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Complex interrelationships between race, sex, obesity and depression have been well-documented. Because of differences in associations between socioeconomic status (SES) and health by race, determining the role of SES may help to further explicate these relationships. The aim of this study was to determine how race and income interact with obesity on depression. Combining data from the 2007-2014 National Health and Nutrition Examination Survey, depressive symptoms was measured with the Patient Health Questionnaire-9 and obesity was assessed as body mass index ≥30 kg/m 2 . Three-way interactions between race, income and obesity on depressive symptoms were determined using ordered regression models. Significant interactions between race, middle income and obesity (OR = 0.66, 95% CI = 0.22-1.96) suggested that, among white women, obesity is positively associated with depressive symptoms across income levels, while obesity was not associated with depression for African American women at any income level. Obesity was only associated with depressive symptoms among middle-income white men (OR = 1.44, 95% CI = 1.02-2.03) and among high-income African American men (OR = 4.65, 95% CI = 1.48-14.59). The associations between obesity and depressive symptoms vary greatly by race and income. Findings from this study underscore the importance of addressing obesity and depression among higher income African American men.

O besity rates in the U.S. are associated with area-level, food-related characteristics. Studies have previously examined the role of structural racism (policies/practices that advantaged White Americans and deprived other racial/ethnic minority groups), but racial inequalities in socioeconomic status (SES) is a novel indicator. The aim of this study is to determine the associations between racial inequalities in SES with obesity and obesogenic environments. Data from 2007⁻2014 County Health Rankings and 2012⁻2016 County Business Patterns were combined to assess the associations between relative SES comparing Blacks to Whites with obesity, and number of grocery stores and fast food restaurants in U.S. counties. Random effects linear and Poisson regressions were used and stratified by county racial composition. Racial inequality in poverty, unemployment, and homeownership were associated with higher obesity rates. Racial inequality in median income, college graduates, and unemployment were associated with fewer grocery stores and more fast food restaurants. Associations varied by county racial composition. The results demonstrate that a novel indicator of structural racism on the county-level is associated with obesity and obesogenic environments. Associations vary by SES measure and county racial composition, suggesting the ability for targeted interventions to improve obesogenic environments and policies to eliminate racial inequalities in SES.

In the US, African Americans have a higher prevalence of hypertension than Whites. Previous studies show that social support contributes to the racial differences in hypertension but are limited in accounting for the social and environmental effects of racial residential segregation. We examined whether the association between race and hypertension varies by the level of social support among African Americans and Whites living in similar social and environmental conditions, specifically an urban, low-income, racially integrated community. Using data from the Exploring Health Disparities in Integrated Communities-Southwest Baltimore (EHDIC-SWB) sample, we hypothesized that social support moderates the relationship between race and hypertension and the racial difference in hypertension is smaller as the level of social support increases. Hypertension was defined as having systolic blood pressure greater than 140 mmHg and/or diastolic blood pressure greater than 90 mmHg, or the participant reports of taking antihypertensive medication(s). The study only included participants that self-reported as “Black/African American” or “White.” Social support was measured as functional social support and marital status. After adjusting for demographics and health-related characteristics, we found no interaction between social support and race (DUFSS score, prevalence ratio 1.00; 95% confidence interval 0.99, 1.01; marital status, prevalence ratio 1.02; 95% confidence interval 0.86, 1.21); thus the hypothesis was not supported. A plausible explanation is that the buffering factor of social support cannot overcome the social and environmental conditions which the participants live in. Further, these findings emphasize social and environmental conditions of participants in EHDIC-SWB may equally impact race and hypertension.

Racial health inequities are not fully explained by socioeconomic status (SES) measures like education, income and wealth. The largest inequities are observed among African American and white college graduates suggesting that African Americans do not receive the same health benefits of education. African Americans do not receive the same income and wealth returns of college education as their white counterparts indicating a racial non-equivalence of SES that may affect health inequities. The aim of this study is to determine whether racial non-equivalence of SES mediates race inequities in self-rated health by education and sex. Using data from the 2007–2016 National Health and Nutrition Examination Survey in the United States, the mediation of the associations between race and self-rated health through household income ≥400% federal poverty line, homeownership, and investment income were assessed among college graduates and non-college graduates by sex. Indirect associations were observed among college graduate women (odds = 0.08, standard error (s.e.) = 0.03), and non-college graduate men (odds = 0.14, s.e. = 0.02) and women (odds = 0.06, s.e. = 0.02). Direct associations between race and self-rated health remained after accounting for household income and wealth indicators suggesting that race differences in income and wealth partially mediate racial inequities in self-rated health. This study demonstrates that the racial non-equivalence of SES has implications for health inequities, but the magnitude of indirect associations varied by sex. Other factors like discrimination, health pessimism and segregation should be considered in light of the racial non-equivalence of SES and racial inequities in self-rated health.

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Alok Bhargava responds to Desmond Tutu's Comparison of Climate Change as Developed Countries' "Climate Apartheid" On the Poor

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