypothetically lead to underestimation of the association with MSD. Furthermore, BMI as a measure does not discriminate adipose from non-adipose body mass, nor does it indicate the distribution of body fat. Stronger associations with abdominal obesity than general obesity and LBP were found in population-based studies [49]. Additional measurements of fat distribution would provide insight in possible factors of the mechanism of the effect (posture, loading etc.). For the first research question the cross-sectional design prevents conclusions of causality. Weight gain may also occur as a consequence of musculoskeletal pain and physical inactivity. Therefore, the measured BMI may not in all cases reflect BMI before the onset of symptoms. Weight gain following the onset of symptoms (e.g. because of reduced physical activity due to symptoms) may have caused overestimation of the associations. For the second research aim prior history (>1 year) of symptoms are not taken into account. In this study, the definition of the symptom-free population was based on reporting no symptoms in the previous 12 months, which is considered long enough to exclude those with frequently recurring symptoms. Selection bias may have occurred as a result of the low response rate. Persons lost to follow-up were younger and less often highly educated than those who responded to the follow up questionnaire. However, no difference was found for BMI and dependent variables musculoskeletal symptoms between those lost to follow-up and respondents.

Conclusions In summary, in this study, BMI was associated with musculoskeletal symptoms, in particular symptoms of the lower extremity. Furthermore, the association was stronger for employees with low physical workload compared to those with high physical workload. Compared to employees with normal weight, obese employees had higher risk for developing symptoms as well as less recovery from symptoms. This study supports the role of biomechanical factors for the relationship between BMI and MSD in the lower extremity. With an increasing public health problem resulting from overweight and obesity, and since overweight and obesity are a preventable or modifiable risk factor, these findings give directions to prevention strategies. The risk on musculoskeletal health problems should be taken into account in primary as well as secondary prevention strategies. To address MSD in a worker population, weight loss or preventing weight gain strategies alone may not be sufficient. The

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physical consequences of loading of major structures, particularly in the lower extremity as a consequence of overweight and obesity deserve attention.

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Chapter 3 VIP in construction: systematic development and evaluation of a multifaceted health programme aiming to improve physical activity levels and dietary patterns among construction workers

Laura Viester, Evert A. L. M. Verhagen, Karin I. Proper, Johanna M. van Dongen, Paulien M. Bongers, Allard J. van der Beek

BMC Public Health. 2012 30;12;89


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Abstract Background: The prevalence of both overweight and musculoskeletal disorders (MSD) in the construction industry is high. Many interventions in the occupational setting aim at the prevention and reduction of these health problems, but it is still unclear how these programmes should be designed. To determine the effectiveness of interventions on these health outcomes randomised controlled trials (RCTs) are needed. The aim of this study is to systematically develop a tailored intervention for prevention and reduction of overweight and MSD among construction workers and to describe the evaluation study regarding its (cost-)effectiveness. Methods/Design: The Intervention Mapping (IM) protocol was applied to develop and implement a tailored programme aimed at the prevention and reduction of overweight and MSD. The (cost-) effectiveness of the intervention programme will be evaluated using an RCT. Furthermore, a process evaluation will be conducted. The research population will consist of blue collar workers of a large construction company in the Netherlands. Intervention: The intervention programme will be aimed at improving (vigorous) physical activity levels and healthy dietary behaviour and will consist of tailored information, face-to-face and telephone counselling, training instruction (a fitness â&#x20AC;&#x153;cardâ&#x20AC;? to be used for exercises), and materials designed for the intervention (overview of the company health promoting facilities, waist circumference measuring tape, pedometer, BMI card, calorie guide, recipes, and knowledge test). Main study parameters/endpoints: The intervention effect on body weight and waist circumference (primary outcome measures), as well as on lifestyle behaviour, MSD, fitness, CVD risk indicators, and work-related outcomes (i.e. productivity, sick leave) (secondary outcome measures) will be assessed. Discussion: The development of the VIP in construction intervention led to a health programme tailored to the needs of construction workers. This programme, if proven effective, can be directly implemented.

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Background The worldwide prevalence of overweight and obesity is increasing at a high rate. This also affects the Dutch population, where in 2009, according to the Central Bureau of Statistics Netherlands (CBS), more than 50% of the male population and 40% of the female population was overweight [body mass index (BMI) ≥ 25 kg m-2] [1]. Of this population 11% of the men and 12% of the women were obese (BMI ≥ 30 kg m-2). Excess body weight is associated with increased mortality and morbidity rates. To illustrate, obesity has a short-term negative impact on health, e.g. musculoskeletal disorders [2-5], as well as long-term consequences, e.g. diabetes mellitus type II and cardiovascular disease [6,7]. In addition to health-related problems in the individual, overweight and obesity are related to work-related measures, such as increased sick leave and decrease of productivity [8-14]. More than 10% of sick leave and productivity loss at work may be attributed to lifestyle behaviours and obesity [14]. Consequently, the economic consequences of overweight and obesity are high. In the Netherlands the annual direct costs have been estimated at €500 million, approximately 2% of the total national health care costs [15]. However, the indirect costs resulting from work absence and work disability related to overweight and obesity are estimated at €2 billion [16]. Recent data obtained from periodic health screenings among 39,400 construction workers showed that the prevalence of overweight and obesity in construction workers is higher than in the general Dutch adult population. Of all construction workers 63% is overweight and 15% is obese [17]. It is argued that within this specific population negative health-related lifestyle factors (e.g. low levels of daily life physical activity, smoking, and dietary patterns) are more prominently present than in the general population. Furthermore, the average age of construction workers has been steadily increasing in the past decade, and will do so in the decade ahead. As a result, employee health is an important concern for the construction industry, both from a corporate social responsibility as well as a risk management view. Fit and healthy employees working in a healthy environment are of critical importance to realise organisational goals. Operating in a highly competitive business environment with increasing pressure on the labour market, and an aging workforce, employers are becoming aware that they need to implement measures to improve productivity and efficiency, and to invest in the health of their employees. Workplace health promotion has been shown to play a major role in achieving such outcomes; directly by educating the workforce and providing opportunities for physical activity, and indirectly by influencing social norms [18]. Workplace health promotion may constitute of a diverse set of health promoting activities, such as periodic health screenings (PHS), courses in smoking cessation, and enhanced access to physical activity. Many employers are offering such fringe benefits to their employees. However, the health enhancing effects of these facilities are not yet identifiable and it remains unclear whether the actual group of workers at risk is being reached. It has been argued that these facilities are predominantly used by the healthy part of the workforce. Therefore, in

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order to increase effectiveness it is crucial to provide a supporting health promotion programme that promotes the utilisation of the offered health enhancing facilities by employees with lifestylerelated risk factors for disease. The overall aim of this study is to develop and evaluate such a supporting health promotion programme (VIP in Construction). More specifically the current study aims to systematically develop a tailored intervention programme for the prevention and reduction of overweight and musculoskeletal disorders (MSD) in construction workers and to describe the evaluation study regarding the (cost-)effectiveness of this programme.

Methods The present study consists of 2 phases. In the first phase a health enhancing intervention was developed, tailored specifically to the possibilities, needs and wishes of the management and employees of the participating construction company. The second phase of this study involves the evaluation of the intervention. The â&#x20AC;&#x153;VIP in constructionâ&#x20AC;? intervention was systematically designed based on the Intervention Mapping (IM) protocol [19]. IM describes a process for developing theory- and evidence-based health promotion programmes, and involves a systematic process that prescribes a series of six steps: (i) performing a needs assessment; (ii) defining suitable programme objectives; (iii) selecting theory-based intervention methods and practical strategies; (iv) producing programme components and materials; (v) designing an implementation plan; and (vi) designing an evaluation plan (Figure 1). Collaboration between the developers, the users of the intervention and the target population is a basic assumption in the IM process [19]. This paper describes in detail the development of a health enhancing intervention programme for construction workers by using the steps of the IM process. Step 6 of the process describes in detail how the (cost-) effectiveness of the developed programme will be evaluated.

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Figure 1 Steps of the Intervention Mapping process.

Phase 1: Intervention development Step 1: Needs assessment Literature was reviewed and interviews, questionnaires, and focus group interviews with management, employees and other stakeholders were carried out. This provided insight into the ruling health issues, underlying risk factors (behaviour and environmental conditions), and determinants of the underlying behaviours. In addition, the reach, success and failure factors of current company health promotion activities were summarised. This needs assessment results in the formulation of programme outcomes. Health problem and target group The target group for this intervention was specified as all blue collar workers of a construction company. From interviews with the management of the company and from information obtained from Occupational Health Services (OHS) reports it was concluded that the main health concerns for the target population are overweight and MSD. In general, in the construction industry MSD are the primary reason for long-term sickness absence and disability [20,21]. Also the company records show that long-term sickness absence among blue collar workers is mainly caused by MSD. Especially in professions with heavy physical demands, such as those in the construction industry, muscle fatigue or musculoskeletal discomfort may be perceived during work and may eventually

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result in musculoskeletal pain [22]. Several work-related physical factors have been identified that can increase the risk of musculoskeletal pain among workers [22-27]. Besides work-related factors, health-related factors, such as obesity may play a role in musculoskeletal pain. Findings of a meta-analysis on the association between obesity and low back pain indicate that overweight and obesity increase the risk of low back pain [5]. In a cohort study of construction workers [28] it was found that MSD represent the most frequent cause of work disability and that obesity increased this risk. Since overweight and MSD are possibly associated, the intervention will aim at addressing these health problems together. Key determinants & risk factors for overweight and MSD Literature was reviewed to identify which theoretical constructs best predict overweight and MSD. Energy-balance-related behaviour is an important factor to consider in the development of health interventions aiming at healthy lifestyle. Weight gain, overweight, and obesity have been associated with various specific behaviours related to diet and physical activity. Risk factors for obesity are considered to be: sedentary lifestyles (i.e., time spent sitting), a high intake of energy-dense high-fat and low-fiber diet, consumption of sugar-sweetened soft drinks, frequent snacking, and large portion sizes [29,30]. Protective factors against obesity are considered to be: regular physical activity and consumption of a high-fiber diet (for instance, a diet high in fruits and vegetables) [29,30]. MSD have a multifactor origin, several work-related and non work-related risk factors contribute to their development [22,31,32]. According to the model of workload and capacity by Van Dijk et al. [33], health effects may result from an imbalance between workload and capacity. A prospective study of Hamberg-van Reenen et al. (2006) [34] confirmed that an imbalance between physical capacity and exposure to work-related physical factors was a risk factor for future musculoskeletal pain. For example, it is generally assumed that for workers with high muscle strength, high exposure to physical factors may result in less musculoskeletal pain than for workers with low muscle strength [35]. Questionnaire and focus group interviews In order to be relevant, the intervention needs to account for the lifestyle habits and preferences of the target group. Therefore, to obtain information on specific dietary and physical activity behaviour in the target group, a short questionnaire was completed by a sample of 42 construction workers. These specific behaviours were further discussed in the focus group interviews. The aims of the focus groups were: identifying the main and modifiable determinants of the lifestyle behaviours (physical activity and diet), risk factors for MSD, and the reach and participation of the current company health promoting activities. Also, input from the focus group interviews was used to determine the content and design of the intervention. A total of 8 focus group interviews

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with construction workers (n = 62) were carried out. The focus group interviews were held at different worksites of the company to reach workers from different professions, and participants were randomly selected to avoid getting input only from workers who are already motivated to participate in health programmes. Risk factors and determinants for the health problems Health beliefs and health behaviours related to diet and physical activity were discussed in focus group interviews. From the focus group interviews it could be concluded that workers have some basic knowledge of nutritional standards, but they are not aware of their personal intake levels. The methods most often listed by the construction workers to improve their energy balance were less snacking and reducing alcohol consumption. Further solutions mentioned: decreasing intake of sugar-sweetened beverages or replacing them with healthier options, increasing fruit intake, and decreasing dinner portion size. From the focus group interviews we also learned that, in general, the workersâ&#x20AC;&#x2122; partner mainly determines the food choice at home, and the workers preferred to get personalised information on diet, as opposed to general information. The interviewed workers indicated that they believed that their work activities provided enough physical activity. However, from periodic health screening data [17] it is clear that a substantial percentage of workers still do not reach healthy levels of physical activity according to the Nederlandse Norm Gezond Bewegen (NNGB) (33%) and the guideline to achieve a good fitness level (Fitnorm) (80%). According to physical activity guidelines these levels should be achieved to improve and maintain health [36]. Workplace physical demands, such as manual material handling (lifting heavy objects), extreme weather and workplace conditions (uneven terrain, awkward working postures), work pace and planning were most mentioned to be risk factors at work for developing MSD. Also behavioural risk factors were mentioned, such as not taking enough rest-breaks during work, wrong work posture, and wrong use of (ergonomic) work aids. A social/managerial factor that was considered important was poor communication between supervisors and the workers concerning problems or solutions for prevention or reduction of MSD in combination with perceived barriers for addressing those problems. Intervention input from focus group interviews Although poor physical fitness was not frequently mentioned as one of the risk factors for MSD in the focus groups, improving physical capacity was mentioned as a possible preventive measure or solution. According to the literature increasing vigorous physical activity (PA) is a preventive method that targets body weight control as well as MSD [37-42]. Strong evidence was found for the effectiveness of workplace physical activity programmes in increasing strenuous physical activity levels as well as in preventing MSD [43].

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To design a feasible intervention programme, the reach of current company health promoting activities and the requirements and design for an intervention programme were also discussed in focus group interviews. From the interviews amongst employees it could be concluded that the current health promoting activities were not optimally reaching the workers. The most important reason indicated by the interviewees was that workers were not aware of the present prevention practices, i.e. that these were not communicated in the right way. Also those who were aware of the possibilities (e.g., the reduction of gym membership fees) were often under the impression that these measures were mainly initiated for office workers of the company. From the interviews it became clear that communicating the health promoting activities in a suitable manner for the target group should be an important objective for the intervention programme. Furthermore, workers were asked about the necessary requirements and design for an intervention programme in order to reach non-participants and motivate them to participate in prevention programmes. Workers argued that an intervention programme should focus on communicating personal health risks, since perceived health was considered to be a necessary motivator for changing behaviour. From the focus group interviews we learned that the regular company periodic health screening (PHS) was generally seen as a positive starting point for discussing lifestyle. However, during the PHS there is often not enough time to discuss the outcomes. It became clear that linking the intervention to the PHS could improve participation to worksite health promoting activities. Programme objectives and outcomes The needs assessment indicated that the intervention should address both dietary habits and physical activity with the overall programme objective being the prevention and reduction of overweight and MSD among construction workers. In addition, to specifically target and prevent MSD by improving physical capacity, workers could be stimulated to increase their general physical activity by means of specific exercises, sports, and daily physical activities during leisure time. Based on literature and focus group input, intervention strategies to prevent or reduce MSD could focus on (1) increasing physical capacity by improving general physical activity or specific exercises and/or (2) decreasing workload. However, there was no management support for implementing strategies aimed at decreasing workload. The management indicated that other company projects have already started considering physical workload; therefore decreasing workload is not a programme objective for the VIP in construction intervention. The risk behaviours described in the needs assessment were translated into health-promoting behaviours. The health behaviours that should be targeted were then formulated in programme outcomes of the VIP in construction intervention, and are presented in Table 1.

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Table 1 Programme outcomes Programme outcomes 1) Energy intake quantity: Workers reduce their energy intake by decreasing portion size and alcohol consumption 2) Energy intake quality: Workers replace energy dense products by healthier options (fibre rich products and beverages without sugar) 3) Energy output quantity: Workers increase their levels of physical activity 4) Energy output quality: Workers perform specific exercises to prevent or reduce MSD

Step 2: Performance objectives, determinants, and change objectives Step 2 provides the foundation for the intervention programme by specifying who and what will change as a result of the intervention. The product of this step is a set of matrices that combines performance objectives with selected personal and external determinants to produce the target of the intervention (change objectives). Performance objectives The programme outcomes formulated in the needs assessment were translated into performance objectives: what do the participants have to do to accomplish these outcomes? Based on the self-regulation theory and determinants for behaviour obtained from literature and focus group interviews, performance objectives were stated for each of the programme objectives. As an example, the performance objectives for the third programme objective are illustrated in Table 2. Table 2 Performance objectives Performance objective related to Programme Outcome 3: â&#x20AC;&#x153;Workers increase their levels of physical activityâ&#x20AC;? Workers should: 1) Self-monitor physical activity 2) Set goals to increase physical activity levels 3) Form implementation intentions 4) Implement healthy levels of physical activity 5) Evaluate personal goals

Determinants of behaviour change IM states that for health promotion intervention development, instead of searching for predictors of present behaviour, health-related behaviour (e.g. high energy intake) should be translated into a health-promoting behaviour or behaviour change (e.g. energy intake reduction) and then search for determinants of the required change. The determinants for the performance objectives in this study were based on literature review and focus group interviews and were selected on importance and changeability for the specific target group. The following personal and external

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determinants for physical activity were identified: skills, self-efficacy, attitudes, barriers, habits, outcome expectations, resources, awareness, risk perception, and health beliefs. For dietary behaviour, the following personal and external determinants were selected for this intervention: knowledge, awareness, risk-perception, health beliefs, habits, and social support. The conceptual

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MSD

Social influence

Figure 2 Conceptual model of the VIP in Construction intervention.

Physical activity Dietary behaviour Sedentary behaviour

Body composition (weight, BMI, WC) Physical fitness Physiological measures (BP, Chol)

Knowledge Skills Awareness Health beliefs Risk perception Outcome expectations

Key determinants

Attitude

Self-efficacy

Intention stage

barriers

habit

Energy related behaviour

Health related factors

Health

health problem

Work related outcomes

Sick leave Productivity Vitality Work ability Work satisfaction

model of the VIP in construction intervention is described in Figure 2.

intervention

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Change objectives Change objectives were created by crossing performance objectives with determinants in a matrix. An example of the matrix for performance objective 3 is given in Table 3. Table 3 Selected change objectives for performance objective 3 Performance Objectives PO.3. â&#x20AC;&#x153;Workers increase their levels of physical activity (by increasing PA of vigorous intensity and decreasing sitting time)â&#x20AC;?

Skills and self-efficacy

PO.3.1 Self-monitor physical activity

SSE.3.1 Know how to self-monitor PA

PO 3.2.Set goals to increase physical activity levels

SSE.3.2 Express confidence for setting goals to increase PA levels

Awareness and attitudes A.3 Express positive attitude towards increasing levels of physical activity

A.3.1 Express positive attitude towards self monitoring of PA A.3.2 Express positive attitudes towards goal setting

Outcome expectations OE.3.Expect that increasing levels of physical activity will have positive health outcomes

OE.3.2. Expect that goal setting will increase PA levels

Step 3: Methods and strategies After constructing the change matrices, the next step was to select appropriate theoretical methods for behaviour change and to translate these into practical strategies. Theory-based intervention methods For each determinant (e.g. self-efficacy, skills, knowledge, social support) appropriate theoretical methods were identified from literature and from guidance of Bartholomew et al. (2006) [19]. Theoretical input for these methods and strategies was derived from behavioural theory literature. This includes health behaviour models (theory of planned behaviour (TPB) [44] and the health belief model (HBM) [45]) as well as behaviour change models (transtheoretical model (TTM) [46] and the precaution adoption process model (PAPM)[47]). Decisions about suitable strategies were made based on feedback of key contacts within the organisation, and focus group data. These were then translated into strategies suitable for implementation in the workplace. The results of this step are presented in Tables 4 and 5.

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b) External Social support

Awareness, risk perception & health believes

Habits

Awareness of personal intake levels

Determinant a) Personal Knowledge

Mobilising social support from spouse/family

Providing healthy recipes tailored to target population

Test recipes

Calorie guide (# min PA required to lose a certain amount of calories)

Awareness of own body composition Waist circumference measuring tape BMI by self-monitoring card

Re-evaluation, self-evaluation, and consciousness raising

Delivering information on the relationship between calories & PA

Providing tailored risk information on Tailored brochures long-term effects and information on benefits of healthy behaviour

Scenario-based risk information

Expert monitoring and evaluation of BMI, waist circumference, blood pressure, behaviour etc. in relation to healthy standards (PHC)

Personal feedback PHC PHC assists in formulating practical goals + PEP form

Personalized risk feedback from health screening

Feedback on intake levels Formulation of specific personal intentions

Knowledge tests Worksheet self-test on healthy standards

Tailored brochures

Tools/ Materials

Information about personal risk

Feedback Implementation intentions (goal setting)

Comparing intake in relation to standards

Providing written and/or verbal information

Passive learning/ providing information Active processing of information Self-evaluation

Strategy

Theoretical Methods

Table 4 Methods and strategies selected for dietary behaviour (programme outcomes 1&2)

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Awareness of own energy balance (PA) behaviour Delivering information on the relationship between calories & PA

Information about personal risk

Scenario-based risk information

Re-evaluation, self-evaluation, and consciousness raising

Awareness, risk perception & health believes

Promotion/facilitation

Calorie guide (energy balance information # min PA required to lose calories)

Providing risk information on longterm effects and information on benefits of healthy behaviour

Implementation intentions (goal setting)

Habits

b) External Perceived physical environment

Pedometer

Personalized risk feedback from health screening

Guided practice

Skills

Providing information on workplace health promotion

Formulation of specific personal intentions

Instruction/skills training

Evaluation of change process Provide personal feedback

Reinforcement Feedback

Attitudes

PHC provides (contact) information on the companies facilities and cost reduction

Tailored brochures

Expert monitoring and evaluation of BMI, waist circumference, blood pressure etc. in relation to healthy standards

Worksheet (PEP form) + PHC assists in goal setting

Training instruction exercise card (core stability & strength)

Follow-up contacts PHC PHC provides feedback on (perceived) positive consequences of PA

Worksheet (PEP form) + PHC assists in goal setting

Formulation of implementation intentions

Goal setting

Tools/ Materials

Strategy

Theoretical Methods

Determinant a) Personal Self- Efficacy

Table 5 Methods and strategies selected for PA (programme outcome 3&4)

3

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Practical strategies Literature was reviewed to identify which strategies are most frequently found as part of successful interventions aimed at increasing (vigorous) physical activity and improving dietary habits. Synergies between diet and exercise in modifying body composition have been reported [48,49]. Furthermore, a combination of interventions on physical activity and dietary habits were found to be more (cost-)effective than interventions on physical activity alone [50]. A review on determinants of participation in worksite health promotion programmes showed that programmes that offer a multi-component strategy and focus on multiple behaviours have a higher overall participation level [51]. When targeting multiple lifestyle behaviours, identifying an individualâ&#x20AC;&#x2122;s stage-of-change on behaviour can help to determine which behaviours an individual should be targeted for change (at various points) in the intervention [52]. The stage-of-change construct can facilitate tailoring of interventions by matching intervention strategies to individualsâ&#x20AC;&#x2122; motivational readiness. Furthermore, in weight management in which multiple diet and activity changes can achieve weight change, individuals may be more motivated to change some specific behaviours than in others. Therefore, participants should be able to choose which behaviour they intend to change. A strategy for increasing risk awareness could be feedback on health screening. The review of Soler et al. 2010 [53] indicates that assessment of health risks with feedback is useful as a gateway intervention to a broader worksite health promotion programme that may include a set of health promotion activities to improve the health of employees. The workers indicated in the focus group interviews that there often is no sufficient follow-up or feedback during or after the PHS. Standardised follow-up is available only in the case of high risk (for example high blood pressure). Also, as a preventive measure, feedback and personal information could be very important to induce behaviour change [54,55]. This was also found to be effective in construction workers [56]. Therefore, personal counselling with extra feedback for behaviour change should be an important element of the intervention. Step 4: Producing programme components and materials In this step of the IM process methods and practical strategies are translated into programme components and materials. The starting point of the intervention should be informing the employees about the company health promotion activities. Personal health coaching and information materials should be added to the current health promoting activities of the company to include all determinants of the formulated programme objectives.

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Programme description The intervention will take place during a 6-month period and will consist of materials and tailored information on physical activity and diet, personal health coaching (PHC), and training instruction. Both the PHC protocol and specific materials were developed to be able to connect the intervention to the PHS and tailor the intervention to the needs (individual risk factors) and wishes of the participants. Based on the baseline measurements and questionnaires a quick scan will be applied to tailor the intervention to the participants. Tailoring variables will be health indicators (BMI and waist circumference), current lifestyle behaviour (physical activity) and stageof-change (for physical activity as well as dietary behaviour). Programme materials The programme materials were made attractive and recognisable for the target group by using a standard lay-out and logo. The â&#x20AC;&#x153;VIP in Construction toolboxâ&#x20AC;? will consist of tailored brochures, a calorie guide, a pedometer, a BMI card and waist circumference measuring tape, recipes and a knowledge tests, an overview of the company health promoting facilities, PEP forms, and an exercise card. The exercises will consist of strengthening and stabilization exercises for the abdominal and dorsal muscles and will be well described on an exercise card. The exercises should be performed 3 times a week. The participants will receive instruction for the use of the exercise card from the PHC. The exercises on the card should be easily fitted in daily life routines; participants should be able to perform the exercises at home, and without any use or purchase of materials which potentially enhances compliance. PHC The coaching contacts will specifically aim at the programme outcomes as formulated in the needs assessment. The coaching contacts will consist of the following elements: 1) feedback, 2) goal setting, 3) feedback on formulated goals, 4) instructions for self-monitoring, and 5) training instruction. 1) The participants will receive additional feedback on their health screening and current lifestyle behaviour. 2) The PHC will support in goal setting, by helping the participants in formulating a personal motivation and action plan. These plans will contain physical activities, healthy food choices or a combination. Participants will be encouraged to target behaviour that is not at the desired level. Questions will be asked on what participants want to change, and they will be asked to formulate and write down specific goals and strategies to change the behaviour. In addition, information about the companyâ&#x20AC;&#x2122;s health promoting activities will be given and the intervention materials will be distributed and clarified. 3) Feedback on formulated goals will be given during the follow-up contacts. The PHC will keep a record of the goals and plans of the participant; in the follow-up contacts these goals should be evaluated. Possible barriers should be discussed and/or new goals should be formulated. Study design | 49

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4) Participants will receive instructions for self-monitoring by using the PEP forms and materials. 5) The PHC will give instructions how to use the exercise card. During the intervention, participants will be coached face-to-face in formulating their personal motivation and action plan. Follow-up contacts (feedback and motivating) will be conducted by telephone. The number and duration of contacts will vary with the outcome of the quick scan, with a minimum of 2 and a maximum of 4 contacts. The number of contacts (A, B, C) will be determined by a participantâ&#x20AC;&#x2122;s stage-of-change (for physical activity as well as dietary behaviour). An overview of the contacts is given in Table 6. A web-based system will be used to register the participantsâ&#x20AC;&#x2122; appointments, follow-up contacts, and content of the contacts (goals & action plans). Table 6 Coaching contact schedule PHC contacts

2 weeks after baseline 1 month measurements

A

Intake (60 min face-to-face)

B

Intake (60 min face-to-face)

Follow-up 1: (30 Follow-up 2: (15 min; telephone) min; telephone)

C

Intake (30 min face-to-face)

Follow-up 1: (10 min telephone)

2 months

3 months

Follow-up 1: (30 Follow-up 2: (15 min; telephone) min; telephone)

4 months Follow-up 3: (15 min; telephone)

Step 5: Adoption & implementation plan The product of step 5 is a plan for accomplishing programme adoption and implementation by influencing behaviour of individuals who will make decisions about adopting and using the programme and the individuals who deliver the programme. Company involvement To gain insight into facilitating factors and possible barriers regarding the adoption and implementation, management and (potential) users of the programme were interviewed. The human recourse management was involved in the programme development from the start to ensure top-down adoption in the organisation and increase of the chance of long-term implementation. During the intervention period the process will be monitored for unforeseen difficulties and possible barriers in adoption. Also a communication plan was written for the company. The main goal of this communication plan was to inform the target group and the management about the project and to obtain support from the direct management.

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Participantsâ&#x20AC;&#x2122; compliance (important factors to encourage the adoption of the intervention by the participants) To decrease barriers for participation, communication to the participants will be performed in cooperation with their employers, to show company involvement and support for the programme. Furthermore, the invitation to the study will be done simultaneously with the invitation to the PHS, to adapt the programme to the regular procedures. To make participation feasible for the participants the follow-up measurements as well as the first face-to-face contact with the coach will take place at the worksite and during work hours. In the planning of the programme, the planning of regular health screening was taken into consideration. Based on de schedules of the health screening, it was decided that the recruitment for the intervention should last at least 12 months, to ensure exposure to all the companiesâ&#x20AC;&#x2122; business units, and worker age groups. The participating occupational physicians (OP) and nurses received instructions during a kick-off meeting as well as by e-mail and telephone, as they will have an important role in linking the intervention to the PHS and motivating the workers to participate. To ensure that a standardised protocol will be used by the PHCs, all coaches received a manual describing the protocol and goals for the coaching sessions in detail. Just before the start of the intervention a training session will be held. Phase II evaluation Step 6: Evaluation plan Study design The effectiveness of the programme will be measured by performing an RCT. Participants will be measured at baseline (T0), at 6 months (T1), and at 12 months (T2). Consenting participants will be randomised to the intervention or control group after the baseline measurement. The control group will receive care as usual and will only be contacted for the baseline and followup measurements. The study design and procedures have been approved by the Medical Ethics Committee of the VU University Medical Centre. Study population and setting The research population will consist of all blue collar workers of a construction company. This will include construction site workers as well as factory workers of the company. The recruitment of participants will be conducted through the usual communication channels of the company at a non-compulsory PHS.

