US State-level income inequality and risks of heart attack and coronary risk behaviors: longitudinal findings

Cardiovascular hospitalizations and mortality among adults aged 25-64 years in the USA

BACKGROUND AND AIMS

Declines in cardiovascular mortality have stagnated in the USA since 2011. There is growing concern that these patterns reflect worsening cardiovascular health in younger adults. However, little is known about how the burden of acute cardiovascular hospitalizations and mortality has changed in this population. Changes in cardiovascular hospitalizations and mortality among adults aged 25-64 years were evaluated, overall and by community-level income.

METHODS

Using the National Inpatient Sample, age-standardized annual hospitalization and in-hospital mortality rates for acute myocardial infarction (AMI), heart failure, and ischaemic stroke were determined among adults aged 25-64 years. Quasi-Poisson and quasi-binominal regression models were fitted to compare outcomes between individuals residing in low- and higher-income communities.

RESULTS

Between 2008 and 2019, age-standardized hospitalization rates for AMI increased among younger adults from 155.0 (95% confidence interval: 154.6, 155.4) per 100 000 to 160.7 (160.3, 161.1) per 100 000 (absolute change +5.7 [5.0, 6.3], P < .001). Heart failure hospitalizations also increased (165.3 [164.8, 165.7] to 225.3 [224.8, 225.8], absolute change +60.0 (59.3, 60.6), P < .001), as ischaemic stroke hospitalizations (76.3 [76.1, 76.7] to 108.1 [107.8, 108.5], absolute change +31.7 (31.2, 32.2), P < .001). Across all conditions, hospitalizations rates were significantly higher among younger adults residing in low-income compared with higher-income communities, and disparities did not narrow between groups. In-hospital mortality decreased for all conditions over the study period.

CONCLUSIONS

There was an alarming increase in cardiovascular hospitalizations among younger adults in the USA from 2008 to 2019, and disparities between those residing in low- and higher-income communities did not narrow.

Inequality's on Tap: A Longitudinal Study of Area-Level Income Inequality and Alcohol Consumption Among Canadian Adolescents

PURPOSE

To determine if income inequality at the census division level is associated with alcohol consumption and abuse among junior high and high school students.

METHODS

Data on adolescents are from the Cannabis use, Obesity, Mental health, Physical activity, Alcohol use, Smoking, and Sedentary behavior (COMPASS) study. Participant data (n = 19,759) were collected during three survey waves (2016-2017, 2017-2018, and 2018-2019) and linked to 30 census divisions within four Canadian provinces. Data on income inequality and other area-level factors were derived from the 2016 Canadian census. Multilevel logistic regression modelling was used to quantify the associations between income inequality, monthly alcohol consumption, and binge drinking.

RESULTS

After adjusting for covariates, students living in census divisions within the second and third quintiles of income inequality experienced an average 80% (OR = 1.80, 95% CI = 1.08-3.02) and 92% (OR = 1.92, 95% CI = 1.05-3.51) increased odds of engaging in monthly binge drinking, respectively, compared to those living in the first quintile. Similarly, adolescents living in census divisions within the second inequality quintile experienced an average 169% (OR = 2.69, 95% CI = 1.45, 4.99) increased odds of engaging in weekly binge drinking, compared to those living in the first quintile. There was no significant association between higher income inequality and current monthly alcohol consumption.

DISCUSSION

Moderate area-level income inequality within census divisions was adversely associated with alcohol consumption among adolescents. Future work should investigate the potential mechanisms that mediate this relationship.

