The influence of mortality and socioeconomic status on risk and delayed rewards: a replication with British participants.
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SUBMITTER: Pepper GV
PROVIDER: S-EPMC5530991 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDifferences in morbidity and mortality between socioeconomic groups constitute one of the most consistent findings of epidemiologic research. However, research on social inequalities in health has yet to provide a comprehensive understanding of the mechanisms underlying this association. In recent analysis, we showed health behaviours, assessed longitudinally over the follow-up, to explain a major proportion of the association of socioeconomic status (SES) with mortality in the British Whitehall II study. However, whether health behaviours are equally important mediators of the SES-mortality association in different cultural settings remains unknown. In the present paper, we examine this issue in Whitehall II and another prospective European cohort, the French GAZEL study.Methods and findingsWe included 9,771 participants from the Whitehall II study and 17,760 from the GAZEL study. Over the follow-up (mean 19.5 y in Whitehall II and 16.5 y in GAZEL), health behaviours (smoking, alcohol consumption, diet, and physical activity), were assessed longitudinally. Occupation (in the main analysis), education, and income (supplementary analysis) were the markers of SES. The socioeconomic gradient in smoking was greater (p<0.001) in Whitehall II (odds ratio [OR] = 3.68, 95% confidence interval [CI] 3.11-4.36) than in GAZEL (OR = 1.33, 95% CI 1.18-1.49); this was also true for unhealthy diet (OR = 7.42, 95% CI 5.19-10.60 in Whitehall II and OR = 1.31, 95% CI 1.15-1.49 in GAZEL, p<0.001). Socioeconomic differences in mortality were similar in the two cohorts, a hazard ratio of 1.62 (95% CI 1.28-2.05) in Whitehall II and 1.94 in GAZEL (95% CI 1.58-2.39) for lowest versus highest occupational position. Health behaviours attenuated the association of SES with mortality by 75% (95% CI 44%-149%) in Whitehall II but only by 19% (95% CI 13%-29%) in GAZEL. Analysis using education and income yielded similar results.ConclusionsHealth behaviours were strong predictors of mortality in both cohorts but their association with SES was remarkably different. Thus, health behaviours are likely to be major contributors of socioeconomic differences in health only in contexts with a marked social characterisation of health behaviours. Please see later in the article for the Editors' Summary.
| S-EPMC3043001 | biostudies-literature
Project description: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 participant's 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.
| S-EPMC3372313 | biostudies-literature
Project description:Little is known about the role of socioeconomic status in relation to Parkinson's disease (PD) risk, and no study has investigated whether the impact of socioeconomic status on all-cause mortality differs between individuals with and without PD.In this population-based prospective study, over 4.6 million Swedish inhabitants who participated in the Swedish census in 1980 were followed from 1981 to 2010. The incidence rate of PD and incidence rate ratio were estimated for the association between socioeconomic status and PD risk. Age-standardized mortality rate and hazard ratio (HR) were estimated for the association between socioeconomic status and all-cause mortality for individuals with and without PD.During follow-up, 66,332 incident PD cases at a mean age of 76.0 years were recorded. Compared to individuals with the highest socioeconomic status (high nonmanual workers), all other socioeconomic groups (manual or nonmanual and self-employed workers) had a lower PD risk. All-cause mortality rates were higher in individuals with lower socioeconomic status compared with high nonmanual workers, but relative risks for all-cause mortality were lower in PD patients than in non-PD individuals (e.g., for low manual workers, HR: 1.12, 95% confidence interval [CI]: 1.09-1.15 for PD patients; HR: 1.36, 95% CI: 1.35-1.36 for non-PD individuals).Individuals with lower socioeconomic status had a lower PD incidence compared to the highest socioeconomic group. Lower socioeconomic status was associated with higher all-cause mortality among individuals with and without PD, but such impact was weaker among PD patients.
| S-EPMC5265853 | biostudies-other
Project description:The prevalence of overweight among Chinese children under 5 years of age has been increasing steadily. Using data from China Health and Nutrition Survey (CHNS) spanning from 1991 to 2015, this study investigates the relationship between maternal employment status, maternal education level, and the prevalence of child overweight among Chinese children under 5 years old. The findings indicate that having mothers with low middle school education significantly reduces their children's body mass index z-scores (BMIZ) (p < 0.05). However, no significant association is observed between maternal education level and childhood overweight in urban areas. In rural areas, only when the maternal education level is college or above, there is a significant increase in BMIZ (p < 0.01). The impact of maternal education level on childhood obesity is influenced by household per capita income, and when household per capita income reaches a certain level, higher maternal education is negatively associated with child BMIZ. The study also reveals a significant negative association between maternal employment (p < 0.01)，average weekly working days (p < 0.01), and the BMIZ of children under 5 years of age, while the interaction effect between them is positive and significant. This study has recommended some policy interventions, by promoting parental education on child feeding and parenting, providing professional child care, and offering financial subsidies to families with children under 5.