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Power calculation Sample size was based on detecting a difference in change in body weight between the intervention and the control group. In each group (intervention and control) 130 participants will be needed, based on a power of 80% and an alpha of 5%, and an expected weight loss of 1.5 kg (sd 4.3 kg) as result of the intervention. The used standard deviation was subtracted from previous work from our research group, studying construction workers [56]. Taking into account a loss to follow-up of 20%, 324 workers should be included in this study. Randomisation Randomisation will take place at an individual level. After baseline measurements the participant will be randomly assigned to either the intervention or the control group by a computer generated list using SPSS (version 15). The randomisation will be prepared and performed by an independent researcher (i.e. the research assistant). Measurements Assessment of the study parameters will be done using a combination of questionnaires and physiological measurements. Part of the study parameters will be obtained from physical examinations and questions on outcome measures are based on questions used for the PHS survey in the construction industry. In the Netherlands, this survey is widely used and tested on validity among construction workers who participate in PHS. Together with the invitation for this company PHS, all workers will receive a brochure about the study, an informed consent form, and an additional questionnaire in order to measure those variables not included in the PHS. For each study parameter, the following paragraphs describe how it will be measured for this study. Primary outcome measures Body composition Body weight and BMI: Body weight and height will be measured at the OHS by the occupational physician or the assistant during the PHS. Weight will be measured using a digital weight scale. Body weight and height will be measured with the participants standing without shoes and heavy outer garments. Data on body weight and height will be used to calculate Body Mass Index (BMI) (kg/m2). Waist circumference: BMI does not give insight into body fat distribution; therefore waist circumference will be measured as an indicator of health risks associated with visceral obesity [57]. Waist circumference will be measured during the PHS by the OP or assistant as midway between the lower rib margin and the iliac crest with participants in standing position at the end of expiration [58]. To standardise waist circumference measurement, OPs and assistants

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will be provided with a Seca 201 waist circumference measure (Seca, Hamburg, Germany) and measuring protocol. Secondary outcome measures Musculoskeletal disorders (MSD) The prevalence of MSD will be assessed using questions derived from the PHS. Using a dichotomous scale (yes/no), questions relate to the prevalence of regular pain or stiffness in both the upper and lower extremity regions. Additionally, using the validated Dutch Musculoskeletal Questionnaire [59], the prevalence of MSD during the past three months will be measured for the different body regions. The intensity of pain will be measured using Von Korff scales [60]. Workers will be asked to indicate their intensity of pain (i.e. average pain and worst pain experienced) on an 11-point numerical scale (0â&#x20AC;&#x201C;10). Energy balance-related behaviour Physical activity: The frequency of vigorous activities will be obtained from the PHS questionnaire and moderate physical activity will be assessed by the number of days per week moderate intensity activities are performed (such as walking and cycling) for at least 30 minutes. These questions relate to international physical activity guidelines [61] as well as to the Dutch guidelines [62]. Additionally, the validated Short Questionnaire to Assess Health enhancing physical activity (SQUASH) will be applied [63]. The SQUASH measures duration, frequency and intensity of different domains of physical activity (active work transportation, occupational physical activity, household activities, and leisure time activities). Data from the SQUASH will be expressed as energy expenditure in METminutes per week. As a complementary method, physical activity and sedentary behaviour will be assessed objectively using accelerometers in a random sample of 50 participants of both the intervention (n = 25) and control group (n = 25). This random sample will wear an accelerometer (Actigraph) during 7 consecutive days. The accelerometer will register the actual physical activity during and outside work hours. Dietary intake: Alcohol consumption will be obtained from the PHS questionnaire asking participants to report their average consumption (in glasses per week). Portion size at dinner, number of beverages and slices bread, as well as consumption of energy dense snacks will be assessed using questions that were also used in the Health under Construction study [64]. Average weekly intake and daily portions of several food groups during a usual week during the past month are indicated in these questions. Fruit and vegetable consumption will be measured using the validated Short Fruit and Vegetable questionnaire (validity r = 0.50) [65]. The number of days per week and the number of daily servings of fruit, vegetables and fruit juice will be measured using five items on citrus fruit, other fruits, cooked vegetables, raw vegetables, and fruit juice.

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Determinants of energy balance-related behaviour The intervention will aim at improving energy balance-related behaviour (physical activity and dietary behaviour). Personal coaching and feedback will be tailored to self-efficacy and stageof-change. Therefore, it is necessary to measure these constructs for physical activity and dietary behaviour. Based on models of behaviour and behaviour change, questions will be asked on knowledge, attitudes, self-efficacy and stage-of-change for physical activity and dietary behaviours [46,47]. Health-related measures Self-reported Physical Functioning: Subjective physical functioning will be measured using the RAND-36 [66,67]. The RAND-36 health survey is a widely known and reasonably reliable and valid measurement of health-related quality-of-life [68]. The RAND-36 consists of 36 questions, with clusters of: physical functioning, social functioning, role limitations (physical problem), role limitations (emotional problem), mental health, pain, general health perception, and health change. In the present study, the validated Dutch version will be used. Fitness: Although maximal volume of oxygen consumption (VO2max) is considered the goldstandard for measuring aerobic capacity, its measurement requires strict protocols and trained personnel. For this study fitness will be measured by using a non-exercise test estimation model including age, BMI, resting heart rate, and self-reported physical activity [69,70]. Cardiovascular disease (CVD) risk profile: CVD risk profile will be assessed using the European Systematic Coronary Risk Evaluation (SCORE) [71]. The SCORE is based on the CVD risk variables smoking, systolic blood pressure, and blood cholesterol levels (either total cholesterol or the ratio total/HDL cholesterol). All variables will be measured by the OP or the assistant during the PHS. Blood cholesterol (mmol/l) will be measured by taking a venous blood sample. The SCORE will be filled in based on blood pressure and cholesterol levels, as assessed in the medical examination and smoking behaviour as assessed in the PHS questionnaire. Work-related measures Workplace productivity loss: Sickness absence data (work absenteeism) will be collected from company records. Presenteeism (reduced productivity while at work) will be measured using the WHO Work Performance Questionnaire (WHO-HPQ) [72,73] and the PROductivity and DISease Questionnaire (PRODISQ) [74]. Participants will be asked to complete these questionnaires at 3, 6, 9, and 12 months. Work ability: For companies work ability is an indicator of the productivity of its own human resources. Work ability will be assessed by the Work Ability Index as measured in the PHS questionnaire. Work engagement, work satisfaction & vitality: Vitality will be assessed by the six items of the Utrecht Engagement Scale (UWES) that refer to high levels of energy and resilience, the

54 | Chapter 3


willingness to invest effort, not being easily fatigued, and persistence in the face of difficulties [75]. In addition, work related measures such as organisational commitment and work satisfaction will be evaluated. Use of company facilities: Since the intervention aims to increase the use of company health promoting facilities (e.g. company sponsored fitness), the use of these facilities will be reported by the participants at 6 and 12 months.

3

Cost measures Intervention costs: These include the costs for the â&#x20AC;&#x153;VIP in Construction toolboxâ&#x20AC;? and the PHC. PHC costs include costs for the health coach, housing costs, costs for printed materials, and travel expenses of the PHC. Since the PHC contacts will take place during work hours, the costs of lost productivity due to the intervention will be included as well. Coaches will record the frequency and duration of the face-to-face and telephone contacts. Intervention costs will be valued using a bottom-up approach. Other workplace health promotion costs: The use of company facilities will be valued using invoices of contractors. Health care costs: These include care by the general practitioner, allied health care, medical specialist, complementary and alternative medicine, hospitalisation, and medications. Data on resource use will be collected at a three monthly basis using retrospective questionnaires. Dutch standard costs will be used to value health care utilization [76]. If these are not available, prices according to professional organisations will be used. Medication use will be valued using unit prices provided by the Dutch Society of Pharmacy [77]. Productivity-related costs: Workplace productivity losses (i.e. work absenteeism and presenteeism) will be valued using salaries of the participants when using the employerâ&#x20AC;&#x2122;s perspective and using average salaries per gender and five-year age group when using the societal perspective. Participant costs: Since the intervention stimulates participants to engage in regular physical activity, self-reported costs related to sports activities (membership fees and sports equipment costs) will be collected on a three monthly basis. Effect analysis The effectiveness of the lifestyle intervention will be assessed using a regression analysis with the outcome measures at follow-up (6 months and 12 months) as the dependent variables and adjusting for the baseline levels of the outcome measure. Both crude and adjusted analyses will be performed. Linear and logistic (longitudinal) regression analyses will be performed using SPSS 18.0 (SPSS Inc. Chicago, Illinois, USA). According to the intention-to-treat principle, all available data of the participants will be used for data analysis. For all analyses, a two-tailed significance level of <0.05 will be considered statistically significant.

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Process evaluation A process evaluation with the aid of the RE-AIM framework will be performed to evaluate the diverse intervention components [78]. The RE-AIM model assesses 5 dimensions: reach, efficacy, adoption, implementation, and maintenance. These dimensions interact to determine the impact of the programme. In addition, an adapted version of the framework of Steckler and Linnan will be applied [79]. The following process indicators will be measured in the first follow-up questionnaire (at 6 months after baseline) and continuously during the intervention period: context, recruitment, reach, dose delivered, dose received, satisfaction about the intervention, and fidelity. Economic evaluation The economic evaluation aims to determine the cost-effectiveness of the intervention compared with usual care from the societal and employer’s perspective. Also, the cost-benefit will be determined from the employer’s perspective. The time horizon will be one year, similar to the trial. Analyses will be performed according to the intention-to-treat principle. In the main analysis, missing data will be imputed using multiple imputation techniques [80]. Sensitivity analyses will be done to assess the robustness of the results. First, the total societal and employer’s costs will be estimated, and compared between the intervention and control group. The 95% confidence intervals will be estimated using approximate bootstrap confidence (ABC) intervals [81]. Societal costs include all cost measures described in the method section. From the employer’s perspective, only costs relevant to the employer are included (i.e. intervention costs, other workplace health promotion costs, and productivityrelated costs). For the cost-effectiveness analysis (CEA), incremental cost-effectiveness ratios will be calculated by dividing the difference in costs between both groups by the difference in effects on the primary outcome measures (societal perspective), and outcomes measures relevant to the company (employer’s perspective). Bootstrapped cost-effect pairs will be graphically presented on cost-effectiveness planes [82]. Cost acceptability curves will be generated, showing the probability for cost-effectiveness of the intervention at different ceiling ratios. Also, a cost-benefit analysis (CBA) will be performed, in which the incremental intervention and other workplace health promotion costs will be compared to the incremental productivity-related costs.

Discussion The aim of this design article was to describe the development and plan for the evaluation of a (lifestyle) programme aimed at prevention and reduction of overweight and MSD among construction workers. This study may be of importance at company level to gain more insight in the effects of preventive measures, and to support decision making on which health promoting

56 | Chapter 3


activities should be applied. Because the intervention is conducted in the occupational setting a large number of people can be reached, which may have an impact on health outcomes, and company as well as health care costs. Strengths The intervention was designed following the IM protocol. This has been done before in health promotion interventions [83-85]. The development has been conducted with key figures in the organisation as well as with the target group aiming at a better compliance of employers and OHS with the VIP in construction protocol and allowing a scientific approach with consideration of daily practice. If the intervention proves to be effective, then the programme can be directly implemented. Although the components of the intervention will not be evaluated separately, the process evaluation will give qualitative insight into the success factors, applicability and usefulness of the separate intervention components. Furthermore, the process evaluation outcomes can improve the programme before it will be really implemented. Limitations Creating matrices in step 5 of the intervention mapping protocol was not fully applied, as this is a very time-consuming process. However, since the most important stakeholders were involved during the design of the study, it is expected that the adoption and implementation of the programme is ensured. Health promotion efforts, particularly those directed to somewhat resistant workers who are at high risk, should preferably be integrated with the provision of improved working conditions. A systematic review of the effectiveness of health promotion interventions in the workplace concluded that participation in workplace health promotion may be increased if interventions also take into account health risks arising from work activities [86]. In this study, not all input of the intended target group has been implemented. This resulted from the fact that the programme has been developed in close cooperation with the management of the organisation, their approval was needed to carry out programme components. It is possible that the programme would have involved other components if only the input of the target group had been taken into account. However, this programme was developed with the intention to be implemented. Therefore, we believe that involving all important stakeholders is necessary. Finally, this programme has been developed within a specific organisation. In this study, only stakeholders from the participating company and its OHSs were involved in the feasibility assessment and the focus group interviews. Also, a specific characteristic of the construction industry is that most employees are not working at a set location. The optimal infrastructure to reach workers is possibly different in other companies/branches. Therefore, it is possible that the IM process would have led to a different protocol in other workplace settings. This should be

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taken into account when implementing the intervention outside the construction industry. When generalising this programme to another context, the IM procedure can be applied to modify the existing programme.

Conclusion In conclusion, the development of the VIP in construction intervention resulted in a health programme tailored to the needs of construction workers. The method of IM provided the tools to do this systematically. If proven (cost-)effective the programme can be directly implemented, and with minor adaptations in other companies involving blue collar workers or companies that are already offering regular health screening. OHSs or human resource managers may incorporate this method in their usual prevention management. The results of the (process) evaluation will help policy makers decide which elements of the intervention can best be used. The (cost-)effectiveness and the (implementation) process regarding this intervention will be evaluated. The results of this RCT will be available in 2012.

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Chapter 4 Process evaluation of a multifaceted health programme aiming to improve physical activity levels and dietary patterns among construction workers

Laura Viester, Evert A. L. M. Verhagen, Paulien M. Bongers, Allard J. van der Beek

Journal of Occupational and Environmental Medicine. 2014 56:1210-1217


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Abstract Objective: To evaluate the process of a health promotion programme, aiming to improve physical activity levels and diet among construction workers. Methods: The process evaluation was conducted following the RE-AIM framework for the evaluation of the public health impact of health promotion interventions. Effectiveness was assessed on motivational stage-of-change, self-efficacy and decisional balance for physical activity as well as dietary behaviour. Results: The external validity of the trial was satisfactory with representative reach of workers and adoption of workplace units in the participating construction company. The extent to which the programme was implemented as intended was modest. The intervention was effective on participantsâ&#x20AC;&#x2122; progress through stages of behaviour change. Conclusions: Based on the RE-AIM dimensions it is concluded that for construction workers the programme is feasible and potentially effective, but adjustments are required before widespread implementation.

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Introduction The worldwide prevalence of overweight and musculoskeletal disorders (MSD) is high [1]. In the Netherlands, prevalence of overweight is over 40% in the adult female population and over 50% in the adult male population [2]. For MSD this is 39% in men and 45% in women [3]. Excess body weight is associated with increased mortality and morbidity rates (e.g. type 2 diabetes, cardiovascular disease, cancer, and MSD) [4-6]. In addition to health-related problems for the individual, overweight as well as MSD are causally related to work-related measures, such as increased sick leave and decreased productivity [7-14]. Consequently, the economic consequences of overweight and MSD are high. In the Netherlands in 2007, back pain alone accounted for an estimated â&#x201A;Ź3.5 billion societal costs [15]. Estimates of annual societal costs of overweight are â&#x201A;Ź500 million direct health care costs, and â&#x201A;Ź2 billion indirect costs, resulting from sick leave and work disability [16,17]. To prevent and reduce these health problems worksite intervention programmes are applied, since these have the potential to reach large groups of the employed population and have shown to be effective in improving health outcomes [18] as well as work-related outcomes [9]. Measuring outcomes of worksite health promotion programmes without providing insight into whether and how programme components are delivered could be considered a black box evaluation. Issues such as translatability and public health impact have been identified as critical. To provide insight into these issues, an important, but infrequently conducted component of evaluating the impact of health promotion interventions, is process evaluation. Process evaluations provide understanding on how and why interventions achieve their effects, how best to conduct intervention programmes to maximise effects, and enhance information on the internal and external validity of the intervention studies. For newly developed health programmes, knowledge of how a successful or an unsuccessful outcome was obtained will have an impact on future decision making. For example, if the outcome of an intervention is not effective, then it can be attributable to lack of implementation or lack of efficacy of the programme. Especially in intervention studies, assessment and reporting of adherence to an intervention programme (compliance with health programme components) is important, since outcomes of these studies can be biased by the level of adherence to the intervention. Furthermore, it provides insight into feasibility of interventions. This paper describes the process evaluation of the VIP in Construction intervention, using the RE-AIM (Reach, Efficacy, Adoption, Implementation, and Maintenance) framework. The results of this evaluation can be used to modify the programme for long term implementation. Also, these findings could provide useful information for the design of future intervention studies in a workplace setting. Process evaluation | 67

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Methods Study population This process evaluation was part of the VIP in Construction study, a randomised controlled trial (RCT) evaluating the multifaceted health programme aiming to improve physical activity levels and dietary patterns among construction workers. Blue collar workers (i.e. construction site and production workers) of a Dutch construction company who attended the voluntary periodical health screening (PHS) at the occupational health service between February 2010 and October 2011 were invited to participate. A total of 314 workers were included. Workers were randomised to an intervention group (n = 162) or a control group (n =152). The study protocol (trial number NTR2095) was approved by the Medical Ethics Committee of the VU University Medical Center Amsterdam (VUmc). The study design and intervention have been described in detail elsewhere [19]. Intervention programme A worksite intervention was developed, aiming at prevention and reduction of overweight and musculoskeletal disorders (MSD) among construction workers [19]. The VIP in Construction intervention programme was designed following the intervention mapping protocol [20], and key figures within the organisation as well as the target group were involved in the development of the programme. The programme consisted of tailored information, face-to-face and telephone counselling, exercises, and materials designed for the intervention (waist circumference measuring tape, pedometer, Body Mass Index (BMI) card, calorie guide, a cookbook including healthy recipes and knowledge tests, Personal Energy Plan (PEP) forms, and an overview of the company health promoting facilities). The intervention was tailored to the participantâ&#x20AC;&#x2122;s body weight status (BMI and waist circumference), physical activity level, and stage-of-change. The Transtheoretical Model (TTM) is a theory-based, widely used approach for conceptualizing behavioural change [21,22]. For interventions aiming at nutrition and physical activity, it is a widely supported model, allowing stratification of participants based on their readiness to change. Behavioural change progresses through a series of stages (pre-contemplation, contemplation, preparation, action, and maintenance). Participants in these strata of stage-of-change have contrasting levels of readiness to change, which requires different intervening strategies and intensity. Coaching intensity (i.e. number and duration of contacts) was tailored to the participantsâ&#x20AC;&#x2122; stage-of-change for improving physical activity and nutrition by using a quick scan (table 1). Face-to-face and telephone coaching contacts were provided by personal health coaches (PHC), during work hours. Face-toface coaching contacts took place at the construction sites. The coaching contacts consisted of the following elements: feedback, goal setting, feedback on formulated goals, instructions for self-monitoring, and training instruction.

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Table 1. Coaching contact schedule Stage-of-change

PHC contact schedule

2 weeks

1 month

2 months

3 months

Pre-contemplation stage

A

Intake (60 min Follow-up 1 Follow-up 2 face-to-face) (30 min; (15 min; telephone) telephone)

Contemplation/ Preparation stage

B

Intake (60 min face-to-face)

Follow-up 1 Follow-up 2 (30 min; (15 min; telephone) telephone)

Action/maintenance C stage

Intake (30 min face-to-face)

Follow-up 1 (10 min telephone)

4 months Follow-up 3 (15 min; telephone)

4

PHC = personal health coach

Data collection The process evaluation was conducted using the RE-AIM framework for the evaluation of the public health impact of health promotion interventions [23]. The RE-AIM model assesses 5 dimensions: Reach, Efficacy, Adoption, Implementation, and Maintenance. These dimensions interact to determine the (public health) impact of the programme. Each component was evaluated by qualitative and/or quantitative aspects. Process indicators were measured continuously in a webbased registration system during the intervention period by the coaches, as well as in the first follow-up questionnaire for participants allocated to the intervention group (at 6 months after baseline, following the intervention period). After the follow-up period, four interviews with providers and one interview with key persons in the organisation were held, with an average duration of 30 minutes. Table 2 provides a more detailed explanation of the procedures of the process evaluation.

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Maintenance

Programme Individual

Individual

Fidelity

Satisfaction

Dose received

Organisation Programme

Participation rate Individual

Programme

Organisation

Adoption

Dose delivered

Individual

Effectiveness

Implementation

Level individual and organisation

Component Reach

organisational intention for long term implementation recommendations from intervention providers

proportion of workers allocated to the intervention group that participates in the intervention components

exposure to the intervention: number of workers who attended the coaching contacts, and completed the programme, used materials

satisfaction of participants, who received the coaching, towards the programme, the coachingâ&#x20AC;&#x2122;s competences, number of coaching contacts, and the programme materials

extent to which the steps of the coaching programme were delivered as intended (timing and content of the sessions)

number of workers that received coaching appointments; number of planned contacts and received materials

distribution of workers participating in organisational units, and context of the programme

short term (6 months) intervention effects on (determinants of) behaviour change

Definition number of workers participating in the study, participantsâ&#x20AC;&#x2122; representativeness, and sources and procedures used to recruit employees,

Table 2. Process evaluation components and levels, their definitions, and data collection methods.

interviews interviews

programme and coaching registrations

coaching registrations and participant follow-up questionnaire

participant follow-up questionnaire

coaching registrations and interviews

participant follow-up questionnaire and coaching registrations

direct observation

participant baseline, and 6 months follow-up questionnaire

Data collection participant baseline data and company data

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Outcome measures Table 2 presents how each of the RE-AIM dimensions was evaluated. First, the reach of the programme was studied at individual and organisational level. Next, the effectiveness component evaluates the intervention effectiveness on (determinants of) behaviour change. To assess whether transitions between TTM stages could be induced by the intervention, motivation for change was assessed for PA as well as dietary behaviour. For the purpose of analysis, motivational stage-of-change was categorised into three categories (similar to the tailoring categories for the intervention): pre-contemplation, contemplation/preparation, and action/maintenance. The TTM involves intermediate measures sensitive to progress through the stages as well. These include pros and cons (decisional balance construct) and the self-efficacy construct. Self-efficacy was assessed using one item measured with a 5-point response, where 1 = very confident and 5 = not at all confident. The item addressed the person’s degree of confidence in being able to change physical activity and nutritional behaviour. Decisional balance was assessed using one item as attitude towards changing physical activity or nutritional behaviour, with 3 response categories: ‘I see more pros than cons’, I see as many pros as cons’, and ‘I see more cons than pros’. In the analysis the last two categories were combined due to a small number of subjects in the last category. The intention-to-treat analysis of the effectiveness of the intervention on health outcomes (biometric measures and lifestyle) and work-related outcomes (sick leave, work-related vitality) will be described elsewhere. Adoption was studied at organisation level (i.e. business unit and subunit level). Implementation was assessed at the level of either the programme (dose delivered and fidelity) or the individual (satisfaction, dose received, and participation rate). Elements for the assessment of the implementation dimension were defined by an adapted version of the framework of Steckler and Linnan [24]. Finally, Maintenance was considered at both organisation and programme level (see table 2). Data analyses Descriptive statistics were used to illustrate the process quantitatively. Furthermore, logistic regression analyses for ordinal variables (proportional odds model) were performed to determine effects of the intervention on stage progression and determinants of behaviour at follow-up, corrected for baseline values. All interviews were audio-recorded and fully transcribed, coded based on the underlying structure of the interview, and subsequently analysed according to the principles of thematic content analyses [25].

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Results Reach Workers of the company were recruited through the usual communication channels of the company, together with the invitation to the PHS, which was sent with an accompanying letter to the home address. Participation in these screenings is generally high (>85% for this company). During the recruitment period approximately 1,021 workers were invited to the PHS. Based on the number of participants and the number of workers in the company eligible for participation in the study, it was estimated that 31% (314/1,021) of the workers were included. In table 3 baseline characteristics of participants are compared to characteristics of the company workers based on PHS data and company records. Mean age of participants was 46.6 (SD 9.7). Participants were slightly older with an over representation of the age group 50-plus (37% of the company workers versus 46% of the participants) and under representation of the group below 40 years of age (29% of the company workers versus 21% of the participants). BMI levels in the study population reflected those of the company as estimated by the PHS data. Table 3. Characteristics (age, levels of BMI) of study participants compared to blue collar workers of the construction company, and PHS participants. Age < 20 20 – 30 30 – 40 40 – 50 50 – 60 =>60 BMI Overweight (BMI >= 25) Obesity (BMI >=30)

Study (n=314)

Company

0% 7% 14% 34% 42% 4%

0%* 9%* 20%* 34%* 31%* 6%*

71% 23%

71%** 21%**

*Based on total company records 2011 **Based on periodical health screening (PHS) data 2010/2011 (n=645)

Effectiveness Intervention effects on stage-of-change, self-efficacy and decisional balance are presented in table 4. At baseline, based upon the stage-of-change question for dietary behaviour, 52% of the participants were in the action/maintenance stage, 31% in the contemplation/preparation stage, and 17% in the pre-contemplation stage. Proportionately more intervention group participants improved (i.e. moved towards action and maintenance) compared to control group participants from baseline to follow-up (OR: 3.18, 95%CI: 1.82-5.54). After 6 months 74% were in the action/maintenance stage in the intervention group versus 48% in the control group. For physical activity, at baseline 32% of the subjects were in the action/maintenance stage, 49% in

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the contemplation/preparation stage, and 18% in the pre-contemplation stage. The intervention group more often progressed through the stages than the control group (OR: 2.13, 95%CI: 1.33-3.42). After 6 months 52% of the intervention group was in the action/maintenance stage compared to 30% in the control group. No significant intervention effects were found on selfefficacy (for changing dietary as well as physical activity behaviour). For dietary behaviour the intervention had a significant positive effect on decisional balance for changing behaviour (OR: 1.95, 95%CI: 1.08-3.54). For physical activity this improvement was not significant by group assignment (OR: 1.45, 95%CI: 0.83-2.45). Table 4. Baseline and follow-up descriptives, and intervention effects on stage-of-change, selfefficacy, and decisional balance.

Stage-of-change Action/maintenance (%) Contemplation/preparation(%) Pre-contemplation (%)

Self-efficacy Very confident Confident Not sure Not confident

Decisional balance More pros than cons As many pros as cons More cons than pros

Physical activity Intervention Control (n=135) (n=137)

Dietary behaviour Intervention Control (n=136) (n=138)

T0

T0

35.2 47.5 17.3

T1 51.1 37.8 11.1

T0 29.1 51.4 19.6

T1 29.9 51.8 18.2

53.2 34.8 12.0

T1

T0

75.0 15.4 9.6

51.0 27.8 21.2

T1 47.8 36.2 15.9

OR (95%CI): p-value 0.002 2.13 (1.33-3.42)

OR (95%CI): p-value: <0.001 3.18 (1.82-5.54)

23.1 42.9 24.5 9.5

20.5 46.2 26.3 7.0

33.6 43.3 14.9 8.2

28.8 43.5 20.1 7.8

24.3 43.4 25.0 7.4

26.9 53.7 14.2 5.2

24.0 42.7 24.0 9.3

OR (95%CI): 1.41 (0.89-2.23) p-value: 0.146

OR (95%CI): 1.53 (0.96-2.45)

66.7 23.3 10.1

57.4 40.6 1.9

76.7 20.3 3.0

61.8 25.0 13.2

65.7 29.2 5.1

OR (95%CI): 1.45 (0.83-2.54) p-value: 0.196

76.7 23.3 0

p-value: 0.073 55.9 39.2 4.9

OR (95%CI): 1.95 (1.08-3.54)

25.2 45.2 23.0 6.6

62.2 35.6 2.2

p-value: 0.033

T0 = baseline, T1 = follow-up at 6 months, OR = odds ratio, CI = confidence interval.