Major and minor ECG abnormalities depending on regional living conditions in Russia

The goal of our study was to explore the effect of living conditions on the odd of major and minor ECG abnormalities on a large region scale in Russia. For the analysis, cross-sectional data of the Russian study, ESSE-RF 2013-2014, were used. They were collected on a sample of 16,400 subjects from 10 regions of the Russia. ECG abnormalities were grouped into two categories: Major and Minor (sensu the 2009 version of the Minnesota Code Classification System). Regional living conditions were considered comprehensively via five indices combining 33 characteristics of the regions. The estimates were presented as odds ratios and their 95% confidence intervals. The prevalence values of major abnormalities in the sample were 8.4% among women and 9.4% among men (p = 0.021). The prevalence of minor abnormalities constituted 34.1% and 45.9%, respectively (p < 0.001). In men, the odd of major ECG abnormalities increased with the demographic depression growth (1.08: 1.04-1.12) and with industrial development growth in the region (1.12: 1.07-1.17). In women, an increase in the odd of major ECG abnormalities was directly associated with industrial development (1.12: 1.07-1.16) and inversely related to the economic development in the region (0.94: 0.89-0.99). The odd of minor ECG abnormalities in men and women declined with the growth of the regional economic development: OR of 0.95: 0.93-0.98, and OR of 0.92: 0.87-0.99, respectively. The study demonstrated an effect of regional living conditions of the Russian population on the odd of major and minor ECG abnormalities. The most stable and logically explainable relationships were obtained for industrial and economic characteristics of living conditions.

Risk factors of deaths related to cardiovascular diseases in World Health Organization (WHO) member countries

This study aims to identify the risk factors affecting deaths related to cardiovascular diseases. The research population comprised of 194 World Health Organization (WHO) member countries, but the data analysis was conducted with the data from 152 countries as 42 of them do not have any data on study variables. Multivariable regression analysis was utilised for this study to analyse the effect of factors regarding metabolism, lifestyle, economic, socio-demographic and health system on the cardiovascular diseases related to deaths. As a result of regression analysis, the number of deaths related to cardiovascular diseases increases with the increase in blood pressure (p < .001), blood glucose (p = .032), obesity rate (p < .001), salt consumption (p < .001), GINI index (p = .002) and dependent age ratio (p < .001); the frequency of cardiovascular disease-related deaths is higher in the countries within low (p < .001) and high (p < .001) middle-income levels; yet, the number of deaths based on cardiovascular diseases diminishes with the increase in the number of doctors (p = .005) and health expenditures per capita (p = .044). The research findings are considered to guide the countries in the determination of their steps towards the prevention of deaths related to cardiovascular diseases.

Socioeconomic inequality in congenital heart diseases in Iran

INTRODUCTION

Social-economic factors have an important role in shaping inequality in congenital heart diseases. The current study aimed to assess and decompose the socio-economic inequality in Congenital Heart Diseases (CHDs) in Iran.

METHODS

This is a cross-sectional research conducted at Shahid Rajaie Cardiovascular Medical and Research Center in Tehran, Iran, as one of the largest referral heart hospitals in Asia. Data were collected primarily from 600 mothers who attended in pediatric cardiology department in 2020. The polychoric principal component analysis (PCA) and Errygers corrected CI (ECI) were used to construct household socioeconomic status and to assess inequality in CHDs, respectively. A regression-based decomposition analysis was also applied to explain socioeconomic-related inequalities. To select the explanatory social, medical/biological, and lifestyle variables, the chi-square test was first used.

RESULTS

There was a significant pro-rich inequality in CHDs (ECI = -0.65, 95% CI, - 0.72 to - 0.58). The social, medical/biological, and lifestyle variables accounted for 51.47, 43.25, and 3.92% of inequality in CHDs, respectively. Among the social variables, family SES (about 50%) and mother's occupation (21.05%) contributed the most to CHDs' inequality. Besides, in the medical/biological group, receiving pregnancy care (22.06%) and using acid folic (15.70%) had the highest contribution.

CONCLUSION

We concluded that Iran suffers from substantial socioeconomic inequality in CHDs that can be predominantly explained by social and medical/biological variables. It seems that distributional policies aim to reduce income inequality while increasing access of prenatal care and folic acid for disadvantaged mothers could address this inequality much more strongly in Iran.

