This cohort study examines disease-free life-years in participants with varying combinations of lifestyle risk factors. Question Are different combinations of lifestyle factors associated with years lived without chronic diseases? Findings In a multicohort study of 116 & x202f;043 participants, a statistically significant association between overall healthy lifestyle score and an increased number of disease-free life-years was noted. Of 16 different lifestyle profiles studied, the 4 that were associated with the greatest disease-free life years included body mass index lower than 25 and at least 2 of 3 factors: never smoking, physical activity, and moderate alcohol consumption. Meaning Various healthy lifestyle profiles appear to be associated with extended gains in life lived without type 2 diabetes, cardiovascular and respiratory diseases, and cancer. Importance It is well established that selected lifestyle factors are individually associated with lower risk of chronic diseases, but how combinations of these factors are associated with disease-free life-years is unknown. Objective To estimate the association between healthy lifestyle and the number of disease-free life-years. Design, Setting, and Participants A prospective multicohort study, including 12 European studies as part of the Individual-Participant-Data Meta-analysis in Working Populations Consortium, was performed. Participants included 116 & x202f;043 people free of major noncommunicable disease at baseline from August 7, 1991, to May 31, 2006. Data analysis was conducted from May 22, 2018, to January 21, 2020. Exposures Four baseline lifestyle factors (smoking, body mass index, physical activity, and alcohol consumption) were each allocated a score based on risk status: optimal (2 points), intermediate (1 point), or poor (0 points) resulting in an aggregated lifestyle score ranging from 0 (worst) to 8 (best). Sixteen lifestyle profiles were constructed from combinations of these risk factors. Main Outcomes and Measures The number of years between ages 40 and 75 years without chronic disease, including type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease. Results Of the 116 & x202f;043 people included in the analysis, the mean (SD) age was 43.7 (10.1) years and 70 & x202f;911 were women (61.1%). During 1.45 million person-years at risk (mean follow-up, 12.5 years; range, 4.9-18.6 years), 17 & x202f;383 participants developed at least 1 chronic disease. There was a linear association between overall healthy lifestyle score and the number of disease-free years, such that a 1-point improvement in the score was associated with an increase of 0.96 (95% CI, 0.83-1.08) disease-free years in men and 0.89 (95% CI, 0.75-1.02) years in women. Comparing the best lifestyle score with the worst lifestyle score was associated with 9.9 (95% CI 6.7-13.1) additional years without chronic diseases in men and 9.4 (95% CI 5.4-13.3) additional years in women (P <.001 for dose-response). All of the 4 lifestyle profiles that were associated with the highest number of disease-free years included a body-mass index less than 25 (calculated as weight in kilograms divided by height in meters squared) and at least 2 of the following factors: never smoking, physical activity, and moderate alcohol consumption. Participants with 1 of these lifestyle profiles reached age 70.3 (95% CI, 69.9-70.8) to 71.4 (95% CI, 70.9-72.0) years disease free depending on the profile and sex. Conclusions and Relevance In this multicohort analysis, various healthy lifestyle profiles appeared to be associated with gains in life-years without major chronic diseases.

Objective: Inflammation may underlie the association between psychological stress and cardiometabolic diseases, but this proposition has not been tested longitudinally. We investigated whether the circulating inflammatory markers interleukin-6 (IL-6) and C-reactive protein (CRP) mediate the relationship between psychosocial work characteristics and diabetes. Methods: We used three phases of data at 5 years intervals from the Whitehall II cohort study, originally recruiting 10,308 civil service employees aged 35-55 years. The data included repeat self-reports of job demands, control and social support, IL-6 from plasma samples, CRP from serum samples, and diabetes, ascertained through oral glucose tolerance test, medications, and self-reports of doctor-diagnosed diabetes. Results: Structural equation models with age, sex and occupational position considering men and women combined, showed that low social support at work, but not high job demands or low job control, was prospectively associated with diabetes (standardized beta = 0.05, 95% confidence interval (CI) 0.01-0.09) and higher levels of IL-6 (beta = 0.03, CI 0.00-0.06). The inflammatory markers and diabetes were bidirectionally associated over time. A mediation model including workplace social support, IL-6 and diabetes further showed that 10% of the association between social support and diabetes over the three repeat examinations (total effect beta = 0.08, CI 0.01-0.15) was attributable to a weak indirect effect through IL-6 (beta = 0.01, CI 0.00-0.02). A similar indirect effect was observed for CRP in men only, while job control was prospectively associated with IL-6 among women. Conclusions: This study indicates an association between poor workplace support and diabetes that is partially ascribed to an inflammatory response.

