CME AVAILABLE FOR THIS ARTICLE AT ACOEM.ORG
Psychosocial Factors at Work and Obesity Among Young Finnish Adults A Cohort Study Anne J¨aa¨ skel¨ainen, PhD, Leena Kaila-Kangas, PhD, P¨aivi Leino-Arjas, MD, PhD, Marja-Liisa Lindbohm, PhD, Nina Nevanper¨a, MSc, Jouko Remes, MSc, Marjo-Riitta J¨arvelin, MD, PhD, and Jaana Laitinen, PhD
Objective: To examine the associations between occupational psychosocial factors and obesity among 31-year-olds, adjusting for adolescent body mass index, physical strenuousness of work, and adverse health behaviors (ie, stress-related eating/drinking, leisure-time physical inactivity, smoking, and high alcohol consumption). Methods: The study population comprised 2083 men and 1770 women from the Northern Finland Birth Cohort 1966. Obesity was defined as a body mass index of 30.0 kg/m2 or more. Psychosocial exposures were defined in terms of demands, control, and social support at work. Results: Among men, high job demands and low worksite social support were independently associated with obesity. Among women, stressrelated eating/drinking and physical inactivity seemed to promote obesity. Body mass index at age 14 was an important predictor of obesity for both sexes. Conclusions: In workplace obesity prevention programs, it might be beneficial to improve the psychosocial work environment and promote healthy behaviors simultaneously.
O
besity is a major public health concern worldwide. It is associated with a large burden of disease and has been shown to generate a high economic impact because of increased medical expenditures and lost productivity.1,2 Reducing the prevalence of obesity among employees could result in significant savings to employers and national economies. In the past three decades, the estimated global prevalence of obesity [body mass index [BMI] ≥30.0 kg/m2 ] among adults has nearly doubled from 6.4% to 12.0%.3 In Western Europe and the United States, the current prevalence estimates are 20.5% and 31.7% for men and 21.0% and 33.9% for women, respectively.4 Although the obesity epidemic in industrialized nations has temporally coincided with a change in the nature of job requirements and psychosocial work environments (ie, a shift from physical demands to mental and emotional demands),5 the association between occupational stress and obesity is unclear. Using the most prominent models on work and health (ie, the demand–control model or From the Finnish Institute of Occupational Health (Dr J¨aa¨ skel¨ainen, Dr KailaKangas, Dr Leino-Arjas, Dr Lindbohm, Ms Nevanper¨a, Mr Remes, and Dr Laitinen), Helsinki; Biocenter Oulu and Institute of Health Sciences (Dr J¨arvelin), University of Oulu; Department of Children and Young People and Families (Dr J¨arvelin), National Institute for Health and Welfare, Oulu, Finland; and Department of Epidemiology and Biostatistics (Dr J¨arvelin), MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, UK. The study was supported by the SalWe Research Programme for Mind and Body (Tekes—the Finnish Funding Agency for Technology and Innovation grant 1104/10) and by EurHEALTHAgeing 277849 (Dr J¨arvelin). Authors J¨aa¨ skel¨ainen, Kaila-Kangas, Leino-Arjas, Lindbohm, Nevanper¨a, Remes, J¨arvelin, and Laitinen have no relationships/conditions/circumstances that present potential conflict of interest. The JOEM editorial board and planners have no financial interest related to this research. Address correspondence to: Anne J¨aa¨ skel¨ainen, PhD, Finnish Institute of Occupational Health, P. O. Box 310, FI-70101 Kuopio, Finland ([email protected]). C 2015 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0000000000000432
JOEM r Volume 57, Number 5, May 2015
Learning Objectives
r Summarize the study findings on work-related psychosocial factors and obesity in a well-characterized cohort of Finnish young adults.
r Explain the differences in work psychosocial factors associated with obesity for women versus men.
r Discuss the findings related to adolescent body mass index/obesity in both sexes.
the effort–reward imbalance model), some studies have reported a positive relationship between self-reported occupational stress and BMI or weight gain6,7 whereas others have not found an association between these factors.7,8 Furthermore, sex differences have been reported.9 In a fairly recent meta-analysis, which included pooled data from 13 European cohorts, the associations of both baseline BMI and weight gain with work stress were relatively modest.10 The mixed findings on the association between occupational stress and obesity might be due to variation in the assessment and definition of psychosocial exposures between studies, and small sample size and low statistical power in many of the studies.7,10,11 According to Solovieva and colleagues,11 cohort studies taking into account baseline BMI are required to examine the causal effect of workrelated factors on weight gain and obesity. In addition, the inclusion of covariates in the analyses should be justified.11 In attempts to understand the impact of occupational stress on health, the job demand–control model is one of the most widely used theoretical frameworks.12 According to the job demand–control model, job strain arises when a job involves high psychological demands but provides little control over work (ie, low in decision latitude).13 The model was later extended by the addition of workplace social support as a third dimension. Indeed, as psychological pressure at work increases, the importance of social support might become more evident.14 Low social support per se has been associated with obesity-related lifestyles, such as poor quality of diet and physical inactivity.15,16 Although Brunner et al6 found a dose– response relationship between worksite social support and both BMI and waist circumference among men and women, reports also exist of statistically insignificant associations between worksite social support and BMI.17 In addition to psychosocial factors, there is evidence that the general increase in the prevalence of sedentary work (ie, decreased physical activity at work) has contributed to the currently high prevalence of obesity.18 . Conversely, a high level of occupational physical activity is associated with a decreased risk of obesity.19 For example, B¨ockerman and colleagues20 estimated BMI to be 2.4% lower among males in a physically very demanding occupation than among those with a sedentary job. Nevertheless, some studies have found no relationship between physical workload and obesity.21 To cope with occupational stressors, individuals may use passive coping strategies including smoking, drinking alcoholic 485
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beverages, and eating energy-dense foods.22,23 Furthermore, the risk of physical inactivity seems to be higher among employees in highstrain jobs.24 Thus, obesity-promoting behaviors may mediate the association between occupational stressors and weight gain. Similarly, low social class and low socioeconomic status have been associated with an increased risk of both obesity and job strain vulnerability.25,26 In this study, we used data from a large birth cohort to examine associations between occupational psychosocial factors defined by job demands, job control and social support at work, and obesity (BMI ≥30.0 kg/m2 ) stratified by sex. We also studied whether BMI at 14 years of age, physical strenuousness of work, basic education level, and adverse health behaviors (ie, stress-related eating, low leisure-time physical activity, smoking, and increased alcohol consumption) modify the associations between occupational psychosocial factors and obesity.
METHODS Study Population We conducted cross-sectional analyses using data from the population-based Northern Finland Birth Cohort 1966. Northern Finland Birth Cohort 1966 consists of mothers and their children who were due to be born in the provinces of Oulu and Lapland between January 1, 1966, and December 31, 1966. The participants were recruited and longitudinally followed up (at 1, 14, and 31 years of age) as described previously.27,28 A total of 12,058 infants (96% of births in the region) were born alive. In 1980, postal questionnaires were sent to the 14-year-olds who were alive and had known addresses (n = 11,764) and, in the case of nonresponse, to their parents. Data were received from 11,010 subjects. At the 31-year follow-up in 1997, the number of people (offspring) alive and traced was 11 541, and data were collected via postal and computer-based questionnaires and clinical examinations. Altogether 8767 subjects (response rate 76%) returned the postal questionnaire. Those who lived in northern Finland or in the capital region of Finland (n = 8463) were invited to a clinical examination, and 6033 (71% of those invited) participated. Alongside the clinical examinations, participants filled in an additional computer-based (or alternatively paper-based) questionnaire (n = 5737, response rate 68%). In this study, analyses are based on the individuals who gave permission to use their data and who reported being currently employed or self-employed (n = 4275). After exclusion of those for whom data on all study variables were not available or who reported being pregnant, the number of subjects was 3853. The flow chart in Fig. 1 summarizes the selection of the final study population. The study was approved by the Ethics Committee of the Finnish Institute of Occupational Health and by the Ethics Committee of the Faculty of Medicine, University of Oulu. Each participant gave written informed consent according to the Declaration of Helsinki.
Measurement of BMI At the clinical examination, trained nurses took anthropometric measurements including height in centimeters and weight in kilograms to one decimal place. Body mass index at 31 years was calculated as weight/height2 and was classified using the World Health Organization criteria as follows: nonobese less than 30.0 kg/m2 and obese 30.0 kg/m2 or more.29 On the basis of self-reported data on height and weight collected at 14-year follow-up, BMI at 14 years was calculated similarly. To examine the transition from normal weight status at age 14 years to obesity at age 31 years, participants were classified as normal weight/underweight or overweight/obese at 14 years according to the International Obesity Task Force age486
FIGURE 1. Flow chart of the Northern Finland Birth Cohort 1966 data collection and selection of study population. and gender-specific BMI cutoff values.30 Else, BMI at 14 years was used as a continuous variable in the analyses.
Occupational Psychosocial Factors In this study, job control and job demand measures were derived from the Job Content Questionnaire31 and the responses were given on a five-point scale, as previously described.32 Job control (control over work) was measured by questions concerning skill discretion, vocational proficiency, authority to make decisions, and opportunities to participate in decision-making. Job demands (psychological demands of work) were addressed with questions covering qualitative aspects, such as demands for attentiveness or precision. Perceived social support at work was measured using the following (four) questions: “If you had long-term stressful problems in interpersonal relations, mental health or work, how much mental support would you get through listening and advice from your co-worker (or your supervisor)?” and “If you were in a difficult situation that you could not cope with on your own (eg, arranging child care, lack of money, and insurmountable problem with work), how much practical help would you get from your coworker (or your supervisor)?” The social support sum score was based on responses on a five-point scale (“a lot,” ”quite a lot,” “some,” “a little,” and “not at all or I do not want support”). The items on social support at work are based on a theoretical framework arising from the evidence for the role of social support in health and well-being.13,32,33
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JOEM r Volume 57, Number 5, May 2015
Psychosocial Factors at Work and Obesity Among Young Finnish Adults
The scales of job demands comprised 11 items (Cronbach α = 0.86), job control 13 items (α = 0.84), and worksite social support four items (α = 0.82). The scores for job control, demands, and social support were divided into sex-specific tertile groups (low, moderate, and high). The scores for job control and job demands were also dichotomized at the median value for men and women separately. Participants with a high level of job demands (above the median) and a low level of job control (below the median) were presumed to be at risk of job strain. All other combinations of job demand and control levels were defined as nonjob strain.