Income inequality and non-communicable disease mortality and morbidity in Brazil States: a longitudinal analysis 2002-2017

Background

Income inequality can negatively affect population health by increasing social stress and conflict, and reducing trust, public goods and healthcare access. However there is limited evidence from low and middle-income countries (LMICs) with high levels of inequality. This study investigates the association between income inequality, morbimortality and risk factors of non-communicable diseases (NCDs) in 26 Brazilian states from 2002 to 2017.

Methods

Data was acquired for men and women from the Global Health Data Exchange, the Brazilian Institute of Geography and Statistics, and the Brazilian Ministry of Health, totalling 416 state-year observations. Disability-adjusted life years (DALYs) and risk factors of NCDs were the dependent variables. Gini Index was the main independent variable. Multivariate linear panel regressions were performed, controlling for state and time fixed effects, gross domestic product per capita, population ageing, poverty and access to healthcare.

Findings

A 1% increase in the Gini Index was associated with increases in alcohol abuse (of 923•4 DALYs per 100,000 people, 95%CI 217•6 to 1629•0) and diabetes mellitus morbidity (of 893•3 DALYs per 100,000 people, 95%CI 127•7 to 1659•0), and decreases in morbidity from attention disorder (of -4•0 DALYs per 100,000 people, 95%CI -7•4 to -0•5) and autism spectrum (of -2•4 DALYs per 100,000 people, 95%CI -4•3 to -0•5). These associations were greater for men, further supported by associations with alcohol use as a risk factor.

Interpretation

This study provides evidence from a highly unequal LMIC, Brazil, of negative associations between income inequality and NCDs, and the importance of addressing wider social determinants of health.

Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) - Finance Code 001 as a Brazilian CAPES scholarship to AZD and by the São Paulo Research Foundation (FAPESP), grant 2020/15944-8 to RSG.

Effect of regional living conditions on middle-term cardiovascular outcomes: data from prospective stage of the ESSE-RF study

Aim. To assess regional living conditions with cardiovascular outcomes based on prospective stage of the Epidemiology of Cardiovascular Diseases and their Risk Factors in Regions of Russian Federation (ESSE-RF) study.

Material and methods. We used data from a 3- and 5-year prospective stage of the ESSE-RF study (2012-2013). For initial screening, 16210 people aged 25-64 were included. To characterize the regions of residence, 5 regional indices (RIs) were used. The following endpoints were considered: cardiovascular death, myocardial infarction, stroke, composite endpoint (cardiovascular death + myocardial infarction + stroke). To assess the correlations, generalized estimating equations with nested data structure (individuals in the regions) were used. The studied associations were adjusted for a wide range of potential effect modifiers.

Results. There are multiple direct associations of RIs with the likelihood of all endpoints. The exception was the reverse association of Industrial RI with cardiovascular death. The most stable associations regarded Mixed RI, Industrial RI and Socio-geographical RI, with a high RI significance in endpoint development, compared with well-known individual cardiovascular risk factors. Separate associations were noted for Economic RI and Demographic RI.

Conclusion. The results indicate a significant contribution of a number of regional living conditions to individual risk of fatal and non-fatal cardiovascular outcomes.

Climate-related migration and population health: social science-oriented dynamic simulation model

BACKGROUND

Social science models find the ecological impacts of climate change (EICC) contribute to internal migration in developing countries and, less so, international migration. Projections expect massive climate-related migration in this century. Nascent research calls to study health, migration, population, and armed conflict potential together, accounting for EICC and other factors. System science offers a way: develop a dynamic simulation model (DSM). We aim to validate the feasibility and usefulness of a pilot DSM intended to serve as a proof-of-concept and a basis for identifying model extensions to make it less simplified and more realistic.

METHODS

Studies have separately examined essential parts. Our DSM integrates their results and computes composites of health problems (HP), health care (HC), non-EICC environmental health problems (EP), and environmental health services (ES) by origin site and by immigrants and natives in a destination site, and conflict risk and intensity per area. The exogenous variables include composites of EICC, sociopolitical, economic, and other factors. We simulate the model for synthetic input values and conduct sensitivity analyses.