Objective To examine the relation between long working hours and change in body mass index (BMI). Methods We performed random effects meta-analyses using individual-participant data from 19 cohort studies from Europe, US and Australia (n = 122,078), with a mean of 4.4-year follow-up. Working hours were measured at baseline and categorised as part time (= 55 h/week (long working hours). There were four outcomes at follow-up: (1) overweight/obesity (BMI >= 25 kg/m(2)) or (2) overweight (BMI 25-29.9 kg/m(2)) among participants without overweight/obesity at baseline; (3) obesity (BMI >= 30 kg/m(2)) among participants with overweight at baseline, and (4) weight loss among participants with obesity at baseline. Results Of the 61,143 participants without overweight/obesity at baseline, 20.2% had overweight/obesity at follow-up. Compared with standard weekly working hours, the age-, sex- and socioeconomic status-adjusted relative risk (RR) of overweight/obesity was 0.95 (95% CI 0.90-1.00) for part-time work, 1.07 (1.02-1.12) for 41-48 weekly working hours, 1.09 (1.03-1.16) for 49-54 h and 1.17 (1.08-1.27) for long working hours (Pfor trend

To summarize the evidence on the relationship between long working hours and cardiovascular disease, such as coronary heart disease and stroke. Large-scale meta-analyses with published and individual participant observational data on more than 740,000 men and women free of cardiovascular disease report a link between long working hours (>= 55 h a week) and the onset of cardiovascular events. Our meta-analytic update of summary evidence suggests a 1.12-fold (95% CI 1.03-1.21) increased risk associated with coronary heart disease and a 1.21-fold (95% CI 1.01-1.45) increased risk of stroke, although the evidence is somewhat inconsistent and the possibility of residual confounding and bias cannot be ruled out. Few studies have examined the mechanisms which may be stress-related, behavioral, or biological. The recent pooled analyses suggest that increased cardiac electric instability and hypercoagulability might play a role. The evidence that long working hours are a risk factor for cardiovascular disease is accumulating and suggests a small risk. Studies on the effects of long working hours in high-risk populations and those with pre-existing cardiovascular disease, mechanistic research, and intervention studies are needed to advance this research field.

Background Working long hours might have adverse health effects, but whether this is true for all socioeconomic status groups is unclear. In this meta-analysis stratified by socioeconomic status, we investigated the role of long working hours as a risk factor for type 2 diabetes. Methods We identified four published studies through a systematic literature search of PubMed and Embase up to April 30, 2014. Study inclusion criteria were English-language publication; prospective design (cohort study); investigation of the effect of working hours or overtime work; incident diabetes as an outcome; and relative risks, odds ratios, or hazard ratios (HRs) with 95% CIs, or sufficient information to calculate these estimates. Additionally, we used unpublished individual-level data from 19 cohort studies from the Individual-Participant-Data Meta-analysis in Working-Populations Consortium and international open-access data archives. Effect estimates from published and unpublished data from 222 120 men and women from the USA, Europe, Japan, and Australia were pooled with random-effects meta-analysis. Findings During 1.7 million person-years at risk, 4963 individuals developed diabetes (incidence 29 per 10 000 person-years). The minimally adjusted summary risk ratio for long (>= 55 h per week) compared with standard working hours (35-40 h) was 1.07 (95% CI 0.89-1.27, difference in incidence three cases per 10 000 person-years) with significant heterogeneity in study-specific estimates (I-2 = 53%, p = 0.0016). In an analysis stratified by socioeconomic status, the association between long working hours and diabetes was evident in the low socioeconomic status group (risk ratio 1.29, 95% CI 1.06-1.57, difference in incidence 13 per 10 000 person-years, I-2 = 0%, p = 0.4662), but was null in the high socioeconomic status group (1. 00, 95% CI 0.80-1.25, incidence diff erence zero per 10 000 person-years, I-2 = 15%, p = 0.2464). The association in the low socioeconomic status group was robust to adjustment for age, sex, obesity, and physical activity, and remained after exclusion of shift workers. Interpretation In this meta-analysis, the link between longer working hours and type 2 diabetes was apparent only in individuals in the low socioeconomic status groups. Copyright (C) Kivimaki et al. Open Access article distributed under the terms of CC BY.