Covariates Physical strenuousness of work was assessed using the question “How strenuous is your work at present?” with six response alternatives: (1) “sedentary work including only light manual tasks,” (2) “sedentary work including some handling of moderately heavy objects,” (3) “standing work without handling heavy loads,” (4) “standing work including bending and carrying moderately heavy loads or a lot of walking,” (5) “standing work with continuous lifting of light objects or occasional lifting of heavy objects” and (6) “standing work with continuous strenuous motions and often for a long time.” The job types were respectively renamed and the latter two categories were combined as follows: (1) sedentary, light; (2) sedentary, moderate; (3) standing, light; (4) standing, moderate; and (5) standing, strenuous. Alcohol consumption was measured in terms of grams of ethanol consumed per day and was divided into sex-specific quartiles. Alcohol use was assessed as the average frequency of consumption of beer, wine, and spirits during the last year, and the usual amount of each consumed on one occasion. The amount of alcohol consumed per day was calculated using the following estimates of alcohol content per portion (vol%): beer 4.8, light wines 5.0, strong wines 14.5, and spirits 37.0, and the information was validated against 7-day food diaries.34 Stress-related eating and drinking behavior was assessed using the item “Recall the most stressful matter, event, or situation that you have experienced in the past month. Did you try to make things easier by eating, drinking or taking medicines?” The response categories “somewhat,” “quite a lot,” and “a lot” were combined into “yes,” whereas “not at all” was considered “no.” Vigorous leisure-time physical activity was measured by asking “How often in your leisure time do you exercise to the point of sweating and getting at least slightly out of breath?” and was classified as “two to seven times a week,” “once a week,” and “less than weekly.” The smoking status categories “never smoked,” “ex-smoker,” “occasionally,” and “regularly” were based on the responses to the questions “Have you ever smoked in your life?” “Have you ever smoked regularly?” and “Do you currently smoke?” Basic education level was defined as either having passed or not having passed the Finnish matriculation examination, taken typically after 12 years of schooling. Marital status was categorized as “married or cohabiting” and “single” (unmarried/judicially separated/divorced/widowed).
Statistical Analyses All analyses were sex-stratified. We used logistic regression analysis to determine the associations between occupational factors and obesity (BMI ≥30.0 kg/m2 ). Every regression model included job demands, job control, and worksite social support to observe the effects of covariate adjustments. The covariates were selected by the authors on the basis of research literature and were simultaneously entered into the models. We present both crude and adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) from logistic regression analysis. In addition, we report the characteristics of the study population as frequencies and percentages, and, for continuous variables, as means and standard deviations (SDs).
Pearson chi-square test was used to study differences between obese and nonobese subjects. We performed statistical analyses using SAS (version 9.2, SAS Institute Inc, Cary, NC) and IBM SPSS Statistics for Windows (version 19.0, IBM Corp, Armonk, NY). The logistic regression models were fitted to the data using the LOGISTIC procedure of the SAS software package. Missing values for BMI at 14 years (n = 326; men 8.9% and women 7.4%) were replaced by the median value of the variable (19.1 for both males and females), whereas an additional category was created for missing data on stress-related eating and drinking behavior (n = 505; men 16.2% and women 8.9%).
RESULTS In the whole study population, the mean BMI at 31 years of age was 25.2 kg/m2 for men and 23.9 kg/m2 for women. The prevalence of obesity at age 31 years was 8.2% for men and 7.8% for women. Light sedentary (29%) and strenuous standing (26%) jobs were almost equally common types of work among all men, whereas 35% of all women had light sedentary jobs and 15% reported high physical workload (ie, strenuous standing). A higher level of basic education was more common among women (51%) than among men (27%). With regard to health behaviors, mean alcohol consumption was higher among men (13.2 g/d) than among women (5.3 g/d), whereas stress-related eating or drinking behavior was more prevalent among women (31%) than among men (23%). As shown in Table 1, job strain as a dichotomized variable was similarly distributed among the obese and nonobese participants in both sexes, thus the separate examination of job demands and control was justified. For both men and women who were not obese at age 31 years, the mean value of BMI at age 14 years was 19.1 (SD, 2.0) kg/m2 . Among obese men and women, the average adolescent BMI values were 22.0 (SD, 3.2) kg/m2 and 22.6 (SD, 3.2) kg/m2 , respectively. The results of logistic regression analysis for men are presented in Table 2. After adjusting for all covariates, significant associations remained for high job demands (OR, 2.01; 95% CI, 1.22 to 3.34) and low social support at work (OR, 1.76; 95% CI, 1.13 to 2.75). Lower level of basic education, higher BMI at 14 years, lowest and highest levels of alcohol consumption, and vigorous leisure-time exercise once a week were also associated with obesity among men. The ORs for high job demands increased after adjustment for basic education level and the physical strenuousness of work (model 1) and BMI at 14 years (model 3), but the adjustment for health behaviors had no essential effect on this risk estimate (model 2). Among the covariates, lower basic education level, moderately strenuous sedentary work, BMI at 14 years, being in the highest quartile group of alcohol consumption, and stress-related eating and drinking behavior were related to obesity among men before any adjustments. The associations between obesity and health behaviors were modified by the inclusion of BMI at 14 years in the analysis (model 3), particularly regarding alcohol consumption. Among women (Table 3), the only work-related determinant associated with obesity was job control (ie, a moderate level of job control was related to a decreased risk of obesity in unadjusted analysis and models 1 and 2). In the fully adjusted model, the greatest odds for obesity were related to infrequent vigorous leisure-time physical activity (ie, once a week and less than weekly) (OR, 2.52; 95% CI, 1.45 to 4.39; and OR, 3.36; 95% CI, 2.02 to 5.59; respectively). Compared with men, the OR related to BMI at 14 years was slightly higher whereas the OR related to a low level of basic education was somewhat lower for women (men: OR, 1.58; 95% CI, 1.47 to 1.70; and OR, 1.89; 95% CI, 1.19 to 3.01; women: OR, 1.74; 95% CI, 1.60 to 1.90; and OR, 1.63; 95% CI, 1.05 to 2.52, respectively). Finally, a statistically significant association between stress-related eating and drinking behavior and an increased risk of obesity was seen among women but not among men.
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TABLE 1. Characteristics of the Northern Finland Birth Cohort 1966 Stratified by Obesity Men
Psychosocial factors at work Job demands Low Moderate High Job control Low Moderate High Job strain (high demands, low control) No Yes Social support at work High Moderate Low Covariates Physical strenuousness of work Sedentary, light Sedentary, moderate Standing, light Standing, moderate Standing, strenuous Basic education Matriculation examination No matriculation examination Marital status Married/cohabiting Single Smoking Never smoked Ex-smoker Occasionally Regularly Alcohol consumption, men/women, g/d 0–2.7/0–0.8 2.8–7.7/0.9–2.8 7.8–16.2/2.9–6.4 >16.2/>6.4 Vigorous leisure-time exercise Two to seven times a week Once a week Less than weekly Stress-related eating or drinking No Yes Missing
488
Women
Nonobese n = 1911
Obese n = 172
Nonobese n = 1634
Obese n = 136
34.8 35.6 29.6
29.7 32.0 38.3
0.056
33.0 31.5 35.5
31.6 33.8 34.6
0.847
35.3 31.7 33.0
35.5 27.9 36.6
0.519
31.9 35.0 33.1
39.0 26.5 34.5
0.098
87.3 12.7
84.9 15.1
0.358
80.3 19.7
86.8 13.2
0.066
38.0 40.5 21.5
30.8 37.8 31.4
0.009
32.3 30.2 37.5
34.5 30.2 35.3
0.835
30.2 10.2 13.3 20.6 25.7
26.7 15.7 12.2 19.2 26.2
0.237
37.0 6.7 20.3 23.4 12.6
33.1 9.6 19.1 22.8 15.4
0.582
32.0 68.0
21.5 78.5
0.005
54.5 45.5
44.9 55.1
0.029
73.7 26.3
73.3 26.7
0.892
74.1 25.9
73.5 26.5
0.894
34.7 31.7 12.6 21.0
32.0 39.0 11.0 18.0
0.269
40.8 23.4 12.4 23.4
40.4 27.9 12.5 19.1
0.547
25.2 24.0 27.0 23.9
19.2 27.3 22.1 31.4
0.045
23.4 23.1 27.7 25.8
27.2 30.1 22.8 19.9
0.101
42.3 21.9 35.8
34.3 26.2 39.5
0.116
42.7 25.6 31.7
25.7 27.9 46.3
16.2 Vigorous leisure-time exercise Two to seven times a week Once a week Less than weekly Stress-related eating or drinking behavior No Yes
Unadjusted OR (95% CI)
Model 1 OR (95% CI)
Model 2 OR (95% CI)
Model 3 OR (95% CI)
Model 4 OR (95% CI)
1.00 1.06 (0.71–1.57) 1.52 (1.04–2.23)
1.00 1.16 (0.76–1.75) 1.70 (1.09–2.64)
1.00 1.17 (0.77–1.78) 1.72 (1.11–2.68)
1.00 1.41 (0.89–2.23) 2.05 (1.25–3.37)
1.00 1.39 (0.87–2.22) 2.01 (1.22–3.34)
1.00 0.88 (0.59–1.30) 1.10 (0.76–1.59)
1.00 0.88 (0.58–1.32) 1.04 (0.68–1.58)
1.00 0.89 (0.59–1.36) 1.08 (0.71–1.65)
1.00 0.85 (0.54–1.33) 1.09 (0.69–1.74)
1.00 0.84 (0.53–1.32) 1.06 (0.66–1.70)
1.00 1.15 (0.79–1.68) 1.80 (1.21–2.68)
1.00 1.20 (0.82–1.75) 1.74 (1.16–2.61)
1.00 1.18 (0.81–1.73) 1.73 (1.16–2.60)
1.00 1.05 (0.69–1.60) 1.76 (1.13–2.73)
1.00 1.06 (0.70–1.62) 1.76 (1.13–2.75)
1.00 1.72 (1.18–2.50) 1.55 (1.45–1.66)
1.00 1.88 (1.24–2.86) – (–)
1.00 1.80 (1.21–2.67) – (–)
1.00 1.83 (1.19–2.82) 1.58 (1.48–1.70)
1.00 1.89 (1.19–3.01) 1.58 (1.47–1.70)
1.00 1.75 (1.06–2.89) 1.04 (0.61–1.77) 1.06 (0.66–1.68) 1.15 (0.75–1.77)
1.00 1.50 (0.89–2.53) 0.93 (0.54–1.61) 0.89 (0.54–1.46) 0.89 (0.56–1.44)
– (–) – (–) – (–) – (–) – (–)
– (–) – (–) – (–) – (–) – (–)
1.00 1.47 (0.81–2.67) 1.05 (0.58–1.93) 0.97 (0.56–1.69) 0.89 (0.52–1.50)
1.00 1.34 (0.92–1.94) 0.95 (0.55–1.64) 0.93 (0.59–1.47)
– (–) – (–) – (–) – (–)
1.00 1.15 (0.77–1.73) 0.94 (0.54–1.64) 0.91 (0.57–1.46)
1.00 0.90 (0.57–1.41) 0.97 (0.53–1.75) 0.84 (0.50–1.39)
1.00 0.89 (0.57–1.39) 0.95 (0.52–1.73) 0.82 (0.49–1.37)
1.49 (0.94–2.37) 1.00 1.08 (0.66–1.74) 1.73 (1.10–2.71)
– (–) – (–) – (–) – (–)
1.48 (0.92–2.37) 1.00 1.15 (0.66–1.98) 1.61 (1.01–2.56)
1.66 (0.99–2.78) 1.00 1.15 (0.67–1.99) 2.09 (1.48–1.70)
1.72 (1.01–2.86) 1.00 1.15 (0.66–1.98) 2.12 (1.26–3.56)
1.00 1.65 (0.98–2.21) 1.36 (0.95–1.96)
– (–) – (–) – (–)
1.00 1.38 (0.91–1.46) 1.16 (0.80–1.70)
1.00 1.63 (1.03–2.58) 1.33 (0.88–2.02)
1.00 1.64 (1.04–2.60) 1.33 (0.88–2.02)
1.00 1.50 (1.04–2.17)
– (–) – (–)
1.00 1.54 (1.05–2.24)
1.00 1.43 (0.94–2.17)
1.00 1.42 (0.93–2.15)
Model 1: Psychosocial factors at work + basic education and physical strain at work. Model 2: Psychosocial factors at work + basic education, smoking, leisure-time exercise, alcohol consumption, and stress-related eating or drinking. Model 3: Psychosocial factors at work + basic education, BMI at 14 years of age, smoking, leisure-time exercise, alcohol consumption, and stress-related eating or drinking. Model 4: All the aforementioned variables. BMI, body mass index; CI, confidence interval; OR, odds ratio.