RESULTS

The simulation results refer to generic origin and destination sites anywhere on Earth. The effects' sizes are likely inaccurate from a real-world view, as our input values are synthetic. Their signs and dynamics are plausible, internally consistent, and, like the sizes, respond logically in sensitivity analyses. Climate migration may harm public health in a host area even with perfect HC/ES qualities and full access; and no HP spillovers across groups, conflict, EICC, and EP. Deviations from these conditions may worsen everyone's health. We consider adaptation options.

CONCLUSIONS

This work shows we can start developing DSMs to understand climate migration and public health by examining each case with its own inputs. Validation of our pilot model suggests we can use it as intended. We lay a path to making it more realistic for policy analysis.

Anti-poverty policy and health: Attributes and diffusion of state earned income tax credits across U.S. states from 1980 to 2020

PURPOSE

The U.S. federal Earned Income Tax Credit (EITC) is often considered the most effective antipoverty program for families in the U.S., leading to a variety of improved outcomes such as educational attainment, work incentives, economic activity, income, and health benefits for mothers, infants and children. State EITC supplements to the federal credit can significantly enhance the magnitude of this intervention. In this paper we advance EITC and health research by: 1) describing the diffusion of state EITC policies over 40 years, 2) presenting patterns in important EITC policy dimensions across space and time, and 3) disseminating a robust data set to advance future research by policy analysts and scientists.

METHODS

We used current public health law research methods to systematically collect, conduct textual legal analysis, and numerically code all EITC legislative changes from 1980 through 2020 in the 50 states and Washington, D.C.

RESULTS

First, the pattern of diffusion across states and time shows initial introductions during the 1990s in the Midwest, then spreading to the Northeast, with more recent expansions in the West and South. Second, differences by state and time of important policy dimensions are evident, including size of credit and refundability. Third, state EITC benefits vary considerably by household structure.

CONCLUSION

Continued research on health outcomes is warranted to capture the full range of potential beneficial effects of EITCs on family and child wellbeing. Lawyers and policy analysts can collaborate with epidemiologists and economists on other high-quality empirical studies to assess the many dimensions of policy and law that potentially affect the social determinants of health.

State-level income inequality and the odds for meeting fruit and vegetable recommendations among US adults

Background

Previous research indicates that income inequality is associated with risk for mortality, self-rated health status, chronic conditions, and health behavior, such as physical activity. However, little is known about the relationship between income inequality and dietary intake, which is a major risk factor for common chronic diseases including heart disease, stroke, diabetes, and certain types of cancers. The objective of this study is to determine the association between US state income inequality and fruit and vegetable consumption among adults.

Methods

Cross-sectional data on 270,612 U.S. adults from the U.S. 2013 Behavioral Risk Factor Surveillance System was used. Fruit and vegetable consumption was assessed from the six-item fruit and vegetable frequency questionnaire, which is part of the Behavioral Risk Factor Surveillance System. Multilevel modeling was used to determine whether US state-level income inequality (measured by the z-transformation of the Gini coefficient) was associated with fruit and vegetable consumption adjusting for individual-level and state-level covariates.

Results

In comparison to men, women were more likely to consume fruits and vegetables ≥5 times daily, fruits ≥2 times daily, vegetables ≥3 times of daily, and less likely to consume fruit juice daily. Among both men and women, a standard deviation increase in Gini coefficient was associated with an increase in consuming fruit juice daily (OR = 1.07, 95% CI = 1.03, 1.11). However, among women, a standard deviation increase in Gini coefficient was associated with a decreased likelihood in meeting daily recommended levels of both fruits and vegetables (OR = 0.93; 0.87–0.99), fruits only (OR = 0.95; 95% CI, 0.92–0.99) and vegetables only (OR = 0.92; 95% CI, 0.89–0.96).

Conclusions

This study is one of the first to show the relationship between income inequality and fruit and vegetable consumption among U.S. adults empirically. Women’s health is more likely to be detrimentally affected when living in a state with higher income inequality.