| S-EPMC10831769 | biostudies-literature
Project description:ImportancePrior studies on the association between fine particulate matter with diameters 2.5 μm or smaller (PM2.5) and probability of death have not applied multilevel analysis disaggregating data for US census tract, states, and counties, nor tested its interaction by socioeconomic status (SES). Such an approach could provide a more refined identification and targeting of populations exposed to increased risk from PM2.5.ObjectiveTo assess the association between PM2.5 and age-specific mortality risk (ASMR) using disaggregated data at the census tract level and evaluate such association according to census tract SES.Design, setting, and participantsThis nationwide cross-sectional study used a linkage of 3 different data sets. ASMR for the period of 2010 to 2015 was obtained from the National Center for Health Statistic, SES data covering a period from 2006 to 2016 came from the American Community Survey, and mean PM2.5 exposure levels from 2010 to 2015 were derived from well-validated atmospheric chemistry and machine learning models. Data were analyzed in April 2021.ExposuresThe main exploratory variable was mean census tract-level long-term exposure to PM2.5 from 2010 to 2015.Main outcomes and measuresThe primary outcome was census tract-level ASMR. Multilevel models were used to quantify the geographic variation in ASMR at levels of census tract, county, and state. Additional analysis explored the interaction of SES in the association of ASMR with PM2.5 exposure.ResultsData from 67 148 census tracts nested in 3087 counties and 50 states were analyzed. The association between exposure to PM2.5 and ASMR varied substantially across census tracts. The magnitude of such association also varied across age groups, being higher among adults and older adults. Census tracts accounted for most of the total geographic variation in mortality risk (range, 77.0%-94.2%). ASMR was higher in deciles with greater PM2.5 concentration. For example, ASMR for age 75 to 84 years was 54.6 per 1000 population higher in the decile with the second-highest PM2.5 concentration than in the decile with the lowest PM2.5 concentration. The ASMR, PM2.5 concentrations, and magnitude of the association between both were higher in the census tracts with the lowest SES.Conclusions and relevanceThis cross-sectional study found that census tracts with lower SES presented higher PM2.5 concentrations. ASMR and air pollution varied substantially across census tracts. There was an association between air pollution and ASMR across all age groups in the United States. These findings suggest that equitable public policies aimed at improving air quality are needed and important to increase life expectancy.
| S-EPMC9131742 | biostudies-literature
Project description:BackgroundThe dimensions along which mortality is patterned in India remains unclear. We examined the specific contribution of social castes, household income, assets, and monthly per capita consumption to mortality differentials in India.Methods and findingsCross-sectional data on 217,363 individuals from 41,554 households from the 2004-2005 India Human Development Survey was analyzed using multiple logistic regressions. Mortality differentials across social castes were attenuated after adjusting for household economic factors such as income and assets. Individuals living in the lowest income and assets quintiles had an increased risk of mortality with odds ratio (OR) of 1.66 (95% CI ?=? 1.23-2.24) in the bottom income quintile and OR of 2.94 (95% CI ?=? 1.66-5.22) in the bottom asset quintile. Counter-intuitively, individuals living in households with lowest monthly consumption per capita had significantly lower probability of death (OR ?= ?0.27, 95% CI ?= ?0.20-0.38).ConclusionsMortality burden in India is largely patterned on economic dimensions as opposed to caste dimensions, though caste may play an important role in predicting economic opportunities.
| S-EPMC3036714 | biostudies-literature
Project description:Socioeconomic status (SES) is a complex construct of multiple indicators, known to impact cancer outcomes, but has not been adequately examined among pediatric AML patients. This study aimed to identify the patterns of co-occurrence of multiple community-level SES indicators and to explore associations between various patterns of these indicators and pediatric AML mortality risk. A nationally representative US sample of 3651 pediatric AML patients, aged 0-19 years at diagnosis was drawn from 17 Surveillance, Epidemiology, and End Results (SEER) database registries created between 1973 and 2012. Factor analysis, cluster analysis, stratified univariable and multivariable Cox proportional hazards models were used. Four SES factors accounting for 87% of the variance in SES indicators were identified: F1) economic/educational disadvantage, less immigration; F2) immigration-related features (foreign-born, language-isolation, crowding), less mobility; F3) housing instability; and, F4) absence of moving. F1 and F3 showed elevated risk of mortality, adjusted hazards ratios (aHR) (95% CI): 1.07(1.02-1.12) and 1.05(1.00-1.10), respectively. Seven SES-defined cluster groups were identified. Cluster 1 (low economic/educational disadvantage, few immigration-related features, and residential-stability) showed the minimum risk of mortality. Compared to Cluster 1, Cluster 3 (high economic/educational disadvantage, high-mobility) and Cluster 6 (moderately-high economic/educational disadvantages, housing-instability and immigration-related features) exhibited substantially greater risk of mortality, aHR(95% CI)=1.19(1.0-1.4) and 1.23 (1.1-1.5), respectively. Factors of correlated SES-indicators and their pattern-based groups demonstrated differential risks in the pediatric AML mortality indicating the need of special public-health attention in areas with economic-educational disadvantages, housing-instability and immigration-related features.
