SummaryBackgroundIn 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.MethodsWe 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.FindingsDuring 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.InterpretationSocioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality.FundingEuropean Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.

Context Previous studies may have underestimated the contribution of health behaviors to social inequalities in mortality because health behaviors were assessed only at the baseline of the study. Objective To examine the role of health behaviors in the association between socioeconomic position and mortality and compare whether their contribution differs when assessed at only one point in time to that assessed longitudinally through the follow-up. Main outcome measures All-cause and cause-specific mortality. Design, Setting, and Participants Participants are drawn from the British Whitehall II longitudinal cohort study, established in 1985 on 10,308 London based civil servants, aged 35–55 years. Analyses are based on 9,590 men and women followed for mortality until 2009. Socioeconomic position was derived from civil service employment grade (high, intermediate and low) at baseline. Smoking, alcohol consumption, diet and physical activity were assessed four times over the follow-up. Results 654 participants died during the follow-up. In analysis adjusted for sex and year of birth, those in the low socioeconomic position had 1.60 times higher risk of death from all causes than those in the high position (a rate difference of 1.94 per 1000 person-years). This association was attenuated by 42% (95% CI, 21%–94%) when health behaviors assessed at baseline were entered into the model and by 72% (95% CI, 42%–154%) when they were entered as time dependent covariates. The corresponding attenuations were 29% (95% CI, 11%–54%) and 45% (95% CI, 24%–79%) for cardiovascular mortality and 61% (95% CI, 16%–425%) and 94% (95% CI, 35%–595%) for non-cancer non-cardiovascular mortality. The difference between the baseline only and repeated assessments of health behaviors was mostly due to an increased explanatory power of diet (from 7% to 17% for all-cause mortality), physical activity (from 5% to 21% for all-cause mortality) and alcohol consumption (from 3% to 12% for all-cause mortality). The role of smoking, the strongest mediator in these analyses, did not change when using baseline or repeat assessments (from 32% to 35% for all-cause mortality). Conclusions In a civil service population in London, there was an association between socioeconomic position and mortality that was substantially accounted for by adjustment for health behaviors, particularly when the behaviors were assessed repeatedly.

In prospective studies, disease rates during follow-up are typically analyzed with respect to the values of factors measured during an initial baseline survey. However, because of "regression dilution," this generally tends to underestimate the real associations of disease rates with the "usual" levels of such risk factors during some particular exposure period. The "regression dilution ratio" describes the ratio of the steepness of the uncorrected association to that of the real association. To assess the relevance of the usual value of a risk factor during particular exposure periods (e.g., first, second, and third decades) to disease risks, regression dilution ratios can be derived by relating baseline measurements of the risk factor to replicate measurements from a reasonably representative sample of study participants after an interval equivalent to about the midpoint of each exposure period (e.g., at 5, 15, and 25 years, respectively). This report illustrates the impact of this time interval on the magnitude of the regression dilution ratios for blood pressure and blood cholesterol. The analyses were based on biennial remeasurements over 30 years for participants in the Framingham Study (Framingham, Massachusetts) and a 26-year resurvey for a sample of men in the Whitehall Study (London, England). They show that uncorrected associations of disease risk with baseline measurements underestimate the strength of the real associations with usual levels of these risk factors during the first decade of exposure by about one-third, the second decade by about one-half, and the third decade by about two-thirds. Hence, to correct appropriately for regression dilution, replicate measurements of such risk factors may be required at varying intervals after baseline for at least a sample of participants.

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Objectives-The impact of work on the risk of future psychiatric disorder has been examined in few longitudinal studies. This was examined prospectively in a large epidemiological study of civil servants. Methods-In the Whitehall II study, a longitudinal, prospective cohort study of 6895 male and 3413 female London based civil servants, work characteristics measured at baseline (phase 1: 1985-8) and first follow up (phase 2: 1989) were used to predict psychiatric disorder measured by a 30 item general health questionnaire (GHQ) at phase 2 and phase 3 follow up (phase 3: 1991-3). Work characteristics and GHQ were measured at all three phases. Results-Low social support at work and low decision authority, high job demands and eVort-reward imbalance were associated with increased risk of psychiatric disorder as assessed by the GHQ at follow up adjusting for age, employment grade, and baseline GHQ score. Conclusions-Social support and control at work protect mental health while high job demands and eVort-reward imbalance are risk factors for future psychiatric disorder. Intervention at the level of work design, organisation, and management might have positive eVects on mental health in working populations. (Occup Environ Med 1999;56:302-307)