Abstract P160: Associations Between Metabolic Syndrome Severity And Race/ethnicity, Socioeconomic, And Lifestyle Factors

Abstract

Introduction/Purpose: Metabolic syndrome (MetS) is a disorder characterized by a cluster of cardiometabolic conditions that increase the risk of cardiovascular disease and diabetes. While MetS is treatable through lifestyle changes and medication, factors of race/ethnicity, socioeconomic, and lifestyle may influence MetS severity. Methods: The National Health and Nutrition Examination Survey (NHANES) 2015-2016 dataset was used for this secondary data analysis. Weighted data from individuals aged ≥ 20, not pregnant during the time of the assessment, with self-reported Non-Hispanic (NH) white, NH black, or Hispanic race/ethnicity, and with the variables needed to calculate MetS severity were included in the analysis (N=1850). Severity of MetS was determined using the formula developed by Gurika and DeBoer (2014) and expressed as a Z-score adjusted for sex and race. The severity score includes systolic blood pressure, triglycerides, HDL cholesterol, glucose, and body mass index. Socioeconomic variables included education level and the ratio between annual household income and poverty level. Lifestyle factors included sleep duration, dietary quality, sedentary time, and meeting the physical activity (PA) recommendation of 500 MET-mins/week (yes/no). Z-scores were converted to percentiles, which were categorized into quartiles. Regression analysis was used to examine the associations between MetS severity and race/ethnicity, socioeconomic, and lifestyle factors. Results: Based on weighted data, prevalence of MetS severity >75 th percentile differed across age (20% for 20-40 y/o, 36.4% for 41-60 y/o, 33.0% for 61-80 y/o) and across racial/ethnic (29.4% for NH white, 29.1% for NH black, and 34.9% for Hispanic) groups. Mean MetS severity scores were significantly different between the age and race/ethnicity groups (p <. 001 and p = .014, respectively). While MetS severity scores were not significantly different among the four income to poverty-index ratio groups, the difference between the lowest (≤ 133%) and highest (≥ 500%) group was significantly different (p = .02). In the regression model, a higher quality diet (p <.001), meeting the PA recommendations (p = .008), and higher education level (p = .027) were associated with lower mean MetS severity score. After adjusting for socioeconomic and lifestyle factors, being in the Hispanic race/ethnicity group was associated with higher MetS severity scores (p = .020) compare to being in the NH white group. Conclusions: Diet, physical activity, and educational level were associated with MetS severity score. After adjusting for socioeconomic and lifestyle factors, being in the Hispanic group was associated with the highest MetS severity scores. Research and preventive efforts should focus on groups at increased risk for MetS and severity. Culturally appropriate education and interventions are needed to address this health inequity.