Poverty over the early life course and young adult cardio-metabolic risk

OBJECTIVES

There is little known about whether exposure to family poverty at specific periods of the early life course independently contributes to coronary heart disease risk beyond the contribution of concurrent poverty.

METHODS

Children were recruited in early pregnancy and additional survey data obtained during the pregnancy and at the 5-, 14- and 30-year follow-ups. Fasting blood samples were also obtained at the 30-year follow-up. Analyses are multinominal logistic regressions stratified by gender and with adjustments for confounding.

RESULTS

For male offspring, family poverty at different stages of the early life course was not associated with measures of cardio-metabolic risk. For females early life course, poverty predicted obesity, homeostatic model assessment of insulin resistance (HOMA-IR) and total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C), as well as concurrent family poverty associated with obesity, HOMA-IR, TC/HDL-C, HDL-C and increased systolic and diastolic blood pressure.

CONCLUSIONS

Family poverty in the early life course independently predicts increased levels of cardio-metabolic risk of females. The primary finding, however, is that concurrent poverty is independently and strongly associated with increased cardio-metabolic risk levels in young adulthood.

Income Inequality and Self-Reported Health Among Older Adults in Brazil

This study analyzes the association between income inequality and self-reported health (SRH) in older adults, and separately for the young-old and very-old groups, residing in each of the 27 Brazilian capitals. The sample consisted of 4,912 individuals aged 60 or older residing in Brazilian capitals in 2013. Bayesian multilevel models were applied to the whole sample and separately for individuals aged 60 to 79 (young-old), and 80 or more (very-old). Our results show significant associations between income inequality and SRH, even after controlling for individual and contextual factors. We found greater odds of poor SRH among older adults living in areas with medium (odds ratio [OR] = 1.66, 95% confidence interval [CI]: 1.49-1.86) and high-income inequality (OR = 2.21, 95% CI: 2.05-2.38). The negative association between income inequality and health, independently of the individual and contextual characteristics, suggests that living in unequal areas can have a detrimental effect on the health of older adults.

Environmental, Nutritional, and Socioeconomic Determinants of IBD Incidence: A Global Ecological Study

BACKGROUND AND AIMS

The wide variation in inflammatory bowel disease [IBD] incidence across countries entails an opportunity to recognise global disease determinants and hypothesise preventive policies.

METHODS

We fitted multivariable models to identify putative environmental, nutritional, and socioeconomic determinants associated with the incidence of IBD (i.e. ulcerative colitis [UC] and Crohn's disease [CD]). We used the latest available country-specific incidence rates, and aggregate data for 20 determinants, from over 50 countries accounting for more than half of the global population. We presented the associations with exponentiated beta coefficients (exp[β]) indicating the relative increase of disease incidence per unit increase in the predictor variables.

RESULTS

Country-specific incidence estimates demonstrate wide variability across the world, with a median of 4.8 new UC cases (interquartile range [IQR] 2.4-9.3), and 3.5 new CD cases [IQR 0.8-5.7] per 100 000 population per year. Latitude (exp[β] 1.05, 95% confidence interval [CI] 1.04‒1.06, per degree increase), prevalence of obesity [1.05, 1.02‒1.07, per 1% increase], and of tobacco smoking [0.97, 0.95‒0.99, per 1% increase] explained 71.5% of UC incidence variation across countries in the adjusted analysis. The model for CD included latitude [1.04, 1.02‒1.06], expenditure for health (1.03, 1.01‒1.05, per 100 purchasing power parity [PPP]/year per capita increase), and physical inactivity prevalence [1.03, 1.00‒1.06, per 1% increase], explaining 58.3% of incidence variation across countries. Besides expenditure for health, these associations were consistent in low/middle- and high-income countries.

CONCLUSIONS

Our analysis highlights factors able to explain a substantial portion of incidence variation across countries. Further high-quality research is warranted to develop global strategies for IBD prevention.