We conducted additional analyses using the transition from normal weight status at age 14 years to obesity at age 31 years as the outcome variable (136 men and 97 women) and observed similar associations as above (data not shown). Among men, the fully adjusted ORs for becoming obese between ages 14 and 31 years were 2.13 (95% CI, 1.26 to 3.59) when job demands were high
and 1.84 (95% CI, 1.17 to 2.89) when worksite social support was low. Job strain as a binary variable (high demands and low control vs other combinations) was not associated with obesity in any model in either sex (data not shown). For example, the unadjusted and fully adjusted ORs were 1.23 (95% CI, 0.79 to 1.10) and 1.29 (95% CI,
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J¨aa¨ skel¨ainen et al
TABLE 3. Associations Between Occupational Exposures and Obesity Among 31-Year-Old Finnish Women (n = 1770) Unadjusted OR (95% CI) Psychosocial factors at work Demands Low 1.00 Moderate 1.12 (0.73–1.73) High 1.02 (0.66–1.56) Control High 1.00 Moderate 0.62 (0.40–0.96) Low 0.86 (0.57–1.29) Social support at work High 1.00 Moderate 0.93 (0.60–1.45) Low 0.88 (0.58–1.34) Covariates Basic education Matriculation examination 1.00 No matriculation examination 1.47 (1.04–2.10) BMI at 14 yrs of age (continuous) 1.70 (1.57–1.85) Physical strain at work Sedentary, light 1.00 Sedentary, moderate 1.59 (0.82–3.04) Standing, light 1.05 (0.64–1.74) Standing, moderate 1.09 (0.68–1.75) Standing, strenuous 1.37 (0.80–2.35) Smoking Never smoked 1.00 Ex-smoker 1.21 (0.78–1.86) Occasionally 1.02 (0.58–1.79) Regularly 0.82 (0.51–1.34) Alcohol consumption, g/d 0–0.8 1.12 (0.70–1.79) 0.9–2.8 1.00 2.9–6.4 0.71 (0.43–1.16) >6.4 0.66 (0.40–1.11) Vigorous leisure-time exercise Two to seven times a week 1.00 Once a week 1.81 (1.13–2.92) Less than weekly 2.43 (1.58–3.72) Stress-related eating or drinking behavior No 1.00 Yes 1.60 (1.10–2.32)
Model 1 OR (95% CI)
Model 2 OR (95% CI)
Model 3 OR (95% CI)
Model 4 OR (95% CI)
1.00 1.14 (0.73–1.78) 0.97 (0.61–1.55)
1.00 1.15 (0.73–1.82) 0.96 (0.60–1.54)
1.00 1.07 (0.63–1.81) 1.10 (0.65–1.86)
1.00 1.05 (0.62–1.78) 1.10 (0.65–1.86)
1.00 0.61 (0.39–0.95) 0.81 (0.52–1.27)
1.00 0.59 (0.37–0.93) 0.79 (0.50–1.23)
1.00 0.65 (0.39–1.09) 0.87 (0.52–1.46)
1.00 0.65 (0.39–1.10) 0.84 (0.50–1.42)
1.00 0.96 (0.62–1.49) 0.86 (0.56–1.33)
1.00 0.95 (0.60–1.48) 0.78 (0.50–1.21)
1.00 1.06 (0.64–1.76) 0.83 (0.50–1.38)
1.00 1.05 (0.63–1.76) 0.83 (0.50–1.39)
1.00 1.44 (1.00–2.08) – (–)
1.00 1.42 (0.97–2.01) – (–)
1.00 1.54 (1.00–2.36) 1.73 (1.58–1.88)
1.00 1.63 (1.05–2.52) 1.74 (1.60–1.90)
1.00 1.50 (0.78–2.89) 1.03 (0.62–1.71) 1.02 (0.63–1.65) 1.24 (0.71–2.16)
– (–) – (–) – (–) – (–) – (–)
– (–) – (–) – (–) – (–) – (–)
1.00 1.08 (0.47–2.45) 0.84 (0.47–1.50) 0.87 (0.50–1.50) 0.61 (0.31–1.20)
– (–) – (–) – (–) – (–)
1.00 1.18 (0.74–1.88) 1.12 (0.62–2.03) 0.77 (0.47–1.26)
1.00 1.02 (0.60–1.76) 1.16 (0.59–2.28) 0.86 (0.50–1.48)
1.00 1.06 (0.62–1.82) 1.15 (0.58–2.27) 0.87 (0.50–1.50)
– (–) – (–) – (–) – (–)
1.15 (0.71–1.86) 1.00 0.68 (0.41–1.11) 0.59 (0.34–1.00)
1.23 (0.71–2.13) 1.00 0.86 (0.49–1.53) 0.67 (0.36–1.23)
1.25 (0.72–2.18) 1.00 0.85 (0.48–1.52) 0.65 (0.35–1.21)
– (–) – (–) – (–)
1.00 1.81 (1.12–2.92) 2.41 (1.56–3.72)
1.00 2.46 (1.42–4.28) 3.36 (2.02–5.60)
1.00 2.52 (1.45–4.39) 3.36 (2.02–5.59)
– (–) – (–)
1.00 1.69 (1.15–2.49)
1.00 1.61 (1.04–2.49)
1.00 1.62 (1.04–2.51)
Model 1: Psychosocial factors at work + basic education and physical strain at work. Model 2: Psychosocial factors at work + basic education, smoking, leisure-time exercise, alcohol consumption, and stress-related eating or drinking. Model 3: Psychosocial factors at work + basic education, BMI at 14 years of age, smoking, leisure-time exercise, alcohol consumption, and stress-related eating or drinking. Model 4: All the aforementioned variables. BMI, body mass index; CI, confidence interval; OR, odds ratio.
0.79 to 2.12) for men and 0.62 (95% CI, 0.37 to 1.04) and 0.56 (95% CI, 0.31 to 1.01) for women.
DISCUSSION Among 31-year-old men, high demands and low social support at work were independently associated with obesity, and these associations were further strengthened when the analyses were adjusted for adolescent obesity and basic education level. The results 490
suggest that high job demands at the beginning of the working career may induce physiological changes that result in weight gain. Among women, however, no associations between psychosocial work characteristics and obesity were detected. The analyses also revealed that BMI at 14 years is an important predictor of adult obesity for both men and women. Some sex similarities and differences in health behavior–obesity associations were observed: among males, alcohol consumption, and among females, stress-related eating or drinking
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Psychosocial Factors at Work and Obesity Among Young Finnish Adults
behavior, and among both sexes, infrequent leisure-time exercise seemed to be obesity-promoting factors. All in all, the main findings among women and men were strikingly different and need to be confirmed in other study populations. Because of a large proportion of 31-year-old women on maternity or childcare leave in our data (16.2% of women and 0.1% of men) and the exclusion of nonworking or pregnant individuals from the analyses, more women than men were excluded. The fact that the working women were leaner (BMI 23.9) than the nonworking women (BMI 24.5) may partly be explained by our previous finding that obese young women have difficulties entering the job market (ie, obese female adolescents were at an increased risk of a long history of unemployment at the age of 31 years in the same data as that which we used).35 In addition, we found that perceived work ability was inversely associated with waist-to-hip ratio among women.36 In fact, “the healthy worker effect” is an inherent source of selection bias in occupational epidemiological studies.37 Thus, the variation in both psychosocial exposures and obesity measures is lower in working populations and, as a result, the associations between these factors are weakened (ie, biased toward the null). Another selection mechanism is reverse causality, which arises when obese individuals are selected into unfavorable psychosocial work environments.38 It is possible that obesity affects job opportunities and performance at work and increases stress vulnerability. In addition to the selection effect, the different patterns of the associations between obesity and occupational factors and covariates for women and men could be because men and women are employed in different occupations and positions and may thus be exposed to different psychosocial and physical working conditions. In our data, substantially more women than men had passed the matriculation examination as basic education, and among men, the low basic education level was more prevalent among obese than among nonobese. These differences may explain why among men the OR related to high job demands increased when taking basic education level into account, whereas among women the associations were unaffected. Because work–family conflicts might constitute a barrier to healthy lifestyle,39 the social support that women receive from family and friends may be more important than that from colleagues and supervisors. It might also be necessary to discriminate between different dimensions of social support (eg, emotional, instrumental/tangible, and informational support). Nevertheless, the relationships may not be straightforward: among young women, low emotional support has been associated with both underweight and overweight statuses.40 Although occupational stress has been associated with adverse lifestyles, the health behaviors in this study did not mediate the effects of occupational psychosocial factors on BMI. It is noteworthy that health behaviors such as smoking habits are often established before entering work life. In addition, we cannot exclude the fact that other lifestyle-related or physiological (psychobiological) factors could explain the association between occupational stress and obesity. For instance, stress may alter the brain’s response to food and shift food choices toward energy-dense items.41,42 On the other hand, the results show the importance of controlling for earlier obesity status to prevent false-positive findings concerning work-related factors and obesity. The study has certain strengths and limitations. This population-based birth cohort study covered three occupational psychosocial hazards—high demands, low control, and low support— adjusted for several covariates known to be related to BMI and which potentially mediate and explain the effects of job characteristics. Weight and height at 31 years of age were clinically measured, whereas all other data, including weight and height at 14 years, were self-reported. The subset of the cohort members who participated in the clinical examination at the 31-year follow-up has shown to be well-representative of the original study population.28 The rate of unemployment in this study population was approximately equal to
that of Finns in general,43 and the prevalence of obesity corresponded to that observed among young Finnish adults.44 Nevertheless, as the participants were young adults, the results cannot be generalized to all age groups. As the data analysis was cross-sectional, no causal inferences can be drawn. Nevertheless, the observed associations were similar in our additional analyses where the development of obesity (transition from normal weight at age 14 years to obesity at age 31 years) was used as the outcome variable. This implies that early obesity cannot have influenced the associations. It can also be postulated that job stress–obesity relationships may become more evident in later life because such associations were detected already among 31-year-old men at the early stages of their careers.