Adoption The programme was developed and implemented in one large company. In the Netherlands, only a small percentage of all construction companies are large companies (>100 employees) [26]. At business unit level, representativeness was satisfactory. Participation rates did not differ

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between the two main company units, general construction and infrastructure. However, within infrastructure participation rate varied between the subunits. The subunits that were under represented in participation were two specialised units involving road construction and earth moving. Implementation Programme level Dose delivered: Of all planned coaching appointments 98.4% was provided by the PHC. One participant did not receive coaching at all, and for another participant one follow-up appointment was missed. The percentage of provided materials was 98.8%; two participants did not receive the VIP in construction toolbox. Fidelity: The intended start of the coaching contacts was two weeks after the participants were included in the study. The first planned contact took place on average 5.7 (SD 3.6) weeks after randomisation. As a consequence three participants did not receive their last follow-up coaching contact before the short term follow-up measurements. Follow-up contacts were planned according to the protocol. However, if a scheduled appointment took place during a vacation period, in some cases the follow-up contact was postponed and the protocol was continued from that point in time. Based on the coaching registration in 6.3% (n=8) of the intakes, goal setting and formulating action plans were not adequately part of the intake session. During followup contacts in 98.2% barriers/successes and long term goals were addressed. The planned 30 minutes for intake C turned out to be insufficient for attending to all intake components; these contacts usually lasted longer than planned according to protocol. In addition to programme information on energy-balance related behaviour, the results of the exercise tests or cholesterol and blood pressure measurements proved useful starting points to motivate participants in goal setting. Not all PHCs prescribed the exercise card in all cases as stated by the protocol. One PHC indicated to have used the card only if participants explicitly mentioned musculoskeletal symptoms. Another PHC had the opinion that the exercises were too advanced for participants with obesity. Table 5. Participation rate and mean number of attended coaching contacts for each coaching group (A,B,C).

A B C Total

Number of contacts 4 3 2

Allocated 40 61 49 150

Perc. Nonadherence* 30.0% 11.5% 10.2% 16%

Mean number attended Mean number attended coaching appointments coaching appointments (n=126; (n=150; allocated, incl. those starting the coaching non-participants) sessions) 2.2 (1.7) 3.2 (1.0) 2.3 (1.1) 2.5 (0.8) 1.8 (0.8) 2.0 (0.4)

*The percentage of study participants in the intervention group allocated to the coaching that did not participate in the coaching at all. 74 | Chapter 4


Individual level Dose received (exposure): Of the 162 workers allocated to the intervention group, based on baseline BMI, waist circumference and amount of physical activity, 150 were eligible for coaching. Based on the coaching registration system, 84% (n=126) of the workers allocated to the PHC attended at least one coaching session. Main reasons for not participating were “not interested” or “no time”, other reasons included health-related issues, and alleged privacy issues (e.g. employer aware of participation in health promotion programme). Table 5 shows participation and mean number of attended coaching contacts for each group. Participation rate differed between coaching groups. In group B (contemplation/preparation) and C (action/ maintenance) this was 11.5 and 10.2%, respectively. The most intensive group A (four sessions), which was the group pre-contemplators, had the highest non-response (30.0%). Of the participants, 61.1% completed all coaching sessions. Main reasons given by the participants for not finishing the contacts were: lack of interest, time, or conflicting expectations of the programme. PHCs confirmed that in some cases during the intake it became apparent that participant’s expectations differed from the actual programme content, such as receiving training guidance or treatment (physiotherapy) from the coaches. Questionnaires on participation and usage of the programme materials and satisfaction were completed by 121 workers at 6 months of follow-up. According to the interviewed PHCs the PEP forms were used in all intake sessions. However, from the questionnaire data it was concluded that only 26% of the participants used the forms further on during the intervention period. Practical materials were used more than informational materials: pedometer (52%), waist circumference measuring tape (43%), and BMI card (30%). The calorie card and cookbook were less used (15%). For the exercise card: 62% of participants indicated to have used the card at least once. However, only 13% used it regularly (once per week), and only 4% used the card as prescribed by the programme (three times per week). Participants’ attitudes: Overall, the mean rating of the programme was 7.6 (SD 1.0) on a scale from 0-10. By the participants who received at least one coaching appointment, the coaching was scored with 7.8 (sd 0.9). The majority of the participants was satisfied with the number of coaching contacts (86.5%), 2.1% perceived the number as too many, and 11.5% as too few. The mean rating of the programme materials was 7.2 (SD 1.1). Of all programme components (materials and coaching) the most appreciated component was the coaching contact. Maintenance The senior human resource manager was interviewed on intention of continuation of the programme after the trial phase. The intention of the organisational decision makers is to implement the programme provided that there is reasonable evidence that the programme will

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produce long term benefits on sick leave or related health outcomes. Barriers for maintenance that were identified from the interview were related to organisational support and the current economic recession. As a consequence of the current economic situation in the construction sector, organisational issues such as financial resource allocation were prominent. Since resources to address worker health issues are limited, there has been a shift to decision making based on short term goals and effects. Lost work time due to participation in the programme might negatively influence support for the programme. A possible facilitator for maintenance that was identified from the interview is that the company is currently changing its policy on work disability prevention, towards a more active role for the employer. As a result of this present organisational transition, follow-up of PHS, becomes integral part of the organisational policy. Within the new situation, the programme would become a more central (as opposed to peripheral) part of the organisation. This could positively contribute to organisational culture for sustainable implementation of the programme. PHCs were interviewed on usability of the programme. Tailoring of the intensity of the coaching based on the stage-of-change questions was in most cases perceived as successful. However, in some cases, based on the intake, the coaches would have assigned the participant to a more or less intensive contact schedule. The first face-to-face contact was perceived as essential to build confidence between coach and participant. According to the coaches, for the follow-up contacts to be more effective, the first follow-up contacts should be planned shortly after the intake. Further, coaches encountered participants with emotional/psychological issues, such as stress or addiction, which probably should be addressed first before changes in lifestyle behaviour can be discussed. These issues might also be associated with unhealthy behaviour [27]; in the current protocol these issues were not addressed.

Discussion The aim of this paper was to evaluate the process of the VIP in Construction intervention, using the RE-AIM framework. The external validity of this worksite health promotion trial was satisfactory with representative reach of workers and adoption of workplace units in the participating construction company. The intervention was effective on participantsâ&#x20AC;&#x2122; progress through stages of behaviour change. The extent to which the programme was implemented as intended was modest. Satisfaction and dose delivered was high. However, adjustments to the programme should be made to improve exposure and fidelity. For the programme to be sustainably integrated into the health promotion practice of organisations, appropriate organisational context and information on health-related, work-related, as well as financial outcomes are essential.

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The two RE-AIM dimensions reach and adoption, at different levels, refer to broadness and representativeness of the study sample [28]. Information on the reach of the programme is needed to gain insight in potentially selective participation and external validity. Participation rate in the VIP in Construction programme was 31% of the eligible workers. Participation in worksite health promotion programmes aimed at physical activity and nutrition levels are typically below 50% [29]. In general, blue collar workers appear less likely to participate in worksite health promotion programmes [28]. However, this programme was developed with input of this specific worker population, which was expected to improve participation rate. PHS was found to be a successful starting point for intervention. Worksites with small numbers of employees are less likely to provide health promotion programmes than larger companies, such as in the present study [30]. Linking programmes to PHS to increase reach might support health promotion in these settings as well. When generalising the results from the specific setting of the RCT to the entire worker population, it should be taken into account that in the study population older workers were slightly over represented. Older workers being more likely to participate, is in line with other trials [31,32]. Some reports find that participants that actively engage in health programmes are those that already have a healthier lifestyle and therefore are more motivated to participate [33,34]. Lack of participation by high-risk employees has been cited as a barrier to adopt WHP programmes [30]. In this programme, based on PHS data of the company, the programme has reached a representative sample regarding levels of BMI. Contextual factors could have played a role in the adoption of the programme. First, during the recruitment period of the study, the economic crisis started to have a negative effect on the construction sector resulting in termination of employment, and workers reporting increased work pressure and job insecurity. Second, the company units that were under represented are, more than other units, characterised by shift work, irregular work hours, and temporary worksites. These characteristics might be barriers for adoption of the programme. Another explanation is that management engagement influenced participation in the programme. In another worksite intervention for construction workers it was found that organisational support was an important factor for participation [35]. In the present study the role of direct supervisors was larger than anticipated in the development of the programme. Appointments (follow-up measurements as well as coaching contacts) for workers in these units were usually made through their supervisors, and as a consequence of increased time and financial pressure the programme might not have had highest priority. Conflicts of work demands have increasingly been found a barrier to offering worksite health promotion programmes [30]. Although top management support was excellent (during the development and continuously during the trial phase), for these units facilitation of participation by supervisors during work hours is probably also essential and could increase

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enrolment. Regarding the representativeness of the setting it should be mentioned that recruiting construction companies for another health promotion intervention was found to be difficult, and company size was found to influence process outcomes [35]. Smaller construction companies might have other factors or decision making processes that are relevant for adoption of health promotion programmes. Tailoring by motivational stage can be used to predetermine readiness for behaviour change in energy-related behaviour, which potentially enables addressing low completion rates in health promotion programmes and its related cost issues [36]. In contrast to another worksite individual counselling study [37] the programme was able to reach a substantial group of precontemplators. Regarding physical activity 26% of the Dutch adult population is considered to be pre-contemplator [38], for dietary change this is approximately 50% [39]. Of the group pre-contemplators included in the study, two third actually started the coaching programme. To increase this rate, a stage-based adjustment of the programme preceding the coaching contacts might be advisable to increase exposure to the programme and motivate workers to the next stage. Furthermore, it has been suggested that tailored interventions may be more effective to induce behaviour changes [21], and stage progression could be a good indicator of the effectiveness of stage-of-change based tailoring as a basis for intervention. Regardless of an already substantial percentage of workers in the action/maintenance stage at baseline, the intervention helped a significantly greater number of workers in the intervention group to progress through the stages of change than did in the control group. Stage movement is a proxy measure of behavioural change, and does not necessarily result in actual behaviour change [21]. However, since a substantial group moved to the action/maintenance stage, the progression could be regarded as intervention effectiveness. At programme level, implementation was defined by dose delivered and fidelity. Dose delivered was satisfactory, but fidelity was moderate. By pilot testing the coaching schedules, some of the practical issues could have been prevented. At individual level dose received and satisfaction were assessed. Satisfaction with the programme and PHCs was high. The majority of participants reported to be satisfied with the number of coaching contacts. Although the intake contacts were organised at the worksite and also the follow-up coaching sessions could be completed in company time, which potentially increases adherence [40], the number of actually received contacts was suboptimal, since 38% of the participants in the coaching sessions did not fully finish the programme. Thus, although in a previous weight loss intervention an association was found between number of contacts and intervention effectiveness on weight loss [41], for this population, increasing number of contacts might be hardly feasible. Practical tools for

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self-monitoring were used more often than paper materials. Since the use of self-monitoring in behavior change has both theoretical foundation and significant association with weight loss [42], successful use of these materials might induce actual change in programme outcomes. Implementation of the exercise component was not successful. This could in part be a result of the PHCs not always prescribing the exercises. For a worksite health promotion programme to be implemented and remain viable in the long term, organisational support and institutionalisation are important factors [43]. First, to decide whether or not to provide worksite health promotion interventions to their employees, employers need information about the trade-off between costs and effects. Economic evaluation of the program from the companyâ&#x20AC;&#x2122;s perspective, especially when resources are limited, would provide essential input for making a business case to obtain senior management support. Further, even if there are no financial limitations for implementation, feasibility of long term implementation of the programme requires appropriate organisational infrastructure and capacity. For the programme maintenance after the trial phase, the role of the researcher/research assistant should be easily transferable to agents in the company. The coaching was delivered by external professionals, who could continue after the trial phase. However, planning and organisation was almost entirely done by the study staff. This was time- consuming and it decreases the influence on company maintenance after the trial phase. Therefore, it is recommended that sustainability, for example by appointing key persons within the company to integrate the programme, becomes part of the design of such programmes. Strengths and limitations The first strength was that in this process evaluation study compliance with the programme was obtained by objective measures. The coaching attendance was registered for each appointment, as well as reasons for not attending. Secondly, process measures were evaluated at different levels. Data were collected from organisational decision makers, participants in the study, as well as intervention deliverers (PHCs). A limitation of this evaluation is that supervisory staff was not involved. Their role was larger than anticipated, and input and support from this particular management level could improve adoption and implementation. Another limitation of this study was that the fidelity concept was partly measured by self-report, instead of fully by objective measurement. To objectively measure the content of coaching appointments, audio recording and analysing the actual conversations would give a more reliable representation of the actual implementation process. Finally, the concepts of the TTM (stage-of-change, self-efficacy, and decisional balance) were measured using single-item questions. Preferably these constructs are measured with more extensive multi-item questions (or algorithms) since physical activity as well as dietary behaviour are complex behaviours. For

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tailoring in a large-scale intervention this would be unpractical. However, this would be a more suitable and valid approach when tailoring is applied in the individual counselling setting. Conclusions Based on the reach dimension, the external validity of the study is satisfactory, with a representative study population. Based on the RE-AIM dimensions implementation and effectiveness, it is concluded that for construction workers the programme is feasible. In addition, the programme is potentially effective based on the intervention effect on movement through the motivational stages-of-change for PA as well as dietary behaviour. However, some adjustments to improve exposure and fidelity should be made. A contextual factor of importance in the process of conducting the programme was the current economic climate in general and specifically in the Dutch building and construction industry. This had consequences for adoption, and could have consequences for the future implementation and maintenance of the programme as well. This evaluation provides insights for researchers and practitioners planning and implementing intervention programmes in a workplace setting. In addition, it may help employers to make informed decisions about worksite health programme adoption and implementation.

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Chapter 5 Improvements in dietary and physical activity behaviours and body mass index as a result of a worksite intervention in construction workers: results of a randomised controlled trial

Laura Viester, Evert A. L. M. Verhagen, Paulien M. Bongers, Allard J. van der Beek

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Abstract Purpose: To evaluate the effectiveness of an individually tailored intervention for improvement of lifestyle behaviour and prevention and reduction of overweight disorders among construction workers. Design: Randomised controlled trial. Setting: Construction industry Subjects: Blue collar workers, randomised to an intervention (n=162) or control group (n = 152). Intervention: The intervention group received individual coaching sessions, tailored information and tailored materials to improve lifestyle behavior, the control group received usual care. Measures: Body weight, body mass index (BMI), waist circumference, physical activity levels (PA), dietary behaviour, blood pressure, and blood cholesterol were assessed. Analysis: Linear and logistic regression analyses were applied, with outcome measures at 6- and 12-month follow-up as dependent variables, adjusting for their baseline levels. Results: After 6 months a statistically significant intervention effect was found on body weight (B -1.06, p=0.010), BMI (B -0.32, p=0.010), and waist circumference (B -1.38, p=0.032). At 6 months vigorous PA increased significantly in the intervention group compared to the control group (B 2.06, p=0.032), and for sugar-sweetened beverages (SSB) an intervention effect was found at 6 months as well (B -2.82, p=0.003). At 12 months, for weight related outcomes, these differences were still present, however slightly smaller and no longer statistically significant. Conclusion: Intervention participants showed positive changes in vigorous PA and dietary behavior compared to controls, as well as effects on weight-related outcomes at 6 months. Longterm effects were still promising, but no longer statistically significant.

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Introduction The worldwide increased prevalence of overweight and obesity is associated with considerable health concern. Excess body weight is associated with increased mortality [1] and adverse health outcomes [2]. The predominant health issues associated with overweight and obesity include type 2 diabetes, cardiovascular disease (CVD), cancer, and musculoskeletal disorders (MSD) [3,4]. The economic burden of overweight is substantial and is expected to increase [5]. In the Netherlands annual overweight related health care costs are estimated at â&#x201A;Ź500 million, while indirect costs, reflecting the value of lost productivity resulting from work absence and disability, are projected to be about â&#x201A;Ź2 billion [6,7]. In general, even after adjustment for socio-demographic factors, the prevalence of overweight and obesity in construction workers is higher than in the general adult population [8-10]. Although in white collar workers with a more sedentary daily routine the overweight issue has also been described, in blue collar (construction) workers the overweight problem is of specific concern. Blue collar workers in the construction industry have an increased risk for sick leave, disability, and decreased productivity as a result of (a combination of) obesity, a high physical workload [11], and musculoskeletal symptoms [12-14]. In addition, due to the physically demanding nature of construction work, we hypothesised that overweight and obesity in this specific group also have more individual and larger economic consequences. This increased prevalence of overweight justifies occupational and sector specific preventive strategies [6] for construction workers. Preventing and reducing excessive body weight among workers with a high physical work demand, might be a strategy to increase or preserve work ability [12], decrease sick leave [11] and musculoskeletal symptoms by lowering the relative load on the musculoskeletal system. In several systematic reviews and a recent meta-analysis evidence was found for effectiveness of worksite physical activity and dietary behaviour interventions on weight outcomes [15,16]. These did not include effective interventions specifically designed for blue collar workers in the construction industry. A lifestyle programme aimed at improving health of construction workers with a high risk for CVD showed promising effects of lifestyle counselling on weight related outcomes [17]. However, this programme aimed at a high risk group, while it could be argued that for prevention in a population with a relatively high prevalence of unhealthy weight, a population approach might be the most appropriate strategy. The World Health Organisation (WHO) has recommended that prevention of overweight and obesity should target adults even while body mass index (BMI) is still within an acceptable range [18].

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The aim of the present study was to evaluate the effectiveness of an individually tailored intervention, â&#x20AC;&#x2DC;VIP in constructionâ&#x20AC;&#x2122;, among blue collar construction workers on body weight-related measures (i.e. body weight, BMI, and waist circumference), blood pressure, and cholesterol. In addition, to gain insight into which behavioural changes may have led to the effects on these outcomes, physical activity and dietary intake were evaluated.

Methods Trial design The effectiveness of the programme was measured by performing a randomised controlled trial (RCT). Participants were measured at baseline (T0), at 6 months (T1), and at 12 months (T2). Written informed consent was obtained from participants before enrolment in the study. Consenting participants were randomised to the intervention or control group after the baseline measurement. The control group received care as usual and was only contacted for the baseline and follow-up measurements. The study design and procedures have been approved by the Medical Ethics Committee of the VU University Medical Center, and the trial has been registered in the Netherlands Trial Register (NTR): NTR2095. Participants The research population consisted of consenting blue collar workers of a construction company who attended a non-compulsory periodic health screening (PHS). The exclusion criterion was being on sick leave > 4 weeks at baseline. In total 314 workers were recruited over a 15-month period (March 2010 to June 2011), and randomised to an intervention (n=162) or control group (n = 152). Randomisation and blinding After baseline measurements the participants were randomly assigned to either the intervention or the control group by a computer generated list using SPSS (version 15). The randomisation was prepared and performed by an independent researcher (i.e. the research assistant). After randomisation, workers assigned to the control group received general information on the follow-up measurements. Intervention providers could not be blinded for allocation; however, they were not involved in the outcome assessment. Intervention The intervention programme aimed at the prevention and reduction of overweight and MSD, and was developed and implemented by applying the Intervention Mapping protocol [19,20]. The programme was offered at the worksite during working hours. The intervention commenced preferably within two weeks after the baseline measurements delivered by study-trained 88 | Chapter 5


health professionals (personal health coaches, PHC) during face-to-face and telephone health coaching sessions. Participants also received personal energy plan (PEP) forms to record their goals and action plans, and which they could use during the follow-up health coaching sessions. The intervention was tailored to the participant’s weight status (BMI and waist circumference), physical activity level, and stage-of-change. The intervention programme focussed on improving (vigorous) physical activity levels and healthy dietary behaviour, and in addition to the coaching sessions consisted of tailored information, training instruction (a fitness “card” to be used for core stability and strengthening exercises), and the ‘VIP in construction toolbox’ (overview of the company health promoting facilities, waist circumference measuring tape, pedometer, BMI card, calorie guide, recipes, and knowledge test). Outcome measures Questionnaire and physiological measurement data were collected from 2009 until 2012, at baseline before the randomisation (n=314), 6 months after baseline, following the intervention (n=277), and 12 months follow-up after baseline (n=261). The periodical health screening provided baseline data and was performed by the occupational physician (OP) or assistant. Participants filled in an additional study questionnaire. Follow-up measurements at 6 and 12 months were performed by study trained research assistants. To ensure standardisation of measurements OPs and assistants were provided with measurement protocols. Body weight and BMI: Body weight was measured using a digital weight scale. Body weight and height were measured with the participants standing without shoes and heavy outer garments. Data on body weight and height were used to calculate BMI (kg/m2). Waist circumference: Waist circumference was measured as midway between the lower rib margin and the iliac crest with participants in standing position at the end of expiration [21]. To standardise waist circumference measurement, OPs and assistants were provided with a Seca 201 waist circumference measure (Seca, Hamburg, Germany). Blood pressure: At follow-up systolic and diastolic blood pressure (mmHg) was measured twice with a fully automated blood pressure monitor (type: OMRON M6). The mean value of the two measurements was computed. Blood cholesterol (total cholesterol, TC): TC (mmol/l) was measured with non-fasting finger stick samples analysed on a Cholestech LDX desktop analyser (Cholestech, Hayward, USA). This analyser has been validated for lipid measurements in clinical practice [22]. Energy balance-related behaviour Physical activity: In the study questionnaire the validated Short Questionnaire to Assess Health enhancing physical activity (SQUASH) was applied [23]. The SQUASH measures duration, frequency and intensity of different domains of physical activity (active work transportation, occupational physical activity, household activities, and leisure time activities). For the leisure time Effect evaluation on primary outcomes | 89

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domain, activities were subdivided into age dependent intensity categories, by the metabolic equivalents (METs) derived from the compendium of physical activities [24]. Since the VIP in Construction intervention was aimed at improving leisure time moderate and vigorous physical activities (MVPA), the outcome measure for this study was total minutes per week for moderate to vigorous activities in leisure time including sports activities, walking, cycling, doing odd jobs, and gardening. Additionally, the frequency of vigorous activities was obtained from the PHS questionnaire as assessed by the number of days per week vigorous intensity leisure time activities that are performed at least 20 minutes. These questions relate to international physical activity guidelines [25] as well as to the Dutch guidelines [26]. Dietary intake: Alcohol consumption was obtained from the PHS questionnaire asking participants to report their average consumption (in glasses per week). Portion size at dinner, number of beverages, as well as consumption of energy dense snacks, fruit and vegetables were assessed using questions that were also used in the Health under Construction study [27]. In these questions average weekly intake and daily portions of several food groups during a usual week during the past month are indicated. Potential confounders and effect modifiers Data on potential confounders and effect modifiers were assessed by questionnaire including age, smoking (yes/no), education (low=elementary school, medium=secondary education, and high=college/university), and marital status (married/ cohabitating, single/ divorced/ widowed). Sample size The sample size calculation has been described elsewhere [19]. In each study group (intervention and control) 130 participants were needed at follow-up. Statistical methods Randomisation was checked for differences in baseline values between the intervention and control group, using independent t-test for continuous variables and Pearsonâ&#x20AC;&#x2122;s Chi-square tests for categorical and dichotomous variables. Regression models were presented as crude (model I) and adjusted full models (model II). The effectiveness of the lifestyle intervention was assessed using a regression analysis with the outcome measures at 6 months and 12 months follow-up as the dependent variables and adjusting for the baseline levels of the outcome measure. Both crude and adjusted analyses were performed. Linear and logistic regression analyses were performed using SPSS 20.0 (SPSS Inc. Chicago, Illinois, USA). According to the intention-to-treat principle, all available data of the participants, regardless of whether or not they actually received the complete intervention, were used for data analysis. The analysis was conducted with all available data of the respondents at the time of follow-up. For all analyses, a two-tailed significance level of <0.05 was considered statistically significant. 90 | Chapter 5


Results Between March 2010 and June 2011, 314 participants were enrolled in the study. Figure 1 presents the CONSORT flow chart of the participants throughout the trial. A total of 162 workers were assigned to the intervention group and 152 to the control group; 83% of the workers remained in the study during the 12-month follow-up.

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Figure 1. Flow chart of the study participants

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Baseline and confounding Baseline characteristics of the two study groups are presented in table 1. All participants were male. Of the total study population 70% was overweight, and 22.7% obese. No statistically significant baseline differences between the intervention or control group were found for outcome measures or potential confounders. Table 1. Baseline characteristics of the total study population and by group allocation. Number of participants Age, mean (SD) Weight, kg (SD) BMI (kg/m2) Normal (<25) (%) Overweight (25-29,9) (%) Obese (>30) (%) Waist circumference (SD) Systolic BP, mmHg (SD) Diastolic BP, mmHg (SD) Blood cholesterol, mmol/l (SD) Smoking (Yes, %)

All N= 314 46.6 (9.7) 88.8 (13.6) 27.4 (3.7) 30.0 47.3 22.7 99.4 (11.0) 131.1 (14.6) 82.8 (9.7) 5.4 (1.0) 29.4

Intervention N= 162 46.3 (9.9) 88.7 (12.9) 27.3 (3.5) 29.2 50.9 19.9 99.1 (10.2) 131.1 (15.4) 82.0 (10.4) 5.3 (1.0) 29.0

Control N= 152 47.0 (9.5) 88.9 (14.4) 27.4 (3.9) 30.9 43.4 25.7 100.0 (11.8) 131.1 (13.7) 83.6 (8.9) 5.4 (1.1) 29.7

Physiological outcomes Table 2 presents the means (SD) for body weight, BMI and waist circumference at baseline, 6 and 12 months follow-up for the intervention and control group, as well as the results of the linear regression analysis. At 6 months, there was a significant intervention effect on body weight (B -1.06, 95%CI: -1.87;-1.26), BMI (B -0.32, 95%CI: -0.57; -0.08), and waist circumference (B -1.38, 95%CI: -2.63; -0.12) (table 2). Directly following the intervention period, body weight and BMI increased in the control group, while it did not change significantly in the intervention group. Waist circumference decreased for the intervention participants. At 12 months, analyses within groups (paired t-tests) showed that the decrease in waist circumference in the intervention group and the increase in body weight and BMI in the control group compared to baseline values were still significant. However, the effects for body weight and BMI in the between group analyses were only marginally significant (p=0.053 and p=0.057, respectively) and even further from statistically significant for waist circumference (p=0.187). No significant intervention effects in diastolic or systolic BP or total cholesterol levels were found (table 3).

92 | Chapter 5


Effect evaluation on primary outcomes | 93

127 27.3 (3.5) 27.5 (3.3) 27.5 (3.5) 119 99.2 (10.0) 97.6 (9.7) 97.9 (9.7)

Body mass index, kg/m2 N Baseline 6 months 12 months

Waist Circumference, cm N Baseline 6 months 12 months 114 100.3 (12.3) 100.0 (11.8) 99.9 (11.8)

129 27.5 (4.0) 27.9 (4.0) 27.9 (4.0)

129 89.1 (15.1) 90.3 (15.1) 90.2 (15.2)

Control Mean (SD)

-1.38 (-2.58 ; -0.18) -0.95 (-2.23 ; 0.32)

-0.29 (-0.52 ; -0.05) -0.25 (-0.55 ; 0.05)

-0.92 (-1.69 ; -0.14) -0.81 (-1.80 ; 0.18)

Model I B(95% CI)

-1.06 (-1.87 ; -0.26) -1.00 (-2.01 ; 0.01)

-0.32 (-0.57 ; -0.08) -0.30 (-0.61 ; 0.01)

-1.38 (-2.63 ; -0.12) -0.91 (-2.25 ; 0.44)

0.017 0.107

0.024 0.142

Model II B(95% CI)

0.021 0.110

p-value

0.032 0.187

0.010 0.057

0.010 0.053

p-value

B-values reflect absolute differences between groups corrected for baseline values of the measures. Model I = crude model, adjusted for baseline values Model II = adjusted model for baseline values, age (continuous), education (categorical), marital status (dichotomous), and smoking (ditochomous)

127 88.3 (12.3) 88.7 (12.1) 88.7 (12.4)

Intervention Mean (SD)

Weight, kg N Baseline 6 months 12 months

Outcome measure

Table 2. Data on primary outcome measures for complete cases at baseline (mean, SD) at 6 and 12 months follow-up in the intervention and control group.

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94 | Chapter 5 115 5.3 (1.0) 4.9 (0.8) 4.7 (0.8)

129 83.6 (9.1) 82.7 (9.6) 80.9 (9.5)

129 131.5 (14.4) 135.3 (14.6) 133.7 (13.3)

Control Mean (SD)

0.03 (-0.15 ; 0.21) 0.07 (-0.10; 0.24)

-0.05 (-2.34 ; 2.24) 2.02 (-0.41; 4.45)

-0.50 (-3.90 ; 2.90) 0.50 (-3.07; 4.07)

B(95% CI)

Model I

0.725 0.404

0.967 0.102

0.770 0.783

p-value

0.05 (-0.13; 0.23) 0.07 (-0.11; 0.25)

0.25 (-2.10; 2.61) 2.22 (-0.28; 4.71)

-1.12 (-4.63; 2.40) 0.16 (-3.49; 3.81)

B(95% CI)

Model II

B-values reflect absolute differences between groups corrected for baseline values of the measures. Model I = crude model, adjusted for baseline values Model II = adjusted model for baseline values, age (continuous), education(categorical), marital status(dichotomous), and smoking (dichotomous)

116 5.3 (1.0) 5.0 (1.0) 4.8 (0.9)

128 82.5 (10.3) 82.1 (10.7) 82.3 (12.1)

Diastolic BP, mmHg N Baseline 6 months 12 months

Blood cholesterol (TC), mmol/l N Baseline 6 months 12 months

128 131.0 (15.8) 134.5 (14.8) 133.9 (18.4)

Intervention Mean (SD)

Systolic BP, mmHg N Baseline 6 months 12 months

Outcome measure

Table 3. Baseline data and estimated effects of the intervention on blood pressure (BP) and cholesterol.

