PC1147: Impact of Race on Cardiometabolic Risk Profile Within a Cohort of Black and Hispanic Adolescents with Different Adiposity Levels: Lifedoc Research Group

Background: Due to Tennessee’s high rates of overweight/obesity (37.7%) among children and adolescents, the prevalence of type 2 diabetes (T2D) and cardiometabolic risk factors (CMRF) have increased. Lifedoc Health (LDH) has successfully implemented a data-driven precision medicine model through several evidence generation initiatives. To refine and scale this self-sustaining model, it is necessary to characterize biological dissimilarities affecting high-risk, underserved populations. Using real-world data, this study describes the differences in the overall risk profile of Black/African American (AA) and Hispanic (H) adolescents with varying levels of adiposity.

Methods: Cross-sectional analysis of a 3-year standardized, pragmatically collected data (2018-2020 ± 6 wks.) from a multi-racial cohort of 2,332 adolescents aged 12-17 y (H: 68.5%, AA: 29.5%, C: 2.1%) receiving care in LDH was conducted. 50.3% were female (F) with a mean age of 13.9yrs ± 0.04. Exposures including gender, self-reported race, and adiposity by BMI percentile (BMI% per CDC) categorized according to NHANES: normal weight (NW), overweight (OW), obese (OB) and severely obese (SVOB). Hemoglobin A1C (A1c), 25-OH-vitamin D (VitD), Triglycerides (TG), total cholesterol (TC), LDL-C, HDL-C, high-sensitivity C-reactive protein (hsCRP), fibrinogen (Fib), liver enzymes (AST and ALT) were measured. AAP accepted criteria were used to classify elevated systolic (SBP) or diastolic blood pressure (DBP) and hypertension (HTN) via BP percentiles (BP%), impaired glucose metabolism via A1c (IGM= prediabetes (preD) or T2D), dyslipidemia, and metabolic syndrome (metS). Means were calculated from last observation, adjusted by age, gender, adiposity (and height for BP), and compared via T-test. Prevalence estimates were calculated for classified biological markers and similarly adjusted, with comparisons via X2. Odds ratio for CMRF among groups were compared via Logistic Regression (95% CI).

Results: Mean weight was 70.9 kg, BMI% 78.8, with 40.6% of subjects NW, 20.2% OW, 25.0% OB, and 14.2% SVOB. Significant differences in means and proportions between AA and H are summarized in tables 1 and 2 below. Results of a linear regression showed that AA carried higher odds than H (reported as OR, 95% CI) of IGM (3.01, 2.09-4.32). H exhibited significantly higher odds of High AST/ALT (5.88, 0.1-0.29), Dyslipidemia (2.56, 0.3-0.52) and metS (1.96, 0.37-0.72). Most significantly, increased adiposity was associated with an exponential step-wise increase in odds of all CMRF compared to NW.

Conclusion: AA had significantly greater odds of developing SVOB, HTN, PreD/DM, subclinical inflammation, and higher LDL-C, while H tend to be at higher risk for fatty liver, high TG and low HDL-C. Development of precision interventions for cardiometabolic conditions in adolescents requires consideration of complexities in the interaction between biological, demographic and social determinants. Further analysis with greater inclusion of social determinants may be required to develop predictive models for effective intervention.