Silvia Stringhini

Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: A multicohort study and meta-analysis of 1·7 million men and women

Summary Background 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. Methods 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. Findings 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. Interpretation 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. Funding European Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.

Socioeconomic Status, Structural and Functional Measures of Social Support, and Mortality The British Whitehall II Cohort Study, 1985–2009

The authors examined the associations of social support with socioeconomic status (SES) and with mortality, as well as how SES differences in social support might account for SES differences in mortality. Analyses were based on 9,333 participants from the British Whitehall II Study cohort, a longitudinal cohort established in 1985 among London-based civil servants who were 35–55 years of age at baseline. SES was assessed using participants employment grades at baseline. Social support was assessed 3 times in the 24.4-year period during which participants were monitored for death. In men, marital status, and to a lesser extent network score (but not low perceived support or high negative aspects of close relationships), predicted both all-cause and cardiovascular mortality. Measures of social support were not associated with cancer mortality. Men in the lowest SES category had an increased risk of death compared with those in the highest category (for all-cause mortality, hazard ratio = 1.59, 95% confidence interval: 1.21, 2.08; for cardiovascular mortality, hazard ratio = 2.48, 95% confidence interval: 1.55, 3.92). Network score and marital status combined explained 27% (95% confidence interval: 14, 43) and 29% (95% confidence interval: 17, 52) of the associations between SES and all-cause and cardiovascular mortality, respectively. In women, there was no consistent association between social support indicators and mortality. The present study suggests that in men, social isolation is not only an important risk factor for mortality but is also likely to contribute to differences in mortality by SES.

Contribution of modifiable risk factors to social inequalities in type 2 diabetes: prospective Whitehall II cohort study

Objective To assess the contribution of modifiable risk factors to social inequalities in the incidence of type 2 diabetes when these factors are measured at study baseline or repeatedly over follow-up and when long term exposure is accounted for. Design Prospective cohort study with risk factors (health behaviours (smoking, alcohol consumption, diet, and physical activity), body mass index, and biological risk markers (systolic blood pressure, triglycerides and high density lipoprotein cholesterol)) measured four times and diabetes status assessed seven times between 1991-93 and 2007-09. Setting Civil service departments in London (Whitehall II study). Participants 7237 adults without diabetes (mean age 49.4 years; 2196 women). Main outcome measures Incidence of type 2 diabetes and contribution of risk factors to its association with socioeconomic status. Results Over a mean follow-up of 14.2 years, 818 incident cases of diabetes were identified. Participants in the lowest occupational category had a 1.86-fold (hazard ratio 1.86, 95% confidence interval 1.48 to 2.32) greater risk of developing diabetes relative to those in the highest occupational category. Health behaviours and body mass index explained 33% (−1% to 78%) of this socioeconomic differential when risk factors were assessed at study baseline (attenuation of hazard ratio from 1.86 to 1.51), 36% (22% to 66%) when they were assessed repeatedly over the follow-up (attenuated hazard ratio 1.48), and 45% (28% to 75%) when long term exposure over the follow-up was accounted for (attenuated hazard ratio 1.41). With additional adjustment for biological risk markers, a total of 53% (29% to 88%) of the socioeconomic differential was explained (attenuated hazard ratio 1.35, 1.05 to 1.72). Conclusions Modifiable risk factors such as health behaviours and obesity, when measured repeatedly over time, explain almost half of the social inequalities in incidence of type 2 diabetes. This is more than was seen in previous studies based on single measurement of risk factors.

Socioeconomic determinants of dietary patterns in low- and middle-income countries: a systematic review

BACKGROUND In high-income countries, high socioeconomic status (SES) is generally associated with a healthier diet, but whether social differences in dietary intake are also present in low- and middle-income countries (LMICs) remains to be established. OBJECTIVE We performed a systematic review of studies that assessed the relation between SES and dietary intake in LMICs. DESIGN We carried out a systematic review of cohort and cross-sectional studies in adults in LMICs and published between 1996 and 2013. We assessed associations between markers of SES or urban and rural settings and dietary intake. RESULTS A total of 33 studies from 17 LMICs were included (5 low-income countries and 12 middle-income countries; 31 cross-sectional and 2 longitudinal studies). A majority of studies were conducted in Brazil (8), China (6), and Iran (4). High SES or living in urban areas was associated with higher intakes of calories; protein; total fat; cholesterol; polyunsaturated, saturated, and monounsaturated fatty acids; iron; and vitamins A and C and with lower intakes of carbohydrates and fiber. High SES was also associated with higher fruit and/or vegetable consumption, diet quality, and diversity. Although very few studies were performed in low-income countries, similar patterns were generally observed in both LMICs except for fruit intake, which was lower in urban than in rural areas in low-income countries. CONCLUSIONS In LMICs, high SES or living in urban areas is associated with overall healthier dietary patterns. However, it is also related to higher energy, cholesterol, and saturated fat intakes. Social inequalities in dietary intake should be considered in the prevention and control of noncommunicable diseases in LMICs.