A "Swiss paradox" in the United States? Level of spatial aggregation changes the association between income inequality and morbidity for older Americans

Although a preponderance of research indicates that increased income inequality negatively impacts population health, several international studies found that a greater income inequality was associated with better population health when measured on a fine geographic level of aggregation. This finding is known as a “Swiss paradox”. To date, no studies have examined variability in the associations between income inequality and health outcomes by spatial aggregation level in the US. Therefore, this study examined associations between income inequality (Gini index, GI) and population health by geographic level using a large, nationally representative dataset of older adults. We geographically linked respondents’ county data from the 2012 Behavioral Risk Factor Surveillance System to 2012 American Community Survey data. Using generalized linear models, we estimated the association between GI decile on the state and county levels and five population health outcomes (diabetes, obesity, smoking, sedentary lifestyle and self-rated health), accounting for confounders and complex sampling. Although state-level GI was not significantly associated with obesity rates (b = − 0.245, 95% CI − 0.497, 0.008), there was a significant, negative association between county-level GI and obesity rates (b = − 0.416, 95% CI − 0.629, − 0.202). State-level GI also associated with an increased diabetes rate (b = 0.304, 95% CI 0.063, 0.546), but the association was not significant for county-level GI and diabetes rate (b = − 0.101, 95% CI − 0.305, 0.104). Associations between both county-level GI and state-level GI and current smoking status were also not significant. These findings show the associations between income inequality and health vary by spatial aggregation level and challenge the preponderance of evidence suggesting that income inequality is consistently associated with worse health. Further research is needed to understand the nuances behind these observed associations to design informed policies and programs designed to reduce socioeconomic health inequities among older adults.

Inequality within a community at the neighborhood level and the incidence of mood disorders in Japan: a multilevel analysis

PURPOSE

This study analyzes whether income inequality within a community at the neighborhood level is associated with incidence of mood disorder in Japan.

METHODS

A retrospective cohort study was performed using the data of 116,658 National Health Insurance beneficiaries aged between 20 and 69 in Chiba City, Japan. To evaluate income inequality within a community, the Gini coefficient within a 30-min walking distance from an individual's residence was calculated using income distribution estimated by the National Census and the Housing and Land Survey 2013. Incidence of mood disorder was determined through insurance claims submitted from April 1, 2013, to March 31, 2016. A multilevel logistic analysis with three levels-the individual, household, and residential district-was performed to evaluate the association.

RESULTS

Income inequality within a community at the neighborhood level was not associated with incidence of mood disorder in the models with and without equivalent household income (p for trend = 0.856 and 0.947, respectively). No difference was observed in the impact of the Gini coefficient among income levels, lower versus higher income groups (p for interaction between Gini coefficient and household income = 0.967). In contrast, lower equivalent income at the household level was significantly associated with higher incidence of mood disorder (p for trend < 0.001).

CONCLUSIONS

While we confirmed that lower income at the household level itself had an adverse effect on mental health, income inequality within a community at the neighborhood level was not a significant factor for incidence of mood disorder in Japan.

Income inequality and self-reported health in a representative sample of 27 017 residents of state capitals of Brazil

Background

The association between income inequality and health has been analyzed predominantly in developed countries with modest levels of inequality. The study aimed to analyze the association between income inequality and self-reported health (SRH) in the adult population of the 27 Brazilian capitals.

Methods

Individuals aged 18 years or older from the National Health survey residing in Brazilian capitals in 2013 were analyzed (n = 27 017). Bayesian multilevel models were applied after controlling for individual factors and area-level socioeconomic characteristics.

Results

We found a significant association between income inequality and SRH, even after controlling for individual and contextual factors. The results indicate greater odds of poor SRH among those living in areas with medium (OR = 1.31, 95% CI: 1.17-1.47) and high income inequality level (OR = 1.39, 95% CI: 1.24-1.56). Income inequality remained significantly associated with SRH, even after controlling for other contextual socioeconomic characteristics, such as local illiteracy rate, violence and per capita income.

Conclusions

The study highlights the importance of the individual and contextual characteristics associated with SRH. Our findings suggest that city-level income inequality can have a detrimental effect on individual health, over and above other contextual socioeconomic characteristics and individual factors.