0.583 0.424

0.832 0.081

0.532 0.932

p-value

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Physical activity No intervention effects were found from complete cases analysis on leisure-time MVPA (table 4). At 6 months intervention group participants increased their leisure time MVPA, but no significant intervention effect was found (B 70.6, 95%CI: -23.3; 165.5). At 6 months after baseline there was a significant intervention effect on meeting the public health guideline of vigorous physical activity (OR 2.06 95%CI: 1.07 ; 3.99). Participants in the intervention group meeting the guideline increased with 8%. After 12 months there was no significant difference between the intervention and the control group. Dietary intake A statistically significant intervention effect on intake of sugar-sweetened beverages was found after 6 months (table 4). Participants in the intervention group decreased their intake with one glass per week, while control group participants increased their intake (B -2.82, 95%CI: -4.67; -0.97). At 12 months after baseline no effect was found on SSB (B -0.96, 95%CI: -2.68; 0.63). No significant short-term or long-term intervention effects were found for any of the other dietary outcome measures.

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96 | Chapter 5

Dietary intake Alcohol (glassesâ&#x20AC; /week) N Baseline 6 months 12 months SSBs (glasses/week) N Baseline 6 months 12 months Snacks (pieces/week) N Baseline 6 months 12 months Fruit (pieces/week)

Physical Activity Leisure time-MVPA (min/week) N Baseline 6 months 12 months Public health guideline VPA (%) N Baseline 6 months 12 months

Outcome measure

127 11.0 (18.8) 10.6 (12.2) 9.7 (11.0) 127 5.5 (7.4) 7.5 (10.5) 6.4 (8.5) 121 11.9 (11.0) 10.2 (8.9) 10.0 (8.0)

124 6.4 (8.8) 5.5 (6.5) 6.2 (8.5) 119 10.5 (9.1) 8.9 (7.4) 8.9 (8.5)

123 20% 21% 27%

122 28% 36% 38%

126 12.7 (19.2) 11.8 (15.6) 12.5 (17.3)

129 370.4 (504.7) 354.0 (444.6) 396.9 (430.3)

Control Mean (SD) or %

127 365.7 (359.4) 428.6 (442.5) 370.8 (374.3)

Intervention Mean (SD) or %

-0.82 (-2.48 ; 0.83) -0.58 (-2.33 ; 1.16)

-2.57 (-4.35 ; -0.77) -0.93 (-2.52 ; 0.66)

0.45 (-2.48 ; 3.37) 2.18 (-0.93 ; 5.28)

2.03 (1.08 ; 3.82)* 1.51 (0.82 ; 2.79)*

77.3 (-12.7 ; 167.3) -23.3(-100.5 ; 53.8)

Model I B(95% CI) or OR(95% CI)*

0.327 0.511

0.005 0.248

0.763 0.168

0.029 0.184

0.092 0.552

p-value

-0.93 (-2.66 ; 0.80) -0.63 (-2.47 ; 1.20)

-2.82 (-4.67 ; -0.97) -0.96 (-2.68 ; 0.63)

-0.33 (-3.20 ; 2.54) 2.33 (-0.90 ; 5.56)

2.06 (1.07 ; 3.99)* 1.52 (0.81 ; 2.83)*

70.6 (-24.3 ; 165.5) -27.0 (-104.7; 50.7)

Model II B(95% CI) or OR(95% CI)*

0.289 0.497

0.003 0.243

0.821 0.157

0.032 0.191

0.144 0.494

p-value

Table 4 Differences in minutes per week spent on at least moderate intensity of physical activity, meeting the public health guideline for vigorous physical activity, and dietary intake between intervention and control group at 6 months and 12 months follow-up, corrected for baseline values.

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126 11.6 (8.4) 10.7 (8.5) 11.9 (8.3) 126 12.4 (7.6) 11.1 (6.8) 11.5 (8.5)

124 10.6 (7.3) 11.3 (7.0) 11.5 (7.4) 125 12.3 (8.0) 12.1 (6.9) 11.9 (7.2) 0.96 (-0.61 ; 2.52) 0.44 (-1.41 ; 2.29)

1.15 (-0.32 ; 2.62) 0.19 (-1.46 ; 1.83)

1.19 (-0.34 ; 2.62) 0.25 (-1.44 ; 1.94)

1.12 (-0.48 ; 2.72) 0.62 (-1.19 ; 2.43)

0.125 0.824

0.229 0.639

0.168 0.498

0.101 0.769

B: unstandardised regression coefficient, OR: odds ratio, MVPA: moderate to vigorous physical activity, VPA: vigorous physical activity, SSBs: sugar-sweetened beverages Model I = crude model, adjusted for baseline values Model II = adjusted model for baseline values, age (continuous), education(categorical), marital status(dichotomous), and smoking (dichotomous) *The numbers in the table represent values for B, numbers marked with ‘*’ represent odds ratios † glasses = standard drink containing approximately 10 grams of alcohol ‡spoon = 50 grams

N Baseline 6 months 12 months Vegetables (spoons‡/week) N Baseline 6 months 12 months

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Discussion Overall, the VIP in construction intervention positively impacted diet and physical activity, and resulted in short-term favourable body weight related outcomes when compared to usual care. After the intervention period, intervention participants showed significantly more positive changes in physical activity and dietary behaviour. These effects did not translate into weight loss. While changes in mean body weight and BMI were negligible across the intervention period for the intervention group, the control group participants gained weight at 6 months, which resulted in an intervention effect on body weight and BMI. Furthermore, the intervention group participants showed a decrease in waist circumference which resulted in a significant intervention effect on waist circumference at 6 months as well. At 12 months follow-up, differences were still present, however slightly smaller and no longer statistically significant. Weight-related outcomes From the perspective of many worksite health promotion programmes, and the overall trend in increasing body weight in the present study, preventing weight gain may be a positive and realistic outcome. The net body weight effects are modest compared to other worksite interventions ranging from -1.2 to -1.3kg and -0.3 to 0.5 kg/m2 for BMI [15,28]. An explanation for these modest results might be that participation this worksite health promotion trial was not restricted to a high risk group only (employees were not pre-selected on high body weight). The present study started with participants that as a group at baseline were overweight, but not obese (mean BMI < 28). In contrast, in weight loss interventions where participants are obese or who otherwise present a specific risk profile, weight loss results are likely to be larger than those obtained from a general worker population. Therefore, the weight loss results are not directly comparable to the overall weight loss literature or to most studies conducted in other clinical settings. Still, the lack of more impressive weight loss results in this study raises questions about the relevance of the effects. Clinically relevant weight loss is associated with an improvement in the clinical risk of adverse health problems [29]. Although often weight loss of 5% has been indicated as clinically relevant, even smaller reductions in weight have been shown to result in clinically meaningful reductions in important CVD risk factors and on risk of diabetes [30,31]. This indicates that very small reductions in body weight could be considered relevant. The goal of the intervention was to improve lifestyle behaviours that would be easy to implement and could be maintained over time. These type of interventions can be incorporated in or linked to routine health screening, which potentially increases reach as well as the likelihood of implementation. It is important to address that the intervention was not designed to maximise short-term weight loss. The lack of overall weight loss in the intervention group could be attributable to intervention intensity. In other studies where weight loss has been a primary outcome, more intensive approaches have typically been more effective than those with less

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contact [32,33]. However, such intensive approaches have a number of limitations. Applying high intensity programmes leads to more expenses and these are likely to appeal to only a small percentage of those who would benefit because of the level of commitment required. In the present study, even though the coaching sessions mostly took place during working hours and at the workplace, some participants indicated lack of time as a reason not to participate or did not complete all contacts. It has been suggested that waist circumference is more sensitive to changes in energy balance than is BMI [34-36]. In the present study, the overall effect on waist circumference was not accompanied by reduction in body weight. Although reductions in central obesity are larger when accompanied by weight loss, increases in physical activity have been associated with significant reductions in waist circumference, despite small or no changes in body weight [37]. BMI reflects lean tissues as well as body fat. Physical activity provides metabolic adaptations that are associated with reductions in abdominal fat and increases in fat free (skeletal muscle mass) as well as metabolic efficiency of muscle. Since a substantial percentage of the study participants had baseline waist circumferences that represent health risk (>102cm), the effect on waist circumference is considered relevant also when considering the association with MSD and central obesity [38]. Energy balance-related behaviour Both changes in physical activity and diet could have contributed to the effects on weight related outcomes. The intervention showed a positive effect on meeting the public guidelines for vigorous physical activity. However, no intervention effects were found for leisure time MVPA. This is in line with the study of Groeneveld et al. [39], who suggested that lack of effect may be related to average high levels of baseline PA at work for construction workers. Furthermore, the SQUASH questionnaire was not designed to measure energy expenditure and changes over time, but to give an indication of habitual PA level [23]. It has been suggested that high intensity activity measures might be more reliable, presumably because these activities are easier to recall. As a result, responsiveness in measures of more intensive levels of PA could be higher. The intervention effect on decreased intake of sugar-sweetened beverages (SSBs) could have contributed to the effect on weight-related outcomes. Intakes of SSBs have been found to significantly contribute to increased caloric intake and higher body weight [40,41]. Although short-term post intervention effects were found, comparable to other weight loss or weight gain prevention studies [42,43], maintaining health behaviour changes and effects on weight-related measures remains difficult. In general, this might be a result of relapse (not maintaining behaviour change) in the intervention participants. A decrease in between-group differences could also be the result of changes in favour of the control group participants. In the present study, at 12-month follow-up, participants in the control group showed slight improvement in several behavioural outcomes. The measurements conducted for the evaluation of the study

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effectiveness itself may have motivated control participants to improve health-related behaviour. In addition, contamination between the intervention group participants and the controls could not be completely ruled out. Contamination of the control group was expected to be minimal, since personal coaching was only available for the intervention participants. However, behaviour change in colleagues, especially dietary behaviour at work could have influenced control participants. This could partly explain the decreased contrast in outcome measures between the two groups at 12 months follow-up. Strengths and limitations A strength of the present study is that it was conducted as a randomised controlled trial. Randomisation was performed at the level of the individual, which reduces the probability of confounding factors through baseline differences between intervention and control participants. Another strength was that the intervention was tailored to the individual worker, which might be especially important in a heterogeneous group of workers (e.g. ranging from crane drivers to bricklayers) and when intervening on complex behaviours. Several methodological limitations deserve attention as well. Diet and physical activity were measured by self-report. The original study design comprised additional accelerometer measurements. In the present trial, this appeared not feasible; insufficient complete data samples were gathered suitable for analysis. Further, social desirability may have resulted in an overestimation of fruit and vegetable intake, and underestimation of snack, alcohol, and sugar-sweetened beverages intake, particularly in intervention group participants [44]. Accurate assessment of actual behaviour without imposing a large burden on respondents (especially in occupational groups where illiteracy is present) remains challenging. Implications for future research It is clear that (sustained) change to energy balance-related behaviour will result in effects on body weight. It is recommended that further worksite health promotion research aims at identifying methods to achieve long-term sustainable impact. Lifestyle interventions aimed at weight loss achieve short-term success, but body weight re-gain is common. To prevent weight regain for those who lost weight, specific strategies are required to maintain specific weight loss goals. These strategies to maintain weight loss may also play an important role in preventing weight gain among normal-weight individuals. However, there is still little evidence from trials what might be effective long-term strategies. From observational studies it is suggested that, for example, continued intervention contacts (face-to-face or by e-mail) [45] or continued self-monitoring of weight [46] lead to sustained effects on body weight related outcomes. Complementary intervention components at company level, for example strategies to enhance social support by colleagues and supervisors, might also reinforce sustained effects [47].

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Implications for practice The intervention programme appeared feasible for blue collar workers with a relatively low intensive intervention and promising short term effects. The programme needs to be adapted to improve long term effectiveness, before implementation or broader implementation in other settings can be recommended. Conclusions The results of this study indicate that a relatively low-intensive worksite intervention has the potential to improve dietary and physical activity behaviour in blue collar construction workers, and to contribute to the prevention of body weight gain. Further research is needed to improve long-term effectiveness, and insight into effectiveness might be increased if more objective measures of physical activity and diet are used. So What? Implications for Health Promotion Practitioners and Researchers

What is already known on this topic

In the literature evidence is found for effectiveness of worksite physical activity and dietary behaviour interventions on weight outcomes. The prevalence of overweight and obesity in blue collar construction workers is higher than in the general adult population, however no effective weight management programmes have been found targeted at this specific occupational group.

What does this article add?

The effectiveness of a newly developed targeted and tailored intervention is assessed in a randomised controlled trial. The relatively low intensive lifestyle intervention appeared feasible for blue collar workers with promising short-term effects.

What are the implications for health promotion practice or research?

Before implementation can be recommended, the programme needs to be adapted to improve long-term effectiveness. It is recommended that for successful weight management further worksite health promotion research aims at identifying methods to achieve long-term sustainable impact.

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Chapter 6 The effect of a health promotion intervention for construction workers on work-related outcomes: results from a randomised controlled trial

Laura Viester, Evert A. L. M. Verhagen, Paulien M. Bongers, Allard J. van der Beek

International Archives of Occupational and Environmental Health. 2015 88;789-798


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Abstract Purpose: The objective of the present study is to investigate the effects of a worksite health promotion intervention on musculoskeletal symptoms, physical functioning, work ability, workrelated vitality, work performance, and sickness absence. Methods: In a randomised controlled design, 314 construction workers were randomised into an intervention group (n=162) receiving personal coaching, tailored information and materials, and a control group (n=152) receiving usual care. Sickness absence was recorded continuously in company records, and questionnaires were completed before, directly after the 6-month intervention period, and 12 months after baseline measurements. Linear and logistic regression analyses were performed to determine intervention effects. Results: No significant changes at 6 or 12 months follow-up were observed in musculoskeletal symptoms, physical functioning, work ability, work-related vitality, work performance, and sickness absence as a result of the intervention. Conclusions: This study shows that the intervention was not statistically significantly effective on secondary outcomes. Although the intervention improved physical activity, dietary, and weightrelated outcomes, it was not successful in decreasing musculoskeletal symptoms and improving other work-related measures. Presumably, more multifaceted interventions are required to establish significant change in these outcomes.

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Introduction Workers in the construction industry are often exposed to physically demanding work tasks. These include, amongst others, the lifting of heavy loads and working in awkward postures. High physical work demands increase the risk for the development of musculoskeletal symptoms [1,2]. In blue collar construction workers musculoskeletal disorders (MSD) are the most prevalent work-related health problem [3,4]. In addition, in the Netherlands, the workforce in physically demanding work is aging and the risk of MDS also increases with age [5,6]. As such, MSD are a major cause for sickness absence, work disability, early exit from work, and are related to lower work performance, and consequently constitute an extensive social, medical as well as economic problem [7,8]. The prevalence of overweight and obesity in construction workers is higher than in the general adult population [9-11]. Both MSD and a high BMI are negatively associated with several workrelated outcomes, but are also associated with each other [12-16]. Since both factors are highly prevalent in blue collar construction workers, these might contribute to the high risk for developing health disorders and associated adverse work-related outcomes compared to workers in other industries and the general population [17,18]. This emphasises the importance to reduce the burden of overweight and obesity in this particular group of workers. Both diet and physical activity are considered of importance in achieving and maintaining a healthy body weight [19,20]. Worksite health promotion programmes aimed at physical activity and diet were found to be effective on weight-related outcomes [21-23]. Moreover, workplace health promotion programs that improve physical activity levels have been shown to also reduce the risk on MSD [24]. A lifestyle intervention among those with jobs involving moderately heavy or heavy work also showed a reduction in prevalence of low back pain [25]. Although intervention studies with MSD as primary outcome have not often been targeted at lifestyle factors, there is evidence from observational studies suggesting that health promotion should be considered in the prevention of MSD [26-29]. Beneficial effects on work-related outcomes, including sickness absence, productivity and work ability, have been reported resulting from preventative measures targeted at healthy lifestyle [30-33]. Consequently, implementation of worksite programmes targeted at lifestyle factors may be a promising strategy to improve worker health and other outcomes relevant to employers. In the Vitality in Practice (VIP) in Construction study it was hypothesised that a worksite health promotion intervention, aiming at improving physical activity and diet, could positively change body weight related outcomes, musculoskeletal symptoms and work-related measures [34]. The aim of the present study was to evaluate whether the intervention programme for blue collar

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construction workers reduced musculoskeletal symptoms, limitations in physical functioning and sickness absence, and increased work-related vitality, work performance and work ability.

Methods Study design and population The effectiveness of the programme was assessed in a randomised controlled trial (RCT). The research population consisted of consenting blue collar employees of a construction company. All employees who attended a non-compulsory periodic health screening (PHS) and who were not on sick leave for more than 4 weeks prior to the PHS were eligible for inclusion. In total, 314 participants were recruited over a 15-month period (March 2010 to June 2011), and randomised to an intervention (n=162) or control group (n = 152). Participants completed questionnaires at baseline (T0), at 6 months (T1), and at 12 months (T2). Written informed consent was obtained from participants before enrolment in the study. The study design and procedures were approved by the Medical Ethics Committee of the VU University Medical Center, and the trial has been registered in the Netherlands Trial Register (NTR, www.trialregister.nl): NTR2095. Randomisation, blinding and sample size Following baseline measurements, participants were randomly assigned to either the intervention or the control group by a computer generated list using SPSS 15 (SPSS Inc. Chicago, Illinois, USA). The randomization was prepared and performed by an independent researcher. Whereas participants could have been aware of the allocated arm, data collectors and analyst were kept blinded to the allocation. The sample size was calculated to identify an effect on body weight (Viester et al., 2012). Based on that calculation in each study group (intervention and control) 130 participants were needed at follow-up. Intervention The intervention programme aimed at the prevention and reduction of overweight and musculoskeletal symptoms, and was developed and implemented via the Intervention Mapping protocol [34,35]. The full programme has been described previously [34]. In short the intervention consisted of an on-site lifestyle coaching program tailored to the participant’s weight status (BMI and waist circumference), physical activity level, and stage-of-change. The intervention program focused on improving (vigorous) physical activity levels and healthy dietary behaviour. The programme consisted of tailored lifestyle information, lifestyle coaching sessions, exercise instructions, and the ‘VIP in construction toolbox’. This toolbox consisted of an overview of the company’s health promoting facilities, a waist circumference measuring tape, a pedometer, a BMI card, a calorie guide, healthy recipes, and a lifestyle knowledge test. 108 | Chapter 6


The intervention was delivered face-to-face and via telephone by personal health coaches (PHC) who were trained specifically for the study. Face-to-face coaching sessions took place at the worksite during working hours. An overview of the timing and duration of the contacts is presented in table 1. Participants additionally received “Personal Energy Plan” (PEP) forms to record their goals and action plans, and to be used during the follow-up health coaching sessions. Intervention providers were not involved in the outcome assessment. Table 1 Coaching contact schedule PHC contact schedule 2 weeks 1 month Pre-contemplation stage Intake (60 min Follow-up 1 face-to-face) (30 min; telephone)

2 months Follow-up 2 (15 min; telephone)

3 months

Contemplation/ Preparation stage

Intake (60 min face-to-face)

Follow-up 1 (30 min; telephone)

Follow-up 2 (15 min; telephone)

Action/maintenance stage

Intake (30 min face-to-face)

4 months Follow-up 3 (15 min; telephone)

Follow-up 1 (10 min telephone)

PHC = personal health coach

The control group received care as usual and was only contacted for the baseline and follow-up measurements. Outcome measures The present study investigated the effectiveness of the intervention on musculoskeletal symptoms, physical functioning and work-related outcomes (work ability, work performance, work-related vitality, and sickness absence). Sickness absence data were obtained from the company’s registration system after follow-up measurements were completed. All other data were obtained using questionnaires. Health-related measures Musculoskeletal symptoms The prevalence of musculoskeletal symptoms during the past three months was assessed using the Dutch Musculoskeletal Questionnaire (DMQ), which has been validated for different body regions [36]. The occurrence of pain or discomfort was rated on a four-point scale (never, sometimes, frequently, and prolonged). For the current analysis the measure was dichotomized; answer categories ‘frequently’ or ‘prolonged’ were classified as having musculoskeletal symptoms, whereas categories ‘never’ or ‘sometimes’ were classified as having no musculoskeletal symptoms. Body regions were grouped into back (upper and lower back), neck/shoulders, upper extremities (elbows and wrist/hands), and lower extremities (hips/thighs, knees, and ankle/feet).

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Physical functioning Physical functioning was measured using a sub-scale of the RAND-36, evaluating functional status [37,38]. The RAND-36 cluster on role limitations caused by physical problems consists of 4 items, and ranges from 0-100 points (higher scores indicating less limitations), with a score of 79.4 considered average [38]. The RAND-36 health survey is a widely adopted, and reliable and valid measurement of health-related quality-of-life [39]. In the present study, the validated Dutch version was used. Work-related measures Work ability was assessed with the Work Ability Index (WAI) [40-42]. The WAI covers 7 dimensions; current work ability, work ability in relation to job demands, number of current diseases, work impairment due to diseases, sickness absence days during past 12 months, own prognosis of work ability in next two years, and mental resources. Total scores over all dimensions range from 7â&#x20AC;&#x201C;49, with 4 categories: poor (7-27 points), moderate (28-36 points), good (37-43 points), excellent (44-49 points). Work-related vitality, defined as vigour, was assessed through a subscale of the Utrecht Engagement Scale (UWES) that refer to high levels of energy and resilience, the willingness to invest effort, not being easily fatigued, and persistence in the face of difficulties [43]. The answers were rated on a 7 point scale from never (0) to daily (6). The mean score of the items resulted in the work-related vitality score, with a higher score indicating a better work-related vitality. Work performance was measured using a single item from the Health Work Performance Questionnaire (WHO-HPQ)[44,45] asking workers to report their overall work performance on a 10-point scale over the past four weeks. Sickness absence data were collected directly from company records. For the analysis, cumulative sickness absence data over 6-month periods were used (pre-, during-, and post-intervention). Sickness absence has a skewed distribution with a substantial fraction clustered at the value zero. Therefore, sickness absence was dichotomized into no or short-term sickness absence (<=7 days), and long-term sickness absence (> 7 days). Statistical analysis The analysis was conducted with all available subjects at 6 and 12 months of follow-up. All available data of the participants, regardless of whether or not they actually (fully) received the intervention, were used for analysis. Data on potential confounders and effect modifiers were assessed through the baseline questionnaire and included age, smoking status, education level, and marital status. For all variables potential baseline differences were checked between intervention and control group.

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Linear and logistic regression analyses were performed for the different outcome measures, both with 6-month and 12-month follow-up as the dependent variables. Analyses were adjusted for the baseline levels. Analyses were performed using SPSS 20.0 (SPSS Inc. Chicago, Illinois, USA). For all analyses, a two-tailed p-value of <0.05 was considered statistically significant.

Results In total, 314 workers responded to the baseline questionnaire. At 12 months follow-up, 83% of the participants completed all measurements; 22 workers of the control group (14%) and 31 workers of the intervention group (19%) did not complete all follow-up measurements. Figure 1 presents the flow chart of the participants throughout the trial. Baseline characteristics are presented in table 2. No differences between groups were found for key variables. Table 2 Baseline characteristics Number of participants Age, mean (SD) Current musculoskeletal symptoms Back (%) Neck/shoulder (%) Upper extremity (%) Lower extremity (%) BMI (kg/m2) Normal (<25) (%) Overweight (25-29.9) (%) Obese (>30) (%) Smoking (Yes, %)

All N= 314 46.6 (9.7)

Intervention N= 162 46.3 (9.9)

Control N= 152 47.0 (9.5)

28.3 (89/314) 20.1 (63/314) 13.4 (42/314) 28.7 (90/314)

32.7 (53/162) 20.4 (33/162) 15.4 (25/162) 29.6 (48/162)

23.7 (36/152) 19.7 (30/152) 11.2 (17/152) 27.6 (42/152)

27.4 (3.7) 30.0 47.3 22.7

27.3 (3.5) 29.2 50.9 19.9

27.4 (3.9) 30.9 43.4 25.7

29.4

29.0

29.7

Table 3 shows complete cases intervention effects on work-related vitality, work performance, work ability, and physical functioning. For all outcome measures, a positive value for B, which represents the estimate (unstandardised coefficient) resulting from the regression analyses, can be interpreted as a positive intervention effect. No statistically significant differences were found for any of the outcome variables after 6 and 12 months of follow-up.

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Table 3 Intervention effects for work-related vitality, work performance, and work ability after 6 and 12 months follow-up Intervention group (mean, SD)

Control group (mean, SD)

Work-related vitality N 113 110 Baseline 4.98 (0.90) 4.99 (1.04) 6 months 5.01 (0.94) 4.83 (1.08) 12 months 4.82 (1.12) 4.82 (1.10) Work performance N 113 116 Baseline 7.6 (1.1) 7.9 (1.0) 6 months 7.7 (0.8) 7.6 (1.2) 12 months 7.5 (1.4) 7.6 (1.4) Work ability N 99 93 Baseline 40.6 (5.3) 40.8 (4.9) 6 months 41.3 (4.1) 40.7 (5.2) 12 months 41.3 (4.7) 40.9 (5.1) Physical functioning N Baseline 6 months 12 months

127 88.6 (25.3) 88.0 (27.6) 86.2 (28.7)

125 87.8 (26.7) 88.0 (25.0) 85.4 (28.8)

B

95%CI

p-value

0.19 0.01

(-0.02 ; 0.40) (-0.22 ; 0.23)

0.081 0.938

0.13 -0.08

(-0.13 ; 0.38) (-0.45 ; 0.28)

0.340 0.656

0.72 0.53

(-0.33 ; 1.77) (-0.59 ; 1.65)

0.177 0.348

-0.29 0.45

(-6.38 ; 5.79) (-6.21 ; 7.10)

0.925 0.895

Musculoskeletal symptoms The intervention did not result in statistically significant effects on musculoskeletal symptoms (table 4). Although for back symptoms at 6 and 12 months follow-up (OR 0.69, 95%CI: 0.361.36, and 0.76, 95%CI: 0.38-1.52, respectively) and lower extremity symptoms at 12 months (OR 0.61, 95%CI: 0.32-1.16) the odds ratios were in favour of the intervention group, differences reached no statistical significance. Sickness absence Table 5 shows mean days of sickness absence in the past 6 months and table 3 presents the course of sickness absence for the study group, dichotomized into no or short term, and longterm sickness absence. Directly following the intervention, the 6-month prevalence of longterm sickness absence was lower in the intervention group than in the control group. At 12 months sickness absence was slightly higher in the intervention group compared to the control group. However, at both 6 and 12 months the between group differences were not statistically significant.

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Table 4 Intervention effects (OR (95%CI) or B (95%CI)) for musculoskeletal symptoms and sickness absence after 6 and 12 months follow-up Intervention group N % Musculoskeletal symptoms Back symptoms Baseline 6 months 12 months Neck/shoulder symptoms Baseline 6 months 12 months Upper extremity symptoms Baseline 6 months 12 months Lower extremity symptoms Baseline 6 months 12 months Sickness absence Baseline No or short-term (<=7days) Long-term 6 months No or short-term (<=7days) Long-term 12 months No or short-term (<=7days) Long-term

Control group N %

OR

95%CI

39 25 23

30.2 19.8 18.6

32 30 25

24.8 23.4 19.4

0.69 0.76

(0.36; 1.36) (0.38; 1.52)

21 20 21

16.2 15.8 16.2

27 24 23

20.9 18.8 17.8

0.92 1.02

(0.46; 1.84) (0.50; 2.10)

17 12 13

13.3 9.6 10.2

16 11 13

12.5 8.7 10.2

1.18 0.98

(0.46; 2.98) (0.42; 2.28)

35 31 26

27.1 24.6 20.2

37 29 36

28.9 22.8 28.1

1.16 0.61

(0.62; 2.19) (0.32; 1.16)

87 39

69.0 31.0

94 35

72.9 27.1 0.86

(0.47; 1.58)

100 26

79.4 20.6

100 29

77.5 22.5 1.19

(0.66; 2.15)

94 32

74.6 25.4

101 28

78.3 21.7

Table 5 Average number of sickness absence days for the intervention and the control group during 6 month periods before the baseline and follow-up measurements.

