OBJECTIVE: To examine the validity of self-reported weight and height and the resulting body mass index (BMI), and to explore the associations between demographic, socioeconomic, and health-related factors on the one hand and bias in self-reported weight and height on the other, in order to determine the groups most likely to exhibit bias. DESIGN: Prospective cohort study. SUBJECTS: 7350 middle-aged subjects, 5445 men and 1905 women, from the GAZEL cohort, who have been followed up since 1989 and work at the French national company Electricite  De France ± Gaz De France (EDF-GDF) in various occupations. MEASUREMENTS: Self-reported weight and height were based on information from yearly mailed questionnaires, and measured weight and height, used here as true values, were provided by occupational physicians from 1994 to 1997. Sex, age, marital status, education, occupation, history of ischemic heart disease, and treatment for cardiovascular risk factors were obtained from the mailed questionnaires or from data provided by the Company's personnel and medical departments. RESULTS: Strong correlations were found between measured and self-reported values, but self-reported weight and height displayed signi®cant systematic errors. Weight was signi®cantly underestimated for men (0.54 kg) and for women (0.85 kg), and height overestimated for men (0.38 cm) and women (0.40 cm). These biases led to signi®cant underestimations of BMI (0.29 and 0.44 kgam 2 for men and women respectively). Consequently, the prevalence of overweight, de®ned as BMI b 26.9 kgam 2 for women and BMI b 27.2 kgam 2 for men, was also underestimated, by 13% for men and 17% for women. The ®ve factors associated with bias in self-reported weight and height were: overweight status, end-digit preference, age, educational level and occupation. CONCLUSION: These ®ndings suggest that self-reported weight and height should be treated with caution, because of biases leading to misclassi®cation for overweight and obesity, especially in certain segments of the population.

Unfavorable work characteristics, such as low job control and too high or too low job demands, have been suggested to increase the likelihood of physical inactivity during leisure time, but this has not been verified in large-scale studies. The authors combined individual-level data from 14 European cohort studies (baseline years from 1985–1988 to 2006–2008) to examine the association between unfavorable work characteristics and leisure-time physical inactivity in a total of 170,162 employees (50% women; mean age, 43.5 years). Of these employees, 56,735 were reexamined after 2–9 years. In cross-sectional analyses, the odds for physical inactivity were 26% higher (odds ratio = 1.26, 95% confidence interval: 1.15, 1.38) for employees with high-strain jobs (low control/high demands) and 21% higher (odds ratio = 1.21, 95% confidence interval: 1.11, 1.31) for those with passive jobs (low control/low demands) compared with employees in low-strain jobs (high control/low demands). In prospective analyses restricted to physically active participants, the odds of becoming physically inactive during follow-up were 21% and 20% higher for those with high-strain (odds ratio = 1.21, 95% confidence interval: 1.11, 1.32) and passive (odds ratio = 1.20, 95% confidence interval: 1.11, 1.30) jobs at baseline. These data suggest that unfavorable work characteristics may have a spillover effect on leisure-time physical activity.

The purpose of this paper is to examine personal and health factors, both at the beginning of the study and thereafter, associated with participation in the GAZEL cohort, set up in 1989 in a large French company. The authors used logistic regression to analyze the associations between participation and data available for both participants (n = 20,093) and nonparticipants (n = 24,829). Higher participation was associated with male sex, marriage, children, managerial status, and residence in particular regions. Among men, lower participation was associated with sick leave in the year before recruitment and afterwards. During follow-up, participation was negatively associated with several groups of diseases, especially those associated with alcohol consumption. The risk of upper respiratory and digestive tract and lung cancer during follow-up was higher among nonparticipants. The same phenomenon occurred among women, but less markedly, for cancers of the breast and genital organs. During follow-up, mortality among men was higher among nonparticipants, especially for alcohol-related diseases. The association among women was less strong. Among men, but not among women, diseases caused by alcohol, smoking, or dangerous behavior were the primary reason for the health differences observed between participants and nonparticipants. Overall, the most important determinants of participation were cultural factors and lifestyle behaviors.