Value of Neighborhood Socioeconomic Status in Predicting Risk of Outcomes in Studies That Use Electronic Health Record Data

IMPORTANCE

Data from electronic health records (EHRs) are increasingly used for risk prediction. However, EHRs do not reliably collect sociodemographic and neighborhood information, which has been shown to be associated with health. The added contribution of neighborhood socioeconomic status (nSES) in predicting health events is unknown and may help inform population-level risk reduction strategies.

OBJECTIVE

To quantify the association of nSES with adverse outcomes and the value of nSES in predicting the risk of adverse outcomes in EHR-based risk models.

DESIGN, SETTING, AND PARTICIPANTS

Cohort study in which data from 90 097 patients 18 years or older in the Duke University Health System and Lincoln Community Health Center EHR from January 1, 2009, to December 31, 2015, with at least 1 health care encounter and residence in Durham County, North Carolina, in the year prior to the index date were linked with census tract data to quantify the association between nSES and the risk of adverse outcomes. Machine learning methods were used to develop risk models and determine how adding nSES to EHR data affects risk prediction. Neighborhood socioeconomic status was defined using the Agency for Healthcare Research and Quality SES index, a weighted measure of multiple indicators of neighborhood deprivation.

MAIN OUTCOMES AND MEASURES

Outcomes included use of health care services (emergency department and inpatient and outpatient encounters) and hospitalizations due to accidents, asthma, influenza, myocardial infarction, and stroke.

RESULTS

Among the 90 097 patients in the training set of the study (57 507 women and 32 590 men; mean [SD] age, 47.2 [17.7] years) and the 122 812 patients in the testing set of the study (75 517 women and 47 295 men; mean [SD] age, 46.2 [17.9] years), those living in neighborhoods with lower nSES had a shorter time to use of emergency department services and inpatient encounters, as well as a shorter time to hospitalizations due to accidents, asthma, influenza, myocardial infarction, and stroke. The predictive value of nSES varied by outcome of interest (C statistic ranged from 0.50 to 0.63). When added to EHR variables, nSES did not improve predictive performance for any health outcome.

CONCLUSIONS AND RELEVANCE

Social determinants of health, including nSES, are associated with the health of a patient. However, the results of this study suggest that information on nSES may not contribute much more to risk prediction above and beyond what is already provided by EHR data. Although this result does not mean that integrating social determinants of health into the EHR has no benefit, researchers may be able to use EHR data alone for population risk assessment.

Income inequality and cardiovascular disease risk factors in a highly unequal country: a fixed-effects analysis from South Africa

Background

Chronic stress associated with high income inequality has been hypothesized to increase CVD risk and other adverse health outcomes. However, most evidence comes from high-income countries, and there is limited evidence on the link between income inequality and biomarkers of chronic stress and risk for CVD. This study examines how changes in income inequality over recent years relate to changes in CVD risk factors in South Africa, home to some of the highest levels of income inequality globally.

Methods

We linked longitudinal data from 9356 individuals interviewed in the 2008 and 2012 National Income Dynamics Study to district-level Gini coefficients estimated from census and survey data. We investigated whether subnational district income inequality was associated with several modifiable risk factors for cardiovascular disease (CVD) in South Africa, including body mass index (BMI), waist circumference, blood pressure, physical inactivity, smoking, and high alcohol consumption. We ran individual fixed-effects models to examine the association between changes in income inequality and changes in CVD risk factors over time. Linear models were used for continuous metabolic outcomes while conditional Poisson models were used to estimate risk ratios for dichotomous behavioral outcomes.

Results

Both income inequality and prevalence of most CVD risk factors increased over the period of study. In longitudinal fixed-effects models, changes in district Gini coefficients were not significantly associated with changes in CVD risk factors.

Conclusions

Our findings do not support the hypothesis that subnational district income inequality is associated with CVD risk factors within the high-inequality setting of South Africa.