Abstract Aim To examine: 1) whether nativity status was associated with workplace discrimination, 2) whether this association was mediated through psychosocial work characteristics (job strain, job demands and job control) among registered female nurses. Design Cross-sectional survey with a self-report questionnaire was conducted. Methods A random sample of 610 native Registered Nurses and a total sample of 188 foreign-born Registered Nurses working in Finland were used. Data were collected between September - November of 2017 and analyzed using a counterfactual approach in the causal mediation framework. Results After adjusting for several potential confounders, foreign-born nurses scored higher on workplace discrimination than native nurses. Approximately 20% of the association between nativity status and workplace discrimination was mediated through job control. Job demands and job strain were unlikely to mediate this association. Conclusion The study provides further evidence that migrant status is associated with a higher risk of workplace discrimination among nurses. Lower levels of control over one's own job may partly contribute to the higher risk of workplace discrimination in foreign-born women nurses. Impact Our study addresses the relationship between nativity status and workplace discrimination among female nurses and its mediating factors. The findings suggest that health care organization leaders need to be aware of the increased risk of workplace discrimination among migrant nurses. Moreover, health care organizations need to consider psychosocial work characteristics, including job control, in the efforts aimed to prevent and reduce discrimination against their foreign-born employees.

OBJECTIVE To examine whether physical inactivity is a risk factor for dementia, with attention to the role of cardiometabolic disease in this association and reverse causation bias that arises from changes in physical activity in the preclinical (prodromal) phase of dementia. DESIGN Meta-analysis of 19 prospective observational cohort studies. DATA SOURCES The Individual-Participant-Data Meta-analysis in Working Populations Consortium, the Inter-University Consortium for Political and Social Research, and the UK Data Service, including a total of 19 of a potential 9741 studies. REVIEW METHOD The search strategy was designed to retrieve individual-participant data from prospective cohort studies. Exposure was physical inactivity; primary outcomes were incident all-cause dementia and Alzheimer's disease; and the secondary outcome was incident cardiometabolic disease (that is, diabetes, coronary heart disease, and stroke). Summary estimates were obtained using random effects meta-analysis. RESULTS Study population included 404 840 people (mean age 45.5 years, 57.7% women) who were initially free of dementia, had a measurement of physical inactivity at study entry, and were linked to electronic health records. In 6.0 million person-years at risk, we recorded 2044 incident cases of all-cause dementia. In studies with data on dementia subtype, the number of incident cases of Alzheimer's disease was 1602 in 5.2 million person-years. When measured <10 years before dementia diagnosis (that is, the preclinical stage of dementia), physical inactivity was associated with increased incidence of all-cause dementia (hazard ratio 1.40, 95% confidence interval 1.23 to 1.71) and Alzheimer's disease (1.36, 1.12 to 1.65). When reverse causation was minimised by assessing physical activity >= 10 years before dementia onset, no difference in dementia risk between physically active and inactive participants was observed (hazard ratios 1.01 (0.89 to 1.14) and 0.96 (0.85 to 1.08) for the two outcomes). Physical inactivity was consistently associated with increased risk of incident diabetes (hazard ratio 1.42, 1.25 to 1.61), coronary heart disease (1.24, 1.13 to 1.36), and stroke (1.16, 1.05 to 1.27). Among people in whom cardiometabolic disease preceded dementia, physical inactivity was non-significantly associated with dementia (hazard ratio for physical activity assessed > 10 before dementia onset 1.30, 0.79 to 2.14). CONCLUSIONS In analyses that addressed bias due to reverse causation, physical inactivity was not associated with all-cause dementia or Alzheimer's disease, although an indication of excess dementia risk was observed in a subgroup of physically inactive individuals who developed cardiometabolic disease.