Baseline 6 months 12 months

N 126 126 126

Intervention Mean SD 11.1 21.8 7.7 21.8 8.5 20.6

Median 2.0 0 0

N 129 129 129

Mean 8.4 7.5 7.5

Control SD 17.6 20.2 16.9

Median 0 0 0

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Discussion The aim of this study was to evaluate the effectiveness on secondary outcomes of a health promotion intervention aiming at increasing physical activity and improving dietary behaviour in construction workers. No significant short- or long-term intervention effects were found on musculoskeletal symptoms, physical functioning, work-related vitality, work performance, work ability, or sickness absence. These findings will be discussed for the different outcome measures. Musculoskeletal symptoms The lack of observed statistically significant intervention effects on musculoskeletal symptoms is in line with other intervention studies in the construction sector [46-48]. Overall in the present study, the prevalence of workers reporting musculoskeletal symptoms declined. For back and lower extremity symptoms, odds ratios were in favour of the intervention group, although not statistically significant. Since sample size calculations were performed to determine effects on the studyâ&#x20AC;&#x2122;s primary outcome measure (body weight), for other outcome measures the study could have been underpowered. In the current study it was hypothesised that an improvement in physical capacity through increased physical activity, and a decrease in workload through a reduction of overweight, would be effective in preventing or reducing musculoskeletal symptoms. Although it is still not clear what type of exercise should be recommended, several reviews support the use of exercise as an effective strategy for the prevention or treatment of musculoskeletal conditions, including a wide range of interventions, such as increasing general physical activity levels, general exercise, and specific body-region exercises for strength and flexibility [49,50]. The current intervention consisted of a combination of exercise prescription and coaching on improving physical activity levels, which implied that participants self-selected their physical activity goals. Although an increase in vigorous physical activity in the intervention group was found, this may not have been exercise or physical activity selected for the purpose to prevent or reduce musculoskeletal symptoms, and might as a result not have been the most appropriate type of activity or exercise to reduce or prevent specific symptoms. Additionally, the increase in physical activity levels may not have led to sufficient physical capacity improvements to be effective on musculoskeletal symptoms. Presumably, the effects on outcomes related to body weight, as found in this study, were not substantial enough to have a direct effect on MSD. Another explanation could be that the intervention period was not long enough for effects on MSD to occur. However, prevention of body weight gain or reducing excess body weight could have future effects by lowering both systemic and metabolic risk factors. Systemic risk factors include a combination of mechanical load on weight bearing joints and work postures. Obesity is one of the components of the

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metabolic syndrome, and metabolic risk factors are increasingly being recognised as a possible cause of MSD [51,52]. To reduce or prevent musculoskeletal symptoms it has been suggested that multi-component interventions are potentially more effective [53]. In these programmes exercise or training interventions are combined with components addressing environmental and/or organisational issues. For example, the physical and psycho-social work environment has been recognised as risk factors for MSD in the construction sector. This is supported by findings from interviews with employees during the development of the present study as well as in the study of Oude Hengel et al. [34,54]. Combining health and lifestyle promotion with efforts to decrease workload and/or change working conditions is probably necessary for programs to be effective. Work-related vitality, physical functioning, work performance, and work ability In addition to the explanation of the lack of effect as described in the section on musculoskeletal symptoms, the initially high scores for work-related vitality, physical functioning and WAI could explain the lack of further detectable increase in these outcomes, i.e. a ceiling effect. For workrelated vitality, this was also found in previous studies [55]. The lack of effect on the WAI in the current study is in accordance with previous studies on work ability [48,56,57]. The average baseline WAI score of 40.7 was only slightly higher compared to the average score of Finnish men in the same age group and engaged in physical work [58], and scores ranging from 37 to 43 are regarded as good work ability. For the physical functioning dimension of the SF-36, baseline values of the study population largely exceeded norm values of a reference population. Sickness absence With regard to sickness absence, the lack of effects is in line with other studies among blue collar worker [48,59]. During the trial period, several factors in addition to illness, which are related to sickness absence, may have influenced the results. Not all absence can be attributed to sickness; sickness absence has been associated with, for example, socioeconomic factors, organisational features, job content and attitudes to work [60]. This is especially of concern when using total sickness absence data, compared to absence related to a specific condition, such as MSD. The current economic recession, that strongly affected the construction sector during the trial period, may have distorted effects on total sickness absence or patterns of sickness absence. Stress, increased (perceived) workload, and fear of job-loss are factors that might have played a larger role under these circumstances during the study period. For all outcome measures, the lack of intervention effects can in part be attributed to the level of implementation of the program. In a process evaluation of the program it was concluded that the extent to which the program was implemented as intended was modest [61]. Although

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R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39

participantsâ&#x20AC;&#x2122; satisfaction with the program and dose delivered by the health coaches was high, exposure and fidelity were not optimal. The compliance to the coaching sessions was acceptable, but the implementation of the exercise component was not successful. Although approximately two thirds of the participants indicated to have done the exercises, only a small percentage exercised regularly as prescribed by the program. The trial findings could be applicable to a larger population of manual labour workers. The intervention was implemented in a diverse group of blue collar workers with comparable participation rates for the subunits of the construction company. However, when generalizing the results from the specific setting of the RCT to a larger worker population, it should be taken into account that compared to the original population older workers were slightly overrepresented in the study population [61]. Strengths and limitations Strengths of the study include the randomised controlled trial design, and obtaining sickness absence data from company records. The use of sickness absence data from company records is preferred since it is more accurate than data gathered via self-report [62]. Some limitations have to be addressed as well. First, power calculation was performed on the primary outcome measure of the study, i.e. body weight. As a result, group sizes might have been below the required number to establish inter-group differences for other study outcomes. Further, missing data on items of the work ability index resulted in a reduced number of complete cases. For participants who did not complete all 7 items, the index could not be determined. With exception of sickness absence, all outcome measures were obtained using self-report which may lead to over- or under-estimations of the outcomes. Finally, although contamination of the control group participants was expected to be minimal, since only intervention participants had access to coaching and the toolbox, it could not be completely ruled out. Behaviour change in colleagues working at the same worksites could have influenced control participants. Implications for practice and future research Maintaining a healthy and productive workforce depends on a wide variety of factors. It is recommended that future interventions aiming to improve work-related outcomes also include organisational and/or environmental components to more effectively target factors related to work ability and performance. Theoretically, improving physical capacity (i.e. improving muscle function or increasing oxidative capacity) by increasing physical activity and exercise might prevent or reduce musculoskeletal symptoms. In the present study we did not include measures to monitor possible effects of increased physical activity levels on physical capacity. To increase knowledge on the relevance

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of increasing physical capacity in this group of workers and to contribute to insight into optimal type, duration and intensity of exercise, future studies should include such measures related to physical capacity. Conclusion The results of this RCT did not show effects of the programme on musculoskeletal symptoms, physical functioning, work-related vitality, work performance, work ability, or sickness absence. Although the intervention programme improved physical activity levels, dietary outcomes, and weight-related outcomes at 6 months, it was not successful in improving other health-related and work-related outcomes. In conclusion, for all outcome measures in the present paper it could be argued that they are affected by additional factors to those included in the current conceptual model of the study [34]. Based on the results of the present study, organisations attempting to improve worker health- and work-related outcomes should provide additional program components. Although a non-significant decline in musculoskeletal symptoms was observed, without co-intervening on (psycho-social) organisational aspects in a more multifaceted intervention, the potential of improving these outcomes by health promotion is probably limited.

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Oude Hengel, K. M., Joling, C. I., Proper, K. I., Blatter, B. M., Bongers, P. M., (2010). A worksite prevention program for construction workers: design of a randomized controlled trial. BMC.Public Health 10, 336.

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55.

Strijk, J. E., Proper, K. I., van Mechelen, W., van der Beek, A. J., (2013). Effectiveness of a worksite lifestyle intervention on vitality, work engagement, productivity, and sick leave: results of a randomized controlled trial. Scand.J Work Environ.Health 39, 66-75.

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Nurminen, E., Malmivaara, A., Ilmarinen, J., Ylostalo, P., Mutanen, P., Ahonen, G., Aro, T., (2002). Effectiveness of a worksite exercise program with respect to perceived work ability and sick leaves among women with physical work. Scand.J Work Environ.Health 28, 85-93.

57.

Pohjonen, T., Ranta, R., (2001). Effects of worksite physical exercise intervention on physical fitness, perceived health status, and work ability among home care workers: five-year follow-up. Prev.Med 32, 465-475.

58.

Ilmarinen, J., Tuomi, K., Klockars, M., (1997). Changes in the work ability of active employees over an 11-year period. Scand.J Work Environ.Health 23 Suppl 1, 49-57.

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Jorgensen, M. B., Faber, A., Hansen, J. V., Holtermann, A., Sogaard, K., (2011). Effects on musculoskeletal pain, work ability and sickness absence in a 1-year randomised controlled trial among cleaners. BMC.Public Health 11, 840.

60.

Briner, R. B., (1996). ABC of work related disorders. Absence from work. BMJ 313, 874-877.

61.

Viester, L., Verhagen, E. A. L. M., Bongers, P. M., van der Beek, A. J., (2014). Process evaluation of a multifaceted health programme aiming to improve physical activity levels and dietary patterns among construction workers. J Occup Environ Med 56,1210-7.

62.

Ferrie, J. E., Kivimaki, M., Head, J., Shipley, M. J., Vahtera, J., Marmot, M. G., (2005). A comparison of self-reported sickness absence with absences recorded in employersâ&#x20AC;&#x2122; registers: evidence from the Whitehall II study. Occup Environ.Med 62, 74-79.

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Chapter 7 Cost-effectiveness and return-on-investment of a worksite intervention aimed at improving physical activity and nutrition among construction workers

Johanna M. van Dongen, Laura Viester, Marieke F. van Wier, Judith E. Bosmans, Evert A.L.M. Verhagen, Maurits W. van Tulder, Paulien M. Bongers, Allard J. van der Beek

To be submitted


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Abstract Objectives: To conduct a cost-effectiveness and return-on-investment (ROI) analysis of a worksite physical activity and nutrition program for construction workers in comparison with usual practice. Methods: The intervention consisted of generic as well as tailored health information and personal health counseling. A total of 314 participants were randomized to the intervention (n=162) or control group (n=152). Data on body weight, waist circumference, musculoskeletal disorders (MSD), work-related vitality, and job satisfaction were collected at baseline, 6, and 12 months. Sickness absence data were collected from company records. Other cost data were collected with 3-monthly questionnaires. Missing data were imputed using multiple imputation. Cost-effectiveness analyses were conducted from both the societal and employer’s perspective. A ROI analysis was performed from the employer’s perspective. Bootstrapping techniques were used to assess the uncertainty of the results. Results: Intervention costs per participant were €178 from the societal perspective (bottomup micro-costed) and €287 from that of the employer (market prices). At 12-month followup, no statistically significant cost and effect differences were found. The probabilities of costeffectiveness for body weight, waist circumference, and MSD gradually increased with an increasing ceiling ratio to 0.84 (willingness-to-pay = €21,000/kg), 0.77 (willingness-to-pay = €18,000/cm), and 0.84 (willingness-to-pay = €42,000/person prevented from having a MSD), respectively. The probabilities of cost-effectiveness for work-related vitality and job satisfaction were low at all ceiling ratios (≤0.54). Financial return estimates were positive, but their confidence intervals were rather wide and none of them was statistically significant. Conclusion: The intervention’s cost-effectiveness in improving weight-related outcomes and MSD depends on the societal and employer’s willingness-to-pay for these effects and the probability of cost-effectiveness that they consider acceptable. From the employer´s perspective, the intervention was not cost-effective in improving work-related vitality and job satisfaction. Also, due to a high level of uncertainty, it cannot be concluded that the intervention was costbeneficial to the employer.

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Introduction Excessive body weight and musculoskeletal disorders (MSD) have a serious impact on public health in many developed countries (1-5). In the Netherlands, the combined prevalence of overweight (Body Mass Index [BMI] 25 - 30 kg/m2) and obesity (BMI ≥ 30 kg/m2) is 48% among adults (6), and that of MSD is estimated to be 39% in adult men and 45% in adult women (7). Among construction workers, these prevalences are even higher (8;9). Both conditions not only reduce a person’s well-being, but also impose a large economic burden on companies and society as a whole due to increased absenteeism, presenteeism (i.e. reduced productivity while at work), and healthcare consumption (10-12). The workplace presents a useful setting to combat the high prevalence of excessive body weight and MSD, as it provides social and organizational support structures that can help improve risk behaviours and many companies have the infrastructure available to offer behaviour change interventions at relatively low costs (13). In addition, worksite physical activity and nutrition programs in particular, cannot only reduce body weight (14) and MSD prevalence (15), but may also generate cost savings to a company through reduced absenteeism (16) and presenteeism (17). Therefore, in the VIP in Construction study, a worksite physical activity and nutrition program was developed aimed at preventing and reducing overweight and MSD among construction workers (i.e. VIP in Construction intervention) (18). An evaluation of the intervention’s effectiveness has been reported elsewhere (19;20). Decisions about investments in worksite health promotion programs typically lie by the company management. In doing so, they are not just interested in the effectiveness of such interventions, but also in their impact on the company’s bottom-line (21;22). To provide this information, return-on-investment (ROI) analyses can be performed in which the costs of an intervention are compared to the company’s resulting financial savings (23;24). However, as health outcomes are not directly considered in a ROI analysis and other stakeholders may reap a large part of the benefits (e.g. health insurance companies), cost-effectiveness analyses (CEAs) and analyses from the broader societal perspective are of importance as well. The present study aimed to conduct CEAs and a ROI analysis, in which the VIP in Construction intervention was compared to usual practice. CEAs were performed from both the societal and employer’s perspective, and the ROI analysis from that of the employer.

Methods Study design Analyses were conducted alongside a 12-month randomized controlled trial (RCT), which took place from 2010 to 2012. The study protocol was approved by the Medical Ethics Committee of

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the VU University Medical Center (18), and the trial has been registered in the Netherlands Trial Register (NTR2095). Participants All blue collar workers of a Dutch construction company who were invited for a voluntary periodical health screening at the occupational health service between February 2010 and October 2011 were recruited for the study. Workers who were on long-term sick leave (≥4 weeks) were excluded. At baseline, all workers who decided to participate in the study provided informed consent. After baseline measurements, participants were randomized to the intervention or control group. Randomization took place at the individual level and was performed by a research assistant using a computer-generated randomization sequence in SPSS (v15, Chicago, IL). The research assistant had no information on the participants to ensure allocation concealment (18). Intervention and control condition All participants received practice as usual. Additionally, intervention group participants received the VIP in Construction intervention. A detailed description of the intervention has been given elsewhere (18). In brief, the intervention consisted of generic as well as tailored health information (i.e. VIP in Construction toolbox) and personal health counseling (PHC). Participants with a healthy weight status (i.e. BMI<25 and waist circumference<94) and a healthy physical activity level (i.e. meeting physical activity recommendations (25;26)) only received the VIP in Construction toolbox; all others also received PHC. The VIP in Construction toolbox consisted of health information brochures tailored to the participants’ physical activity level and weight status, a calorie guide, a pedometer, a BMI card, a waist circumference measuring tape, a cookbook including healthy recipes and a knowledge test, “personal energy plan” forms, an overview of the health promotion facilities of the company, and an exercise card. PHC intensity (i.e. number and duration of contacts) was tailored to the participants’ stage-ofchange for improving physical activity and nutrition (Table 1) (18;27). Face-to-face and telephone coaching contacts were provided during work hours and were given by physiotherapists specialized in lifestyle coaching (i.e. health coaches). Face-to-face coaching contacts took place at the worksite. A web-based system was used to register the participants’ coaching contacts (i.e. date, time), as well as their content (i.e. goals, action plans).

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Table 1. Personal health coaching (PHC) contact schedule Stage-of-change(27)

PHCgroup

2 weeks

1 month

2 months

Pre-contemplation stage

A

Intake

Follow-up 1: Follow-up 2:

3 months

Follow-up 3:

The participant does not intend to change his risk behavior(s)

(60 min face- (30 min; to-face) telephone)

(15 min; telephone)

Contemplation/Preparation B stage

Intake

Follow-up 1: Follow-up 2

(60 min faceto-face)

(30 min; telephone)

The participant wants to change his risk behavior(s), but does not know how Action stage The participant already started changing his risk behavior(s)

C

4 months

(15 min; telephone)

(15 min; telephone)

Intake

Follow-up 1

(30 min faceto-face)

(10 min telephone)

Abbreviations: min: minutes

Effect measures Primary and secondary outcomes were assessed at baseline, six, and 12 months.

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Primary outcomes Primary outcomes were body weight and waist circumference. Body weight was measured using a calibrated scale with participants wearing light clothes and no shoes. Waist circumference was measured midway between the lower rib margin and the iliac crest, and was rounded to the nearest 0.1cm. Measurements were performed in a standing position, over bare skin, and at the end of expiration (28). At baseline, these measurements were performed by occupational physicians or their assistants. At 6 and 12 months, they were performed by the research team. Secondary outcomes Secondary outcomes were MSD, work-related vitality, and job satisfaction. The prevalence of MSD was assessed using the “Dutch Musculoskeletal Questionnaire” (DMQ) (29). Participants were asked to rate the occurrence of pain or discomfort in the neck, shoulders, upper and lower back, elbows, wrists/hands, knees, and ankles/feet during the previous three months on a 4-point scale (never, sometimes, frequent, and prolonged). Participants who answered “frequent” or “prolonged” on one or more of the questions were classified as having MSD; all others as not having MSD. Work-related vitality was assessed using a subscale of the “Utrecht Work Engagement Scale” (i.e. UWES Vitality Scale). This scale included six items, scored on a 7-point scale ranging from “never”(0) to “always”(6). The UWES Vitality Score ranged from 0-6 (higher scores indicate a better work-related vitality) (30). Job satisfaction was assessed using a 1-item question of the

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“Netherlands Working Conditions Survey” (31). Participants were asked to rate their overall job satisfaction on a 5-point scale ranging from “very dissatisfied”(1) to “very satisfied”(5). Resource use and valuation Intervention costs For the societal perspective, bottom-up micro-costing was used to quantify intervention costs (32). Intervention costs included those related to the development, implementation, and operation of the intervention. Frequency, duration, preparation time, and locations of coaching contacts were recorded by the coaches. Labor costs were valued by multiplying the intervention staff’s time investments (hours) by their gross hourly salaries including overhead costs. Capital costs were valued using cost data collected from finance department staff. Material costs were estimated using invoices. Coaches’ travelling costs were valued according to the Dutch manual of costing (33). As PHC contacts took place during work hours, the participants’ lost productivity costs for the duration of the contacts were included as well, and were valued using the average salary (including overhead costs) of Dutch construction workers (Economic Institute of the Dutch construction industry, personal communication). For the employer’s perspective, intervention costs were valued using charges paid. Lost productivity due to PHC was valued using the average salary (including overhead costs) of blue collar workers of the participating company. Healthcare costs Healthcare utilization was assessed using 3-monthly retrospective questionnaires and included costs of primary healthcare (i.e. general practitioner, allied health professionals, complementary medicine), secondary healthcare (i.e. medical specialist, hospitalization), and both prescribed and over-the-counter medications. Dutch standard costs were used to value primary and secondary healthcare utilization (33). If unavailable, prices according to professional organizations were used. Medication use was valued using unit prices of the Royal Dutch Society of Pharmacy (34). Occupational health costs Occupational health costs consisted of gym membership subsidies, as provided by the employer. The duration of the memberships was assessed using 3-monthly retrospective questionnaires. The associated costs were calculated by multiplying the duration of the memberships (in months) by the height of the subsidy (i.e. €10/month). Sports costs Sports costs were assessed using 3-monthly retrospective questionnaires asking participants to report their sports membership fees and expenses on sports equipment during the previous three months.

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Absenteeism costs Baseline (i.e. one year prior to baseline) and follow-up sickness absence data were collected from company records. For the societal perspective, costs per sickness absence day were calculated by dividing the average annual salary of Dutch construction workers (including overhead costs) by the associated number of workable days (i.e. 214) (33). Absenteeism costs were estimated using the “Friction Cost Approach”(FCA) (35). A friction period of 23 weeks (i.e. period needed to replace a sick worker) and an elasticity of 0.8 (i.e. a 100% reduction in work time corresponds with an 80% reduction in productivity) were assumed (33;35). For the employer’s perspective, costs per sickness absence day were calculated using the average annual salary of blue collar workers of the participating company (including overhead costs). Subsequently, absenteeism costs were estimated using the “Human Capital Approach”(HCA), in which absenteeism costs are neither truncated as in the FCA, nor is elasticity considered (33). Presenteeism costs Presenteeism was assessed on a 3-monthly basis using an item of “The World Health Organization Health and Work Performance Questionnaire”(WHO-HPQ) (36;37). In the WHO-HPQ, presenteeism is conceptualized as a measure of actual work performance in relation to “best performance”, irrespective of the presence or absence of health complaints (37). Participants were asked to rate their overall work performance during the previous three months on an 11-point scale ranging from “worst performance”(0) to “best performance”(10). Their average work performance during follow-up (Wown) was estimated and the participants’ level of presenteeism (PHPQ) was calculated using the following formula: PHPQ = (10 – Wown)/10 Presenteeism days were calculated by multiplying the participants’ PHPQ by their number of days worked during follow-up; i.e. working days minus sickness absence days. Presenteeism days were valued using the average salary of Dutch construction workers (societal perspective) and that of blue collar workers of the participating company (employer’s perspective). Using consumer price indices, all costs were converted to 2011 Euros (38). Discounting of costs and effects was not necessary, because the follow-up of the trial was one year (39). Price weights used for valuing resource use are given in Appendix 1. Data analysis Analyses were performed according to the intention-to-treat method. Descriptive statistics were used to compare baseline characteristics between intervention and control group participants, and participants with complete and incomplete data. Missing data were imputed in IBM SPSS

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(v20, Chicago, IL) using Fully Conditional Specification and Predictive Mean Matching. An imputation model was constructed that included variables related to the “missingness” of data and those that predicted the outcome variables. The model included age, smoking status, baseline sickness absence, baseline effect measure values, and available midpoint and followup cost and effect measure values (6- and 12 months). Fifteen different data sets were created (Loss of Efficiency≤5%) (40). Each data set was analyzed separately as specified below. Pooled estimates were subsequently calculated using Rubin’s rules (41). Data were imputed at the cost level. Therefore, a descriptive analysis of resource use was performed using the complete-cases only. T-tests were used for continuous variables and Chi-square tests for dichotomous variables. For skewed data, uncertainty was assessed using the bias-corrected accelerated (BCA) bootstrap method (5000 replications). Unless otherwise stated, data were analyzed in STATA (V12, Stata Corp, College Station, TX), with a level of significance of p<0.05. Cost-effectiveness analysis CEAs in terms of body weight and waist circumference were conducted from the societal perspective (i.e. all costs were taken into consideration regardless of who pays or benefits). CEAs in terms of work-related vitality, job satisfaction, and MSD were conducted from the employer’s perspective (i.e. only the costs borne by employers were considered). Linear regression analyses were used to compare outcomes between the intervention and control group. Follow-up outcomes were adjusted for their baseline values. To compare costs between both groups, 95% confidence intervals (95%CIs) around the unadjusted mean differences in total and disaggregated costs were calculated using BCA bootstrapping (5000 replications). Seemingly unrelated regression (SUR) analyses were performed, in which effect differences were corrected for their baseline values and cost differences for baseline sickness absence and presenteeism scores (42). Incremental cost-effectiveness ratios (ICERs) were calculated by dividing the corrected cost differences by those in effects. Uncertainty was graphically illustrated by plotting bootstrapped incremental cost-effect pairs (CE-pairs) on cost-effectiveness planes (CE-planes) (43). A summary measure of the joint uncertainty of costs and effects was provided using cost-effectiveness acceptability curves (CEACs), which provide an indication of the intervention’s probability of cost-effectiveness at different ceiling ratios (i.e. the maximum amount of money decision-makers are willing to pay per unit of effect) (44). Return-on-investment analysis The ROI analysis was performed from the employer’s perspective, in which only employer costs and benefits were considered. Costs were defined as intervention costs. Benefits were defined as the difference in total monetized outcome measures (i.e. absenteeism, presenteeism, and occupational health costs) between the intervention and control group during follow-up, with positive benefits indicating reduced spending. The ROI analysis (costs and benefits) was

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conducted using SUR analyses, in which benefits were adjusted for baseline sickness absence and presenteeism scores. Three ROI metrics were calculated; 1) Net Benefits (NB), 2) Benefit Cost Ratio (BCR), and 3) Return On Investment (ROI) (23;24;45). NB = Benefits – Costs BCR = Benefits / Costs ROI = ((Benefits – Costs)/Costs)*100 To quantify precision, 95% bootstrapped confidence intervals (5000 replications) were estimated around the benefits and ROI metrics using the percentile method. Financial returns are positive if the following criteria are met: NB>0, BCR>1, and ROI>0% (23;24;45). Sensitivity analyses Five sensitivity analyses were conducted to test the robustness of the results. First, analyses were performed using the complete-cases only (SA1). Second, analyses were performed in which intervention costs were estimated under the assumption that the intervention took place outside work hours (SA2). Thus, the costs of lost productivity due to PHC were excluded. Third, analyses were performed in which absenteeism costs were valued using the HCA for the societal perspective and the FCA for the employer’s perspective (SA3). Fourth, analyses were performed in which presenteeism costs were estimated using a slightly modified version of the “PROductivity and DISease Questionnaire” (PRODISQ) (46;47). In this version of the PRODISQ, presenteeism was conceptualized as reduced work performance due to health complaints and was valued by considering both the quantity and quality of labor input (SA4). Fifth, as overall consensus about whether or not to include presenteeism costs in economic evaluations does currently not exist, analyses were performed in which presenteeism costs were excluded (SA5).

Results Participants After randomization, 162 participants were allocated to the intervention group and 152 to the control group. At baseline, intervention group participants had approximately four more sickness absence days than their control group counterparts. Also, the prevalence of MSD was higher in the intervention group (55.6%) than in the control group (49.3%) (Table 2). After 12 months, 32 intervention group (19.7%) and 22 control group participants (14.5%) were lost to followup, among others, because they lost their job or lost interest in the study (Figure 1). Complete data were obtained from 62.4% of participants on the effect measures (n=196; 101 intervention group participants and 95 control group participants) and 40.5% on the cost measures (n=127;

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Economic evaluation VIP in Construction

participants and 95 control group participants) and 40.5% on the cost measures (n=127; 62 intervention group participants and 65 control group participants). Some 62 intervention group participants and 65 control group participants). Someincomplete differences data were differences were observed between participants with complete and observed between participants with complete and incomplete data in both the intervention and

in both the intervention and control group (Table 2).

control group (Table 2).

