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

sj-docx-1-sjp-10.1177_14034948241242160 – Supplemental material for The effect of improving psychosocial stressors on psychological distress: a quasi-experiment of Finnish health and social care workers

Supplemental material, sj-docx-1-sjp-10.1177_14034948241242160 for The effect of improving psychosocial stressors on psychological distress: a quasi-experiment of Finnish health and social care workers by Risto Nikunlaakso, Rahman Shiri, Tuula Oksanen and Jaana Laitinen in Scandinavian Journal of Public Health</p

Odds ratios for overweight associated with workplace social capital, Osaka, Japan (2012).

<p>CI, confidence interval; NA, not applicable; OR, odds ratio.</p>a<p>Adjusted for age.</p>b<p>Adjusted for age, sleep hours, educational attainment, occupation, frequencies of alcohol consumption and physical activity, smoking status, and K6 scores.</p

Participants' characteristics and descriptive statistics of workplace social capital, Osaka, Japan (2012).

<p>BMI, body mass index; K6, Kessler 6; NA, not applicable; SD, standard deviation.</p>a<p>Categorized as follows: none/rarely (less than 1 day/month), sometimes (1 day/month to 2 days/week), and often (3 days/week to almost every day).</p

Odds ratios for underweight/overweight per a 1-SD decrease in the mean of workplace social capital relative to normal weight, Osaka, Japan (2012).

<p>CI, confidence interval; OR, odds ratio; SD, standard deviation.</p>a<p>Adjusted for age.</p>b<p>Adjusted for age, sleep hours, educational attainment, occupation, frequencies of alcohol consumption and physical activity, smoking status, and K6 scores.</p

Effects of a Randomized Intervention to Improve Workplace Social Capital in Community Health Centers in China

<div><p>Objective</p><p>To examine whether workplace social capital improved after implementing a workplace social capital intervention in community health centers in China.</p><p>Methods</p><p>This study was conducted in 20 community health centers of similar size in Jinan of China during 2012–2013. Using the stratified site randomization, 10 centers were randomized into the intervention group; one center was excluded due to leadership change in final analyses. The baseline survey including 447 staff (response rate: 93.1%) was conducted in 2012, and followed by a six-month workplace social capital intervention, including team building courses for directors of community health centers, voluntarily public services, group psychological consultation, and outdoor training. The follow-up survey in July 2013 was responded to by 390 staff members (response rate: 86.9%). Workplace social capital was assessed with the translated and culturally adapted scale, divided into vertical and horizontal dimensions. The facility-level intervention effects were based on all baseline (n = 427) and follow-up (n = 377) respondents, except for Weibei respondents. We conducted a bivariate Difference-in-Difference analysis to estimate the facility-level intervention effects.</p><p>Results</p><p>No statistically significant intervention effects were observed at the center level; the intervention increased the facility-level workplace social capital, and its horizontal and vertical dimensions by 1.0 (p = 0.24), 0.4 (p = 0.46) and 0.8 (p = 0.16), respectively.</p><p>Conclusions</p><p>The comprehensive intervention seemed to slightly improve workplace social capital in community health centers of urban China at the center level. High attrition rate limits any causal interpretation of the results. Further studies are warranted to test these findings.</p></div

The flowchart of this study.

<p>This figure shows the study design of the study. N is the number of CHCs, and n is the number of staff in selected CHCs. In baseline survey, 480 questionnaires were distributed, and we finally got 447 valid questionnaires returned by eligible respondents. And then, 10 centers were randomly selected as the intervention group. The numbers of involved intervention centers and staff in each activity are shown in the figure. 390 staff participated in the follow-up survey, and the numbers of lost to follow-up and new enrollment are also shown. Other reasons for lost to follow-up included retirement, turnover, sick leave, causal leave, refusing to fill in the follow-up questionnaires, and uncompleted follow-up WSC answers. Finally, the facility-level intervention effects were evaluated based on all baseline and follow-up samples (n = 336+468 = 804) except Weibei respondents (n = 33).</p

Baseline characteristics comparison between the intervention and control CHCs.

<p>Baseline characteristics comparison between the intervention and control CHCs.</p