In 2011, WHO member states signed up to the 25 × 25 initiative, a plan to cut mortality due to non-communicable diseases by 25% by 2025. However, socioeconomic factors influencing non-communicable diseases have not been included in the plan. In this study, we aimed to compare the contribution of socioeconomic status to mortality and years-of-life-lost with that of the 25 × 25 conventional risk factors. We did a multicohort study and meta-analysis with individual-level data from 48 independent prospective cohort studies with information about socioeconomic status, indexed by occupational position, 25 × 25 risk factors (high alcohol intake, physical inactivity, current smoking, hypertension, diabetes, and obesity), and mortality, for a total population of 1 751 479 (54% women) from seven high-income WHO member countries. We estimated the association of socioeconomic status and the 25 × 25 risk factors with all-cause mortality and cause-specific mortality by calculating minimally adjusted and mutually adjusted hazard ratios [HR] and 95% CIs. We also estimated the population attributable fraction and the years of life lost due to suboptimal risk factors. During 26·6 million person-years at risk (mean follow-up 13·3 years [SD 6·4 years]), 310 277 participants died. HR for the 25 × 25 risk factors and mortality varied between 1·04 (95% CI 0·98-1·11) for obesity in men and 2 ·17 (2·06-2·29) for current smoking in men. Participants with low socioeconomic status had greater mortality compared with those with high socioeconomic status (HR 1·42, 95% CI 1·38-1·45 for men; 1·34, 1·28-1·39 for women); this association remained significant in mutually adjusted models that included the 25 × 25 factors (HR 1·26, 1·21-1·32, men and women combined). The population attributable fraction was highest for smoking, followed by physical inactivity then socioeconomic status. Low socioeconomic status was associated with a 2·1-year reduction in life expectancy between ages 40 and 85 years, the corresponding years-of-life-lost were 0·5 years for high alcohol intake, 0·7 years for obesity, 3·9 years for diabetes, 1·6 years for hypertension, 2·4 years for physical inactivity, and 4·8 years for current smoking. Socioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality. European Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.

Cannabis use is observationally associated with an increased risk of schizophrenia, but whether the relationship is causal is not known. Using a genetic approach, we took 10 independent genetic variants previously identified to associate with cannabis use in 32 330 individuals to determine the nature of the association between cannabis use and risk of schizophrenia. Genetic variants were employed as instruments to recapitulate a randomized controlled trial involving two groups (cannabis users vs nonusers) to estimate the causal effect of cannabis use on risk of schizophrenia in 34 241 cases and 45 604 controls from predominantly European descent. Genetically-derived estimates were compared with a meta-analysis of observational studies reporting ever use of cannabis and risk of schizophrenia or related disorders. Based on the genetic approach, use of cannabis was associated with increased risk of schizophrenia (odds ratio (OR) of schizophrenia for users vs nonusers of cannabis: 1.37; 95% confidence interval (CI), 1.09–1.67; P-value=0.007). The corresponding estimate from observational analysis was 1.43 (95% CI, 1.19–1.67; P-value for heterogeneity =0.76). The genetic markers did not show evidence of pleiotropic effects and accounting for tobacco exposure did not alter the association (OR of schizophrenia for users vs nonusers of cannabis, adjusted for ever vs never smoker: 1.41; 95% CI, 1.09–1.83). This adds to the substantial evidence base that has previously identified cannabis use to associate with increased risk of schizophrenia, by suggesting that the relationship is causal. Such robust evidence may inform public health messages about cannabis use, especially regarding its potential mental health consequences.

Major depressive disorder (MDD) is among the diseases with the greatest public health impact worldwide¹ and confers an approximately 50% elevated mortality of various causes.² Obesity represents another major burden for public health and is also associated with elevated mortality.³ Moreover, both depression and obesity are associated with various chronic diseases such as diabetes mellitus, hypertension, dyslipidemia, cancer, and respiratory and osteoarticular diseases.^4-9 Obesity could also be one explanation for the approximately doubled risk for cardiovascular disease (CVD)¹⁰ and cerebrovascular diseases and the excess mortality among depressed individuals.² Accordingly, gaining a better understanding of the mechanisms underlying the association between MDD and obesity is of high clinical and scientific relevance.

Depressive disorders (DD) and alcohol use disorders (AUD) frequently co-occur. They are key to understanding the current increases in “deaths of despair” among individuals with lower socioeconomic status (SES). The aim of this study was to assess the prospective bidirectional associations between AUD and DD, as well as the effect of SES on these two conditions. The National Epidemiologic Survey on Alcohol and Related Conditions is a cohort study representative of the US adult population, which began in 2001-2002, with follow-up interviews conducted 3 years later. SES was primarily operationalized as educational attainment. AUD, DD, and their levels of severity were defined according to the DSM-5 criteria. The risk of developing an incident DD increased gradually with the recency and the severity of AUD at baseline, but the converse was not observed. Lower SES was an independent risk for incident AUD or DD. SES did not modify the prospective association between AUD and DD. The absence of interaction between SES and moderate or severe AUD for the incident DD must be considered with caution due to the limited number of DD cases reported in these AUD categories. This result is consistent with a causal relationship between AUD and DD, and suggests that therapeutic interventions for AUD may also have beneficial effects to lower DD rates. The independent effects of a lower SES and AUD on DD may result in a vulnerable population cumulating disorders with heavy consequences on health and social well-being.