Blue collar workers invited to participate (n=1021)

Enrollment

Willing to participate (n=327)

Excluded (n=13) â&#x2122;Ś Not meeting inclusion criteria (n=10) â&#x2122;Ś Other reasons (n=3)

Randomized (n=314)

Allocation Allocated to intervention (n=162)

Allocated to control (n=152)

6 Follow-Up after 6 months

Reasons at 6 months: Termination of employment (n=10); No time/interest (n=10); health problems (n=1); deceased (n=1); unknown (n=3)

Lost to follow-up after baseline (n=15)

Lost to follow-up after baseline (n=25)

Follow-Up after 12 months

Reasons at 12 months: Termination of employment (n=11); No time/interest (n=15); health problems (n=1); deceased (n=1); unknown (n=3); other (n=1)

Reasons at 6 months:

Reasons at 12 months:

Lost to follow-up after baseline (n=32)

Lost to follow-up after baseline (n=22)

Complete cases (n=52; 32.1%)

Complete cases (n=47; 30.1%)

Effect data: n=101 Cost data: n=62

Effect data: n=95 Cost data: n=65

Multiple imputations (n=110)

Termination of employment (n=5); No time/interest (n=17)

Multiple imputations (n=105)

Analysis Imputed dataset (n=162; 100.0%)

Termination of employment (n=5); No time/interest (n=10)

Imputed dataset (n=152; 100.0%)

Figure of participants to theto VIPthe in Construction study Figure1.1:Flow Flowchart chart of participants VIP in Construction study

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72 (44.4); n=162 4.9 (1.0); n=157 4.0 (0.7); n=157

No

Work-related vitality (range: 0-6) [mean (SD)]

Job satisfaction (range: 1-5) [mean (SD)]

77 (50.7); n=152 5.0 (1.0); n=142 3.9 (0.9); n=146

50 (45.5); n=110 4.8 (1.1); n=105 4.0 (0.7); n=105

5.0 (1.00); n=52 4.0 (0.8); n=52

75 (49.3); n=152

60 (54.5); n=110

11 (42.3); n=52

30 (57.7); n=52

27.4 (3.9); n=152

7.7 (0.9); n=52

7.5 (1.2); n=102

7.9 (1.0); n=143

Abbreviations: n: number, SD: standard deviation, WHO-HPQ: World Health Organization Work Performance Questionnaire

Work performance: WHO-HPQ work performance 7.6 (1.1); n=154 score during a 4-week period prior to baseline [mean (SD)]

Sickness absence: number of sickness absence 14.0 (26.9); n=162 11.9 (24.7); n=52 15.0 (27.9); n=110 9.8 (20.6); n=152 days during the year prior to baseline [mean (SD)]

90 (55.6); n=162

Yes

Musculoskeletal disorders [n (%)]

99.0 (10.2); n=152 99.4 (10.1); n=52 98.9 (10.3); n=100 100.0 (11.8); n=133 100.3 (12.9); n=47 99.8 (11.2); n=86

Waist circumference (centimetres) [mean (SD)]

27.2 (3.3); n=52

7.9 (1.0); n=47

11.1 (25.8); n=47

4.0 (0.9); n=47

5.0 (1.0); n=47

26 (55.3); n=47

21 (44.7); n=47

27.9 (4.4); n=47

89.9 (16.3); n=47

27.3 (3.5); n=161

Body Mass Index (kg/m-2) [mean (SD)]

27.4 (3.6); n=109

88.7 (12.9); n=161 87.4 (11.8); n=52 89.3 (13.4); n=110 88.9 (14.4); n=152

Body weight (kilograms) [mean (SD)]

14 (31.1); n=45

44 (29.7); n=148

33 (31.7); n=104

12 (23.5); n=51

45 (27.8); n=155

7.9 (1.0); n=96

9.3 (17.8); n=105

3.9 (0.9); n=99

5.0 (1.0); n=95

51 (48.6); n=105

54 (51.4); n=105

27.2 (3.7); n=105

88.5 (13.5); n=105

30 (29.1); n=103

46.8 (9.9); n=104

105 (100); n=105

Incomplete (n=105)

Smokers [n (%)]

47 (100); n=47 47.5 (8.7); n=47

152 (100); n=152

110 (100); n=110 45.3 (10.1); n=110 47.0 (9.5); n=151

52 (100); n=52

Complete (n=47)

Control group

48.2 (9.2); n=52

All (n=152)

46.3 (9.9); n=162

Incomplete (n=110)

162 (100); n=162

Complete (n=52)

Intervention group

Age (years) [mean (SD)]

All (n=162)

Male [n (%)]

Baseline characteristics

Table 2. Baseline characteristics of the study population

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Effectiveness After 12 months, no statistically significant differences were found between the intervention and control group for body weight (-0.7; 95%CI: -2.2 to 0.7), waist circumference (-0.7; 95%CI: -2.5 to 1.1), MSD (-0.07; 95%CI -0.22 to 0.08), work-related vitality (-0.03; 95%CI: -0.39 to 0.33), and job satisfaction (-0.01; 95%CI: -0.34 to 0.32). Resource use Forty participants were allocated to PHC group A, 61 to PHC group B, 48 to PHC group C, and 13 only received the VIP in Construction toolbox (Table 1). During the intervention period, 126 face-to-face and 173 telephone counseling contacts were provided. Based on the completecases, intervention and control group participants did not significantly differ in terms of their average number of visits to a care provider (-2.4; 95%CI: -5.7 to 0.7), average number of days of hospitalization (-0.1; 95%CI: -0.4 to 0.2), average number of months of gym membership subsidies (0.5; 95%CI: -0.3 to 1.3), average number of sickness absence days (-2.7; 95%CI: -9.7 to 3.0), and average number of presenteeism days (-2.6; 95%CI: -9.6 to 4.1). However, significantly more intervention group participants (n=36) had sports costs than their control group counterparts (n=23; X2: 5.3, p=0.02) (Appendix 1). Costs Average intervention costs per participant were €178 (SD=77) from the societal perspective and €287 (SD=22) from the employer’s perspective (Appendix 2). No statistically significant differences were found on all cost measures (Table 3).

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Table 3. Mean costs per participant in the intervention and control group, and unadjusted mean cost differences between both groups during the 12-month follow-up period Cost category

Intervention costs Medical costs Occupational health costs Sports costs Absenteeism costs Presenteeism costs Total Intervention costs Occupational health costs Absenteeism costs Presenteeism costs Total

Intervention group n=162; mean (SEM)

Control group n=152; mean (SEM)

Societal perspective 178 (6) 0 (0) 1499 (356) 1033 (174) 26 (4) 20 (3) 461 (98) 265 (46) 2214 (338) 2055 (345) 9382 (550) 9663 (975) 13760 (725) 13037 (1025) Employer’s perspective 287 (2) 0 (0) 26 (4) 20 (3) 2543 (447) 2217 (374) 10088 (591) 10390 (1048) 12943 (616) 12626 (1111)

Mean cost difference (95%CI) 178 (166 to 190) 457 (-129 to 1434) 5 (-3 to 15) 156 (32 to 497) 150 (-802 to 1094) -533 (-2449 to 1597) 412 (-1572 to 3093) 287 (283 to 290) 5 (-3 to 15) 306 (-742 to 1551) -573 (-2634 to 1717) 25 (-2005 to 2485)

Abbreviations: n: number; SEM: Standard Error of the Mean, CI: Confidence Interval, NA: Not Applicable, SD: Standard Deviation Note: Costs are expressed in 2011 Euros

Societal perspective: cost-effectiveness The ICER for body weight was -371, indicating that society has to pay €371 for an additional kilogram body weight loss. An ICER in the similar direction was found for waist circumference (ICER:-392). In both cases, the majority of CE-pairs were located in the north-east quadrant (Table 4; Figure 2 (1a-b)). These results imply that the intervention was more costly and more effective than usual practice, but the wide distribution of CE-pairs around the quadrants of the CE-planes indicates that the uncertainty surrounding these estimates was large (Table 4; Figure 2 (1a-b)). The CEAC in Figure 2 (2a) indicates that if society is not willing to pay anything for a kilogram body weight loss, the probability of cost-effectiveness is 0.41. This probability increased with an increasing willingness-to-pay to 0.84 at a ceiling ratio of €21,000/kg. The CEAC for waist circumference showed a similar picture, with a 0.41 probability at a ceiling ratio of €0/cm and a maximum of 0.77 at a ceiling ratio of €18,000/cm (Figure 2(2b)).

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R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39

Economic evaluation VIP in Construction

(1) a

(2) a

(1) b

(2) b

6 (1) c

(3) c

Figure indicating the the uncertainty around the incremental cost-effectiveness Figure 2. 2: Cost-effectiveness Cost-effectivenessplanes planes indicating uncertainty around the incremental costratios (1) and cost-effectiveness acceptability curves indicating the probability of the intervention being costeffectiveness ratios (1) and cost-effectiveness acceptability curves indicating the probability effectiveness at different values (â&#x201A;Ź) of willingness to per unitvalues of effect (2) for weight loss per (a), waist of the intervention being cost-effectiveness atpay different (â&#x201A;Ź)gained of willingness to pay circumference (b), and MSD (c) (based on the imputed dataset). unit of effect gained (2) for weight loss (a), waist circumference (b), and MSD (c) (based on Note: Effects are expressed in terms of kilogram body weight loss and waist circumference, and MSD the imputed dataset). prevalence reduction

Note: Effects are expressed in terms of kilogram body weight loss and waist circumference, and MSD prevalence reduction

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179


Employer’s perspective: cost-effectiveness For MSD, an ICER of 2000 was found, indicating that employers save €2,000 per additional person prevented from having a MSD. Most CE-pairs were contained in the north-east quadrant (Table 4; Figure 2(1c)). This implies that the intervention was less costly and more effective than usual practice, but the level of uncertainty was large. The CEAC in Figure 2 (2c) indicates that the probability of cost-effectiveness was 0.55 at a ceiling ratio of €0/person, increasing to 0.84 at a ceiling ratio of €42,000/person. The ICERs for work-related vitality and job satisfaction were 3322 and 16328, respectively (Table 4). In both cases, the intervention was less costly and less effective than usual practice. CEACs showed that the associated maximum probabilities of cost-effectiveness were 0.54 for both outcomes, irrespective of the willingness-to-pay (Figures not shown). Employer’s perspective: financial return Total benefits in terms of absenteeism, presenteeism, and occupational health costs were on average €424 (95%CI: -1789 to 2923) (Table 5). The NB was on average 138 (95%CI: -2073 to 2641), suggesting that the intervention resulted in a net saving to the employer of €138 per participant. The BCR (i.e. amount of money returned per Euro invested) and ROI (i.e. percentage of profit per Euro invested) were 1.48 (95%CI: -6.23 to 10.21) and 48% (95%CI: -723 to 921), respectively. However, their confidence intervals were rather wide and none of them was statistically significant. Sensitivity analyses The results of SA2 and SA3 were similar to those of the main analysis, whereas the outcomes of SA1 (complete-case analysis), SA4 (PRODISQ), and SA5 (Excluding presenteeism) differed in some aspects from those of the main analysis (Table 4; Table 5).

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- Outside work hours

- HCA

- PRODISQ

- Excluding presenteeism costs

SA2

SA3

SA4

SA5

- Complete-cases

- Outside work hours

- FCA

SA1

SA2

SA3

Main analysis - Imputed dataset

- Complete-cases

SA1

Main analysis - Imputed dataset

Analysis

152 152 152

162 162

152

162 162

152

162

47

52 152

47

52 162

47

152

162 52

152

162

Control

Intervention 152

152

162

162

152

152

162 162

152

152

162 162

152

152

162 162

152

47

52 162

47

152

52

152

162

Control

162

Intervention

Sample size

Job satisfaction (range: 1-5)

Work-related vitality (range: 0-6)

MSD

Job satisfaction (range: 1-5)

Work-related vitality (range: 0-6)

MSD

Job satisfaction (range: 1-5)

Work-related vitality (range: 0-6)

MSD

Job satisfaction (range: 1-5)

Work-related vitality (range: 0-6)

MSD

Employer’s perspective

Waist circumference

Body weight

Waist circumference

Body weight

Waist circumference

Body weight

Waist circumference

Body weight

Waist circumference

Body weight

Waist circumference

Body weight

Societal perspective

Outcome

-0.7 (-2.5 to 1.1)

-0.7 (-2.2 to 0.7)

Points

∆E (95% CI)

Points/ proportions

-0.7 (-2.5 to 1.1)

-0.7 (-2.2 to 0.7)

-0.7 (-2.5 to 1.1)

-0.7 (-2.2 to 0.7)

-0.7 (-2.5 to 1.1)

-0.7 (-2.2 to 0.7)

-0.7 (-2.5 to 1.1)

-0.7 (-2.2 to 0.7)

-294 (-2761 to 1946) -0.01 (-0.34 to 0.32)

-236 (-2742 to 1954) -0.03 (-0.39 to 0.32)

-260 (-2824 to 1914) -0.07 (-0.22 to 0.08)

-158 (-2638 to 2041) -0.01 (-0.34 to 0.32)

-142 (-2611 to 2055) -0.03 (-0.39 to 0.32)

-171 (-2702 to 2028) -0.07 (-0.22 to 0.08)

-1126 (-3266 to 550) 0.02 (-0.22 to 0.26)

-1180 (-3300 to 496) -0.05 (-0.36 to 0.25)

-1161 (-3027 to 706) 0.01(-0.19 – 0.18)

-129 (-2610 to 2070) -0.01 (-0.34 to 0.32)

-113 (-2583 to 2083) -0.03 (-0.39 to 0.33)

-142 (-2674 to 2056) -0.07 (-0.22 to 0.08)

796 (-433 to 2327)

799 (-430 to 2317)

-89 (-1586 to 1564)

-89 (-1586 to 1559)

386 (-2001 to 2800)

386 (-2011 to 2794)

246 (-2168 to 2665)

245 (-2181 to 2653)

-1196 (-3400 to 602) -1.1 (-3.0 to 0.8)

-1228 (-3514 to 576) -0.5 (-1.8 to 0.8)

272 (-2140 to 2692)

271 (-2155 to 2679)

∆C (95% CI)

20.2

15.6

38.9

NE1

69.6

74.5

36.0

39.2

51.7

53.6

47.6

49.2

13.7

10.7

48.3

50.0

NE1

3.1

30671

9677

3700

19960

4167

2400

18.1

13.8

35.3

19.6

15.2

38.1

-54230 4.4

22121

29.7

30.0

47.7

28.2

28.5

45.0

52.5

33.1

45.8

27.7

28.1

44.1

SE2

9.9

9.9

43.5

45.3

27.8

30.9

31.9

35.3

74.4

67.9

31.2

34.4

SE2

28.6

27.8

10.6

26.6

25.7

10.1

34.4

53.5

40.4

26.1

25.0

10.0

SW3

2.2

2.1

11.2

9.5

9.2

6.1

10.0

6.6

10.5

17.4

9.8

6.5

SW3

23.7

28.4

6.4

25.6

30.7

6.8

8.6

10.3

8.2

26.0

31.3

7.0

NW4

18.4

13.5

9.3

6.1

11.3

9.4

10.5

8.9

1.4

4.0

10.7

9.1

NW4

Distribution CE-plane (%)

248800 5.6

16328

3322

2000

€/point

-1147

-1093

128

122

-556

-527

-354

-334

1068

2418

-392

-371

€/point

ICER

Table 4. Differences in pooled mean costs and effects (95% Confidence intervals), incremental cost-effectiveness ratios, and the distribution of incremental cost-effect pairs around the quadrants of the cost-effectiveness planes

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39


- Excluding presenteeism

SA5 152 152

162 162

152

162 152

152

162 162

152

162

-0.07 (-0.22 to 0.08)

422 (-559 to 1517) 416 (-563 to 1504)

Work-related vitality (range: 0-6) Job satisfaction (range: 1-5)

-0.01 (-0.34 to 0.32)

-0.03 (-0.39 to 0.32)

-0.01 (0.34 to 0.32)

408 (-567 to 1487)

Job satisfaction (range: 1-5)

-0.07 (-0.22 to 0.08) -0.03 (-0.39 to 0.32)

-544 (-1807 to 744)

Work-related vitality (range: 0-6) MSD

-556 (-1811 to 727) -535 (-1798 to 760)

MSD

7800

15.6

64.4

8.4

8.5

-43750 36.2

-13155 34.9

-5700

57512

16464

67.8

11.4

9.1

19.0

39.2

35.5

12.6

10.2

12.2

3.0

40.5

43.9

4.0

42.1

43.7

13.6

11.8

12.2

Abbreviations: CI: Confidence Interval, C: Costs, E: Effects, ICER: Incremental Cost-Effectiveness Ratio, CE-plane: Cost-Effectiveness plane, SA: Sensitivity Analysis, HCA: Human Capital Approach, FCA: Friction Cost Approach, MSD: Musculoskeletal Disorders Note: Costs are expressed in 2011 Euros 1 Refers to the northeast quadrant of the CE plane, indicating that the VIP in Construction intervention is more effective and more costly than usual practice 2 Refers to the southeast quadrant of the CE plane, indicating that the VIP in Construction intervention is more effective and less costly than usual practice 3 Refers to the northwest quadrant of the CE plane, indicating that the VIP in Construction intervention is less effective and more costly than usual practice 4 Refers to the southwest quadrant of the CE plane, indicating that the VIP in Construction intervention is less effective and less costly than usual practice

- PRODISQ

SA4

7

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-

Sample size I C Imputed dataset 162 152 Complete dataset 52 47 Outside work hours 162 152 HCA 162 152 PRODISQ 162 152 Excluding presenteeism 162 152

Costs â&#x201A;Ź 287 (283 to 290) 289 (283 to 295) 258 (258 to 258) 287 (283 to 290) 287 (283 to 290) 287 (283 to 290)

Benefits Total (95% CI) 424 (-1789 to 2923) 1447 (-265 to 3530) 430 (-1783 to 2928) 543 (-1697 to 3034) 840 (-442 to 2099) -123 (-1142 to 910) NB1 (95% CI) 138 (-2073 to 2641) 1158 (-757 to 2948) 172 (-2039 to 2677) 257 (-1967 to 2769) 553 (-728 to 1814) -410 (-1458 to 595)

Financial return BCR2 (95% CI) 1.48 (-6.23 to 10.21) 5.00 (-1.64 to 11.20) 1.67 (-6.90 to 11.38) 1.90 (-5.87 to 10.67) 2.93 (-1.54 to 7.33) -0.43 (-4.08 to 3.08)

ROI (%)3 (95% CI) 48 (-723 to 921) 400 (-264 to 1020) 67 (-790 to 1038) 90 (-687 to 967) 193 (-254 to 633) -143 (-508 to 208)

Abbreviations: CI: Confidence Interval, NB: Net Benefit, BCR: Benefit Cost Ratio, ROI: Return-On-Investment, I: Intervention, C: Control, SA: Sensitivity Analysis, HCA: Human Capital Approach Note 1: Costs are expressed in 2011 Euros Note 2: Financial returns are positive if the following criteria are met: NB>0, BCR>1, and ROI>0 1 Indicates the amount of money returned after intervention costs are recovered 2 Indicates the amount of money returned per Euro invested in the intervention 3 Indicates the percentage of profit per Euro invested in the intervention

Main analysis SA1 SA2 SA3 SA4 SA5

Analysis

Table 5. Intervention costs, benefits, Net Benefits (NB), Benefit Cost Ratio (BCR), and Return-On-Investment (ROI) per participant

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39


In SA1, total societal and employer’s costs were lower in the intervention group than in the control group. All cost and effect differences were not statistically significant. CEACs differed from those of the main analysis (Figures not shown). Most notably, a 0.88 probability of costeffectiveness was found for body weight at a ceiling ratio of €0/kg, increasing to 0.94 at €1,000/ kg. In accordance with the main analysis, financial return estimates were positive, but their confidence intervals were rather wide and not statistically significant. When using the PRODISQ (SA4), total societal and employer’s costs were lower in the intervention group than in the control group. All cost and effect differences were not statistically significant. CEACs differed from those of the main analysis (Figure not shown). Most notably, a 0.54 probability of cost-effectiveness was found for body weight at a ceiling ratio of €0/kg, increasing to 0.84 at €4,000/kg. In accordance with the main analysis, financial return estimates were positive, but their confidence intervals were rather wide and not statistically significant. When excluding presenteeism costs (SA5), total societal and employer’s costs were higher in the intervention group than in the control group. All cost and effect differences were not statistically significant. CEACs differed from those of the main analysis (Figures not shown). Most notably, a 0.22 probability of cost-effectiveness was found for MSD at a ceiling ratio of €0/person, increasing to 0.82 at €100,000/person. In contrast to the main analysis, financial return estimates were negative, but statistically non-significant as well.

7 Discussion This study evaluated the cost-effectiveness and financial return of a worksite physical activity and nutrition program for construction workers. In comparison with usual practice, the intervention had no significant effect on all cost and effect measures. The probabilities of cost-effectiveness for body weight, waist circumference, and MSD increased with an increasing ceiling ratio to 0.84 (willingness-to-pay = €21,000/kg), 0.77 (willingness-to-pay = €18,000/cm), and 0.84 (willingnessto-pay = €42,000/person prevented from having MSD), respectively. The probabilities of costeffectiveness for work-related vitality and job satisfaction were low at all ceiling ratios (≤0.54). Also, per Euro invested in the program, €1.48 was returned to the employer, but the uncertainty surrounding this estimate was large. Effects and costs Various reasons may explain the lack of significant effects at 12-month follow-up. First, as the intervention focused on both the prevention and treatment of excessive body weight and MSD, participation in the intervention was not restricted to high-risk individuals (e.g. employees were not pre-selected on high body weight). As a consequence, many participants were relatively healthy at baseline, leaving less room for improvement. Second, a lower than expected number

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R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39

of participants fully participated in the program; e.g. 39% of participants eligible for counselling did not complete the PHC program and most of the VIP in Construction toolbox materials were used by fewer than 50% of participants (48). Third, it is possible that the intensity of the intervention was too low to improve the participants’ lifestyle behaviours in such a way that it translates in long-term health improvements. To illustrate, the intervention was previously found effective in reducing body weight at 6-month follow-up (19), but this effect was not sustained at the long-term. To sustain this effect, more counselling contacts and/or booster sessions after the termination of the intervention may be needed. As for the lack of significant cost differences, it is known that cost data are right skewed and therefore require relatively large sample sizes to detect relevant differences. Nonetheless, as in most trial-based economic evaluations, the sample size was based on one of the primary outcomes (i.e. body weight) (18), which likely underpowered it to detect relevant cost differences. It is noteworthy that the present findings with respect to body weight-related outcomes (i.e. the primary outcomes) contrast those of previous studies. Two systematic reviews found worksite physical activity and nutrition programs to significantly reduce body weight by -1.3kg and -1.2kg (14;49). In addition, Groeneveld et al. (2010) showed in an RCT that a similar intervention for construction workers resulted in a statistically significant body weight loss of -1.8kg at 12-month follow-up (50). The difference in effect between both studies is likely explained by the fact that their intervention was more intensive than ours; i.e. three face-to-face and four telephone contacts versus a maximum of one face-to-face and three telephone contacts. Furthermore, their intervention was aimed at construction workers with an elevated risk of cardiovascular disease, whereas the present intervention was aimed at construction workers in general. This supports our reasoning that a more intensive program, aimed at high-risk individuals, may have been needed to produce better effects. Societal perspective: Cost-effectiveness The intervention’s cost-effectiveness in improving weight-related outcomes depends on the societal willingness-to-pay for these effects and the probability of cost-effectiveness that society considers acceptable. Since both are unknown, however, strong conclusions cannot be made. Nonetheless, decision-makers themselves can use the present results to consider whether they perceive that the intervention provides “good value for money” at an acceptable probability of cost-effectiveness. The aforementioned study of Groeneveld et al. (2011) also evaluated the societal costeffectiveness of the worksite physical activity and nutrition program. They found an ICER of €145/ kg body weight loss, a 0.60 probability of cost-effectiveness at a ceiling ratio of €250/kg, which increased to 0.95 at €2,000/kg (51). In contrast to the present study, however, presenteeism and occupational health costs were not included. If we would exclude both cost categories as well, an ICER of €1088/kg body weight loss would be found. Van Wier et al. (2013) evaluated the

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societal cost-effectiveness of an occupational health guideline aimed at preventing weight gain among Dutch employees. As the probabilities of cost-effectiveness were low for body weight and waist circumference (≤0.52), the intervention was not considered cost-effective (52). Most other studies that evaluated the cost-effectiveness of similar interventions in improving weight-related outcomes solely included intervention costs (53). Employer’s perspective: Cost-effectiveness The intervention was not cost-effective in improving work-related vitality and job satisfaction (≤0.54 probabilities of cost-effectiveness). If employers are not willing to pay anything for preventing one person from having a MSD, there is a 0.55 probability of the intervention being cost-effective. This probability increased with an increasing willingness-to-pay to 0.84 at a ceiling ratio of €42,000/person. Again, however, strong conclusions about the intervention’s cost-effectiveness in terms of this outcome cannot be made, and employers themselves should consider whether the intervention provides “good value for money” at an acceptable probability of cost-effectiveness. To our knowledge, studies evaluating the employer’s cost-effectiveness of similar interventions in improving work-related vitality and MSD are lacking. One study, however, evaluated the employer’s cost-effectiveness in improving job satisfaction of a mindfulness-based worksite intervention aimed at improving work engagement and energy balance-related behaviours (54). Irrespective of the maximum willingness-to-pay, the intervention had a low probability of cost-effectiveness (≤0.25) and was therefore not considered cost-effective in improving job satisfaction either. Employer’s perspective: Financial return On average, €1.48 was returned to the employer per Euro invested in the program. However, as the uncertainty surrounding the financial return estimates was large and none of them was statistically significant, it cannot be concluded that the intervention was cost-beneficial to the employer. A systematic review found worksite physical activity and/or nutrition programs to result in positive financial returns in terms of absenteeism benefits according to non-randomized studies (BCR: 4.25), but negative financial returns according to RCTs (BCR: 0.51). If we would solely include absenteeism benefits, our results would be in line with those of the review (BCR: 0.41). The review also indicated that the current evidence on the financial return of such interventions is limited by the fact that few studies incorporate presenteeism benefits and none of them report on the uncertainty surrounding their results. The present findings underscore the importance of addressing these limitations. Namely, as financial return estimates were positive, but statistically non-significant, wrong conclusions would have been drawn if the level of uncertainty was not taken into account. Furthermore, the direction of the financial return estimates proved to be highly influenced by the in- or exclusion of presenteeism benefits; i.e. positive when included, but negative when excluded. Economic evaluation | 143

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R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39

Robustness of the study results In accordance with the main analysis, cost and effect differences as well as financial return estimates were not statistically significant in all sensitivity analyses. Also, the overall conclusions would not change when using the results of any of the sensitivity analyses. Nonetheless, it is important to mention that the results of the complete-case analysis (SA1) were much more favorable than those of the main analysis. Amongst others, relatively high probabilities of costeffectiveness were found at ceiling ratios of €0; e.g. a 0.88 probability at a ceiling ratio of €0/ kg body weight loss. However, as a post-hoc analysis indicated that participants with complete data had fewer sickness absence days during follow-up than those with incomplete data (i.e. 6.7 versus 13.3 in the intervention group and 9.5 versus 10.9 in the control group), self-selection of participants seems to have biased these results, and the results of the main analysis were considered more valid. Strengths and limitations An important strength of the present study is its pragmatic RCT design. The pragmatic aspect of the trial enabled us to evaluate the intervention’s resource implications under “real world” circumstances. This facilitates the generalizability of the results (i.e. external validity), whereas the internal validity is guaranteed by the randomization of participants (55;56). Another strength concerns the use of state-of-the-art statistical methods that are not or infrequently used in occupational health research. Amongst others, multiple imputation was used to deal with missing data, SUR analyses were performed to account for the possible correlation between costs and effects/benefits, and bootstrapping was used to estimate the uncertainty surrounding cost differences as well as cost-effectiveness and financial return estimates. Furthermore, both absenteeism and presenteeism costs were included, whereas most previous studies solely included absenteeism costs (45;53). This is of importance because efforts to improve health seem to have a more immediate effect on presenteeism than on absenteeism (57). Several limitations deserve attention as well. First, complete cost and effect data were only obtained from 40.5% and 62.4% of participants, respectively. To deal with this issue, missing values were imputed using multiple imputation. While having complete data is always preferred, multiple imputation is increasingly being acknowledged as a more valid and precise way to deal with missing data than a complete-case analysis (56;58).Complete-case analyses reduce the power of a study and ignore available information of participants who only have missing data on a few measurement points. Also, complete-case analyses only produce reliable estimates when there are no systematic differences between the missing and observed values, which, according to a post-hoc analysis, was probably not the case (40;58). Second, many cost and effect data were gathered using self-report of participants, which may have causes “social desirability bias” and/or “recall bias”. Amongst others, we had to rely on self-reported values of healthcare utilization as health insurance claim data of participants are practically inaccessible in

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Dutch economic evaluations. Also, the period over which participants had to report their resource use was relatively long (i.e. 3 months). This might be a particular concern for presenteeism, as relatively short recall periods seem to be needed for this outcome (59). In future studies, mobile apps might provide a solution for this issue, as they can be used to collect data in a way that is relatively non-burdensome to participants. Third, the presence of MSD was assessed in terms of “self-reported pain or discomfort in one or more body regions”. As discomfort can be regarded as an early manifestation of MSD, participants classified as having MSD may not necessarily have serious functional limitations and/or low levels of health-related welfare. This should be kept in mind while interpreting the results. It is also important to bear in mind that economic evaluation results are not directly transferable between countries or jurisdictions due to differences in healthcare and/or social security systems (60;61). In the Netherlands, for example, healthcare costs are generally borne by the government and/or health insurance companies, whereas in countries with employer-provided healthcare (e.g. The United States) they accrue to the employer. Furthermore, for the employer’s perspective, the HCA was used for estimating absenteeism costs. This was done because Dutch employers are obliged to pay at least 70% of the salary of sick employees for a period of two years, and most of them top up the wage payments from 70% to 100% during the first year of sickness absence (62). Thus, although the initial productivity level of a Dutch company may be restored after the friction period, employers still bear the salary costs of a sick worker. Readers should keep in mind that alternative valuation methods may be more appropriate in other countries or jurisdictions (61). Conclusion The intervention’s cost-effectiveness in improving weight-related outcomes and MSD depends on the societal and employer’s willingness to pay for these effects and the probability of costeffectiveness that they consider acceptable. From the employer’s perspective, the intervention was not cost-effective in improving work-related vitality and job satisfaction. Also, due to a large degree of uncertainty, it cannot be concluded that the intervention is cost saving to the employer Acknowledgements This project is part of a research program called “Vitality In Practice”, which is funded by Fonds Nuts Ohra (Nuts Ohra Foundation). The authors wish to thank Anneke van Paridon for her help with the data collection. The authors would also like to thank all participants and health coaches.

