Race and other sociodemographic categories are differentially linked to multiple dimensions of interpersonal-level discrimination: Implications for intersectional, health research.

OBJECTIVES: To examine whether intersections of race with other key sociodemographic categories contribute to variations in multiple dimensions of race- and non-race-related, interpersonal-level discrimination and burden in urban-dwelling African Americans and Whites. METHODS: Data from 2,958 participants aged 30-64 in the population-based Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study were used to estimate up to four-way interactions of race, age, gender, and poverty status with reports of racial and everyday discrimination, discrimination across multiple social statuses, and related lifetime discrimination burden in multiple regression models. RESULTS: We observed that: 1) African Americans experienced all forms of discrimination more frequently than Whites, but this finding was qualified by interactions of race with age, gender, and/or poverty status; 2) older African Americans, particularly African American men, and African American men living in poverty reported the greatest lifetime discrimination burden; 3) older African Americans reported greater racial discrimination and greater frequency of multiple social status-based discrimination than younger African Americans; 4) African American men reported greater racial and everyday discrimination and a greater frequency of social status discrimination than African American women; and, 5) White women reported greater frequency of discrimination than White men. All p's < .05. CONCLUSIONS: Within African Americans, older, male individuals with lower SES experienced greater racial, lifetime, and multiple social status-based discrimination, but this pattern was not observed in Whites. Among Whites, women reported greater frequency of discrimination across multiple social statuses and other factors (i.e., gender, income, appearance, and health status) than men. Efforts to reduce discrimination-related health disparities should concurrently assess dimensions of interpersonal-level discrimination across multiple sociodemographic categories, while simultaneously considering the broader socioecological context shaping these factors.

Lifetime discrimination burden, racial discrimination, and subclinical cerebrovascular disease among African Americans.

OBJECTIVE: Explore interactive relations of lifetime discrimination burden and racial discrimination-chronic stressors among African Americans (AAs)-and age with MRI-assessed white matter lesion volume (WMLV), a prognostic indicator of poor clinical brain health outcomes. METHOD: AAs (N = 71; 60.6% female, mean age = 50) participating in the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) SCAN study underwent quantitative magnetic resonance imaging coded for WMLV. Participants self-reported lifetime discrimination burden and racial discrimination approximately 5 years earlier. Multivariable regression models assessed interactions of linear and quadratic effects of discrimination and age with WMLV adjusted for sex and socioeconomic status. RESULTS: Findings revealed significant interactive relations of age and (a) quadratic, lifetime discrimination burden, B = .05, p = .014, ηpartial2 = .092, and (b) quadratic, racial discrimination, B = .03, p = .001, ηpartial2 = .155, with WMLV. Among older AA, increases in lifetime discrimination burden and racial discrimination were associated with increases in WMLV (ps < .03); in younger AA, decreasing levels of racial discrimination were related to increases in WMLV (p = .006). CONCLUSIONS: Among older AA, as lifetime discrimination burden and racial discrimination increased, so did WMLV. However, in younger AA, decreases in racial discrimination were associated with increased WMLV. Elucidation of complex mechanistic underpinnings, including potentially differential impacts of the acknowledgment versus suppression or underreporting of discriminatory experiences, among AA of different age cohorts, is critical to understanding the present pattern of findings. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Cross-sectional relations of race and poverty status to cardiovascular risk factors in the Healthy Aging in Neighborhoods of Diversity across the Lifespan (HANDLS) study.

BACKGROUND: Examine interactive relations of race and poverty status with cardiovascular disease (CVD) risk factors in a socioeconomically diverse sample of urban-dwelling African American (AA) and White adults. METHODS: Participants were 2,270 AAs and Whites (57% AA; 57% female; ages 30-64 years) who completed the first wave of the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study. CVD risk factors assessed included body mass index (BMI), waist circumference (WC), total cholesterol (TC), high- and low-density lipoprotein cholesterol (HDL-C, LDL-C), triglycerides (TG), glycated hemoglobin (HbA1c), high-sensitivity C-reactive protein (CRP), and systolic, diastolic, and pulse pressure (SBP, DBP, PP). Interactive and independent relations of race, poverty status, and sex were examined for each outcome via ordinary least squares regression adjusted for age, education, literacy, substance use, depressive symptoms, perceived health care barriers, medical co-morbidities, and medications. RESULTS: Significant interactions of race and poverty status (p's < .05) indicated that AAs living in poverty had lower BMI and WC and higher HDL-C than non-poverty AAs, whereas Whites living in poverty had higher BMI and WC and lower HDL-C than non-poverty Whites. Main effects of race revealed that AAs had higher levels of HbA1c, SBP, and PP, and Whites had higher levels of TC, LDL-C and TG (p's < .05). CONCLUSION: Poverty status moderated race differences for BMI, WC, and HDL-C, conveying increased risk among Whites living in poverty, but reduced risk in their AA counterparts. Race differences for six additional risk factors withstood extensive statistical adjustments including SES indicators.