1979-LB: Factors Predicting Elevated LDL Cholesterol in a Type 1 Diabetes Cohort—A Cross-Sectional Study

Introduction & Objective: Type 1 diabetes (T1D) confers substantial cardiovascular disease (CVD) risk. Major U.S. guidelines recommend statin use in all people with T1D ages 40-75, with target low density lipoprotein (LDL) cholesterol level < 100 mg/dL. The objective of this study was to assess frequency of LDL above target and to examine demographic and socioeconomic characteristics associated with LDL above target in individuals with T1D.

Methods: We conducted a cross-sectional analysis of individuals with T1D ages 55-75 using Premier Healthcare Database (PHD) outpatient encounter data from January 2020 to December 2022. The outcome variable was LDL ≥ 100 mg/dL. Predictor variables included age, sex, race, ethnicity, CVD diagnosis, and insurance payor (Medicare/other government payor, Medicaid, Commercial, Managed Care, self-pay or other). Using SAS 9.4, a logistic regression model was used to determine covariates associated with LDL≥100 mg/dL after adjusting for other covariates.

Results: Of 5,344 individuals in the cohort (51.5% women, mean age 65.3 ± 5.9 years, and 6.3% with CVD diagnosis), 34.9% had LDL ≥100 mg/dL. Female sex (OR 1.59, 95% CI 1.42-1.77, p < 0.0001) and insurance coverage by Medicaid (OR 1.74, 95% CI 1.94-2.53, p < 0.01) were independently associated with increased odds of LDL above target. Older age (OR 0.98, 95% CI 0.97-0.99, p = 0.01) and CVD diagnosis (OR 0.60, 95% CI 0.46-0.77, p < 0.0001) were independently associated with reduced odds of LDL above target. Race and ethnicity were not associated with LDL above target.

Conclusion: A large percentage of this cohort at high-risk for CVD had elevated LDL, and factors independently associated with elevated LDL levels were female sex, Medicaid insurance, younger age, and lack of CVD diagnosis. Female sex or Medicaid insurance increased odds of elevated LDL by 59% and 74% respectively adjusting for other covariates. Further study to understand cause of these disparities is needed.