Association of alcohol use with years lived without major chronic diseases: A multicohort study from the IPD-Work consortium and UK Biobank.

Background: Heavy alcohol consumption increases the risk of several chronic diseases. In this multicohort study, we estimated the number of life-years without major chronic diseases according to different characteristics of alcohol use. Methods: In primary analysis, we pooled individual-level data from up to 129,942 adults across 12 cohort studies with baseline data collection on alcohol consumption, drinking patterns, and history between 1986 and 2005 (the IPD-Work Consortium). Self-reported alcohol consumption was categorised according to UK guidelines - non-drinking (never or former drinkers); moderate consumption (1-14 units); heavy consumption (>14 units per week). We further subdivided moderate and heavy drinkers by binge drinking pattern (alcohol-induced loss of consciousness). In addition, we assessed problem drinking using linked data on hospitalisations due to alcohol abuse or poisoning. Follow-up for chronic diseases for all participants included incident type 2 diabetes, coronary heart disease, stroke, cancer, and respiratory disease (asthma and chronic obstructive pulmonary disease) as ascertained via linkage to national morbidity and mortality registries, repeated medical examinations, and/or self-report. We estimated years lived without any of these diseases between 40 and 75 years of age according to sex and characteristics of alcohol use. We repeated the main analyses using data from 427,621 participants in the UK Biobank cohort study. Findings: During 1·73 million person-years at risk, 22,676 participants in IPD-Work cohorts developed at least one chronic condition. From age 40 to 75 years, never-drinkers [men: 29·3 (95%CI 27·9-30·8) years, women 29·8 (29·2-30·4) years)] and moderate drinkers with no binge drinking habit [men 28·7 (28·4-29·0) years, women 29·6 (29·4-29·7) years] had the longest disease-free life span. A much shorter disease-free life span was apparent in participants who experienced alcohol poisoning [men 23·4 (20·9-26·0) years, women 24·0 (21·4-26·5) years] and those with self-reported heavy overall consumption and binge drinking [men: 26·0 (25·3-26·8), women 27·5 (26·4-28·5) years]. The pattern of results for alcohol poisoning and self-reported alcohol consumption was similar in UK Biobank. In IPD-Work and UK Biobank, differences in disease-free years between self-reported moderate drinkers and heavy drinkers were 1·5 years or less. Interpretation: Individuals with alcohol poisonings or heavy self-reported overall consumption combined with a binge drinking habit have a marked 3- to 6-year loss in healthy longevity. Differences in disease-free life between categories of self-reported weekly alcohol consumption were smaller. Funding: Medical Research Council, National Institute on Aging, NordForsk, Academy of Finland, Finnish Work Environment Fund.

Association of Healthy Lifestyle With Years Lived Without Major Chronic Diseases.

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 116 043 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 116 043 people included in the analysis, the mean (SD) age was 43.7 (10.1) years and 70 911 were women (61.1%). During 1.45 million person-years at risk (mean follow-up, 12.5 years; range, 4.9-18.6 years), 17 383 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.

Job Strain as a Risk Factor for Peripheral Artery Disease: A Multi-Cohort Study.

Background Job strain is implicated in many atherosclerotic diseases, but its role in peripheral artery disease (PAD) is unclear. We investigated the association of job strain with hospital records of PAD, using individual-level data from 11 prospective cohort studies from Finland, Sweden, Denmark, and the United Kingdom. Methods and Results Job strain (high demands and low control at work) was self-reported at baseline (1985-2008). PAD records were ascertained from national hospitalization data. We used Cox regression to examine the associations of job strain with PAD in each study, and combined the study-specific estimates in random effects meta-analyses. We used τ2, I2, and subgroup analyses to examine heterogeneity. Of the 139 132 participants with no previous hospitalization with PAD, 32 489 (23.4%) reported job strain at baseline. During 1 718 132 person-years at risk (mean follow-up 12.8 years), 667 individuals had a hospital record of PAD (3.88 per 10 000 person-years). Job strain was associated with a 1.41-fold (95% CI, 1.11-1.80) increased average risk of hospitalization with PAD. The study-specific estimates were moderately heterogeneous (τ2=0.0427, I2: 26.9%). Despite variation in their magnitude, the estimates were consistent in both sexes, across the socioeconomic hierarchy and by baseline smoking status. Additional adjustment for baseline diabetes mellitus did not change the direction or magnitude of the observed associations. Conclusions Job strain was associated with small but consistent increase in the risk of hospitalization with PAD, with the relative risks on par with those for coronary heart disease and ischemic stroke.