CONCLUSIONS High demands and low social support at work were robustly associated with an increased risk of obesity among men, and the association between job demands and obesity was further strengthened by adjustments for adolescent obesity and basic education level. Among women, individual behavioral factors such as stress-related eating or drinking behavior and infrequent exercise outweighed occupational stressors as determinants of obesity. On the basis of the results, it could be hypothesized that in workplace health promotion to prevent obesity it is important to improve the psychosocial work environment as well as promote healthy behaviors. Considering the public health burden of obesity, this hypothesis deserves further investigation in intervention settings.
ACKNOWLEDGMENTS We thank the late Professor Paula Rantakallio for the initiation of the Northern Finland Birth Cohort study project and Ms Alice Lehtinen for editing the language in the article.
REFERENCES 1. Schmier JK, Jones ML, Halpern MT. Cost of obesity in the workplace. Scand J Work Environ Health. 2006;32:5–11. 2. Finkelstein EA, DiBonaventura MD, Burgess SM, Hale BC. The costs of obesity in the workplace. J Occup Environ Med. 2010;52:971–976. 3. Stevens GA, Singh GM, Lu Y, et al. National, regional, and global trends in adult overweight and obesity prevalences. Popul Health Metr. 2012;10:22. 4. Ng M, Fleming T, Robinson M, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:766–781. 5. Johnson JV. Globalization, workers’ power and the psychosocial work environment—is the demand-control model still useful in a neoliberal era? Scand J Environ Health. 2008;6(suppl):15–21. 6. Brunner EJ, Chandola T, Marmot MG. Prospective effect of job strain on general and central obesity in the Whitehall II Study. Am J Epidemiol. 2007;165:828–837. 7. Siegrist J, R¨odel A. Work stress and health risk behavior. Scand J Work Environ Health. 2006;32:473–481. 8. Lallukka T, Sarlio-L¨ahteenkorva S, Kaila-Kangas L, Pitk¨aniemi J, Luukkonen R, Leino-Arjas P. Working conditions and weight gain: a 28-year follow-up study of industrial employees. Eur J Epidemiol 2008;23:303–310. 9. Ostry AS, Radi S, Louie AM, LaMontagne AD. Psychosocial and other working conditions in relation to body mass index in a representative sample of Australian workers. BMC Public Health. 2006;6:53. 10. Nyberg ST, Heikkil¨a K, Fransson EI, et al. Job strain in relation to body mass index: pooled analysis of 160 000 adults from 13 cohort studies. J Intern Med. 2012;272:65–73. 11. Solovieva S, Lallukka T, Virtanen M, Viikari-Juntura E. Psychosocial factors at work, long work hours, and obesity: a systematic review. Scand J Work Environ Health. 2013;39:241–258. 12. Karasek RA. Job demands, job decision latitude, and mental strain: implications for job redesign. Adm Sci Q. 1979;24:285–308. 13. Karasek RA, Theorell T. Healthy Work: Stress, Productivity and the Reconstruction of Working Life. New York: Basic Books; 1990.
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14. Falk A, Hanson BS, Isacsson SO, Ostergren PO. Job strain and mortality in elderly men: social network, support, and influence as buffers. Am J Public Health. 1992;82:1136–1139. 15. Eyler AA, Brownson RC, Donatelle RJ, King AC, Brown D, Sallis JF. Physical activity social support and middle- and older-aged minority women: results from a US survey. Soc Sci Med. 1999;49:781–789. 16. Shaikh AR, Yaroch AL, Nebeling L, Yeh MC, Resnicow K. Psychosocial predictors of fruit and vegetable consumption in adults: a review of the literature. Am J Prev Med. 2008;34:535–543. 17. Tamers SL, Beresford SA, Cheadle AD, Zheng Y, Bishop SK, Thompson B. The association between worksite social support, diet, physical activity and body mass index. Prev Med. 2011;53:53–56. 18. Church TS, Thomas DM, Tudor-Locke C, et al. Trends over 5 decades in U.S. occupation-related physical activity and their associations with obesity. PLoS One. 2011;6:e19657. 19. King GA, Fitzhugh EC, Bassett DR Jr, et al. Relationship of leisure-time physical activity and occupational activity to the prevalence of obesity. Int J Obes Relat Metab Disord. 2001;25:606–612. 20. B¨ockerman P, Johansson E, Jousilahti P, Uutela A. The physical strenuousness of work is slightly associated with an upward trend in the BMI. Soc Sci Med. 2008;66:1346–1355. 21. Nishitani N, Sakakibara H. Relationship of obesity to job stress and eating behavior in male Japanese workers. Int J Obes (Lond). 2006;30:528–533. 22. Lindquist TL, Beilin LJ, Knuiman MW. Influence of lifestyle, coping, and job stress on blood pressure in men and women. Hypertension. 1997;29:1–7. 23. Laitinen J, Ek E, Sovio U. Stress-related eating and drinking behavior and body mass index and predictors of this behavior. Prev Med. 2002;34:29–39. 24. Fransson EI, Heikkil¨a K, Nyberg ST, et al. Job strain as a risk factor for leisure-time physical inactivity: an individual-participant meta-analysis of up to 170,000 men and women: the IPD-Work Consortium. Am J Epidemiol. 2012;176:1078–1089. 25. McLaren L. Socioeconomic status and obesity. Epidemiol Rev. 2007;29: 29–48. 26. Cho SI, Eum KD, Choi BK, Paek D, Karasek R. Social class, job insecurity and job strain in Korea. Scand J Work Environ Health. 2008;6(suppl):60–65. 27. Rantakallio P. The longitudinal study of the Northern Finland Birth Cohort of 1966. Paediatr Perinat Epidemiol. 1988;2:59–88. 28. Sovio U, King V, Miettunen J, et al. Cloninger’s Temperament dimensions, socio-economic and lifestyle factors and metabolic syndrome markers at age 31 years in the Northern Finland Birth Cohort 1966. J Health Psychol. 2008;12:371–382. 29. World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:1–253.
492
30. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000;320:1240–1243. 31. Karasek RA, Brisson C, Kawakami N, Houtman I, Bongers P, Amick B. The Job Content Questionnaire (JCQ): an instrument for internationally comparative assessments of psychological job characteristics. J Occup Health Psychol. 1998;3:322–355. 32. Kujala V, Tammelin T, Remes J, Vammavaara E, Ek E, Laitinen J. Work ability index of young employees and their sickness absence during the following year. Scand J Work Environ Health. 2006;32:75–84. 33. Sarason IG, Pierce GR, Sarason BR. Social support and interactional processes: a triadic hypothesis. J Soc Pers Relat. 1990;7:495– 506. 34. Laitinen J, Pietil¨ainen K, Wadsworth M, Sovio U, J¨arvelin MR. Predictors of abdominal obesity among 31-y-old men and women born in Northern Finland in 1966. Eur J Clin Nutr. 2004;58:180–190. 35. Laitinen J, Power C, Ek E, Sovio U, J¨arvelin MR. Unemployment and obesity among adults in a northern Finland 1966 birth cohort. Int J Obes Relat Metab Disord. 2002;26:1329–1338. 36. Laitinen J, N¨ayh¨a S, Kujala V. Body mass index and weight change from adolescence into adulthood, waist-hip ratio and perceived work ability among young adults. Int J Obes (Lond). 2005;29:697–702. 37. Pearce N, Checkoway H, Kriebel D. Bias in occupational epidemiology studies. Occup Environ Med. 2007;64:562–568. 38. Wilcosky T, Wing S. The healthy worker effect. Selection of workers and work forces. Scand J Work Environ Health 1987;13:70–72. 39. Roos E, Sarlio-L¨ahteenkorva S, Lallukka T, Lahelma E. Associations of workfamily conflicts with food habits and physical activity. Public Health Nutr. 2007;10:222–229. 40. Ali SM, Lindstr¨om M. Socioeconomic, psychosocial, behavioural and psychological determinants of BMI among young women: differing patterns for underweight and overweight/obesity. Eur J Public Health. 2006;16: 325–331. 41. Wardle J, Steptoe A, Oliver G, Lipsey Z. Stress, dietary restraint and food intake. J Psychosom Res. 2000;48:195–202. 42. Tryon MS, Carter CS, Decant R, Laugero KD. Chronic stress exposure may affect the brain’s response to high calorie food cues and predispose to obesogenic eating habits. Physiol Behav. 2013;120C:233–242. 43. Statistics Finland. Statistical Yearbook of Finland 2000. Helsinki; 2000: 355–356. 44. Lahti-Koski M, Vartiainen E, M¨annist¨o S, Pietinen P. Age, education and occupation as determinants of trends in body mass index in Finland from 1982 to 1997. Int J Obes Relat Metab Disord. 2000;24:1669– 1676.
