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.

Objectives. We estimated the burden of disease in the United States attributable to obesity by gender, with life expectancy, quality-adjusted life expectancy, years of life lost annually, and quality-adjusted life years lost annually as outcome measures. Methods. We obtained burden of disease estimates for adults falling into the following body-mass index categories: normal weight (23 to <25), overweight (25 to <30), and obese (≥ 30). We analyzed the 2000 Medical Expenditure Panel Survey to obtain health-related quality-of-life scores and the 1990–1992 National Health Interview Survey linked to National Death Index data through the end of 1995 for mortality. Results. Overweight men and women lost 270 000 and 1.8 million quality-adjusted life years, respectively, relative to their normal-weight counterparts. Obese men and women lost 1.9 million and 3.4 million quality-adjusted life years, respectively, per year. Much of the burden of disease among overweight and obese women arose from lower health-related quality of life and late life mortality. Conclusions. Relative to men, women suffer a disproportionate burden of disease attributable to overweight and obesity, mostly because of differences in health-related quality of life.

Epilepsy accounts for 1% of the global burden of disease due to disability, affecting 0.5% to 1% of the world's population.¹ Despite currently available antiepileptic drugs, 20% to 40% of all patients with epilepsy remain refractory to medical management.^2-5 For such patients, epilepsy surgery still remains underused worldwide.^6-8 Few patients are referred for epilepsy surgery evaluation, and these referrals commonly occur late in the course of their disease, after 20 years of seizures.^9-11 Temporal lobe epilepsy is the most common form of epilepsy¹² and the most likely to be medically refractory.¹³

Although recent declines in life expectancy among non-Hispanic Whites, coined “deaths of despair,” grabbed the headlines of most major media outlets, this is neither a recent problem nor is it confined to Whites. The decline in America’s health has been described in the public health literature for decades and has long been hypothesized to be attributable to an array of worsening psychosocial problems that are not specific to Whites. To test some of the dominant hypotheses, we show how various measures of despair have been increasing in the United States since 1980 and how these trends relate to changes in health and longevity. We show that mortality increases among Whites caused by the opioid epidemic come on the heels of the crack and HIV syndemic among Blacks. Both occurred on top of already higher mortality rates among all Americans relative to people in other nations, and both occurred among declines in measures of well-being. We believe that the attention given to Whites is distracting researchers and policymakers from much more serious, longer-term structural problems that affect all Americans.

Objectives. We used 37 years of follow-up data from a randomized controlled trial to explore the linkage between an early educational intervention and adult health. Methods. We analyzed data from the High/Scope Perry Preschool Program (PPP), an early school-based intervention in which 123 children were randomized to a prekindergarten education group or a control group. In addition to exploring the effects of the program on health behavioral risk factors and health outcomes, we examined the extent to which educational attainment, income, family environment, and health insurance access mediated the relationship between randomization to PPP and behavioral and health outcomes. Results. The PPP led to improvements in educational attainment, health insurance, income, and family environment Improvements in these domains, in turn, lead to improvements in an array of behavioral risk factors and health (P = .01). However, despite these reductions in behavioral risk factors, participants did not exhibit any overall improvement in physical health outcomes by the age of 40 years. Conclusions. Early education reduces health behavioral risk factors by enhancing educational attainment, health insurance coverage, income, and family environments. Further follow-up will be needed to determine the long-term health effects of PPP.