Abstract
INTRODUCTION: Obesity is a common disease and a known risk factor for many other conditions such as hypertension, type 2 diabetes, and cancer. Treatment options for obesity include lifestyle changes, pharmacotherapy, and surgical interventions such as bariatric surgery. In this study, we examine the use of prescription drugs and dietary supplements by the individuals with obesity. METHODS: We conducted a cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES) data 2003-2018. We used multivariate logistic regression to analyze the correlations of demographics and obesity status with the use of prescription drugs and dietary supplement use. We also built machine learning models to classify prescription drug and dietary supplement use using demographic data and obesity status. RESULTS: Individuals with obesity are more likely to take cardiovascular agents (OR = 2.095, 95% CI 1.989-2.207) and metabolic agents (OR = 1.658, 95% CI 1.573-1.748) than individuals without obesity. Gender, age, race, poverty income ratio, and insurance status are significantly correlated with dietary supplement use. The best performing model for classifying prescription drug use had the accuracy of 74.3% and the AUROC of 0.82. The best performing model for classifying dietary supplement use had the accuracy of 65.3% and the AUROC of 0.71. CONCLUSIONS: This study can inform clinical practice and patient education of the use of prescription drugs and dietary supplements and their correlation with obesity.