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Psychosocial Factors at Work and Obesity Among Young Finnish Adults A Cohort Study Anne J¨aa¨ skel¨ainen, PhD, Leena Kaila-Kangas, PhD, P¨aivi Leino-Arjas, MD, PhD, Marja-Liisa Lindbohm, PhD, Nina Nevanper¨a, MSc, Jouko Remes, MSc, Marjo-Riitta J¨arvelin, MD, PhD, and Jaana Laitinen, PhD
Objective: To examine the associations between occupational psychosocial factors and obesity among 31-year-olds, adjusting for adolescent body mass index, physical strenuousness of work, and adverse health behaviors (ie, stress-related eating/drinking, leisure-time physical inactivity, smoking, and high alcohol consumption). Methods: The study population comprised 2083 men and 1770 women from the Northern Finland Birth Cohort 1966. Obesity was defined as a body mass index of 30.0 kg/m2 or more. Psychosocial exposures were defined in terms of demands, control, and social support at work. Results: Among men, high job demands and low worksite social support were independently associated with obesity. Among women, stressrelated eating/drinking and physical inactivity seemed to promote obesity. Body mass index at age 14 was an important predictor of obesity for both sexes. Conclusions: In workplace obesity prevention programs, it might be beneficial to improve the psychosocial work environment and promote healthy behaviors simultaneously.
O
besity is a major public health concern worldwide. It is associated with a large burden of disease and has been shown to generate a high economic impact because of increased medical expenditures and lost productivity.1,2 Reducing the prevalence of obesity among employees could result in significant savings to employers and national economies. In the past three decades, the estimated global prevalence of obesity [body mass index [BMI] ≥30.0 kg/m2 ] among adults has nearly doubled from 6.4% to 12.0%.3 In Western Europe and the United States, the current prevalence estimates are 20.5% and 31.7% for men and 21.0% and 33.9% for women, respectively.4 Although the obesity epidemic in industrialized nations has temporally coincided with a change in the nature of job requirements and psychosocial work environments (ie, a shift from physical demands to mental and emotional demands),5 the association between occupational stress and obesity is unclear. Using the most prominent models on work and health (ie, the demand–control model or From the Finnish Institute of Occupational Health (Dr J¨aa¨ skel¨ainen, Dr KailaKangas, Dr Leino-Arjas, Dr Lindbohm, Ms Nevanper¨a, Mr Remes, and Dr Laitinen), Helsinki; Biocenter Oulu and Institute of Health Sciences (Dr J¨arvelin), University of Oulu; Department of Children and Young People and Families (Dr J¨arvelin), National Institute for Health and Welfare, Oulu, Finland; and Department of Epidemiology and Biostatistics (Dr J¨arvelin), MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, UK. The study was supported by the SalWe Research Programme for Mind and Body (Tekes—the Finnish Funding Agency for Technology and Innovation grant 1104/10) and by EurHEALTHAgeing 277849 (Dr J¨arvelin). Authors J¨aa¨ skel¨ainen, Kaila-Kangas, Leino-Arjas, Lindbohm, Nevanper¨a, Remes, J¨arvelin, and Laitinen have no relationships/conditions/circumstances that present potential conflict of interest. The JOEM editorial board and planners have no financial interest related to this research. Address correspondence to: Anne J¨aa¨ skel¨ainen, PhD, Finnish Institute of Occupational Health, P. O. Box 310, FI-70101 Kuopio, Finland ([email protected]). C 2015 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0000000000000432
JOEM r Volume 57, Number 5, May 2015
Learning Objectives
r Summarize the study findings on work-related psychosocial factors and obesity in a well-characterized cohort of Finnish young adults.
r Explain the differences in work psychosocial factors associated with obesity for women versus men.
r Discuss the findings related to adolescent body mass index/obesity in both sexes.
the effort–reward imbalance model), some studies have reported a positive relationship between self-reported occupational stress and BMI or weight gain6,7 whereas others have not found an association between these factors.7,8 Furthermore, sex differences have been reported.9 In a fairly recent meta-analysis, which included pooled data from 13 European cohorts, the associations of both baseline BMI and weight gain with work stress were relatively modest.10 The mixed findings on the association between occupational stress and obesity might be due to variation in the assessment and definition of psychosocial exposures between studies, and small sample size and low statistical power in many of the studies.7,10,11 According to Solovieva and colleagues,11 cohort studies taking into account baseline BMI are required to examine the causal effect of workrelated factors on weight gain and obesity. In addition, the inclusion of covariates in the analyses should be justified.11 In attempts to understand the impact of occupational stress on health, the job demand–control model is one of the most widely used theoretical frameworks.12 According to the job demand–control model, job strain arises when a job involves high psychological demands but provides little control over work (ie, low in decision latitude).13 The model was later extended by the addition of workplace social support as a third dimension. Indeed, as psychological pressure at work increases, the importance of social support might become more evident.14 Low social support per se has been associated with obesity-related lifestyles, such as poor quality of diet and physical inactivity.15,16 Although Brunner et al6 found a dose– response relationship between worksite social support and both BMI and waist circumference among men and women, reports also exist of statistically insignificant associations between worksite social support and BMI.17 In addition to psychosocial factors, there is evidence that the general increase in the prevalence of sedentary work (ie, decreased physical activity at work) has contributed to the currently high prevalence of obesity.18 . Conversely, a high level of occupational physical activity is associated with a decreased risk of obesity.19 For example, B¨ockerman and colleagues20 estimated BMI to be 2.4% lower among males in a physically very demanding occupation than among those with a sedentary job. Nevertheless, some studies have found no relationship between physical workload and obesity.21 To cope with occupational stressors, individuals may use passive coping strategies including smoking, drinking alcoholic 485
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beverages, and eating energy-dense foods.22,23 Furthermore, the risk of physical inactivity seems to be higher among employees in highstrain jobs.24 Thus, obesity-promoting behaviors may mediate the association between occupational stressors and weight gain. Similarly, low social class and low socioeconomic status have been associated with an increased risk of both obesity and job strain vulnerability.25,26 In this study, we used data from a large birth cohort to examine associations between occupational psychosocial factors defined by job demands, job control and social support at work, and obesity (BMI ≥30.0 kg/m2 ) stratified by sex. We also studied whether BMI at 14 years of age, physical strenuousness of work, basic education level, and adverse health behaviors (ie, stress-related eating, low leisure-time physical activity, smoking, and increased alcohol consumption) modify the associations between occupational psychosocial factors and obesity.
METHODS Study Population We conducted cross-sectional analyses using data from the population-based Northern Finland Birth Cohort 1966. Northern Finland Birth Cohort 1966 consists of mothers and their children who were due to be born in the provinces of Oulu and Lapland between January 1, 1966, and December 31, 1966. The participants were recruited and longitudinally followed up (at 1, 14, and 31 years of age) as described previously.27,28 A total of 12,058 infants (96% of births in the region) were born alive. In 1980, postal questionnaires were sent to the 14-year-olds who were alive and had known addresses (n = 11,764) and, in the case of nonresponse, to their parents. Data were received from 11,010 subjects. At the 31-year follow-up in 1997, the number of people (offspring) alive and traced was 11 541, and data were collected via postal and computer-based questionnaires and clinical examinations. Altogether 8767 subjects (response rate 76%) returned the postal questionnaire. Those who lived in northern Finland or in the capital region of Finland (n = 8463) were invited to a clinical examination, and 6033 (71% of those invited) participated. Alongside the clinical examinations, participants filled in an additional computer-based (or alternatively paper-based) questionnaire (n = 5737, response rate 68%). In this study, analyses are based on the individuals who gave permission to use their data and who reported being currently employed or self-employed (n = 4275). After exclusion of those for whom data on all study variables were not available or who reported being pregnant, the number of subjects was 3853. The flow chart in Fig. 1 summarizes the selection of the final study population. The study was approved by the Ethics Committee of the Finnish Institute of Occupational Health and by the Ethics Committee of the Faculty of Medicine, University of Oulu. Each participant gave written informed consent according to the Declaration of Helsinki.
Measurement of BMI At the clinical examination, trained nurses took anthropometric measurements including height in centimeters and weight in kilograms to one decimal place. Body mass index at 31 years was calculated as weight/height2 and was classified using the World Health Organization criteria as follows: nonobese less than 30.0 kg/m2 and obese 30.0 kg/m2 or more.29 On the basis of self-reported data on height and weight collected at 14-year follow-up, BMI at 14 years was calculated similarly. To examine the transition from normal weight status at age 14 years to obesity at age 31 years, participants were classified as normal weight/underweight or overweight/obese at 14 years according to the International Obesity Task Force age486
FIGURE 1. Flow chart of the Northern Finland Birth Cohort 1966 data collection and selection of study population. and gender-specific BMI cutoff values.30 Else, BMI at 14 years was used as a continuous variable in the analyses.
Occupational Psychosocial Factors In this study, job control and job demand measures were derived from the Job Content Questionnaire31 and the responses were given on a five-point scale, as previously described.32 Job control (control over work) was measured by questions concerning skill discretion, vocational proficiency, authority to make decisions, and opportunities to participate in decision-making. Job demands (psychological demands of work) were addressed with questions covering qualitative aspects, such as demands for attentiveness or precision. Perceived social support at work was measured using the following (four) questions: “If you had long-term stressful problems in interpersonal relations, mental health or work, how much mental support would you get through listening and advice from your co-worker (or your supervisor)?” and “If you were in a difficult situation that you could not cope with on your own (eg, arranging child care, lack of money, and insurmountable problem with work), how much practical help would you get from your coworker (or your supervisor)?” The social support sum score was based on responses on a five-point scale (“a lot,” ”quite a lot,” “some,” “a little,” and “not at all or I do not want support”). The items on social support at work are based on a theoretical framework arising from the evidence for the role of social support in health and well-being.13,32,33
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Psychosocial Factors at Work and Obesity Among Young Finnish Adults
The scales of job demands comprised 11 items (Cronbach α = 0.86), job control 13 items (α = 0.84), and worksite social support four items (α = 0.82). The scores for job control, demands, and social support were divided into sex-specific tertile groups (low, moderate, and high). The scores for job control and job demands were also dichotomized at the median value for men and women separately. Participants with a high level of job demands (above the median) and a low level of job control (below the median) were presumed to be at risk of job strain. All other combinations of job demand and control levels were defined as nonjob strain.