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Appendix 1. Price weights used for valuing resource use and resources consumed by the intervention and control group participants during follow-up (based on the complete-cases) Units [Units of measurement]

Price weight Societal perspective

Employer’s perspective

€ 177.77

€ 287.56

€ 28.96c € 14.48c € 44.47c

N.A. N.A. N.A.

1.3 (1.9) 0.2 (0.5) 0.0 (0.3)

1.6 (2.2) 0.2 (0.8) 0.0 (0.2)

€ 82.47c € 27.93c € 37.23c Variablec,d

N.A. N.A. N.A. N.A.

0.8 (3.3) 0.0 (0.0) 0.7 (2.3) 0.7 (3.7)

0.2 (0.1) 0.0 (0.3) 3.8 (8.0)* 0.5 (1.9)

€ 106.53c € 74.47c Variablec,d

N.A. N.A. N.A.

0.0 (0.0) 0.8 (1.7) 0.2 (1.7)

0.0 (0.0) 0.8 (1.8) 0.4 (1.8)

€ 472.66c € 2257.82c Variablee

N.A. N.A. N.A.

0.2 (0.2) 0.0 (0.0) 30 (58.8)

0.3 (0.8) 0.0 (0.0) 25 (52.1)

Absenteeism costs Sickness absence [days; Mean (SD)]

198.20f

213.10g

6.7 (9.5)

9.4 (21.9)

Presenteeism costs Presenteeism [days; Mean (SD)]

198.20f

213.10g

43.7 (14.5)

46.3 (19.7)

Variableh

N.A.

36 (70.6)

23 (47.9)*

€ 10.00i

€ 10.00i

0.9 (2.5)

0.4 (1.6)

Intervention costs Medical costs Visits to a care provider [No. of visits; mean (SD)] General practitioner Office consultation Telephone consultation House call Allied health professionals Psychologist Dietician Physical therapist Other allied health professionals Medical specialists Psychiatrist Other medical specialists Complementary medicine Hospitalization [No. of days; mean (SD)] Ward Intensive care Medications [No. of participants using medication; Number (%)]

Sports costs [No. of participants with sports costs; Number (%)] Occupational health costs In-company fitness [No. of months; mean (SD)]

Resources consumed Intervention Control group group (n=51) (n=48)

* Significant at p<0.05 Abbreviations: n: Number, SD: Standard Deviation, N.A.: Not ApplicableNote: Costs are expressed in 2011 Euros Price weight sources: a Bottum-up micro-costed, valued using tariffs and depleted sources (See Appendix 2); b Market prices, valued using invoices of contractors; c Dutch Manual of Costing; d Professional organizations; e Dutch Society of Pharmacy; f Average gross annual salary of Dutch construction workers including holiday allowances and premiums; g Average gross annual salary of blue collar workers of the participating construction company including holiday allowances and premiums; h Self-reported expenses on sports memberships and sports equipment; i Height of the employer’s gym membership subsidy

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150 | Chapter 7 40 brochures 61 brochures 48 brochures 13 brochures

65.9 hours 52.3 hours 65.9 hours 52.3 hours 3132 minutes

297.2 hoursa 104.0 hours 114.5 hours 14563.6 kilometres

162 calorie guides 162 pedometer 162 cookbooks 162 packages

Pedometer

Cookbook

Exercise card / Personal energy plan forms

162 quick scans

27 hours

162 packages

Occupational physician

FIXED COSTS

Health coach Construction worker Health coach Construction worker

Health coach Construction worker

Calorie guide

Labor costs Capital costs Material costs

Capital costs Capital costs Phone costs

Labor costs

Capital costs Travelling costs

Labor costs

VARIABLE COSTS

Units

Waist circumference measuring tape / BMI card

VIP in Construction toolbox

Quick scan processing

TOTAL VARIABLE COSTS

Health information brochure PHC-group A PHC-group B PHC-group C No counselling

Telephone contacts

Face-to-face contacts

Personal Health Coaching (PHC)

Cost categories Intervention staff / Worker

€ 0.74/ package

€ 0.80/ cookbook

€ 2.00/ pedometer

€ 0.74/ guide

€ 3.10/ package

€ 168.47/ hour € 3.90/ hour € 0.20/ quick scan

€ 4.68/ brochure € 4.68/ brochure € 3.20/ brochure € 4.80/ brochure

€ 35.72/ hour € 27.53/ hour € 0.44/ hour € 0.44/ hour € 0.09/ min

€ 35.72/ hour € 27.53/ hour € 0.44/ hour € 0.21/ km

Unit Prices

€ 4.25 (0.69)

Subtotal:

€ 0.74

€ 0.74 € 7.38

Subtotal:

€ 0.80

€ 2.00 € 119.63

€ 129.60

€ 324.00

€ 119.63

€ 3.10

€ 28.93

Subtotal: € 502.66

€ 28.08 € 0.65 € 0.20 € 5,548.69 € 105.30 € 32.40

€ 132.21 (76.88)

€ 1.16 (2.02) € 1.76 (2.28) € 0.95 (1.47) € 0.39 (1.31)

€ 14.53 (16.12) € 8.89 (10.22) € 0.18 (0.20) € 0.14 (0.16) € 1.74 (2.00) € 127.96 (76.81)

€ 65.53 (35.93) € 17.67 (11.11) € 0.31 (0.19) € 18.95 (10.15)

Mean costs per worker (SD) (Euros 2011)

€ 187.08 € 285.30 € 153.60 € 62.40

€ 2,353.86 € 1,440.18 € 29.16 € 22.68 € 281.88 Subtotal:

€ 10,615.98 € 2,863.12 € 50.07 € 3,077.52

Total Costs (Euros 2011)

Appendix 2. Cost of the VIP in Construction intervention from the societal perspective, valued using a bottom-up micro-costing approach (Euros 2011)

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162 folders

€ 0.77/ folder € 0.77

Subtotal:

€ 177.77 (76.88)

€ 45.56

€ 8.48

€ 116,107.80 € 8.48c

€ 0.77

€ 123.74 Subtotal:

Abbreviations: SD: Standard Deviation, PHC: Personal Health Coaching, BMI: Body Mass Index a The time investment of the health coaches includes travelling, preparation, and coaching time b €116,107.80 was paid for the development of the VIP in Construction intervention. For calculating the development costs per participant, these were divided by the expected number of program users during the first five years after implementation (13,695). In the Netherlands, 221,250 construction workers are employed by a medium- (10-100 employees) or large-scale (>100 employees) construction company(63;64). During the five year period, it was hypothesized that the intervention will be offered to 20% of these construction workers and that 31% of them will participate to the intervention(48).

TOTAL INTERVENTION COSTS

TOTAL FIXED COSTS

Development interventionb

Recruitment folder

7

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Chapter 8 General discussion


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As described in the general introduction the main goal of this dissertation was to systematically develop a tailored intervention to prevent and reduce overweight and MSD in a specific high-risk occupational group of blue collar construction workers, and to evaluate this programme in a randomised controlled trial: VIP in Construction. In order to gain more insight into the potential of body weight management as strategy for reducing MSD, we also studied the relation between body weight and musculoskeletal symptoms in worker populations. In this final chapter the main findings will be presented, discussed and interpreted in the context of recent literature. Finally, these reflections will be translated into recommendations for future research and practice.

Main findings To explore if interventions reducing body weight are potentially an effective primary and secondary prevention strategy for musculoskeletal symptoms, we investigated the relation between these two health problems in chapter 2. Based on analyses in a large working population sample we found BMI to be associated with musculoskeletal symptoms, in particular symptoms of the lower extremities. Additionally, compared to employees with normal weight, obese employees were at increased risk for developing symptoms as well as having impaired recovery from symptoms. Contradictory to our hypothesis, the association was stronger for employees with low physical workload compared to those with high physical workload. In chapter 3 the systematic development of the intervention programme as well as the design of the RCT was described. The Intervention Mapping protocol was applied to systematically develop the VIP in Construction programme, targeted at blue collar workers of a large construction company. This resulted in specific programme objectives aimed at quantity and quality of energy intake and output. After selecting relevant determinants and theoretical methods of behaviour change, practical strategies were formulated. The intervention programme consisted of individual face-to-face and telephone counselling, both employing information and materials aimed to improve lifestyle behaviour. The programme was tailored to each participantâ&#x20AC;&#x2122;s motivational readiness for change, varying in focus, number, and duration of counselling sessions. The intervention was linked to the companyâ&#x20AC;&#x2122;s periodic health screening and took place at the worksite and during working hours. Management and workers were involved in the development of the programme. Therefore, the programme matched the needs and preferences of the target group, which facilitated implementation. In chapter 4 the process evaluation of the intervention was reported. The process evaluation was conducted following the RE-AIM framework for the evaluation of the public health impact of health promotion interventions. The external validity of the trial was satisfactory with representative

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reach of workers and adoption of workplace units in the participating construction company. Intervention participants showed significantly more progression through the different stages of behaviour change than did controls. The extent to which the programme was implemented as intended was concluded to be modest. The satisfaction of participants and dose delivered was, however, high; 84% of the participants received at least one counselling session. However, adjustments to the programme should be made to improve exposure and fidelity (the extent to which the steps of the coaching programme were delivered as intended) to the protocol. Overall, based on the RE-AIM dimensions, it was concluded that the programme is feasible and based on improvements on determinants of behaviour change potentially effective in blue collar construction workers. Effectiveness of the programme on body weight, BMI, waist circumference, physical activity (PA), dietary intake, blood pressure, and blood cholesterol was assessed in chapter 5. Linear and logistic regression analyses were applied at 6- and 12-month follow-up. Initially, at 6-month follow-up, intervention participants showed positive changes in vigorous physical activity and dietary behaviour (decrease in intake of sugar-sweetened beverages) compared to controls, as well as positive changes in weight-related outcomes (body weight, BMI and waist circumference). Long-term effects on weight-related outcomes were still promising, but no longer statistically significant. Chapter 6 described the evaluation on secondary outcomes. Neither at 6-month follow-up nor at 12-month follow-up statistically significant intervention effects were found on musculoskeletal symptoms, physical functioning, work-related vitality, work performance, work ability, or sickness absence. Finally, a cost-effectiveness evaluation from both the societal and employers perspective was conducted alongside the RCT with a follow-up of 12 months, as described in chapter 7. Based on the economic evaluation, the programme appeared not cost-effective from the employers perspective in improving work-related vitality and job satisfaction. It was concluded that the cost-effectiveness of the programme, of which the costs were â&#x201A;Ź287 per worker, depends on the â&#x20AC;&#x153;willingness to payâ&#x20AC;? of decision makers for their effects. Financial return estimates were positive for the employer, but these estimates showed a high level of uncertainty. In conclusion, overall this tailored intervention showed no beneficial cost-effectiveness or statistically significant financial return after the first year of implementation. Therefore, based on the result of this thesis, we cannot recommend implementation of the programme in the current form.

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Methodological considerations The RCT evaluating VIP in Construction was designed to meet most of the CONSORT statement requirements, which is a standard for the reporting of trials [1]. RCTs are regarded as the gold standard for evaluating effectiveness of interventions and are considered the most scientifically rigorous method [2]. The main purpose of randomization is to avoid selection bias and distribute known and unknown attributes that influence outcomes (i.e. confounding factors) randomly between the groups that receive the interventions and the comparison groups. Still, bias may occur even within the strict design of an RCT, for example as a result of non-response or drop-out. Therefore, several important methodological aspects have to be discussed. Validity and generalizability of the results External validity of a study refers to the extent to which the results of a study can be generalised to other settings, situations and populations [3]. The study as described in this thesis focused on a specific occupational group; blue collar workers in the construction industry. As we did not have many strict exclusion criteria for workers to participate in this programme, and it was carried out under â&#x20AC;&#x153;real lifeâ&#x20AC;? circumstances, it is expected that the results are transferable outside the research trial setting. Various subgroups of blue collar workers were included, such as carpenters, masons, crane drivers, workers in road construction and factory workers, which favours representativeness for a broader group of workers involved in moderate to heavy physically demanding occupations. Another element of external validity is the participation rate or reach, as described in chapter 4. The research population was recruited over a 15-month period and consisted of workers who attended a non-compulsory periodic health screening and were not on long-term sick leave at baseline. It was estimated that 31% of the eligible workers were included in the study. Differences between efficacy and effectiveness of a programme may result from selective recruitment. Participation in the trial was on voluntary basis, but there were no indications that participants differed in health indicators compared to other workers attending screenings. Unfortunately, we were not able to compare study participantsâ&#x20AC;&#x2122; health characteristics to workers who did not participate in screenings. Baseline data of the study participants was also compared to company data. No indication for selection bias based on health-related variables was found; percentages overweight and obesity in the study group were similar to the company average. We did find that older workers were slightly overrepresented in the study, which could be a result of older workers being invited to participate in PHS more frequently than younger workers (every two years, compared to every four years). We tried to identify reasons for declining the invitation for participation among non-responders, but we did not succeed in getting answers from this group. Increasing participation by more intensive recruitment strategies is not always preferable considering that these strategies will probably also negatively affect compliance, by including less motivated workers. Moreover, the company was already making an effort to maximise General discussion | 157

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participation in the periodic health screenings, for example by performing the screenings at the worksite. When missing data are extensive this could also threaten the validity and generalizability of the conclusions of an RCT. It has been proposed that, in general, more than 20% loss to follow-up could be a threat to internal validity [4,5]. Dropout rate in obesity RCTs at 1 year after the start are estimated to be as high as 37% [6]. After 1 year in the VIP in Construction study complete data was obtained from 83% (17% dropout), which seems acceptable. Furthermore, dropout did not seem to differ on health indicators compared to completers. As described in chapter 5, long-term results of the trial showed decreased contrast between intervention and control participants in weight-related and lifestyle behaviour outcomes. This was the result of a combination of a relapse in the intervention group, as well as improvements in the control group. Contamination might be one of the factors that contributed to improvement in the control group. Workers in the intervention and control group were not isolated in the trial setting, and crossover effects in lifestyle behaviour from the intervention participants to the control participants could have occurred. Contamination of the control group was expected to be minimal, since personal counselling and the toolbox were only available for the intervention participants. Randomisation at the individual level, as performed in this RCT, could be regarded as a weakness of the study design, since contamination could not be fully excluded. Within companies cluster randomization, for example at department level, might therefore be preferred. However, workers in the construction sector work at mobile and temporary worksites, which complicates the cluster design. An additional explanation for the observed improvements in the control group is a possible effect of the measurements as performed in this study. Feedback on measurements concerning health status or behaviour at baseline and follow-up of an intervention study can result in improvement of readiness for behaviour change [7]. Measurement issues Measuring energy intake and energy expenditure Most of the study outcomes, such as weight-related measures, were measured objectively, and sickness absence data was collected from company records, which is regarded more reliable than self-report [8]. For several other outcome measures, we did rely on self-report. Health behaviour (physical activity and dietary behaviour) was measured by self-report and as a result potentially differential misclassification in reporting of health behaviours in the follow-up measurements between intervention and control participants should be considered. Although possible resulting bias does not affect RCT results, because it is expected that it is the same for intervention and control participants, it is conceivable that due to the intervention, intervention participants are more aware of recommended standards for physical activity and diet and as a result report differently at follow-up. 158 | Chapter 8


BMI as a measure for fatness In chapter 2 BMI was used as identifier for excess fatness. BMI is a widely accepted, recommended, and easy to use measure for assessing excess body weight in populations. There has been some discussion, however, on the misclassification by BMI since it does not discriminate between lean body mass or fat mass. In a group of workers that are on average more physically active at work, with an expected higher percentage of muscle mass, this might result in overestimation of the number of workers in high-risk categories. However, it could also be considered a conservative measure when assessing health risks. In adults the use of BMI as a measure of adiposity (excessive body fatness) was concluded to result in a serious underestimation of obesity prevalence [9]. Health-related excess of body fat is not always accompanied by BMI values above the standard cut-off values for healthy body weight. Also in the relation with MSD, it is relevant to distinguish between fat and fat-free mass; for example in knee osteoarthrosis, the relation between fat-free mass and MSD has been found to be beneficial, while fat mass has been negatively related to MSD [10]. As an additional measure in the trial waist circumference was included as a measure of excess body weight. Waist circumference is a measure of central overweight and obesity directly related to health risk, and changes in waist circumference have found to better reflect changes in energy-balance-related behaviour than do changes in BMI [11]. It should be mentioned that that this measure is prone to large measurement error [12]. Therefore, waist circumference is an important additional measure, provided that the measurements are preceded by protocol and training, repeated measures are used. By using average values of multiple measures, random measurement error, which can be positive or negative about the true value, can be decreased.

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Programme design Understanding determinants of behaviour is a key component of developing effective behavioural interventions [13,14]. Changes in the targeted determinants should result in changes in the behaviour. If a programme has small or no effects, the intervention strategies for changing these mediating variables may not be optimal or the proposed theoretical model should be revised to include important mediating variables. Theoretical framework In the VIP in Construction programme several theoretical models were integrated (chapter 3) to match a specific population and its specific context. In this study the stages of change construct from the transtheoretical model (TTM) that maps the process of behaviour change [15] has been used to tailor the intervention. This was done by matching intervention strategy and intensity to individualsâ&#x20AC;&#x2122; motivational readiness to change (chapter 3) as well as to compare workers longitudinal shift in readiness to change pre- and post-intervention (chapter 4). Several reviews have questioned the effectiveness of health promotion and physical activity programmes based on TTM [16-19]. At present, evidence is not very strong that stage-based interventions

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significantly increase effectiveness. Stage-based interventions have been found to be reasonably effective in adoption of behaviour, but not on long term adherence [18]. Another critique is that the TTM focusses on personal motivation and not on external and social factors, such as age or socioeconomic position [19]. Therefore, the impact of TTM and the stages of change construct as a theoretical basis in weight management may depend on how it is used as a framework for intervention and in combination with other strategies aiming at diet and physical activities [20]. As a tool, TTM provides a useful basis for designing interventions. The model has the potential to increase effectiveness of counselling. Yet, in effectiveness studies the results of changes in stages of change should be interpreted with caution. The constructs of the model are not the same for all types of behaviour, and for complex health behaviours, such as lifestyle behaviour, validity of the constructs is not clear and should be tested in specific populations [21]. In chapter 4 we reported effects on psychosocial constructs related to behaviour. The observation that motivational stage of change improved, does not necessarily demonstrate these constructs to mediate physical activity and dietary behaviour. It would be of interest to further test this using mediation analysis. Intervention strategies and components aimed at MSD Despite the high level of involvement of workers and the employer in the development of the programme, not all factors that are considered important risks for MSD could be included in the final programme (chapter 3). Known risk factors for MSD related to the workplace and workload should also be considered. Although in the past decades primary prevention on physical work demands has improved and biomechanical load for construction work has decreased, results from long-term follow-up studies do not show a significant preventive effect for MSD [22]. Ergonomic measures can be used to reduce the burden of physically demanding work tasks [23]. Linking the programme to periodical health screening Motivating workers to participate in health promotion programmes is a challenge. Among individuals with weight-related health risks, many are not considering to lose weight [24]. Blue collar workers are less likely to participate in health promotion programmes [25]. Accurate perception of body weight and awareness of associated health risks are motivators for individuals to make changes in lifestyle behaviour [24,26]. From interviews with the target population (chapter 3) we learned that overweight was perceived less as a health problem than for example other risk for cardiovascular disease, such as high blood pressure. Recruiting through periodical health screening is therefore considered a strength of the study, because it enabled linking the lifestyle programme to several health outcomes. Further explanation of health risks might also increase effectiveness of these screenings in construction workers [27].

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Comparison of the findings with those of other studies Considering the lack of sustained effects of the VIP in Construction intervention, it is of interest to compare the study findings to the results of other studies. Lifestyle weight loss interventions in the workplace In general, it appears that worksite health promotion interventions targeting overweight populations have positive effects on measures of dietary behaviour [28] and physical activity [29] but effect sizes are small. Systematic reviews on workplace interventions aiming at reducing body weight conclude that modest positive effects can be expected [30]. Many of these studies, however, targeted workers in white-collar occupations. Intervention studies in blue collar occupations with a high-risk approach, including only overweight workers (BMI > 25) or workers with an elevated risk on CVD, with higher baseline BMI did show modest reductions in body weight and BMI after 12 months [31,32]. Weight gain prevention Worksites increasingly have a key role in public health strategies in preventing illness as well as promoting health. Therefore, there has been a shift in focus towards primary prevention in body weight management. Relatively few trials are found on the prevention of weight gain [33-35]. Five studies reported a significant difference in body weight between intervention and control group (1.0-3.5 kg) largely due to an increase in body weight in the control groups [34]. A meta-analyses of workplace interventions of Verweij et al. (2011) found interventions to be moderately effective in reducing body weight with 1.2 kg, with subgroup analysis showing a greater reduction for interventions containing an environmental component [36]. Compared to the evidence on strategies for initiation of body weight loss, the evidence base of maintenance strategies is very small. A possible explanation for the lack of sustained effects has been proposed by Katan & Ludwig (2010). They argue that single changes in diet or physical activity will elicit compensatory mechanisms in the body that limit long-term effects on body weight. When reaching a lower body weight, energy expenditure of maintaining and moving the body decreases. This implies that after initial changes in body weight, even more effort has to be made to maintain the lower body weight. This would require longer follow-up in intervention programmes, either by increasing the number of contacts or other means to stimulate continuation of adjusting energybalance-related behaviour. Compared to studies that show larger effects, the intervention studied in the present thesis was rather low-intensive. Lifestyle and weight loss interventions have demonstrated larger effects when comprising numerous contacts of long duration [37]. One study found an average of General discussion | 161

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participants 43.6% in low intensity interventions lost no weight or gained weight [38]. In studies with weight loss as a primary outcome, more intensive approaches have typically been more effective than those with less contact [33,39]. However, for weight gain prevention there is no similar evidence for larger effects with more intensive interventions [34]. Moreover, such intensive approaches have a number of limitations. The costs are higher and they are likely to appeal to only a small percentage of those who would benefit because of the level of commitment required. Low-intensity, tailored interventions that can be incorporated in or linked to ongoing routine health screenings will probably increase the likelihood of compliance. To increase the probability of sustaining the initial effects, interventions should consist of longer follow-up periods. Followup contacts with the coaches could be telephone contact, text messages or by e-mail. It should be kept in mind that personal contact with the coaches was the most appreciated component of the intervention. This is supported by weight gain prevention literature providing evidence that interventions with some personal contact in delivery of the intervention were more successful [34]. Lifestyle interventions and MSD Workplace health promotion programmes that improve physical activity levels have been shown to reduce the risk on MSD [40,41]. In the present study increased vigorous physical activity in the intervention group was not accompanied by a significant decrease in MSD. We did not assess if changes in physical capacity occurred resulting from an increase in physical activity. A study that was effective in increasing the amount of physical activity in construction workers, but not effective in decreasing musculoskeletal pain, showed an increase in aerobe capacity, but no increase in muscle strength [42,43]. Therefore, this might not have been the appropriate type of physical activity to increase functional capacity and the potential to reduce or prevent MSD. International health guidelines recommend adults to perform at least 30 minutes of moderate physical activity 5 days per week [44]. While these guidelines are based on prevention of metabolic syndrome related disorders, the optimal duration and frequency of physical exercise for proper musculoskeletal function, especially in physically straining jobs, remains to be established. In office workers there is moderate to strong evidence for effectiveness of muscle strength training [45], and a recent study that was effective on pain relief in industrial workers shows that programmes should include high-intensity progressive strength training[46].

Reflections Relevance of fatness as health indicator, fitness versus fatness In apparently healthy individuals, physical health-related quality of life decreases with increasing level of BMI [47]. Both overweight and physical activity levels (inactivity) have adverse effects

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on health. However, contradictory findings from studies have led to debate about the relative importance of fitness and body fatness on disease risks [48]. When considering all-cause mortality risk, a recent study advocates focusing on physical activity and fitness-based interventions rather than weight loss driven approaches [49]. There is also debate on the role of exercise and cardiorespiratory fitness as potential modifiers in the relation between BMI and cardiovascular disease [50]. A number of studies indeed suggest that physical activity counteracts some of the health risk of overweight. Physical activity has beneficial effects on inflammatory processes and insulin and blood sugar levels, resulting from excess weight, especially central obesity. However, other studies found that abdominal obesity is a predictor of cardiovascular disease independent of fitness level [51,52] or that BMI showed the highest risk [53]. It can be concluded that there is conflicting evidence, and although in mildly overweight individuals physical activity will offset some of the effects of extra weight, increasing physical activity or exercising will not completely erase all health risk of being overweight [53]. Furthermore, the higher physical activity levels at work of blue collar workers are not associated with higher cardiorespiratory fitness and health [54,55]. Moreover, in addition to overweight and obesity related health problems, such as cardiovascular disease or metabolic syndrome, musculoskeletal problems associated with high BMI should be considered [56]. Weight loss has been found to reduce musculoskeletal pain, which could encourage compliance with health promotion programmes [57]. Therefore, the focus should be on healthy weight and physical activity should be an essential part of weight loss or weight gain prevention programmes. High-risk versus population based approach Interventions to combat the obesity epidemic have mainly targeted at weight loss treatment in obese adults, with limited long-term effects [33]. With the increasing number of people at risk or being overweight, there has been a shift in focus towards prevention of obesity. Considering the small short-term intervention effects on body weight-related outcomes in the group of participants in this study, which consisted of a group of workers that were not specifically selected on overweight, the question rises if we should specifically aim at a high-risk group, where individual effects could be expected to be more substantial. In the present study, baseline scores on BMI did not appear to be modifiers for the intervention; the intervention was effective (short-term) on body weight-related measures, independent of participants being overweight, obese or healthy weight (unpublished data). Based on these results, BMI should not be a basis for assignment or exclusion for workers to the workplace intervention. In general, for long-term health gains it is preferable to remove the underlying risk, which is the aim of primary prevention, and supports the population approach. Also the potential negative impact by increasing weightbased stigma of programmes that specifically target individuals based on their weight status should be considered [58]. Although primary prevention is preferred, resources for prevention are limited, which stresses the need to select priority groups [59]. Through workplaces there is the

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ability to reach specific occupational groups that consist of populations that are homogeneous in working conditions, educational level, social class, and health. Based on their socioeconomic status, blue collar construction workers can be considered a high-risk group regarding health status, and health behaviour. Within the population approach it is possible to differentiate within a programme to reduce the costs. In the VIP in Construction programme this was applied on the level of the individual worker with differences in focus and intensity of the intervention. In a modified programme, this could be applied in a more environmental focused intervention including components and strategies that are suitable for a worker population consisting of a group with varying motivational stages and risk levels. Multicomponent comprehensive programmes and the Total Worker Health concept The Total Worker Health concept as conceived by the National Institute for Occupational Safety and Health (NIOSH) advocates integrating health protection and health promotion programmes [60]. To decrease risk factors in the work environment, health protection programmes traditionally focused on safety, whereas workplace health promotion programmes focus on lifestyle factors off-the-job. The integrated approach potentially increases participation [61] and contributes to larger improvements in behaviour change [62,63]. In this paragraph I will illustrate this with examples on energy balance and MSD. Dimensions beyond the energy balance When summarizing the conclusions of reviews on worksite health promotion programmes, although overall moderate positive results are found for interventions aiming at individual determinants, effects are small and not easy to maintain, and more impact is expected from comprehensive programmes when environmental and cultural changes in the workplace are also included [64]. Integrating worksite health promotion to occupational safety and health might also be relevant in targeting lifestyle behaviour, as unhealthy dietary habits and other health behaviour, such as smoking, in blue collar workers have been found to correlate with increased exposure to work-related risks[65]. Programmes should be tailored to meet the specific employee health concerns, and work settings. Environmental strategies that are currently found in lifestyle interventions are usually modifications in the physical environment, such as modifications in workplace canteens and offering physical activity programmes at work. These strategies are not suitable or easy to implement for all occupational groups, particularly in construction workers who often work at mobile and temporary workplaces. This diversity and geographical dispersion of physical work settings shows the need to focus on factors in the social context of the workplace, such as management support and social norms. Changes in socio-cultural aspects of the worksite therefore deserve more consideration in future interventions involving worker populations with comparable characteristics. 164 | Chapter 8


Addressing the complexity and multicausality of MSD As argued in the paragraph on programme design, workers health and safety problems are recognised to result from both work-related factors and health factors beyond the workplace. For the prevention of MSDs there is moderate evidence that interventions based on single measures are ineffective. The multiple factors involved in the development of MSD, such as work related factors (e.g. lifting, awkward postures), individual factors (e.g. age, body weight, physical capacity), and also psychosocial risk factors (e.g. social support and job satisfaction) [66-68]. In addition to the broad range of risk factors there are other arguments that support multi-component programmes. Based on focus group interviews with the target population it can be concluded that risks outside personal control are given highest priority. Therefore, workers may feel that the importance and benefits of individual health behaviour changes are less than those of work-related factors. To illustrate, blue collar workers were more likely to participate in smoking cessation and nutrition programmes if they reported changes of their employer to reduce work-related risk factors [69]. Thus, more effect can be expected when workers perceive that the employer is not only initiating a health promotion programme but simultaneously making changes in the work environment and organisational culture in an effort to promote health. In blue collar occupations with increased work-related risk of adverse health effects, integrating worksite health promotion to other efforts for occupational health and safety may increase programme participation. The previous paragraphs reinforce the rationale for the potential larger effects that could be gained from a multidisciplinary approach, combining several intervention components, including individual measures combined with organisational â&#x20AC;&#x153;redesignâ&#x20AC;? to reduce workload. A systematic review on occupational safety and health interventions to reduce musculoskeletal symptoms in the health care sector concluded that there is moderate level of evidence for exercise and multi-component interventions [70]. However, recent multi-component intervention studies on musculoskeletal symptoms focusing on workers in physically demanding jobs, such as construction workers or cleaners, did not show effects on symptoms [43,71,72]. Further research for effective strategies is therefore warranted. Towards Total Workforce Health The VIP in Construction programme provided a strategy to reach workers who are at high risk but may be unable to participate in traditional worksite health promotion. Linking the programme to periodical health screening, tailoring the programme to make it personally relevant and planning the counselling sessions at work and during working hours were elements of the programme to match the context and individual worker need and preferences. In the VIP in Construction programme external determinants for physical activity behaviour and dietary behaviour were included in the conceptual model. However, the main focus in the current programme was on personal determinants of lifestyle behaviour change. In an adapted and improved version of the

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VIP in Construction programme, the physical and social work environment should be considered to improve reach and increase effectiveness. Based on the current thesis and the growing body of evidence in this direction, I suggest integrating occupational health and safety and worksite health promotion. Intervention developers should use the stages of change model to design and include components for all motivational and health risk levels in programmes aiming at the total workforce. Implementation of worksite health promotion into practice Managing human capital and human resource management will become one of company’s most important business issues. Especially in a tight job market improving worker productivity by decreasing sickness absenteeism and presenteism might be the most important incentive to invest in health promotion. In the work setting, starting new projects or implementing health promotion programmes is a business decision. It is challenging for employers to weigh effectiveness against economic viability of worksite health promotion programmes. If consequences of improved employee health cannot be quantified to support business decisions, employers may not be willing to invest in health interventions. In my view, this would be a missed opportunity, as health promotion and employee health can be considered an investment in ‘human capital’, with more intangible factors, such as corporate image and job satisfaction, which probably have a less detectable financial profit, and require long-term investment. Therefore, additional research is required to investigate if and how improvements in workforce health translate into improvements in work-related measures relevant to employers, in order to establish a better link between health promoting programmes and business objectives. While research indicates that worksite health promotion programmes are effective in reducing absenteeism and presenteism rates [73-75], evidence on their impact on other endpoints remains limited. Recent work has been conducted to better conceptualise and measure individual work performance [76], and more needs to be done to further understand the relationship between these measures and individual or total workforce health.