Electronic supplementary material

The online version of this article (10.1186/s12939-018-0741-0) contains supplementary material, which is available to authorized users.

Why Stress Remains an Ambiguous Concept: Reply to McEwen & McEwen (2016) and Cohen et al. (2016)

This reply to the commentaries by Cohen, Giannaros, and Manuck (2016, this issue) and McEwen and McEwen (2016, this issue) acknowledges investigators' reluctance to relinquish the term stress, despite the lack of agreement on its meaning and the evidence that is a sign of its presence. This brief reply urges scientists studying the exemplars of this ambiguous concept to search for robust relations that specify the type of event, the properties of the agent, the agent's circumstances, and the behavioral or biological consequences. The accumulation of these relations will reveal that the word stress adds little to our understanding.

Income inequality and depressive symptoms in South Africa: A longitudinal analysis of the National Income Dynamics Study

Research suggests that income inequality may detrimentally affect mental health. We examined the relationship between district-level income inequality and depressive symptoms among individuals in South Africa-one of the most unequal countries in the world-using longitudinal data from Wave 1 (2008) and Wave 3 (2012) of the National Income Dynamics Study. Depressive symptoms were measured using the Center for Epidemiological Studies of Depression Short Form while district Gini coefficients were estimated from census and survey sources. Age, African population group, being single, being female, and having lower household income were independently associated with higher depressive symptoms. However, in longitudinal, fixed-effects regression models controlling for several factors, district-level Gini coefficients were not significantly associated with depressive symptoms scores. Our results do not support the hypothesis of a causal link between income inequality and depressive symptoms in the short-run. Possible explanations include the high underlying levels of inequality in all districts, or potential lags in the effect of inequality on depression.

Race, Neighborhood Economic Status, Income Inequality and Mortality

Mortality rates in the United States vary based on race, individual economic status and neighborhood. Correlations among these variables in most urban areas have limited what conclusions can be drawn from existing research. Our study employs a unique factorial design of race, sex, age and individual poverty status, measuring time to death as an objective measure of health, and including both neighborhood economic status and income inequality for a sample of middle-aged urban-dwelling adults (N = 3675). At enrollment, African American and White participants lived in 46 unique census tracts in Baltimore, Maryland, which varied in neighborhood economic status and degree of income inequality. A Cox regression model for 9-year mortality identified a three-way interaction among sex, race and individual poverty status (p = 0.03), with African American men living below poverty having the highest mortality. Neighborhood economic status, whether measured by a composite index or simply median household income, was negatively associated with overall mortality (p<0.001). Neighborhood income inequality was associated with mortality through an interaction with individual poverty status (p = 0.04). While racial and economic disparities in mortality are well known, this study suggests that several social conditions associated with health may unequally affect African American men in poverty in the United States. Beyond these individual factors are the influences of neighborhood economic status and income inequality, which may be affected by a history of residential segregation. The significant association of neighborhood economic status and income inequality with mortality beyond the synergistic combination of sex, race and individual poverty status suggests the long-term importance of small area influence on overall mortality.

Inequalities of Income and Inequalities of Longevity: A Cross-Country Study

OBJECTIVES

We examined the effects of market income inequality (income inequality before taxes and transfers) and income redistribution via taxes and transfers on inequality in longevity.

METHODS

We used life tables to compute Gini coefficients of longevity inequality for all individuals and for individuals who survived to at least 10 years of age. We regressed longevity inequality on market income inequality and income redistribution, and we controlled for potential confounders, in a cross-sectional time-series sample of up to 28 predominantly Western developed countries and up to 37 years (1974-2011).

RESULTS

Income inequality before taxes and transfers was positively associated with inequality in the number of years lived; income redistribution (the difference between market income inequality and income inequality after taxes and transfers were accounted for) was negatively associated with longevity inequality.

CONCLUSIONS

To the extent that our estimated effects derived from observational data are causal, governments can reduce longevity inequality not only via public health policies, but also via their influence on market income inequality and the redistribution of incomes from the relatively rich to the relatively poor.