Combined effect of physical activity and leisure time sitting on long-term risk of incident obesity and metabolic risk factor clustering

Aims/hypothesis Our study aimed to investigate the combined effects of moderate-to-vigorous physical activity and leisure time sitting on the long-term risk of obesity and clustering of metabolic risk factors. Methods The duration of moderate and vigorous physical activity and of leisure time sitting was assessed by questionnaire between 1997 and 1999 among 3,670 participants from the Whitehall II cohort study (73% male; mean age 56 years). Multivariable-adjusted logistic regression models examined associations of physical activity and leisure time sitting tertiles with odds of incident obesity (BMI ≥ 30 kg/m2) and incident metabolic risk factor clustering (two or more of the following: low HDL-cholesterol, high triacylglycerol, hypertension, hyperglycaemia, insulin resistance) at 5 and 10 year follow-ups. Results Physical activity, but not leisure time sitting, was associated with incident obesity. The lowest odds of incident obesity after 5 years were observed for individuals reporting both high physical activity and low leisure time sitting (OR = 0.26; 95% CI 0.11, 0.64), with weaker effects after 10 years. Compared with individuals in the low physical activity/high leisure time sitting group, those with intermediate levels of both physical activity and leisure time sitting had lower odds of incident metabolic risk factor clustering after 5 years (OR 0.53; 95% CI 0.36, 0.78), with similar odds after 10 years. Conclusions/interpretation Both high levels of physical activity and low levels of leisure time sitting may be required to substantially reduce the risk of obesity. Associations with developing metabolic risk factor clustering were less clear

Healthy obesity and objective physical activity

Background: Disease risk is lower in metabolically healthy obese adults than in their unhealthy obese counterparts. Studies considering physical activity as a modifiable determinant of healthy obesity have relied on self-reported measures, which are prone to inaccuracies and do not capture all movements that contribute to health. Objective: We aimed to examine differences in total and moderate-to-vigorous physical activity between healthy and unhealthy obese groups by using both self-report and wrist-worn accelerometer assessments. Design: Cross-sectional analyses were based on 3457 adults aged 60–82 y (77% male) participating in the British Whitehall II cohort study in 2012–2013. Normal-weight, overweight, and obese adults were considered “healthy” if they had <2 of the following risk factors: low HDL cholesterol, hypertension, high blood glucose, high triacylglycerol, and insulin resistance. Differences across groups in total physical activity, based on questionnaire and wrist-worn triaxial accelerometer assessments (GENEActiv), were examined by using linear regression. The likelihood of meeting 2010 World Health Organization recommendations for moderate-to-vigorous activity (≥2.5 h/wk) was compared by using prevalence ratios. Results: Of 3457 adults, 616 were obese [body mass index (in kg/m2) ≥30]; 161 (26%) of those were healthy obese. Obese adults were less physically active than were normal-weight adults, regardless of metabolic health status or method of physical activity assessment. Healthy obese adults had higher total physical activity than did unhealthy obese adults only when assessed by accelerometer (P = 0.002). Healthy obese adults were less likely to meet recommendations for moderate-to-vigorous physical activity than were healthy normal-weight adults based on accelerometer assessment (prevalence ratio: 0.59; 95% CI: 0.43, 0.79) but were not more likely to meet these recommendations than were unhealthy obese adults (prevalence ratio: 1.26; 95% CI: 0.89, 1.80). Conclusions: Higher total physical activity in healthy than in unhealthy obese adults is evident only when measured objectively, which suggests that physical activity has a greater role in promoting health among obese populations than previously thought

Long working hours and risk of coronary heart disease and stroke: a systematic review and meta-analysis of published and unpublished data for 603 838 individuals

Background Long working hours might increase the risk of cardiovascular disease, but prospective evidence is scarce, imprecise, and mostly limited to coronary heart disease. We aimed to assess long working hours as a risk factor for incident coronary heart disease and stroke. Methods We identifi ed published studies through a systematic review of PubMed and Embase from inception to Aug 20, 2014. We obtained unpublished data for 20 cohort studies from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium and open-access data archives. We used cumulative random-eff ects meta-analysis to combine eff ect estimates from published and unpublished data. Findings We included 25 studies from 24 cohorts in Europe, the USA, and Australia. The meta-analysis of coronary heart disease comprised data for 603 838 men and women who were free from coronary heart disease at baseline; the meta-analysis of stroke comprised data for 528 908 men and women who were free from stroke at baseline. Follow-up for coronary heart disease was 5·1 million person-years (mean 8·5 years), in which 4768 events were recorded, and for stroke was 3·8 million person-years (mean 7·2 years), in which 1722 events were recorded. In cumulative meta-analysis adjusted for age, sex, and socioeconomic status, compared with standard hours (35–40 h per week), working long hours (≥55 h per week) was associated with an increase in risk of incident coronary heart disease (relative risk [RR] 1·13, 95% CI 1·02–1·26; p=0·02) and incident stroke (1·33, 1·11–1·61; p=0·002). The excess risk of stroke remained unchanged in analyses that addressed reverse causation, multivariable adjustments for other risk factors, and diff erent methods of stroke ascertainment (range of RR estimates 1·30–1·42). We recorded a dose–response association for stroke, with RR estimates of 1·10 (95% CI 0·94–1·28; p=0·24) for 41–48 working hours, 1·27 (1·03–1·56; p=0·03) for 49–54 working hours, and 1·33 (1·11–1·61; p=0·002) for 55 working hours or more per week compared with standard working hours (ptrend<0·0001). Interpretation Employees who work long hours have a higher risk of stroke than those working standard hours; the association with coronary heart disease is weaker. These findings suggest that more attention should be paid to the management of vascular risk factors in individuals who work long hours

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

Fully adjusted model of factors associated with non-consent in the measure of physical activity by accelerometer.

<p>Fully adjusted model of factors associated with non-consent in the measure of physical activity by accelerometer.</p

Association between socio-demographic factors and non-consent in the measure of physical activity by accelerometer.

<p>Association between socio-demographic factors and non-consent in the measure of physical activity by accelerometer.</p

Association of behavioural and anthropometric factors with non-consent to the measure of physical activity by accelerometer.

<p>Association of behavioural and anthropometric factors with non-consent to the measure of physical activity by accelerometer.</p

Characteristics of outliers compared to others assessed at the clinic in 2012–13.

<p>*For difference between outliers and non-outliers</p><p>Figures are means (SD) unless stated otherwise.</p><p>Characteristics of outliers compared to others assessed at the clinic in 2012–13.</p