Implications and recommendations for practice Following the results as described in the separate chapters of this thesis, and the reflections in the current chapter, I would like to provide practical recommendations for programmes in the occupational setting. •

It is not recommended to implement the VIP in Construction programme in its current form. In order for worksite health promotion programmes to have a meaningful impact, the programme’s effectiveness should be long lasting. However, transition in motivation

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to change behaviour and initial short-term change in behaviour and health outcomes as found in this trial is an important, although not sufficient, condition for long-term change to occur. To increase the probability of sustaining the initial effects, interventions should consist of longer follow-up contact periods. •

Increasing participation and effectiveness of worksite health promotion programmes would require the design of these programmes to include the social and physical work environment in addition to the individual level, and integrate health promotion with occupational health and safety efforts. This applies to outcomes that are related to health and health behaviour, as well as work-related outcomes, such as work ability and sickness absence.

To reach a worker population that is not highly motivated and difficult to reach in health promotion practices, linking interventions to periodical health screening is a promising strategy. It has the potential to increase participation, and could be a useful starting point for further integration of worksite health promotion and occupational health and safety programmes.

It is recommended to combine the population and high-risk approach. Employers should aim at health promotion initiatives for all their employees, provided that elements for workers at different health risk and motivational levels are included.

Future scientific perspectives and recommendations

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Some implications for research arise from the results of the current thesis: •

This thesis started with the question of whether managing overweight could also be a potential effective strategy for the prevention or reduction of MSD. Overweight as a modifying factor in the relation between strenuous work and musculoskeletal symptoms has been rarely addressed in previous studies. To better understand the possible benefits of lifestyle interventions on the musculoskeletal system, well designed studies that assess the effects of significant body weight reduction and specific types of physical activity and exercise on MSD are needed.

In physical activity and exercise interventions aiming at improving MSD, physical capacity measures should be included. This would provide more evidence for the type or intensity of physical activity or specific exercises for preventing or improving musculoskeletal symptoms.

The process evaluation gave insight in the applicability of the programme components, as well as effectiveness on potential mediating factors. However, since this does not necessarily demonstrate these constructs to mediate lifestyle behaviour change, it would be of interest to further test this using mediation analysis. General discussion | 167

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â&#x20AC;˘

Given the general frequency of body weight rebound after short-term weight loss, additional research is needed regarding the most effective means of maintaining initial success. More research is needed to determine if successful body weight maintenance or sustained body weight loss share the same behavioural determinants or metabolic factors that play a role in initial body weight loss.

â&#x20AC;˘

In designing future programmes, environmental and cultural changes should be considered. This would require the use of ecological frameworks for interventions that include the complexity of the (work) environment and levels of intervention. Thus, future research on worksite health promotion should also include looking into the (cost-)effectiveness for programmes with combined individual and environmental components.

Conclusion Despite a systematic design and theory-based approach resulting in a tailored programme with promising short-term results on intermediate and primary outcomes, overall the VIP in Construction study did not prove to be (cost-)effective after 12 months follow-up. The results of this study indicate that a relatively low-intensity worksite intervention has the potential to improve dietary and physical activity behaviour, and to contribute to the prevention of body weight gain in blue collar construction workers. Although these outcomes initially improved, the programme was not successful in improving other health-related, work-related, or long-term outcomes. Organisations attempting to improve worker health and work-related outcomes, should therefore provide a more multifaceted intervention including (psycho-social) work organisational and environmental aspects and focus additionally on effective maintenance strategies.

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Summary In the construction industry, the workforce is ageing and despite technological innovations workers are still facing high physical work demands. Especially in combination with unfavourable health and lifestyle indicators this provides challenges for maintaining a sustainable and productive workforce, which emphasises the need for interventions in the construction industry. Chapter 1 provides an introduction to the background and objectives of this thesis. The main goal of this thesis was to systematically develop a tailored intervention to prevent and reduce overweight and musculoskeletal disorders in blue collar construction workers. This intervention programme (VIP in Construction) was evaluated in a randomised controlled trial. In order to gain more insight into the potential of body weight management as a strategy for reducing musculoskeletal disorders, the relation between body weight and musculoskeletal symptoms was studied (chapter 2). Based on analyses in a large working population sample, body mass index (BMI) was found to be positively associated with musculoskeletal symptoms, in particular symptoms of the lower extremity. Additionally, compared to employees with normal weight, obese employees were at increased risk for developing musculoskeletal symptoms and suffered impaired recovery. Surprisingly, the association was stronger for employees with a low physical workload compared to those with a high physical workload. The systematic development of the VIP in Construction intervention, as well as the design of the randomised controlled trial, is thoroughly described in chapter 3. The Intervention Mapping protocol was applied to systematically develop the intervention. By doing so, the intervention matched the needs and preferences of the target population and was based on the current evidence for the effectiveness of lifestyle interventions. The intervention programme consisted of individual face-to-face and telephone counselling, both employing information and materials aimed to improve lifestyle behaviour. The intervention was tailored to each participantâ&#x20AC;&#x2122;s motivational readiness for change, varying in focus, number, and duration of counselling sessions. To further increase compliance, the intervention was linked to the companyâ&#x20AC;&#x2122;s periodic medical examinations and took place at the worksite and during working hours. A process evaluation was conducted to better explain the studyâ&#x20AC;&#x2122;s findings, and to give insight in the implementation of the intervention. The process evaluation of the intervention (chapter 4) was conducted following the RE-AIM framework for the evaluation of the public health impact of health promotion interventions. Both qualitative and quantitative methods were applied to evaluate process measures. The external validity of the trial was satisfactory, based on representative reach of workers and adoption of workplace units in the participating construction company. Intervention participants showed significantly more progression through the different stages of

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behaviour change than did controls. The extent to which the intervention was implemented was, however, modest. The satisfaction of participants was, in contrast, high and 84% of the participants received at least one counselling session. Still, adjustments to the intervention should be made to improve exposure and fidelity to the protocol. Based on the RE-AIM dimensions, it was concluded that the intervention is feasible and based on improvements on determinants of behaviour change potentially effective in blue-collar construction workers. Chapter 5 and 6 present the effect evaluation of the worksite health promotion intervention. A total of 314 participants were randomised to the intervention (n=162) or control group (n=152). Data were collected at baseline, at 6 months directly following the intervention, and at 12 months. After 12 months the loss to follow-up was 17%. The effectiveness of the intervention compared to usual care was assessed using regression analyses with the outcome measures at 6 months and 12 months follow-up as the dependent variables and adjusting for the baseline levels of the outcome measure. Effectiveness of the intervention on body weight, BMI, waist circumference, physical activity, dietary intake, blood pressure, and blood cholesterol is presented in chapter 5. Initially, at 6-month follow-up, intervention participants significantly showed positive changes in physical activity and dietary behaviours (decrease in intake of sugar-sweetened beverages) compared to controls, as well as positive effects in body weight and related outcomes (body weight, BMI and waist circumference). Long-term effects on body weight and related outcomes were still promising, but no longer statistically significant. Chapter 6 describes the evaluation on musculoskeletal symptoms, physical functioning, work-related vitality, work performance, work ability, and sickness absence. Neither at 6-month follow-up nor at 12-month follow-up statistically significant intervention effects on these outcomes were found. Chapter 7 describes a cost-effectiveness and financial return evaluation of the intervention compared to usual care. The evaluation was conducted alongside the RCT with a follow-up of 12 months and included both the societal and the employer’s perspective. The intervention was found to be not cost-effective from the employer’s perspective, in improving work-related vitality and job satisfaction. It was concluded that the cost-effectiveness of the intervention, of which the costs were €287 per worker, depends on the “willingness to pay” of decision makers for their effects. Financial return estimates were positive for the employer, but these estimates showed a high level of statistical uncertainty. In the final chapter (chapter 8) the main findings are discussed and interpreted, and recommendations for future research and practice are given. It was concluded that despite a systematic design and theory-based approach resulting in promising short-term results on intermediate and primary outcomes, overall the VIP in Construction intervention showed no additional beneficial (cost-)effectiveness or statistically significant financial return after the

176 | Summary


first year of implementation. Therefore, the implementation of the intervention in its current form cannot be recommended. Based on the findings of this thesis, organisations attempting to improve worker health and work-related outcomes should provide a more multifaceted intervention including (psycho-social) work organisational and environmental aspects and should additionally focus on effective maintenance strategies.

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Samenvatting De bouwsector heeft te maken met vergrijzing van werknemers en met zware fysieke werkbelasting. In combinatie met ongunstige gezondheids- en leefstijlindicatoren leidt dit tot uitdagingen om werknemers in deze sector duurzaam inzetbaar en productief te houden. Hoofdstuk 1 is een introductie op de achtergronden en doelstellingen van dit proefschrift. Het primaire doel van de studie, zoals beschreven in dit proefschrift, was om op systematische wijze een programma op maat te ontwikkelen ter preventie en reductie van zowel overgewicht als bewegingsapparaat-klachten bij werknemers in de bouw. Het ontwikkelde programma (VIP in de bouw) is vervolgens geĂŤvalueerd in een gerandomiseerde en gecontroleerde trial (RCT). Om het potentieel van beĂŻnvloeding van lichaamsgewicht als strategie voor het verminderen van bewegingsapparaat-klachten beter te begrijpen, is in hoofdstuk 2 de relatie tussen lichaamsgewicht en bewegingsapparaat-klachten bestudeerd. In een grote steekproef van de beroepsbevolking vonden we een positieve associatie tussen body mass index (BMI) en bewegingsapparaat-klachten, in het bijzonder die van de onderste extremiteit (zoals knieklachten). Daarnaast hadden werknemers met ernstig overgewicht (obesitas) meer risico op het ontwikkelen van bewegingsapparaat-klachten en een kleinere kans op herstel ervan, vergeleken met werknemers met gezond gewicht. We vonden het verassend dat deze associatie sterker was voor werknemers met lage fysieke werkbelasting dan met hoge fysieke werkbelasting. De systematische ontwikkeling van de VIP in de Bouw interventie en het design van de RCT is beschreven in hoofdstuk 3. De interventie is ontwikkeld met behulp van het Intervention Mapping protocol. Door het toepassen van dit protocol sluit de interventie zoveel mogelijk aan bij de behoeften en voorkeuren van de doelgroep ĂŠn bij beschikbare wetenschappelijke kennis. De interventie bestond uit individuele face-to-face en telefonische counseling met een leefstijlcoach, waarbij informatie en materialen werden aangeboden gericht op het verbeteren van voeding en lichamelijke activiteit. De interventie was toegespitst op de motivatie van de individuele deelnemer om aanpassingen te doen in zijn leefstijlgedrag, en varieerde daarmee in focus, aantal en duur van de sessies met de leefstijlcoach. Om de deelname te vergroten werd de interventie gekoppeld aan de bij het bouwbedrijf gebruikelijke periodiek medische keuringen en vond de interventie gedurende werktijd plaats op de werkplek. Om de resultaten van de studie beter te kunnen verklaren en ook om inzicht te geven in de implementatie van de interventie, is er een procesevaluatie uitgevoerd. Deze evaluatie van het proces van het programma (hoofdstuk 4) is uitgevoerd en beschreven volgens het RE-AIM framework voor de evaluatie van de impact van gezondheidsbevorderende interventies. Om het proces te evalueren is zowel van kwalitatieve als van kwantitatieve onderzoeksmethoden gebruik

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gemaakt. We concludeerden dat de studiepopulatie een representatieve afspiegeling was van de verschillende afdelingen van het deelnemende bouwbedrijf. Deelnemers aan de interventie lieten significant meer progressie zien door de verschillende fasen van gedragsverandering dan de controlegroep. Maar de interventie bleek niet geheel te zijn geïmplementeerd zoals beoogd. De tevredenheid van de deelnemers was echter hoog en 84% van de deelnemers ontving ten minste één coaching sessie. Desalniettemin zouden er aanpassingen aan de interventie moeten worden gedaan om blootstelling aan de interventie en het volgen van het protocol te verbeteren. Gebaseerd op de dimensies van RE-AIM concludeerden we dat de interventie haalbaar is in de uitvoering en implementatie. Daarnaast werden er verbeteringen in determinanten van gedragsverandering gevonden. Hoofdstukken 5 en 6 beschrijven de effect-evaluatie van de interventie. In totaal werden 314 werknemers gerandomiseerd; 162 werden toegewezen aan de interventiegroep en 152 aan de controlegroep. Gegevens werden verzameld voor aanvang van de interventie, direct na de interventieperiode (na 6 maanden), en na 12 maanden. Na 12 maanden was 17% van de deelnemers uitgevallen. Met regressie-analyses onderzochten we de effectiviteit van de interventie, waarbij gecorrigeerd werd voor de uitgangswaarden van de uitkomstmaten. Effectiviteit van de interventie op lichaamsgewicht, BMI, middelomtrek, lichamelijke activiteit, voeding, bloeddruk en cholesterol is beschreven in hoofdstuk 5. Op korte termijn (na 6 maanden), werden positieve effecten gevonden voor werknemers in de interventiegroep op beweeg- en voedingsgedrag (inname van gezoete dranken/frisdrank) vergeleken met hun collega’s in de controlegroep. Ook werden positieve effecten op lichaamsgewicht en daaraan gerelateerde uitkomstmaten gevonden (BMI en middelomtrek). Op lange termijn waren effecten op lichaamsgewicht en daaraan gerelateerde uitkomsten nog steeds veelbelovend, maar niet langer statistisch significant. In hoofdstuk 6 is de evaluatie van uitkomsten ten aanzien van klachten aan het bewegingsapparaat, fysiek functioneren, werkgerelateerde vitaliteit, werkvermogen, werkprestatie en ziekteverzuim beschreven. Voor deze uitkomsten werden zowel na 6 maanden als na 12 maanden geen statistisch significante interventie-effecten gevonden. Hoofdstuk 7 beschrijft de economische evaluatie van de interventie. Deze evaluatie is uitgevoerd naast de RCT en vanuit zowel het maatschappelijke als het bedrijfsperspectief. De interventie bleek niet kosten-effectief in het verbeteren van werkgerelateerde vitaliteit en werktevredenheid vanuit het bedrijfsperspectief. We concludeerden dat de kosten-effectiviteit van de interventie, waarvan de kosten €287 per werknemer bedragen, afhankelijk is van de investeringsbereidheid van beslissers en de kans op kosten-effectiviteit die zij acceptabel achten. De schattingen van het financiële rendement voor het bedrijf lieten een kostenbesparing zien, maar de statistische onzekerheid rondom deze schatting was groot.

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In het afsluitende hoofdstuk (hoofdstuk 8) zijn de belangrijkste bevindingen samengevat, bediscussieerd en ge誰nterpreteerd. Daarnaast zijn er aanbevelingen gedaan voor zowel de praktijk als voor toekomstig onderzoek. Op basis van dit proefschrift kan geconcludeerd worden dat de ontwikkelde interventie na 12 maanden niet tot positieve effecten of statistisch significante baten heeft geleid. Dit ondanks een systematische ontwikkeling en een op theorie gebaseerde aanpak. We vonden na 6 maanden wel veelbelovende korte termijn effecten op zowel intermediaire als primaire uitkomstmaten. Op basis van deze conclusie kan de implementatie van de interventie in de huidige vorm niet worden aanbevolen. Gebaseerd op de bevindingen in dit proefschrift is het aan te bevelen dat organisaties die de gezondheid van hun medewerkers willen verbeteren en ook werkgerelateerde uitkomsten positief willen be誰nvloeden, een veelzijdiger programma aanbieden. In een dergelijk programma zouden ook organisatie- en omgevingselementen moeten worden meegenomen. Het is daarnaast raadzaam dat toekomstige interventies elementen bevatten die er specifiek op gericht zijn om de effecten op lange termijn te behouden.

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Dankwoord Nu is dan het moment dat alles op papier staat, met het dankwoord nog te gaan. Alleen daarvoor ben ik al dankbaar. Promoveren doe je zeker niet alleen. Gelukkig heeft het me de afgelopen jaren zeker niet ontbroken aan inspirerende, motiverende en lieve mensen om me heen. Graag wil ik daarom hier de volgende mensen bedanken. Begeleiding Allereerst wil ik graag mijn promotoren, prof. dr. Allard van der Beek en prof. dr. ir. Paulien Bongers en mijn co-promotor dr. Evert Verhagen bedanken. Evert, een fijnere begeleider had ik me niet kunnen wensen. Ik heb veel bewondering voor je snelle en analytische blik, en het vermogen om meteen to-the-point te komen. Met je eeuwige optimisme en ‘alles komt goed’ bracht je me weer in balans als ik ergens over piekerde. Ondanks dat je veel op reis was, kon ik altijd rekenen op razendsnelle respons. Allard, ik heb het even in de van Dale opgezocht, pragmatisch=gericht op feiten, inspelend op de praktijk; zakelijk. Een effectieve eigenschap die ik je toedicht en waar ik je hartelijk voor wil danken. Daarnaast waardeer ik de persoonlijke aandacht die je aan je promovendi weet te geven zeer. Heel bijzonder dat het ondanks je volle agenda toch altijd mogelijk was om op korte termijn (‘loop zo maar even langs’) een overleg te regelen. Paulien, naast dat ik veel respect heb voor jou als begeleider van dit traject, bewonder ik ook je harde werk bij TNO. Hierdoor moest je je vaak snel inlezen in mijn stukken, en toch ontbrak het nooit aan waardevolle feedback. Wat mij betreft zelfs onmisbaar voor het vasthouden van de grote lijn en ook om het project te kunnen zien in de context van ontwikkelingen in de praktijk. Graag wil ik ook de leden van de leescommissie bedanken voor hun aandacht en tijd die zij aan het beoordelen van mijn proefschrift hebben besteed: dr. L.A.M. Elders, prof. A. Holtermann, PhD, prof. dr. W. van Mechelen, dr. K.M. Oude Hengel, dr. S.J.W. Robroek, en prof. dr. J.K. Sluiter. Bouw Deelnemers aan VIP in de bouw project. Bedankt, zonder jullie deelname was dit project er niet geweest. Dankzij jullie unieke en soms ook heel persoonlijke verhalen, bleef het project altijd met twee benen in de praktijk staan. Robbert en Teun, wat fijn dat jullie altijd ruimte in de agenda’s konden maken voor overleg en dat jullie zo direct betrokken zijn gebleven tijdens het hele proces. Pim, Hans, en vele anderen, dank voor het wegwijs maken in de bouw. Alle mensen bij Ballast Nedam die bereid waren om tijd en energie in het project te steken, en

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dat waren er heel wat, bedankt!

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Arbodiensten Daarnaast ben ik veel dank verschuldigd aan alle deelnemende arbodiensten en mensen bij Arbouw, Arbo Unie, ArboDuo/ArboNed en Bouw & Gezond die tijd hebben geïnvesteerd in het project. Jos, Marco en Klaas, dank voor jullie inzet en professionele aanpak om het project op te kunnen starten. Extra veel dank gaat uit naar Carla. Hoe druk je het ook had, ik kon altijd bij je aankloppen voor planningen en speurwerk. Ondersteuning Anneke, onze Sherlock van het project. Je bleef altijd volhouden en daarmee heb je er zeker toe bijgedragen dat zoveel deelnemers ook bereid waren om tot het einde toe met alle metingen mee te doen. Irene je hebt me als stagiair veel werk uit handen genomen en ik wil je bedanken voor de gezellige tripjes naar de bouw. Ook alle anderen die zich hebben ingezet voor de metingen, dank. Dank aan Rogier, Sandy en alle coaches van HC health die zich hebben ingezet tijdens het project! De positieve feedback van de deelnemers zegt veel. Edwin, bedankt voor het kritisch bekijken van het protocol en het begeleiden van de coaches. Alle medewerkers van Arboriginals en Meester Ontwerpers, en in het bijzonder Jos, Marijke en Linda, dank voor jullie creatieve input. Sonja, Brahim, Trees en Inge, ook op de afdeling was er altijd iemand die klaarstond, voor eigenlijk bijna alles! Medeauteurs Graag bedank ik ook mijn medeauteurs voor hun bijdragen aan de artikelen in dit proefschrift. Karin, wat jammer dat jij niet bij het hele proces betrokken bent gebleven. Bedankt voor je inspanningen bij het opstarten van het project en waardevolle bijdrage. Ik ben blij voor je dat je zo’n fijne nieuwe uitdaging hebt gevonden. Karen en Lando, dank dat ik gebruik heb mogen maken van jullie NEA expertise. Jullie hulp en geduld heeft geleid tot een mooie publicatie. Hanneke, Judith, Marieke en Maurits, ik ben dankbaar dat jullie je expertise op het gebied van economische evaluaties op dit project hebben toegepast. Collega’s VIP collega’s Jantien, Hanneke, Jennifer, Arjella, Cecile, Ernst, Chantal en de rest van de VIPfamilie. Dank voor de getoonde interesse tijdens en ook nog nadat het project was afgerond. Alle leden van de begeleidingscommissie, dank voor de input tijdens de bijeenkomsten. Maaike, Frederieke en Han, dank dat ik ook bij jullie de ruimte kreeg om naast leuke projecten het proefschrift nog af te ronden. Maaike wat bewonder ik je inzet voor zowel je werk als voor de mensen in je omgeving, ik heb veel van je geleerd.

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Hier mag ook, zoals inmiddels in heel wat dankwoorden, de G/H-0 gang niet ontbreken. De “oude garde”, Karen B, Jorien, Lisanne, Iris, Nicolette, Marije, Marieke, Alwin, David, Maurice, wat fijn dat jullie deuren altijd openstonden en er altijd tijd was voor dringende vragen en gezelligheid. Esther, Myrthe, Susanne, Roos, Astrid, Linda K, Lieke, Joppe, Martine, Joeri, Ruben, Magdalena en ik weet zeker dat ik ook hier nog mensen vergeet, maar jullie horen hier ook! Caro, fijn dat ik ook nog even kort jouw kamergenootje mocht zijn. Babette, ik hoop dat je een fijne tijd hebt in Stellenbosch, ik ben supertrots op je! Pieter, mijn mede-organisator van het juniorenoverleg, veel succes in Australië! Femke en Anouk, mijn Gent-maatjes. Een gezelliger congres had ik me niet kunnen wensen. Sport en wetenschap gaan goed samen. SLHamsterdam collega’s en EMGO runners, Judith, Joske, Kasper, Fenneke, Suzanne, Saskia en Saskia wat fijn dat ik een tijdje bij jullie kon aanhaken. Ik ben benieuwd of onze eerste triathlon naar meer gaat smaken. En natuurlijk bedankt voor het advies ‘what to wear’! Een speciaal plekje hier in dit dankwoord voor mijn roomies. Linda en Jantien, wat een geluk dat ik bij jullie op de kamer mocht zitten. Naast het delen van onze beperkte vierkante meters, onze (werkgerelateerde) gesprekken, deelden we ook ervaringen rond het (prille) moederschap. H-032 was door jullie een beetje thuis. En dat bezoekje aan Artis komt vast nog wel een keer. Linda wat fijn dat jij ook op de dag van de promotie naast mij wil staan. Vriendschap Lieve Mirka, wij delen sinds onze studie niet alleen een heleboel dezelfde interesses maar ook een speciale vriendschap. Ik ben zo trots op wat jij allemaal doet, wat fijn dat jij tijdens de verdediging naast mij wil staan. Ragna en Eva mijn lieve meiden, wat hebben we nog een hoop verjaardags-etentjes tegoed. De tijd konden we vaak niet vinden, als de plannen maar blijven. Dank voor alle koffie, het luisteren en alle goede raad. Annemieke, onze vriendschap gaat al heel ver terug en we delen al heel wat lief en leed. Jij bent er altijd voor een gezonde dosis werkelijkheid. Nynke en Ebelien, wij kwamen elkaar tegen op een voor ons allemaal bijzonder moment. Wat gezellig dat we contact blijven houden! Texel was een goed startpunt voor onze reizen om de wereld ;-) Lieve El, ik ben zo blij voor je! Lieve “MTB” vriendjes en vriendinnetjes. Jullie zijn zoveel meer dan dat. Het begon op het Spinoza en de groep breidt nog steeds uit. De vaste uitjes naar de Ardennen waren altijd iets om naar toe te leven, dat moeten we nog heel lang volhouden! Fijn dat een collega de in mijn agenda nogal cryptische omschrijving GNO hielp ontcijferen, ik had de eerste nog bijna gemist. Lieve buurtjes, dank voor jullie interesse en gezellige afleiding tijdens de laatste loodjes.

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Familie Lieve schoonfamilie, met jullie komst uit Italië werd het hier een Dolce Vita. Fijn dat jullie deur/ pizzaoven altijd openstaat. Greet en Pieter, bedankt voor jullie interesse in hoe het met mij en alle studies gaat. Mijn meedenkers, meelezers en meelevers, lieve pappa en mamma, Rob en Christien, wat fijn dat jullie altijd achter me staan (‘lekker uit de wind’). Met de (thuis)basis die jullie me hebben gegeven, kan ik de hele wereld aan. Lieve Viggo en Isabel. Mijn kleine grote wondertjes. Bedankt voor al jullie onvoorwaardelijke liefde, lachjes, grapjes, driftbuien en meestal volslagen maling aan wat mamma verder uitspookt dan mamma zijn. Het leven is zo mooi met jullie! Chris, er is geen zonder jou.

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Laura Viester

Uitnodiging

Worksite health promotion in the construction industry Laura Viester

voor het bijwonen van de openbare verdediging van mijn proefschrift

Worksite health promotion in the construction industry

Worksite health promotion in the construction industry

op dinsdag 24 november 2015 om 13.45 uur in de aula van de Vrije Universiteit aan de Boelelaan 1105 te Amsterdam Na afloop bent u van harte welkom op de receptie

Laura Viester Ohmstraat 4-II 1098 SR Amsterdam 06-24472241 laura.viester@gmail.com

Paranimfen Linda Eijckelhof eijckelhof@hotmail.com Mirka Janssen mirka_janssen@hotmail.com

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