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Discrimination, High-Effort Coping, and Cardiovascular Risk Profiles in the Jackson Heart Study: a Latent Profile
Amber J Johnson1, Kenya McCloyn2, Mario Sims3
1Department of Health Science, California State University, Long Beach, 1250 Bellflower Blvd. FOA-13, Long Beach, CA, 90840, USA. amber.johnson@csulb.edu.
Abstract:
African Americans exhibit heightened risk of cardiovascular disease (CVD) necessitating further examination of biological pathways contributing to CVD incidence. An integrated specificity model suggests discrimination elicits psychophysiological responses that contribute to allostatic load (AL) but may differ by level of perceived discrimination and coping style. Differing psychophysiological risk responses may contribute to varying CVD risk patterns overtime. This study sought to (1) determine CVD risk profiles using AL biomarkers and (2) determine the extent discrimination and high-effort coping (HEC) contribute to inclusion in these profiles. Using Jackson Heart Study data (N = 4476), a latent profile analysis (LPA) using AL indicators was conducted to identify CVD risk profiles. Multinomial logistic regression analysis estimated the odds of risk profile inclusion according to everyday discrimination, lifetime discrimination, discrimination burden, and high-effort coping, adjusting for sex, age, body mass index, and smoking status. LPA identified five profiles exhibiting inflammatory, diabetes, hyperlipidemia, hypertension, and low risk. Greater lifetime discrimination lowered odds of inclusion in the inflammatory risk profile relative to the low risk profile (OR = .82, 95% CI [.73-.93]). Greater HEC increased odds of inclusion in the hyperlipidemia (OR = 1.03, 95% CI [1.00-1.05]) and hypertension (OR = 1.02, 95% CI [1.00-1.04]) risk profiles. Greater discrimination burden with greater HEC increased the likelihood of inclusion in the inflammatory risk profile (OR = 1.07, 95% = [1.06-1.13]). The study supports the use of an integrated specificity model to examine perceived discrimination and underlying CVD risk profiles among African American populations.
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