EDF-GDF) is the only utility firm in France involved in production, transmission and distribution of energy. For several reasons, EDF-GDF is a unique setting for epidemiology. The company employs about 150,000 workers in all regions of France, from large cities to small villages; there is a wide socioeconomic range of occupational positions, including white and blue-collars workers. The workforce is very stable due to their civil servant-like status, employees almost never leave the company and are not lost to follow-up even after retirement, since retirement benefits are paid by the company itself. An extensive human resources system allows for a complete follow-up of the workers, even when they retire. EDF-GDF has its own Occupational Health and Social Security system; about 300 physicians work for the company and are responsible for the health surveillance of the workers.During the seventies the medical department of EDF-GDF decided to build a comprehensive data base on the health of the workforce. The data base was designed in close collaboration with researchers at INSERM -the French National Institute for Health and Medical Research -Research Unit 88, directed at that time by one of us who was also a Scientific advisor for the medical department of the company (MG). The data base contained demographic, socioeconomic and professional data on each worker. An exhaustive register of sick leave, accidents, permanent disabilities, compensated diseases, causes of death, cancer and coronary heart disease incidence among active workers was created. Further, a jobexposure matrix was established for 30 potentially carcinogenic agents 1,2 . Using these data bases several epidemiological studies on working accidents, sick leave, cancer and mortality were carried out [3][4][5][6][7][8] . However the absence of individual level data on lifestyle, self-reported

BackgroundJob strain (i.e., high job demands combined with low job control) is a frequently used indicator of harmful work stress, but studies have often used partial versions of the complete multi-item job demands and control scales. Understanding whether the different instruments assess the same underlying concepts has crucial implications for the interpretation of findings across studies, harmonisation of multi-cohort data for pooled analyses, and design of future studies. As part of the 'IPD-Work' (Individual-participant-data meta-analysis in working populations) consortium, we compared different versions of the demands and control scales available in 17 European cohort studies.MethodsSix of the 17 studies had information on the complete scales and 11 on partial scales. Here, we analyse individual level data from 70 751 participants of the studies which had complete scales (5 demand items, 6 job control items).ResultsWe found high Pearson correlation coefficients between complete scales of job demands and control relative to scales with at least three items (r > 0.90) and for partial scales with two items only (r = 0.76-0.88). In comparison with scores from the complete scales, the agreement between job strain definitions was very good when only one item was missing in either the demands or the control scale (kappa > 0.80); good for job strain assessed with three demand items and all six control items (kappa > 0.68) and moderate to good when items were missing from both scales (kappa = 0.54-0.76). The sensitivity was > 0.80 when only one item was missing from either scale, decreasing when several items were missing in one or both job strain subscales.ConclusionsPartial job demand and job control scales with at least half of the items of the complete scales, and job strain indices based on one complete and one partial scale, seemed to assess the same underlying concepts as the complete survey instruments.

Nyberg ST, Heikkilä K, Fransson EI, Alfredsson L, De Bacquer D, Bjorner JB, Bonenfant S, Borritz M, Burr H, Casini A, Clays E, Dragano N, Erbel R, Geuskens GA, Goldberg M, Hooftman WE, Houtman IL, Jöckel K-H, Kittel F, Knutsson A, Koskenvuo M, Leineweber C, Lunau T, Madsen IEH, Magnusson Hanson LL, Marmot MG, Nielsen ML, Nordin M, Oksanen T, Pentti J, Rugulies R, Siegrist J, Suominen S, Vahtera J, Virtanen M, Westerholm P, Westerlund H, Zins M, Ferrie JE, Theorell T, Steptoe A, Hamer M, Singh-Manoux A, Batty GD, Kivimäki M, for the IPD-Work Consortium (Finnish Institute of Occupational Health, Helsinki, Finland; Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Jönköping University, Jönköping, Sweden; Ghent University, Ghent, Belgium; National Research Centre for the Working Environment, Copenhagen, Denmark; Versailles-Saint Quentin University, Versailles, France; Centre for Research in Epidemiology and Population Health, Villejuif, France; Bispebjerg University Hospital, Copenhagen, Denmark; Centre for Maritime Health and Safety, Esbjerg, Denmark; Université Libre de Bruxelles, Brussels, Belgium; University Duisburg-Essen, Essen, Germany; West-German Heart Center Essen, University Duisburg-Essen, Essen, Germany; TNO, Hoofddorp, the Netherlands; Mid Sweden University, Sundsvall, Sweden; University of Helsinki, Helsinki, Finland; Stockholm University, Stockholm, Sweden; University College London, London, UK; Bispebjerg University Hospital, Copenhagen, Denmark; Umeå University, Umeå, Sweden; Finnish Institute of Occupational Health, Turku, Finland; Harvard School of Public Health, Boston, MA, USA; University of Copenhagen, Copenhagen, Denmark; University of Düsseldorf, Düsseldorf, Germany; University of Turku, Turku; Folkhälsan Research Center, Helsinki; Turku University Hospital, Turku, Finland; Uppsala University, Uppsala; Karolinska Institutet, Stockholm, Sweden; University of Bristol, Bristol; University of Edinburgh, Edinburgh, UK; and University of Helsinki, Helsinki, Finland). 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.BackgroundEvidence of an association between job strain and obesity is inconsistent, mostly limited to small-scale studies, and does not distinguish between categories of underweight or obesity subclasses.ObjectivesTo examine the association between job strain and body mass index (BMI) in a large adult population.MethodsWe performed a pooled cross-sectional analysis based on individual-level data from 13 European studies resulting in a total of 161 746 participants (49% men, mean age, 43.7 years). Longitudinal analysis with a median follow-up of 4 years was possible for four cohort studies (n = 42 222).ResultsA total of 86 429 participants were of normal weight (BMI 18.5–24.9 kg m−2), 2149 were underweight (BMI < 18.5 kg m−2), 56 572 overweight (BMI 25.0–29.9 kg m−2) and 13 523 class I (BMI 30–34.9 kg m−2) and 3073 classes II/III (BMI ≥ 35 kg m−2) obese. In addition, 27 010 (17%...