| S-EPMC5050140 | biostudies-literature
Project description:This paper presents new evidence on the impact of socioeconomic status (SES) and education on knowledge attribution. I examine a variety of cases, including vignettes where agents have been Gettiered, have false beliefs, and possess knowledge (according to orthodoxy). Early work investigated whether SES might be associated with knowledge attribution (Weinberg et al. in Philos Top 29(1-2):429-460, 2001; Seyedsayamdost in Episteme 12(1):95-116, 2014). But these studies used college education as a dummy variable for SES. I use the recently developed Great British Class Survey (Savage et al. in Sociology 47(2):219-250, 2013) to measure SES. The paper reports evidence against an association between SES and patterns of knowledge ascription, and reports mixed evidence about education effects.Supplementary informationThe online version contains supplementary material available at 10.1007/s11229-021-03131-6.
| S-EPMC8435110 | biostudies-literature
Project description:Bangladesh has achieved remarkable gains in health indicators during the last four decades despite low levels of economic development. However, the persistence of inequities remains disturbing. This success was also accompanied by health and demographic transitions, which in turn brings new challenges for a nation that has yet to come to terms with pre-transition health challenges. It is therefore important to understand the causes of death and their relationship with socioeconomic status (SES).The paper aims to assess the causes of death by SES based on surveillance data from a rural area of Bangladesh, in order to understand the situation and inform policy makers and programme leaders.We analysed population-based mortality data collected from the Chakaria Health and Demographic Surveillance System in Bangladesh. The causes of death were determined by using a Bayesian-based programme for interpreting verbal autopsy findings (InterVA-4). The data included 1,391 deaths in 217,167 person-years of observation between 2010 and 2012. The wealth index constructed using household assets was used to assess the SES, and disease burdens were compared among the wealth quintiles.Analysing cause of death (CoD) revealed that non-communicable diseases (NCDs) were the leading causes of deaths (37%), followed by communicable diseases (CDs) (22%), perinatal and neonatal conditions (11%), and injury and accidents (6%); the cause of remaining 24% of deaths could not be determined. Age-specific mortality showed premature birth, respiratory infections, and drowning were the dominant causes of death for childhood mortality (0-14 years), which was inversely associated with SES (p<0.04). For adult and the elderly (15 years and older), NCDs were the leading cause of death (51%), followed by CDs (23%). For adult and the elderly, NCDs concentrated among the population from higher SES groups (p<0.005), and CDs among the lower SES groups (p<0.001).Epidemiologic transition is taking place with a shift from the dominance of CDs to NCDs. SES inequity in mortality still persists--the poor suffer from CDs in all age groups, whereas those better off suffer more from NCDs than CDs. Policy makers thus need to consider the social distribution of diseases before developing any public health action targeted towards reducing mortality and the extent of disease burden in an equitable manner.
| S-EPMC4220129 | biostudies-literature
Project description:IntroductionThe effect of socioeconomic status (SES) on stroke mortality at population level has been controversial. This study explores the association of SES in childhood and adulthood with stroke mortality, as well as variations in this association among countries/regions.MethodsSex-specific stroke mortality at country level with death registry covering ≥ 70% population was obtained from the World Health Organization. Human Development Index (HDI) developed by the United Nations was chosen as the SES indicator. The associations between the latest available stroke mortality with HDI in 1999 (adulthood SES) and with HDI in 1960 (childhood SES) for the group aged 45-54 years among countries were examined with regression analysis. Age-standardized stroke mortality and HDI during 1974-2001 were used to estimate the association by time point.ResultsThe population data were available mostly for low-middle to high income countries. HDI in 1960 and 1999 were both inversely associated with stroke mortality in the group aged 45-54 years in 39 countries/regions. HDI in 1960 accounted for 37% of variance of stroke mortality among countries/regions; HDI in 1999 for 35% in men and 53% in women (P < 0.001). There was a quadratic relationship between age-standardized stroke mortality and HDI for the countries from 1974 to 2001: the association was positive when HDI < 0.77 but it became negative when HDI > 0.80.ConclusionsSES is a strong predictor of stroke mortality at country level. Stroke mortality increased with improvement of SES in less developed countries/region, while it decreased with advancing SES in more developed areas.
| S-EPMC3695775 | biostudies-literature