Covariates Physical strenuousness of work was assessed using the question “How strenuous is your work at present?” with six response alternatives: (1) “sedentary work including only light manual tasks,” (2) “sedentary work including some handling of moderately heavy objects,” (3) “standing work without handling heavy loads,” (4) “standing work including bending and carrying moderately heavy loads or a lot of walking,” (5) “standing work with continuous lifting of light objects or occasional lifting of heavy objects” and (6) “standing work with continuous strenuous motions and often for a long time.” The job types were respectively renamed and the latter two categories were combined as follows: (1) sedentary, light; (2) sedentary, moderate; (3) standing, light; (4) standing, moderate; and (5) standing, strenuous. Alcohol consumption was measured in terms of grams of ethanol consumed per day and was divided into sex-specific quartiles. Alcohol use was assessed as the average frequency of consumption of beer, wine, and spirits during the last year, and the usual amount of each consumed on one occasion. The amount of alcohol consumed per day was calculated using the following estimates of alcohol content per portion (vol%): beer 4.8, light wines 5.0, strong wines 14.5, and spirits 37.0, and the information was validated against 7-day food diaries.34 Stress-related eating and drinking behavior was assessed using the item “Recall the most stressful matter, event, or situation that you have experienced in the past month. Did you try to make things easier by eating, drinking or taking medicines?” The response categories “somewhat,” “quite a lot,” and “a lot” were combined into “yes,” whereas “not at all” was considered “no.” Vigorous leisure-time physical activity was measured by asking “How often in your leisure time do you exercise to the point of sweating and getting at least slightly out of breath?” and was classified as “two to seven times a week,” “once a week,” and “less than weekly.” The smoking status categories “never smoked,” “ex-smoker,” “occasionally,” and “regularly” were based on the responses to the questions “Have you ever smoked in your life?” “Have you ever smoked regularly?” and “Do you currently smoke?” Basic education level was defined as either having passed or not having passed the Finnish matriculation examination, taken typically after 12 years of schooling. Marital status was categorized as “married or cohabiting” and “single” (unmarried/judicially separated/divorced/widowed).
Statistical Analyses All analyses were sex-stratified. We used logistic regression analysis to determine the associations between occupational factors and obesity (BMI ≥30.0 kg/m2 ). Every regression model included job demands, job control, and worksite social support to observe the effects of covariate adjustments. The covariates were selected by the authors on the basis of research literature and were simultaneously entered into the models. We present both crude and adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) from logistic regression analysis. In addition, we report the characteristics of the study population as frequencies and percentages, and, for continuous variables, as means and standard deviations (SDs).
Pearson chi-square test was used to study differences between obese and nonobese subjects. We performed statistical analyses using SAS (version 9.2, SAS Institute Inc, Cary, NC) and IBM SPSS Statistics for Windows (version 19.0, IBM Corp, Armonk, NY). The logistic regression models were fitted to the data using the LOGISTIC procedure of the SAS software package. Missing values for BMI at 14 years (n = 326; men 8.9% and women 7.4%) were replaced by the median value of the variable (19.1 for both males and females), whereas an additional category was created for missing data on stress-related eating and drinking behavior (n = 505; men 16.2% and women 8.9%).
RESULTS In the whole study population, the mean BMI at 31 years of age was 25.2 kg/m2 for men and 23.9 kg/m2 for women. The prevalence of obesity at age 31 years was 8.2% for men and 7.8% for women. Light sedentary (29%) and strenuous standing (26%) jobs were almost equally common types of work among all men, whereas 35% of all women had light sedentary jobs and 15% reported high physical workload (ie, strenuous standing). A higher level of basic education was more common among women (51%) than among men (27%). With regard to health behaviors, mean alcohol consumption was higher among men (13.2 g/d) than among women (5.3 g/d), whereas stress-related eating or drinking behavior was more prevalent among women (31%) than among men (23%). As shown in Table 1, job strain as a dichotomized variable was similarly distributed among the obese and nonobese participants in both sexes, thus the separate examination of job demands and control was justified. For both men and women who were not obese at age 31 years, the mean value of BMI at age 14 years was 19.1 (SD, 2.0) kg/m2 . Among obese men and women, the average adolescent BMI values were 22.0 (SD, 3.2) kg/m2 and 22.6 (SD, 3.2) kg/m2 , respectively. The results of logistic regression analysis for men are presented in Table 2. After adjusting for all covariates, significant associations remained for high job demands (OR, 2.01; 95% CI, 1.22 to 3.34) and low social support at work (OR, 1.76; 95% CI, 1.13 to 2.75). Lower level of basic education, higher BMI at 14 years, lowest and highest levels of alcohol consumption, and vigorous leisure-time exercise once a week were also associated with obesity among men. The ORs for high job demands increased after adjustment for basic education level and the physical strenuousness of work (model 1) and BMI at 14 years (model 3), but the adjustment for health behaviors had no essential effect on this risk estimate (model 2). Among the covariates, lower basic education level, moderately strenuous sedentary work, BMI at 14 years, being in the highest quartile group of alcohol consumption, and stress-related eating and drinking behavior were related to obesity among men before any adjustments. The associations between obesity and health behaviors were modified by the inclusion of BMI at 14 years in the analysis (model 3), particularly regarding alcohol consumption. Among women (Table 3), the only work-related determinant associated with obesity was job control (ie, a moderate level of job control was related to a decreased risk of obesity in unadjusted analysis and models 1 and 2). In the fully adjusted model, the greatest odds for obesity were related to infrequent vigorous leisure-time physical activity (ie, once a week and less than weekly) (OR, 2.52; 95% CI, 1.45 to 4.39; and OR, 3.36; 95% CI, 2.02 to 5.59; respectively). Compared with men, the OR related to BMI at 14 years was slightly higher whereas the OR related to a low level of basic education was somewhat lower for women (men: OR, 1.58; 95% CI, 1.47 to 1.70; and OR, 1.89; 95% CI, 1.19 to 3.01; women: OR, 1.74; 95% CI, 1.60 to 1.90; and OR, 1.63; 95% CI, 1.05 to 2.52, respectively). Finally, a statistically significant association between stress-related eating and drinking behavior and an increased risk of obesity was seen among women but not among men.
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TABLE 1. Characteristics of the Northern Finland Birth Cohort 1966 Stratified by Obesity Men
Psychosocial factors at work Job demands Low Moderate High Job control Low Moderate High Job strain (high demands, low control) No Yes Social support at work High Moderate Low Covariates Physical strenuousness of work Sedentary, light Sedentary, moderate Standing, light Standing, moderate Standing, strenuous Basic education Matriculation examination No matriculation examination Marital status Married/cohabiting Single Smoking Never smoked Ex-smoker Occasionally Regularly Alcohol consumption, men/women, g/d 0–2.7/0–0.8 2.8–7.7/0.9–2.8 7.8–16.2/2.9–6.4 >16.2/>6.4 Vigorous leisure-time exercise Two to seven times a week Once a week Less than weekly Stress-related eating or drinking No Yes Missing
488
Women
Nonobese n = 1911
Obese n = 172
Nonobese n = 1634
Obese n = 136
34.8 35.6 29.6
29.7 32.0 38.3
0.056
33.0 31.5 35.5
31.6 33.8 34.6
0.847
35.3 31.7 33.0
35.5 27.9 36.6
0.519
31.9 35.0 33.1
39.0 26.5 34.5
0.098
87.3 12.7
84.9 15.1
0.358
80.3 19.7
86.8 13.2
0.066
38.0 40.5 21.5
30.8 37.8 31.4
0.009
32.3 30.2 37.5
34.5 30.2 35.3
0.835
30.2 10.2 13.3 20.6 25.7
26.7 15.7 12.2 19.2 26.2
0.237
37.0 6.7 20.3 23.4 12.6
33.1 9.6 19.1 22.8 15.4
0.582
32.0 68.0
21.5 78.5
0.005
54.5 45.5
44.9 55.1
0.029
73.7 26.3
73.3 26.7
0.892
74.1 25.9
73.5 26.5
0.894
34.7 31.7 12.6 21.0
32.0 39.0 11.0 18.0
0.269
40.8 23.4 12.4 23.4
40.4 27.9 12.5 19.1
0.547
25.2 24.0 27.0 23.9
19.2 27.3 22.1 31.4
0.045
23.4 23.1 27.7 25.8
27.2 30.1 22.8 19.9
0.101
42.3 21.9 35.8
34.3 26.2 39.5
0.116
42.7 25.6 31.7
25.7 27.9 46.3
16.2 Vigorous leisure-time exercise Two to seven times a week Once a week Less than weekly Stress-related eating or drinking behavior No Yes
Unadjusted OR (95% CI)
Model 1 OR (95% CI)
Model 2 OR (95% CI)
Model 3 OR (95% CI)
Model 4 OR (95% CI)
1.00 1.06 (0.71–1.57) 1.52 (1.04–2.23)
1.00 1.16 (0.76–1.75) 1.70 (1.09–2.64)
1.00 1.17 (0.77–1.78) 1.72 (1.11–2.68)
1.00 1.41 (0.89–2.23) 2.05 (1.25–3.37)
1.00 1.39 (0.87–2.22) 2.01 (1.22–3.34)
1.00 0.88 (0.59–1.30) 1.10 (0.76–1.59)
1.00 0.88 (0.58–1.32) 1.04 (0.68–1.58)
1.00 0.89 (0.59–1.36) 1.08 (0.71–1.65)
1.00 0.85 (0.54–1.33) 1.09 (0.69–1.74)
1.00 0.84 (0.53–1.32) 1.06 (0.66–1.70)
1.00 1.15 (0.79–1.68) 1.80 (1.21–2.68)
1.00 1.20 (0.82–1.75) 1.74 (1.16–2.61)
1.00 1.18 (0.81–1.73) 1.73 (1.16–2.60)
1.00 1.05 (0.69–1.60) 1.76 (1.13–2.73)
1.00 1.06 (0.70–1.62) 1.76 (1.13–2.75)
1.00 1.72 (1.18–2.50) 1.55 (1.45–1.66)
1.00 1.88 (1.24–2.86) – (–)
1.00 1.80 (1.21–2.67) – (–)
1.00 1.83 (1.19–2.82) 1.58 (1.48–1.70)
1.00 1.89 (1.19–3.01) 1.58 (1.47–1.70)
1.00 1.75 (1.06–2.89) 1.04 (0.61–1.77) 1.06 (0.66–1.68) 1.15 (0.75–1.77)
1.00 1.50 (0.89–2.53) 0.93 (0.54–1.61) 0.89 (0.54–1.46) 0.89 (0.56–1.44)
– (–) – (–) – (–) – (–) – (–)
– (–) – (–) – (–) – (–) – (–)
1.00 1.47 (0.81–2.67) 1.05 (0.58–1.93) 0.97 (0.56–1.69) 0.89 (0.52–1.50)
1.00 1.34 (0.92–1.94) 0.95 (0.55–1.64) 0.93 (0.59–1.47)
– (–) – (–) – (–) – (–)
1.00 1.15 (0.77–1.73) 0.94 (0.54–1.64) 0.91 (0.57–1.46)
1.00 0.90 (0.57–1.41) 0.97 (0.53–1.75) 0.84 (0.50–1.39)
1.00 0.89 (0.57–1.39) 0.95 (0.52–1.73) 0.82 (0.49–1.37)
1.49 (0.94–2.37) 1.00 1.08 (0.66–1.74) 1.73 (1.10–2.71)
– (–) – (–) – (–) – (–)
1.48 (0.92–2.37) 1.00 1.15 (0.66–1.98) 1.61 (1.01–2.56)
1.66 (0.99–2.78) 1.00 1.15 (0.67–1.99) 2.09 (1.48–1.70)
1.72 (1.01–2.86) 1.00 1.15 (0.66–1.98) 2.12 (1.26–3.56)
1.00 1.65 (0.98–2.21) 1.36 (0.95–1.96)
– (–) – (–) – (–)
1.00 1.38 (0.91–1.46) 1.16 (0.80–1.70)
1.00 1.63 (1.03–2.58) 1.33 (0.88–2.02)
1.00 1.64 (1.04–2.60) 1.33 (0.88–2.02)
1.00 1.50 (1.04–2.17)
– (–) – (–)
1.00 1.54 (1.05–2.24)
1.00 1.43 (0.94–2.17)
1.00 1.42 (0.93–2.15)
Model 1: Psychosocial factors at work + basic education and physical strain at work. Model 2: Psychosocial factors at work + basic education, smoking, leisure-time exercise, alcohol consumption, and stress-related eating or drinking. Model 3: Psychosocial factors at work + basic education, BMI at 14 years of age, smoking, leisure-time exercise, alcohol consumption, and stress-related eating or drinking. Model 4: All the aforementioned variables. BMI, body mass index; CI, confidence interval; OR, odds ratio.
