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Objective:  The association between social norms and dietary behaviors is well-documented, but few studies examine the role of race. The aim of this study was to determine the interrelationships among race, social norms, and dietary behaviors.  Methods:  We used data from the Healthy Friends Network Study (a pilot study of women attending a southern university). Dietary behaviors, social norms, and self-identified race were obtained.  Results:  African Americans had lower odds of daily vegetable (OR = 0.55, 95% CI = 0.38-0.79) and fruit consumption (OR = 0.45, 95% CI = 0.30-0.67), but no race difference in frequent consumption of fatty/fried/salty/sugary foods was observed in fully adjusted models. Proximal descriptive norms were associated with all dietary behaviors, but distal injunctive social norms were associated with lower odds of frequent unhealthy food consumption (OR = 0.10, 95% CI = 0.05-0.21). Race differences in family descriptive norms were found to mediate race differences in vegetable and fruit consumption by 7%-9%. However, race differences in friend and family injunctive norms mediated 20%-50% of the effects of race on frequent unhealthy food consumption.  Conclusions:  Proximal injunctive norms account for race differences in unhealthy food consumption. Future studies should further explicate the mechanisms and seek to utilize social norms in behavior change interventions.

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.

Racial disparities in obesity among men are accompanied by positive associations between income and obesity among Black men only. Race also moderates the positive association between marital status and obesity. This study sought to determine how race, income, and marital status interact on obesity among men. Using data from the 2007 to 2014 National Health and Nutrition Examination Survey, obesity was measured as body mass index ≥30 kg/m 2  among 6,145 Black and White men. Income was measured by percentage of the federal poverty line and marital status was categorized as currently, formerly, or never married. Using logistic regression and interaction terms, the associations between income and obesity were assessed by race and marital status categories adjusted for covariates. Black compared to White (OR = 1.19, 95% CI [1.03, 1.38]), currently married compared to never married (OR = 1.45, 95% CI [1.24, 1.69]), and high-income men compared to low income men (OR = 1.26, 95% CI [1.06, 1.50]) had higher odds of obesity. A three-way interaction was significant and analyses identified that income was positively associated with obesity among currently married Black men and never married White men with the highest and lowest probabilities of obesity, respectively. High-income, currently married Black men had higher obesity rates and may be at increased risk for obesity-related morbidities.

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.

Background Recent years have seen increased interest in the role of neighborhood factors in chronic diseases such as cancers. Less is known about the role of neighborhood factors beyond individual demographics such as age or education. It is particularly important to examine neighborhood effects on health among African American men and women, considering the disproportionate impact of cancer on this group. This study evaluated the unique contribution of neighborhood characteristics (e.g., racial/ethnic diversity, income) beyond individual demographics, to cancer control behaviors in African American men and women. Methods Individual-level data were drawn from a national survey (N = 2,222). Participants’ home addresses were geocoded and merged with neighborhood data from the American Community Survey. Multi-level regressions examined the unique contribution of neighborhood characteristics beyond individual demographics, to a variety of cancer risk, prevention, and screening behaviors. Results Neighborhood racial/ethnic diversity, median income, and percentage of home ownership made modest significant contributions beyond individual factors, in particular to smoking status where these factors were associated with lower likelihood of smoking (ps < .05). Men living in neighborhoods with older residents, and greater income and home ownership were significantly more likely to report prostate specific antigen testing (ps < .05). Regional analyses suggested different neighborhood factors were associated with smoking status depending on the region. Conclusion Findings provide a more nuanced understanding of the interplay of social determinants of health and neighborhood social environment among African American men and women, with implications for cancer control interventions to eliminate cancer disparities.

Recent attention to the interrelationship between racism, socioeconomic status (SES) and health has led to a small, but growing literature of empirical work on the role of structural racism in population health. Area-level racial inequities in SES are an indicator of structural racism, and the associations between structural racism indicators and self-rated health are unknown. Further, because urban-rural differences have been observed in population health and are associated with different manifestations of structural racism, explicating the role of urban-rural classification is warranted. This study examined the associations between racial inequities in SES and self-rated health by county urban-rural classification. Using data from County Health Rankings and American Communities Surveys, black-white ratios of SES were regressed on rates of fair/poor health in U.S. counties. Racial inequities in homeownership were negatively associated with fair/poor health ( β  = −0.87, s.e. = 0.18), but racial inequities in unemployment were positively associated with fair/poor health ( β  = 0.03, s.e. = 0.01). The associations between structural racism and fair/poor health varied by county urban-rural classification. Potential mechanisms include the concentration of resources in racially segregated counties with high racial inequities that lead to better health outcomes, but are associated with extreme black SES disadvantage. Racial inequities in SES are a social justice imperative with implications for population health that can be targeted by urban-rural classification and other social contextual characteristics.

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.