Objective To investigate whether work related stress, measured and defined as job strain, is associated with the overall risk of cancer and the risk of colorectal, lung, breast, or prostate cancers.Design Meta-analysis of pooled prospective individual participant data from 12 European cohort studies including 116 056 men and women aged 17-70 who were free from cancer at study baseline and were followed-up for a median of 12 years. Work stress was measured and defined as job strain, which was self reported at baseline. Incident cancers (all n=5765, colorectal cancer n=522, lung cancer n=374, breast cancer n=1010, prostate cancer n=865) were ascertained from cancer, hospital admission, and death registers. Data were analysed in each study with Cox regression and the study specific estimates pooled in meta-analyses. Models were adjusted for age, sex, socioeconomic position, body mass index (BMI), smoking, and alcohol intake Results A harmonised measure of work stress, high job strain, was not associated with overall risk of cancer (hazard ratio 0.97, 95% confidence interval 0.90 to 1.04) in the multivariable adjusted analyses. Similarly, no association was observed between job strain and the risk of colorectal (1.16, 0.90 to 1.48), lung (1.17, 0.88 to 1.54), breast (0.97, 0.82 to 1.14), or prostate (0.86, 0.68 to 1.09) cancers. There was no clear evidence for an association between the categories of job strain and the risk of cancer.Conclusions These findings suggest that work related stress, measured and defined as job strain, at baseline is unlikely to be an important risk factor for colorectal, lung, breast, or prostate cancers.

BackgroundTobacco smoking is a major contributor to the public health burden and healthcare costs worldwide, but the determinants of smoking behaviours are poorly understood. We conducted a large individual-participant meta-analysis to examine the extent to which work-related stress, operationalised as job strain, is associated with tobacco smoking in working adults.Methodology and Principal Findings We analysed cross-sectional data from 15 European studies comprising 166 130 participants. Longitudinal data from six studies were used. Job strain and smoking were self-reported. Smoking was harmonised into three categories never, ex- and current. We modelled the cross-sectional associations using logistic regression and the results pooled in random effects meta-analyses. Mixed effects logistic regression was used to examine longitudinal associations. Of the 166 130 participants, 17% reported job strain, 42% were never smokers, 33% ex-smokers and 25% current smokers. In the analyses of the cross-sectional data, current smokers had higher odds of job strain than never-smokers (age, sex and socioeconomic position-adjusted odds ratio: 1.11, 95% confidence interval: 1.03, 1.18). Current smokers with job strain smoked, on average, three cigarettes per week more than current smokers without job strain. In the analyses of longitudinal data (1 to 9 years of follow-up), there was no clear evidence for longitudinal associations between job strain and taking up or quitting smoking.ConclusionsOur findings show that smokers are slightly more likely than non-smokers to report work-related stress. In addition, smokers who reported work stress smoked, on average, slightly more cigarettes than stress-free smokers.