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.
IntroductionObesity 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.MethodsWe conducted a cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES) data 2003-2014. 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 predict prescription drug and dietary supplement use using demographic data and obesity status.ResultsIndividuals with obesity are more likely to take cardiovascular agents (OR=1.265, 95% CI 1.222-1.311) and metabolic agents (OR=1.398, 95% CI 1.343-1.456) than individuals without obesity. The best performing prediction model for predicting prescription drugs had the accuracy of 74.5% and the AUROC of 0.817.ConclusionsThis study can inform clinical practice and patient education of the use of prescription drugs and dietary supplements and their correlation with obesity.
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