We conducted additional analyses using the transition from normal weight status at age 14 years to obesity at age 31 years as the outcome variable (136 men and 97 women) and observed similar associations as above (data not shown). Among men, the fully adjusted ORs for becoming obese between ages 14 and 31 years were 2.13 (95% CI, 1.26 to 3.59) when job demands were high
and 1.84 (95% CI, 1.17 to 2.89) when worksite social support was low. Job strain as a binary variable (high demands and low control vs other combinations) was not associated with obesity in any model in either sex (data not shown). For example, the unadjusted and fully adjusted ORs were 1.23 (95% CI, 0.79 to 1.10) and 1.29 (95% CI,
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TABLE 3. Associations Between Occupational Exposures and Obesity Among 31-Year-Old Finnish Women (n = 1770) Unadjusted OR (95% CI) Psychosocial factors at work Demands Low 1.00 Moderate 1.12 (0.73–1.73) High 1.02 (0.66–1.56) Control High 1.00 Moderate 0.62 (0.40–0.96) Low 0.86 (0.57–1.29) Social support at work High 1.00 Moderate 0.93 (0.60–1.45) Low 0.88 (0.58–1.34) Covariates Basic education Matriculation examination 1.00 No matriculation examination 1.47 (1.04–2.10) BMI at 14 yrs of age (continuous) 1.70 (1.57–1.85) Physical strain at work Sedentary, light 1.00 Sedentary, moderate 1.59 (0.82–3.04) Standing, light 1.05 (0.64–1.74) Standing, moderate 1.09 (0.68–1.75) Standing, strenuous 1.37 (0.80–2.35) Smoking Never smoked 1.00 Ex-smoker 1.21 (0.78–1.86) Occasionally 1.02 (0.58–1.79) Regularly 0.82 (0.51–1.34) Alcohol consumption, g/d 0–0.8 1.12 (0.70–1.79) 0.9–2.8 1.00 2.9–6.4 0.71 (0.43–1.16) >6.4 0.66 (0.40–1.11) Vigorous leisure-time exercise Two to seven times a week 1.00 Once a week 1.81 (1.13–2.92) Less than weekly 2.43 (1.58–3.72) Stress-related eating or drinking behavior No 1.00 Yes 1.60 (1.10–2.32)
Model 1 OR (95% CI)
Model 2 OR (95% CI)
Model 3 OR (95% CI)
Model 4 OR (95% CI)
1.00 1.14 (0.73–1.78) 0.97 (0.61–1.55)
1.00 1.15 (0.73–1.82) 0.96 (0.60–1.54)
1.00 1.07 (0.63–1.81) 1.10 (0.65–1.86)
1.00 1.05 (0.62–1.78) 1.10 (0.65–1.86)
1.00 0.61 (0.39–0.95) 0.81 (0.52–1.27)
1.00 0.59 (0.37–0.93) 0.79 (0.50–1.23)
1.00 0.65 (0.39–1.09) 0.87 (0.52–1.46)
1.00 0.65 (0.39–1.10) 0.84 (0.50–1.42)
1.00 0.96 (0.62–1.49) 0.86 (0.56–1.33)
1.00 0.95 (0.60–1.48) 0.78 (0.50–1.21)
1.00 1.06 (0.64–1.76) 0.83 (0.50–1.38)
1.00 1.05 (0.63–1.76) 0.83 (0.50–1.39)
1.00 1.44 (1.00–2.08) – (–)
1.00 1.42 (0.97–2.01) – (–)
1.00 1.54 (1.00–2.36) 1.73 (1.58–1.88)
1.00 1.63 (1.05–2.52) 1.74 (1.60–1.90)
1.00 1.50 (0.78–2.89) 1.03 (0.62–1.71) 1.02 (0.63–1.65) 1.24 (0.71–2.16)
– (–) – (–) – (–) – (–) – (–)
– (–) – (–) – (–) – (–) – (–)
1.00 1.08 (0.47–2.45) 0.84 (0.47–1.50) 0.87 (0.50–1.50) 0.61 (0.31–1.20)
– (–) – (–) – (–) – (–)
1.00 1.18 (0.74–1.88) 1.12 (0.62–2.03) 0.77 (0.47–1.26)
1.00 1.02 (0.60–1.76) 1.16 (0.59–2.28) 0.86 (0.50–1.48)
1.00 1.06 (0.62–1.82) 1.15 (0.58–2.27) 0.87 (0.50–1.50)
– (–) – (–) – (–) – (–)
1.15 (0.71–1.86) 1.00 0.68 (0.41–1.11) 0.59 (0.34–1.00)
1.23 (0.71–2.13) 1.00 0.86 (0.49–1.53) 0.67 (0.36–1.23)
1.25 (0.72–2.18) 1.00 0.85 (0.48–1.52) 0.65 (0.35–1.21)
– (–) – (–) – (–)
1.00 1.81 (1.12–2.92) 2.41 (1.56–3.72)
1.00 2.46 (1.42–4.28) 3.36 (2.02–5.60)
1.00 2.52 (1.45–4.39) 3.36 (2.02–5.59)
– (–) – (–)
1.00 1.69 (1.15–2.49)
1.00 1.61 (1.04–2.49)
1.00 1.62 (1.04–2.51)
Model 1: Psychosocial factors at work + basic education and physical strain at work. Model 2: Psychosocial factors at work + basic education, smoking, leisure-time exercise, alcohol consumption, and stress-related eating or drinking. Model 3: Psychosocial factors at work + basic education, BMI at 14 years of age, smoking, leisure-time exercise, alcohol consumption, and stress-related eating or drinking. Model 4: All the aforementioned variables. BMI, body mass index; CI, confidence interval; OR, odds ratio.
0.79 to 2.12) for men and 0.62 (95% CI, 0.37 to 1.04) and 0.56 (95% CI, 0.31 to 1.01) for women.
DISCUSSION Among 31-year-old men, high demands and low social support at work were independently associated with obesity, and these associations were further strengthened when the analyses were adjusted for adolescent obesity and basic education level. The results 490
suggest that high job demands at the beginning of the working career may induce physiological changes that result in weight gain. Among women, however, no associations between psychosocial work characteristics and obesity were detected. The analyses also revealed that BMI at 14 years is an important predictor of adult obesity for both men and women. Some sex similarities and differences in health behavior–obesity associations were observed: among males, alcohol consumption, and among females, stress-related eating or drinking
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Psychosocial Factors at Work and Obesity Among Young Finnish Adults
behavior, and among both sexes, infrequent leisure-time exercise seemed to be obesity-promoting factors. All in all, the main findings among women and men were strikingly different and need to be confirmed in other study populations. Because of a large proportion of 31-year-old women on maternity or childcare leave in our data (16.2% of women and 0.1% of men) and the exclusion of nonworking or pregnant individuals from the analyses, more women than men were excluded. The fact that the working women were leaner (BMI 23.9) than the nonworking women (BMI 24.5) may partly be explained by our previous finding that obese young women have difficulties entering the job market (ie, obese female adolescents were at an increased risk of a long history of unemployment at the age of 31 years in the same data as that which we used).35 In addition, we found that perceived work ability was inversely associated with waist-to-hip ratio among women.36 In fact, “the healthy worker effect” is an inherent source of selection bias in occupational epidemiological studies.37 Thus, the variation in both psychosocial exposures and obesity measures is lower in working populations and, as a result, the associations between these factors are weakened (ie, biased toward the null). Another selection mechanism is reverse causality, which arises when obese individuals are selected into unfavorable psychosocial work environments.38 It is possible that obesity affects job opportunities and performance at work and increases stress vulnerability. In addition to the selection effect, the different patterns of the associations between obesity and occupational factors and covariates for women and men could be because men and women are employed in different occupations and positions and may thus be exposed to different psychosocial and physical working conditions. In our data, substantially more women than men had passed the matriculation examination as basic education, and among men, the low basic education level was more prevalent among obese than among nonobese. These differences may explain why among men the OR related to high job demands increased when taking basic education level into account, whereas among women the associations were unaffected. Because work–family conflicts might constitute a barrier to healthy lifestyle,39 the social support that women receive from family and friends may be more important than that from colleagues and supervisors. It might also be necessary to discriminate between different dimensions of social support (eg, emotional, instrumental/tangible, and informational support). Nevertheless, the relationships may not be straightforward: among young women, low emotional support has been associated with both underweight and overweight statuses.40 Although occupational stress has been associated with adverse lifestyles, the health behaviors in this study did not mediate the effects of occupational psychosocial factors on BMI. It is noteworthy that health behaviors such as smoking habits are often established before entering work life. In addition, we cannot exclude the fact that other lifestyle-related or physiological (psychobiological) factors could explain the association between occupational stress and obesity. For instance, stress may alter the brain’s response to food and shift food choices toward energy-dense items.41,42 On the other hand, the results show the importance of controlling for earlier obesity status to prevent false-positive findings concerning work-related factors and obesity. The study has certain strengths and limitations. This population-based birth cohort study covered three occupational psychosocial hazards—high demands, low control, and low support— adjusted for several covariates known to be related to BMI and which potentially mediate and explain the effects of job characteristics. Weight and height at 31 years of age were clinically measured, whereas all other data, including weight and height at 14 years, were self-reported. The subset of the cohort members who participated in the clinical examination at the 31-year follow-up has shown to be well-representative of the original study population.28 The rate of unemployment in this study population was approximately equal to
that of Finns in general,43 and the prevalence of obesity corresponded to that observed among young Finnish adults.44 Nevertheless, as the participants were young adults, the results cannot be generalized to all age groups. As the data analysis was cross-sectional, no causal inferences can be drawn. Nevertheless, the observed associations were similar in our additional analyses where the development of obesity (transition from normal weight at age 14 years to obesity at age 31 years) was used as the outcome variable. This implies that early obesity cannot have influenced the associations. It can also be postulated that job stress–obesity relationships may become more evident in later life because such associations were detected already among 31-year-old men at the early stages of their careers.
