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Therapeutic Area: ASCVD/CVD in Special Populations Background: Association between socioeconomic status and cardiovascular diseases (CVD) is well-documented. Racial disparities in prevalence and outcomes of CVD have also been extensively studied. The intersection of income, race, and CVD is relatively underexplored. Hence, we aimed to study the prevalence of CVD and associated risk factors among different races/ethnicities across different income groups. Methods: This retrospective analysis included data from participants from the National Health and Nutrition Examination Survey from 2005-2018. Adults ≥20 years who identified as non-Hispanic (NH) White, NH Black, or Hispanic (Mexican-American and other Hispanics) were included. Family income to poverty ratio (PIR) was calculated by dividing family (or individual) income by poverty guidelines specific to the survey year and used as a measure of socioeconomic status. The participants were divided into four quartiles based on PIR 3.9 (highest income). Weighted logistic regression was performed to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to determine the association of race/ethnicity and CVD and associated risk factors in each quartile. Models were adjusted for age, sex, race, health insurance, marital status, citizenship status, and level of education and PIR. Results: We included 31,884 unweighted participants that corresponded to 191,307,167 weighted, nationally representative participants. Of these, 8,009 (weighted 16.3%), 7,967 (weighted 19.2%), 7,944 (weighted 26.9%), and 7,964 (weighted 37.5%) participants belonged to 1st, 2nd, 3rd, and 4th quartiles respectively. The proportion of NH-Whites increased with increasing PIR quartiles whereas the proportion of NH-Blacks and Hispanics decreased with increasing PIR quartiles. In adjusted analyses, the prevalence odds of diabetes mellitus (DM), hypertension, coronary artery disease (CAD), congestive heart failure (CHF), and stroke decreased in a step-wise manner from 1st to 4th PIR quartile. Overall, NH Blacks had higher prevalence odds of DM, hypertension, obesity, CHF, and stroke compared to NH Whites, whereas NH Whites had higher prevalence odds of CAD and dyslipidemia compared to NH Blacks (Figure 1). The model testing for PIR-race/ethnicity interaction revealed that PIR-race/ethnicity interaction was significant for obesity (P-interaction 0.002) and diabetes mellitus (P-interaction 0.027) (Figure 2). The difference in prevalence odds between NH White adults and NH Black adults was greater for obesity and diabetes mellitus in the highest PIR quartile compared to the lowest PIR quartile. PIR-race/ethnicity interaction for stroke was 0.053 with the difference in prevalence odds between NH White adults and NH Black adults being greater in the higher PIR quartiles compared to the lowest PIR quartile. Conclusions: The difference in prevalence between NH White and NH Black adults was greater for diabetes mellitus, obesity and stroke in the highest PIR quartile compared to the lowest PIR quartile. These data suggest a complex interplay between race/ethnicities and income inequalities resulting in disparities in CVD.

Therapeutic Area: ASCVD/CVD in Special Populations Background: Association between socioeconomic status and cardiovascular diseases (CVD) is well-documented. Racial disparities in prevalence and outcomes of CVD have also been extensively studied. The intersection of income, race, and CVD is relatively underexplored. Hence, we aimed to study the prevalence of CVD and associated risk factors among different races/ethnicities across different income groups. Methods: This retrospective analysis included data from participants from the National Health and Nutrition Examination Survey from 2005-2018. Adults ≥20 years who identified as non-Hispanic (NH) White, NH Black, or Hispanic (Mexican-American and other Hispanics) were included. Family income to poverty ratio (PIR) was calculated by dividing family (or individual) income by poverty guidelines specific to the survey year and used as a measure of socioeconomic status. The participants were divided into four quartiles based on PIR 3.9 (highest income). Weighted logistic regression was performed to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to determine the association of race/ethnicity and CVD and associated risk factors in each quartile. Models were adjusted for age, sex, race, health insurance, marital status, citizenship status, and level of education and PIR. Results: We included 31,884 unweighted participants that corresponded to 191,307,167 weighted, nationally representative participants. Of these, 8,009 (weighted 16.3%), 7,967 (weighted 19.2%), 7,944 (weighted 26.9%), and 7,964 (weighted 37.5%) participants belonged to 1st, 2nd, 3rd, and 4th quartiles respectively. The proportion of NH-Whites increased with increasing PIR quartiles whereas the proportion of NH-Blacks and Hispanics decreased with increasing PIR quartiles. In adjusted analyses, the prevalence odds of diabetes mellitus (DM), hypertension, coronary artery disease (CAD), congestive heart failure (CHF), and stroke decreased in a step-wise manner from 1st to 4th PIR quartile. Overall, NH Blacks had higher prevalence odds of DM, hypertension, obesity, CHF, and stroke compared to NH Whites, whereas NH Whites had higher prevalence odds of CAD and dyslipidemia compared to NH Blacks (Figure 1). The model testing for PIR-race/ethnicity interaction revealed that PIR-race/ethnicity interaction was significant for obesity (P-interaction 0.002) and diabetes mellitus (P-interaction 0.027) (Figure 2). The difference in prevalence odds between NH White adults and NH Black adults was greater for obesity and diabetes mellitus in the highest PIR quartile compared to the lowest PIR quartile. PIR-race/ethnicity interaction for stroke was 0.053 with the difference in prevalence odds between NH White adults and NH Black adults being greater in the higher PIR quartiles compared to the lowest PIR quartile. Conclusions: The difference in prevalence between NH White and NH Black adults was greater for diabetes mellitus, obesity and stroke in the highest PIR quartile compared to the lowest PIR quartile. These data suggest a complex interplay between race/ethnicities and income inequalities resulting in disparities in CVD.