Life-course socioeconomic status and DNA methylation of genes regulating inflammation

BACKGROUND In humans, low socioeconomic status (SES) across the life course is associated with greater diurnal cortisol production, increased inflammatory activity and higher circulating antibodies for several pathogens, all suggesting a dampened immune response. Recent evidence suggests that DNA methylation of pro-inflammatory genes may be implicated in the biological embedding of the social environment. METHODS The present study examines the association between life-course SES and DNA methylation of candidate genes, selected on the basis of their involvement in SES-related inflammation, in the context of a genome-wide methylation study. Participants were 857 healthy individuals sampled from the EPIC Italy prospective cohort study. RESULTS Indicators of SES were associated with DNA methylation of genes involved in inflammation. NFATC1, in particular, was consistently found to be less methylated in individuals with low vs high SES, in a dose-dependent manner. IL1A, GPR132 and genes belonging to the MAPK family were also less methylated among individuals with low SES. In addition, associations were found between SES and CXCL2 and PTGS2, but these genes were consistently more methylated among low SES individuals. CONCLUSIONS Our findings support the hypothesis that the social environment leaves an epigenetic signature in cells. Although the functional significance of SES-related DNA methylation is still unclear, we hypothesize that it may link SES to chronic disease risk.

Seasonal Variation of Overall and Cardiovascular Mortality: A Study in 19 Countries from Different Geographic Locations

Background Cardiovascular diseases (CVD) mortality has been shown to follow a seasonal pattern. Several studies suggested several possible determinants of this pattern, including misclassification of causes of deaths. We aimed at assessing seasonality in overall, CVD, cancer and non-CVD/non-cancer mortality using data from 19 countries from different latitudes. Methods and Findings Monthly mortality data were compiled from 19 countries, amounting to over 54 million deaths. We calculated ratios of the observed to the expected numbers of deaths in the absence of a seasonal pattern. Seasonal variation (peak to nadir difference) for overall and cause-specific (CVD, cancer or non-CVD/non-cancer) mortality was analyzed using the cosinor function model. Mortality from overall, CVD and non-CVD/non-cancer showed a consistent seasonal pattern. In both hemispheres, the number of deaths was higher than expected in winter. In countries close to the Equator the seasonal pattern was considerably lower for mortality from any cause. For CVD mortality, the peak to nadir differences ranged from 0.185 to 0.466 in the Northern Hemisphere, from 0.087 to 0.108 near the Equator, and from 0.219 to 0.409 in the Southern Hemisphere. For cancer mortality, the seasonal variation was nonexistent in most countries. Conclusions In countries with seasonal variation, mortality from overall, CVD and non-CVD/non-cancer show a seasonal pattern with mortality being higher in winter than in summer. Conversely, cancer mortality shows no substantial seasonality.

The social transition of risk factors for cardiovascular disease in the African region: Evidence from three cross-sectional surveys in the Seychelles

OBJECTIVES To examine the association between socioeconomic status (SES) and several cardiovascular disease risk factors (CVRFs) and to assess whether this association has changed over a 15-year observation period. METHODS Three independent population-based surveys of CVRFs were conducted in representative samples of all adults aged 25-64 years in the Seychelles, a small island state located east to Kenya, in 1989 (N=1081), 1994 (N=1067) and 2004 (N=1255). RESULTS Among men, current smoking and heavy drinking were more prevalent in the low versus the high SES group, and obesity was less prevalent. The socioeconomic gradient in diabetes reversed over the study period from lower prevalence in the low versus the high SES group to higher prevalence in the low SES group. Hypercholesterolemia was less prevalent in the low versus the high SES group in 1989 but the prevalence was similar in the two groups in 2004. Hypertension showed no consistent socioeconomic pattern. Among women, the SES gradient in smoking tended to reverse over time from lower prevalence in the low SES group to lower prevalence in the high SES group. Obesity and diabetes were more common in the low versus the high SES group over the study period. Heavy drinking, hypertension and hypercholesterolemia were not socially patterned among women. CONCLUSION The prevalence of several CVRFs was higher in low versus high SES groups in a rapidly developing country in the African region, and an increase of the burden of these CVRFs in the most disadvantaged groups of the population was observed over the 15 years study period.