Job insecurity and risk of diabetes: a meta-analysis of individual participant data.

BACKGROUND: Job insecurity has been associated with certain health outcomes. We examined the role of job insecurity as a risk factor for incident diabetes. METHODS: We used individual participant data from 8 cohort studies identified in 2 open-access data archives and 11 cohort studies participating in the Individual-Participant-Data Meta-analysis in Working Populations Consortium. We calculated study-specific estimates of the association between job insecurity reported at baseline and incident diabetes over the follow-up period. We pooled the estimates in a meta-analysis to produce a summary risk estimate. RESULTS: The 19 studies involved 140 825 participants from Australia, Europe and the United States, with a mean follow-up of 9.4 years and 3954 incident cases of diabetes. In the preliminary analysis adjusted for age and sex, high job insecurity was associated with an increased risk of incident diabetes compared with low job insecurity (adjusted odds ratio [OR] 1.19, 95% confidence interval [CI] 1.09-1.30). In the multivariable-adjusted analysis restricted to 15 studies with baseline data for all covariates (age, sex, socioeconomic status, obesity, physical activity, alcohol and smoking), the association was slightly attenuated (adjusted OR 1.12, 95% CI 1.01-1.24). Heterogeneity between the studies was low to moderate (age- and sex-adjusted model: I2 = 24%, p = 0.2; multivariable-adjusted model: I2 = 27%, p = 0.2). In the multivariable-adjusted analysis restricted to high-quality studies, in which the diabetes diagnosis was ascertained from electronic medical records or clinical examination, the association was similar to that in the main analysis (adjusted OR 1.19, 95% CI 1.04-1.35). INTERPRETATION: Our findings suggest that self-reported job insecurity is associated with a modest increased risk of incident diabetes. Health care personnel should be aware of this association among workers reporting job insecurity.

Long working hours and cancer risk: a multi-cohort study.

BACKGROUND: Working longer than the maximum recommended hours is associated with an increased risk of cardiovascular disease, but the relationship of excess working hours with incident cancer is unclear. METHODS: This multi-cohort study examined the association between working hours and cancer risk in 116 462 men and women who were free of cancer at baseline. Incident cancers were ascertained from national cancer, hospitalisation and death registers; weekly working hours were self-reported. RESULTS: During median follow-up of 10.8 years, 4371 participants developed cancer (n colorectal cancer: 393; n lung cancer: 247; n breast cancer: 833; and n prostate cancer: 534). We found no clear evidence for an association between working hours and the overall cancer risk. Working hours were also unrelated the risk of incident colorectal, lung or prostate cancers. Working ⩾55 h per week was associated with 1.60-fold (95% confidence interval 1.12-2.29) increase in female breast cancer risk independently of age, socioeconomic position, shift- and night-time work and lifestyle factors, but this observation may have been influenced by residual confounding from parity. CONCLUSIONS: Our findings suggest that working long hours is unrelated to the overall cancer risk or the risk of lung, colorectal or prostate cancers. The observed association with breast cancer would warrant further research.

Sickness absence associated with shared and open-plan offices--a national cross sectional questionnaire survey.

OBJECTIVE: The aim of this study was to examine whether shared and open-plan offices are associated with more days of sickness absence than cellular offices. METHODS: The analysis was based on a national survey of Danish inhabitants between 18-59 years of age (response rate 62%), and the study population consisted of the 2403 employees that reported working in offices. The different types of offices were characterized according to self-reported number of occupants in the space. The log-linear Poisson model was used to model the number of self-reported sickness absence days depending on the type of office; the analysis was adjusted for age, gender, socioeconomic status, body mass index, alcohol consumption, smoking habits, and physical activity during leisure time. RESULTS: Sickness absence was significantly related to having a greater number of occupants in the office (P<0.001) when adjusting for confounders. Compared to cellular offices, occupants in 2-person offices had 50% more days of sickness absence [rate ratio (RR) 1.50, 95% confidence interval (95% CI) 1.13-1.98], occupants in 3-6-person offices had 36% more days of sickness absence (RR 1.36, 95% CI 1.08-1.73), and occupants in open-plan offices (>6 persons) had 62% more days of sickness absence (RR 1.62, 95% CI 1.30-2.02). CONCLUSION: Occupants sharing an office and occupants in open-plan offices (>6 occupants) had significantly more days of sickness absence than occupants in cellular offices.