0620 Is SVI a Risk Factor for Sleep and Cardiometabolic Health Among Blacks?. (25th May 2022)

• Record Type: Journal Article
• Authors: Locklear, Clarence; Jin, Peng; Seixas, Azizi; Briggs, Anthony; Rogers, April; Turner, Arlener; Blanc, Judite; Jean-Louis, Girardin
• Is Part Of: Sleep. Volume 45(2022)Supplement 1
• Page Start: A271
• Page End: A272
• Publication Date: 2022-05-25
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsac079.617
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: The Social Vulnerability Index (SVI) is a novel metric that incorporates a multitude of population factors to predict the susceptibility of communities to deleterious effects of disaster, natural hazards, and environmental insult. Studies show socioeconomic status (SES), an important component of SVI, is a risk factor for cardiometabolic disease and sleep quality. Objectives: This study examined the effect of SVI on cardiometabolic and sleep health among Blacks. Methods: We utilized harmonized data extracted from two NIH-funded studies enrolling Blacks (i.e., MetSO and PEERS-ED registries). Participants (N=1, 497) included New York residents; 65% were male, with a mean(SD) age of 55(±16.2). Data were collected via self-reports (e.g., ARES questionnaire) for sleep quality/duration and cardiometabolic factors (e.g., weight and diet). SVI components included SES, household composition, minority status, and housing type. Mixed-effect logistic regression models were applied, which assessed the effect of SVI and its many subcomponents on each health-related variable of interest. The model was adjusted for age, sex, and education to account for the effects of these factors overlapping in the SVI subcomponents. Results: Approximately 81% of the sample population was obese, 37.9% were diabetic, 62.3% had a history of hypertension, and 18.4% with a heart disease. Regarding sleep health, 7.7% suffered from sleep apnea, 66.6% were short sleepers, 6.64% were long sleepers, and 14.2% reported insomnia. They had a mean(SD) sleep time of 5.92(±2.05) hours. "Overall SVI" was associated with hypertension (OR=3.98) and "housing type & transport" was correlated with heart disease (OR=4.44) prior to adjusting the model. Applying the adjusted model, "minority status & language" predicts obesity (OR=5.32). Also, "overall SVI" and "SES" were associated with diabetes (OR=3.26; OR=2.71) and hypertension (OR=4.00; OR=3.95). "Household composition" approaches significance as a predictor for sleep apnea (unadjusted - OR=0.26; adjusted - OR=0.26) despite the relatively low case proportion. Conclusion: SVI seems to be a good indicator of cardiometabolic health among Blacks. However, it is likely a poor marker for sleep health in that population, although trends were observed suggesting that it might play an important role. Further studies are necessary to elucidate the role of SVI on sleep health among Blacks. Support (If Any): R01HL142066, R01HL095799, RO1MD004113, R01HL152453