Declining Stroke and Myocardial Infarction Mortality Between 1989 and 2010 in a Country of the African Region

Background and Purpose— In low- and middle-income countries, the total burden of cardiovascular diseases is expected to increase due to demographic and epidemiological transitions. However, data on cause-specific mortality are lacking in sub-Saharan Africa. Seychelles is one of the few countries in the region where all deaths are registered and medically certified. In this study, we examine trends in mortality for stroke and myocardial infarction (MI) between 1989 and 2010. Methods— Based on vital statistics, we ascertained stroke and MI as the cause of death if appearing in any of the 4 fields for immediate, intermediate, underlying, and contributory causes in death certificates. Results— Mortality rates (per 100 000, age-standardized to World Health Organization standard population) decreased from 1669/710 (men/women) in 1989 to 1991 to 1113/535 in 2008–10 for all causes, from 250/140 to 141/86 for stroke, and from 117/51 to 59/24 for MI, corresponding to proportionate decreases of 33%/25% for all-cause mortality, 44%/39% for stroke, and 50%/53% for MI over 22 years. The absolute number of stroke and MI deaths did not increase over time. In 2008 to 2010, the median age of death was 65/78 years (men/women) for all causes, 68/78 for stroke, and 66/73 for MI. Conclusions— Between 1989 and 2010, age-standardized stroke and MI mortality decreased markedly and more rapidly than all-cause mortality. The absolute number of cardiovascular disease deaths did not increase over time because the impact of population aging was fully compensated by the decline in cardiovascular disease mortality. Stroke mortality remained high, emphasizing the need to strengthen cardiovascular disease prevention and control.

Age and Gender Differences in the Social Patterning of Cardiovascular Risk Factors in Switzerland: The CoLaus Study

Objectives We examined the social distribution of a comprehensive range of cardiovascular risk factors (CVRF) in a Swiss population and assessed whether socioeconomic differences varied by age and gender. Methods Participants were 2960 men and 3343 women aged 35–75 years from a population-based survey conducted in Lausanne, Switzerland (CoLaus study). Educational level was the indicator of socioeconomic status used in this study. Analyses were stratified by gender and age group (35–54 years; 55–75 years). Results There were large educational differences in the prevalence of CVRF such as current smoking (Δ = absolute difference in prevalence between highest and lowest educational group:15.1%/12.6% in men/women aged 35–54 years), physical inactivity (Δ = 25.3%/22.7% in men/women aged 35–54 years), overweight and obesity (Δ = 14.6%/14.8% in men/women aged 55–75 years for obesity), hypertension (Δ = 16.7%/11.4% in men/women aged 55–75 years), dyslipidemia (Δ = 2.8%/6.2% in men/women aged 35–54 years for high LDL-cholesterol) and diabetes (Δ = 6.0%/2.6% in men/women aged 55–75 years). Educational inequalities in the distribution of CVRF were larger in women than in men for alcohol consumption, obesity, hypertension and dyslipidemia (p<0.05). Relative educational inequalities in CVRF tended to be greater among the younger (35–54 years) than among the older age group (55–75 years), particularly for behavioral CVRF and abdominal obesity among men and for physiological CVRF among women (p<0.05). Conclusion Large absolute differences in the prevalence of CVRF according to education categories were observed in this Swiss population. The socioeconomic gradient in CVRF tended to be larger in women and in younger persons.

Biological embedding of early-life exposures and disease risk in humans: a role for DNA methylation

Following wider acceptance of ‘the thrifty phenotype’ hypothesis and the convincing evidence that early‐life exposures can influence adult health even decades after the exposure, much interest has been placed on the mechanisms through which early‐life exposures become biologically embedded.