CONCLUSIONS High demands and low social support at work were robustly associated with an increased risk of obesity among men, and the association between job demands and obesity was further strengthened by adjustments for adolescent obesity and basic education level. Among women, individual behavioral factors such as stress-related eating or drinking behavior and infrequent exercise outweighed occupational stressors as determinants of obesity. On the basis of the results, it could be hypothesized that in workplace health promotion to prevent obesity it is important to improve the psychosocial work environment as well as promote healthy behaviors. Considering the public health burden of obesity, this hypothesis deserves further investigation in intervention settings.
ACKNOWLEDGMENTS We thank the late Professor Paula Rantakallio for the initiation of the Northern Finland Birth Cohort study project and Ms Alice Lehtinen for editing the language in the article.
REFERENCES 1. Schmier JK, Jones ML, Halpern MT. Cost of obesity in the workplace. Scand J Work Environ Health. 2006;32:5–11. 2. Finkelstein EA, DiBonaventura MD, Burgess SM, Hale BC. The costs of obesity in the workplace. J Occup Environ Med. 2010;52:971–976. 3. Stevens GA, Singh GM, Lu Y, et al. National, regional, and global trends in adult overweight and obesity prevalences. Popul Health Metr. 2012;10:22. 4. Ng M, Fleming T, Robinson M, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:766–781. 5. Johnson JV. Globalization, workers’ power and the psychosocial work environment—is the demand-control model still useful in a neoliberal era? Scand J Environ Health. 2008;6(suppl):15–21. 6. Brunner EJ, Chandola T, Marmot MG. Prospective effect of job strain on general and central obesity in the Whitehall II Study. Am J Epidemiol. 2007;165:828–837. 7. Siegrist J, R¨odel A. Work stress and health risk behavior. Scand J Work Environ Health. 2006;32:473–481. 8. Lallukka T, Sarlio-L¨ahteenkorva S, Kaila-Kangas L, Pitk¨aniemi J, Luukkonen R, Leino-Arjas P. Working conditions and weight gain: a 28-year follow-up study of industrial employees. Eur J Epidemiol 2008;23:303–310. 9. Ostry AS, Radi S, Louie AM, LaMontagne AD. Psychosocial and other working conditions in relation to body mass index in a representative sample of Australian workers. BMC Public Health. 2006;6:53. 10. Nyberg ST, Heikkil¨a K, Fransson EI, et al. Job strain in relation to body mass index: pooled analysis of 160 000 adults from 13 cohort studies. J Intern Med. 2012;272:65–73. 11. Solovieva S, Lallukka T, Virtanen M, Viikari-Juntura E. Psychosocial factors at work, long work hours, and obesity: a systematic review. Scand J Work Environ Health. 2013;39:241–258. 12. Karasek RA. Job demands, job decision latitude, and mental strain: implications for job redesign. Adm Sci Q. 1979;24:285–308. 13. Karasek RA, Theorell T. Healthy Work: Stress, Productivity and the Reconstruction of Working Life. New York: Basic Books; 1990.
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14. Falk A, Hanson BS, Isacsson SO, Ostergren PO. Job strain and mortality in elderly men: social network, support, and influence as buffers. Am J Public Health. 1992;82:1136–1139. 15. Eyler AA, Brownson RC, Donatelle RJ, King AC, Brown D, Sallis JF. Physical activity social support and middle- and older-aged minority women: results from a US survey. Soc Sci Med. 1999;49:781–789. 16. Shaikh AR, Yaroch AL, Nebeling L, Yeh MC, Resnicow K. Psychosocial predictors of fruit and vegetable consumption in adults: a review of the literature. Am J Prev Med. 2008;34:535–543. 17. Tamers SL, Beresford SA, Cheadle AD, Zheng Y, Bishop SK, Thompson B. The association between worksite social support, diet, physical activity and body mass index. Prev Med. 2011;53:53–56. 18. Church TS, Thomas DM, Tudor-Locke C, et al. Trends over 5 decades in U.S. occupation-related physical activity and their associations with obesity. PLoS One. 2011;6:e19657. 19. King GA, Fitzhugh EC, Bassett DR Jr, et al. Relationship of leisure-time physical activity and occupational activity to the prevalence of obesity. Int J Obes Relat Metab Disord. 2001;25:606–612. 20. B¨ockerman P, Johansson E, Jousilahti P, Uutela A. The physical strenuousness of work is slightly associated with an upward trend in the BMI. Soc Sci Med. 2008;66:1346–1355. 21. Nishitani N, Sakakibara H. Relationship of obesity to job stress and eating behavior in male Japanese workers. Int J Obes (Lond). 2006;30:528–533. 22. Lindquist TL, Beilin LJ, Knuiman MW. Influence of lifestyle, coping, and job stress on blood pressure in men and women. Hypertension. 1997;29:1–7. 23. Laitinen J, Ek E, Sovio U. Stress-related eating and drinking behavior and body mass index and predictors of this behavior. Prev Med. 2002;34:29–39. 24. Fransson EI, Heikkil¨a K, Nyberg ST, et al. Job strain as a risk factor for leisure-time physical inactivity: an individual-participant meta-analysis of up to 170,000 men and women: the IPD-Work Consortium. Am J Epidemiol. 2012;176:1078–1089. 25. McLaren L. Socioeconomic status and obesity. Epidemiol Rev. 2007;29: 29–48. 26. Cho SI, Eum KD, Choi BK, Paek D, Karasek R. Social class, job insecurity and job strain in Korea. Scand J Work Environ Health. 2008;6(suppl):60–65. 27. Rantakallio P. The longitudinal study of the Northern Finland Birth Cohort of 1966. Paediatr Perinat Epidemiol. 1988;2:59–88. 28. Sovio U, King V, Miettunen J, et al. Cloninger’s Temperament dimensions, socio-economic and lifestyle factors and metabolic syndrome markers at age 31 years in the Northern Finland Birth Cohort 1966. J Health Psychol. 2008;12:371–382. 29. World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:1–253.
492
30. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000;320:1240–1243. 31. Karasek RA, Brisson C, Kawakami N, Houtman I, Bongers P, Amick B. The Job Content Questionnaire (JCQ): an instrument for internationally comparative assessments of psychological job characteristics. J Occup Health Psychol. 1998;3:322–355. 32. Kujala V, Tammelin T, Remes J, Vammavaara E, Ek E, Laitinen J. Work ability index of young employees and their sickness absence during the following year. Scand J Work Environ Health. 2006;32:75–84. 33. Sarason IG, Pierce GR, Sarason BR. Social support and interactional processes: a triadic hypothesis. J Soc Pers Relat. 1990;7:495– 506. 34. Laitinen J, Pietil¨ainen K, Wadsworth M, Sovio U, J¨arvelin MR. Predictors of abdominal obesity among 31-y-old men and women born in Northern Finland in 1966. Eur J Clin Nutr. 2004;58:180–190. 35. Laitinen J, Power C, Ek E, Sovio U, J¨arvelin MR. Unemployment and obesity among adults in a northern Finland 1966 birth cohort. Int J Obes Relat Metab Disord. 2002;26:1329–1338. 36. Laitinen J, N¨ayh¨a S, Kujala V. Body mass index and weight change from adolescence into adulthood, waist-hip ratio and perceived work ability among young adults. Int J Obes (Lond). 2005;29:697–702. 37. Pearce N, Checkoway H, Kriebel D. Bias in occupational epidemiology studies. Occup Environ Med. 2007;64:562–568. 38. Wilcosky T, Wing S. The healthy worker effect. Selection of workers and work forces. Scand J Work Environ Health 1987;13:70–72. 39. Roos E, Sarlio-L¨ahteenkorva S, Lallukka T, Lahelma E. Associations of workfamily conflicts with food habits and physical activity. Public Health Nutr. 2007;10:222–229. 40. Ali SM, Lindstr¨om M. Socioeconomic, psychosocial, behavioural and psychological determinants of BMI among young women: differing patterns for underweight and overweight/obesity. Eur J Public Health. 2006;16: 325–331. 41. Wardle J, Steptoe A, Oliver G, Lipsey Z. Stress, dietary restraint and food intake. J Psychosom Res. 2000;48:195–202. 42. Tryon MS, Carter CS, Decant R, Laugero KD. Chronic stress exposure may affect the brain’s response to high calorie food cues and predispose to obesogenic eating habits. Physiol Behav. 2013;120C:233–242. 43. Statistics Finland. Statistical Yearbook of Finland 2000. Helsinki; 2000: 355–356. 44. Lahti-Koski M, Vartiainen E, M¨annist¨o S, Pietinen P. Age, education and occupation as determinants of trends in body mass index in Finland from 1982 to 1997. Int J Obes Relat Metab Disord. 2000;24:1669– 1676.
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