Overweight, obesity and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120,813 adults from 16 cohort studies from the USA and Europe

Background Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight. Methods We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0–24·9 kg/m²), overweight (25·0–29·9 kg/m²), class I (mild) obesity (30·0–34·9 kg/m²), and class II and III (severe) obesity (≥35·0 kg/m²). We used an inclusive definition of underweight (<20 kg/m²) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis. Findings Participants were 120 813 adults (mean age 51·4 years, range 35–103; 71445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973–2012). During a mean follow-up of 10·7 years (1995–2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio [OR] 2·0, 95% CI 1·7–2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5–5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1–21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9–2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1–17·9) for vascular disease followed by diabetes, 18·6 (16·6–20·9) for diabetes only, and 29·8 (21·7–40·8) for diabetes followed by vascular disease. Interpretation The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes

Long working hours as a risk factor for atrial fibrillation: A multi-cohort study

Aims Studies suggest that people who work long hours are at increased risk of stroke, but the association of long working hours with atrial fibrillation, the most common cardiac arrhythmia and a risk factor for stroke, is unknown. We examined the risk of atrial fibrillation in individuals working long hours (>55 per week) and those working standard 35-40 hours per week. Methods In this prospective multi-cohort study from the Individual-Participant-Data Meta-analysis in and results Working Populations (IPD-Work) Consortium, the study population was 85,494 working men and women (mean age 43.4 years) with no recorded atrial fibrillation. Working hours were assessed at study baseline (1991-2004). Mean follow-up for incident atrial fibrillation was 10 years and cases were defined using data on electrocardiograms, hospital records, drug reimbursement registers, and death certificates. We identified 1061 new cases of atrial fibrillation (10-year cumulative incidence 12.4 per 1000). After adjustment for age, sex and socioeconomic status, individuals working long hours had a 1.4-fold increased risk of atrial fibrillation compared to those working standard hours (hazard ratio=1.42, 95%CI=1.13-1.80, P=0.003). There was no significant heterogeneity between the cohortspecific effect estimates (I2=0%, P=0.66) and the finding remained after excluding participants with coronary heart disease or stroke at baseline or during the follow-up (N=2006, hazard ratio=1.36, 95%CI=1.05-1.76, P=0. 0180). Adjustment for potential confounding factors, such as obesity, risky alcohol use and high blood pressure, had little impact on this association. Conclusion Individuals who worked long hours were more likely to develop atrial fibrillation than those working standard hours

Job strain as a risk factor for clinical depression: systematic review and meta-analysis with additional individual participant data

Background Adverse psychosocial working environments characterized by job strain (the combination of high demands and low control at work) are associated with an increased risk of depressive symptoms among employees, but evidence on clinically diagnosed depression is scarce. We examined job strain as a risk factor for clinical depression. Methods We identified published cohort studies from a systematic literature search in PubMed and PsycNET and obtained 14 cohort studies with unpublished individuallevel data from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) consortium. Summary estimates of the association were obtained using random effects models. Individual-level data analyses were based on a pre-published study protocol (F1000Res 2013;2:233). Results We included 6 published studies with a total of 27 461 individuals and 914 incident cases of clinical depression. From unpublished datasets we included 120 221 individuals and 982 first episodes of hospital-treated clinical depression. Job strain was associated with an increased risk of clinical depression in both published (Relative Risk [RR]= 1.77, 95% confidence interval [CI] 1.47-2.13) and unpublished datasets (RR=1.27, 95% CI 1.04-1.55). Further individual participant analyses showed a similar association across sociodemographic subgroups and after excluding individuals with baseline somatic disease. The association was unchanged when excluding individuals with baseline depressive symptoms (RR=1.25, 95% CI: 0.94-1.65), but attenuated on adjustment for a continuous depressive symptoms score (RR=1.03, 95% CI: 0.81- 1.32). Conclusion Job strain may precipitate clinical depression among employees. Future intervention studies

Participant and study summary.

<p>SD: standard deviation.</p>1<p>Study acronyms: DWECS: Danish Work Environment Cohort Study; FPS: Finnish Public Sector Study; HeSSup: Health and Social Support; HNR: Heinz Nixdorf Recall study; IPAW: Intervention Project on Absence and Well-being; POLS: Permanent Onderzoek Leefsituatie; PUMA: Burnout, Motivation and Job Satisfaction study; WOLF: Work Lipids and Fibrinogen. ² Participants with complete data on job strain, age, sex and socioeconomic position.</p>2<p>Moderate drinking (women: 1–14 drinks/week, men: 1–21 drinks/week); intermediate drinking (women: 15–20 drinks/week, men: 22–27 drinks/week); heavy drinking (women: > = 21 drinks/wk, men: > = 28 drinks/week).</p

Longitudinal associations between job strain and taking up excessive drinking¹ among baseline moderate and non-drinkers (n = 43 665)².

1<p>Excessive drinker: an individual who drinks more than recommended amounts of alcohol (intermediate or heavy drinker).</p>2<p>Studies and follow-up times: Belstress (4–7 years), FPS (2–4 years), HeSSup (5 years) and Whitehall II (3–9 years.).</p>3<p>Odds ratios (ORs) from a mixed effects logistic model, adjusted for baseline age, sex and baseline socioeconomic position, with study as the random effect.</p

Longitudinal associations between job strain at baseline and quitting smoking among baseline smokers (n = 9 975)¹.

1<p>Studies and follow-up times: Belstress (4–7 years), FPS (2–4 years), HeSSup (5 years), SLOSH (1–4 years), WOLF Norrland (3–7 years) and Whitehall II (3–9 years.).</p>2<p>Effect estimates from a mixed effects logistic model, adjusted for baseline age, sex and baseline socioeconomic position, with study as the random effect.</p

Associations of alcohol intake at baseline and job strain at follow-up, stratified by baseline job strain (n = 48 646)¹.

1<p>Studies and follow-up times: Belstress (4–8 years), FPS (2–4 years), HeSSup (5 years) and Whitehall II (3–9 years).</p>2<p>Odds ratios (ORs) from a mixed effects logistic model, adjusted for baseline age, sex and baseline socioeconomic position, with study as the random effect.</p>3<p>Incidence rate ratios (IRRs) from a modified Poisson model, adjusted for baseline age, sex and baseline socioeconomic position, with robust standard errors and study as the cluster variable.</p

Association of alcohol intake and job strain (adjusted for age, sex and socioeconomic position) (N = 142 140).

<p>Association of alcohol intake and job strain (adjusted for age, sex and socioeconomic position) (N = 142 140).</p

Longitudinal associations between job strain and reducing alcohol intake to moderate or no alcohol, among baseline excessive drinkers (n = 4 981)¹².

1<p>Excessive drinker: an individual who drinks more than recommended amounts of alcohol (intermediate or heavy drinker).</p>2<p>Studies and follow-up times: Belstress (4–7 years), FPS (2–4 years), HeSSup (5 years) and Whitehall II (3–9 years.).</p>3<p>Odds ratios (ORs) from a mixed effects logistic model, adjusted for baseline age, sex and baseline socioeconomic position, with study as the random effect.</p

Association of tobacco smoking and job strain (adjusted for age, sex and socioeconomic status) (N = 166 130).

<p>Association of tobacco smoking and job strain (adjusted for age, sex and socioeconomic status) (N  = 166 130).</p