To review literature and provide a pooled effect for the association between multimorbidity and mortality in older adults. A systematic review was performed of articles held on the PUBMED database published up until January 2015. Studies which used different diseases and other conditions to define frailty, evaluated multimorbidity related only to mental health or which presented disease homogeneity were not included. A meta-analysis using random effect to obtain a pooled effect of multimorbidity on mortality in older adults was conducted only with studies which reported hazard ratio (HR). Stratified analysis and univariate meta-regression were performed to evaluate sources of heterogeneity. Out of 5806 identified articles, 26 were included in meta-analysis. Overall, positive association between multimorbidity and mortality [HR: 1.44 (95%CI: 1.34; 1.55)] was detected. The number of morbidities was positively related to risk of death [HR: 1.20 (95%CI: 1.10; 1.30)]. Compared to individuals without multimorbidity, the risk of death was 1.73 (95%CI: 1.41; 2.13) and 2.72 (95%CI: 1.81; 4.08) for people with 2 or more and 3 or more morbidities, respectively. Heterogeneity between studies was high (96.5%). The sample, adjustment and follow-up modified the associations. Only nine estimates performed adjustment which included demographic, socioeconomic and behaviour variables. Disabilities appear to mediate the effect of multimorbidity on mortality. Multimorbidity was associated with an increase in risk of death. Multimorbidity measurement standardization is needed to produce more comparable estimates. Adjusted analysis which includes potential confounders might contribute to better understanding of causal relationships between multimorbidity and mortality.

Objectives The aim of this review was to assess the risk of cardiovascular disease (CVD) events associated with shift work and determine if there is a dose–response relationship in this association. Method Electronic databases (PubMed, Scopus, and Web of Science) were searched for cohort or case–control control study designs in any population, reporting exposure to shift work as the main contributing factor to estimate CVD risk. For each study, adjusted relative risk (RR) ratios and 95% confidence intervals (CI) were extracted, and used to calculate the pooled RR using random-effect models. Meta-regression analysis was conducted to explore potential heterogeneity sources. Potential non-linear dose–response relationships were examined using fractional polynomial models. Results We included 21 studies with a total of 173 010 unique participants. The majority of the studies were ranked low-to-moderate risk of bias. The risk of any CVD event was 17% higher among shift workers than day workers. The risk of coronary heart disease (CHD) morbidity was 26% higher (1.26, 95% CI 1.10–1.43, I 2 = 48.0%). Sub-group analysis showed an almost 20% higher risk of CVD and CHD mortality among shift workers than those who did not work shifts (1.22, 95% CI 1.09–1.37, I 2 = 0% and 1.18, 95% CI 1.06–1.32 I 2 =0%; respectively). After the first five years of shift work, there was a 7.1% increase in risk of CVD events for every additional five years of exposure (95% CI 1.05–1.10). Heterogeneity of the pooled effect size (ES) estimates was high (I 2 =67%), and meta-regression analysis showed that sample size explained 7.7% of this. Conclusions The association between shift work and CVD risk is non-linear and seems to appear only after the first five years of exposure. As shift work remains crucial for meeting production and service demands across many industries, policies and initiatives are needed to reduce shift workers’ CVD risk.

Background. Shift work is characterized by employees working outside the standard hours of 7:00 am to 6:00 pm. Because shift work includes night work, the normal sleep–wake cycle (circadian rhythm) is disrupted, with potential consequences for shift workers’ physical and mental health. Objectives. To assess the pooled effects of shift work on mental health and to evaluate whether these differ in men and women. Search Methods. We searched PubMed, Scopus, and Web of Science databases for peer-reviewed or government reports published up to August 2018 Selection Criteria. To be included, studies had to be longitudinal or case–control studies of shift work exposure associated with adverse mental health outcomes. For subanalyses, we grouped these outcomes as anxiety symptoms, depressive symptoms, or general poor mental health symptoms. Data Collection and Analysis. We followed the Meta-Analysis of Observational Studies in Epidemiology Group guidelines. We extracted adjusted risk estimates for each study to calculate pooled effect sizes (ESs) using random effect models and metaregression analysis to explore sources of heterogeneity. Main Results. We included 7 longitudinal studies, with 28 431 unique participants. Shift work was associated with increased overall risk of adverse mental health outcomes combined (ES = 1.28; 95% confidence interval [CI] = 1.02, 1.62; I² = 70.6%) and specifically for depressive symptoms (ES = 1.33; 95% CI = 1.02, 1.74; I² = 31.5%). Gender differences explained more than 90% of heterogeneity, with female shift workers more likely to experience depressive symptoms than female non–shift workers (odds ratio = 1.73; 95% CI = 1.39, 2.14). Authors’ Conclusions. To our knowledge, this is the first meta-analysis to investigate the pooled effects of shift work on the risk of poor mental health, including subanalyses by type of poor mental health and gender. Shift workers, particularly women, are at increased risk for poor mental health, particularly depressive symptoms. Public Health Implications. Depression accounts for 4.3% of the global burden of disease and incidence, with mental disorders worldwide predicted to cost US $16.3 million by 2030. With 1 in 5 people in the United States and Europe doing shift work, and the increased risk of poor mental health among shift workers, shift work industries are a priority context for reducing this burden. Workplace health promotion programs and policies are needed to minimize shift workers’ risk of poor mental health.

Background The body of evidence on associations between socioeconomic status (SES) and sedentary behaviors in adolescents is growing. Objectives The overall aims of our study were to conduct a systematic review and meta-analysis of this evidence and to assess whether (1) the associations between SES and sedentary behavior are consistent in adolescents from low-middle-income and from high-income countries, (2) the associations vary by domain of sedentary behavior, and (3) the associations vary by SES measure. Methods We performed a systematic literature search to identify population-based studies that investigated the association between SES and sedentary behavior in adolescents (aged 10–19 years). Only studies that presented risk estimates were included. We conducted meta-analyses using random effects and univariate meta-regression and calculated pooled effect sizes (ES). Results Data from 39 studies were included; this provided 106 independent estimates for meta-analyses. Overall, there was an inverse association between SES and sedentary behavior (ES 0.89; 95 % confidence interval [CI] 0.81–0.98). However, the direction of the association varied: in high-income countries, SES was inversely associated with sedentary behavior (ES 0.67; 95 % CI 0.62–0.73), whereas in low-middle-income countries, there was a positive association between SES and sedentary behavior (ES 1.18; 95 % CI 1.04–1.34). In high-income countries, the associations were strongest for screen time (ES 0.68; 95 % CI 0.62–0.74) and television (TV) time (ES 0.58; 95 % CI 0.49–0.69), whereas in low-middle-income countries, the associations were strongest for ‘other’ screen time (i.e., computer, video, study time, but not including TV time) (ES 1.38; 95 % CI 1.07–1.79). All indicators of SES were negatively associated with sedentary behavior in high-income countries, but only resources (income and assets indexes) showed a significant positive association in low-middle-income countries. Conclusion The associations between SES and sedentary behavior are different in high- and low-middle-income countries, and vary by domain of sedentary behavior. These findings suggest that different approaches may be required when developing intervention strategies for reducing sedentary behavior in adolescents in different parts of the world.