Abstract
OBJECTIVES: Although lifestyle modification programs are widely implemented for diabetes prevention, the contributions of individual lifestyle factors remain unclear. This study investigated lifestyle risk factors for prediabetes and employed a regression-based approach for estimating their population-attributable fractions (PAFs) using nationally representative data. METHODS: We analyzed data from 3104 adults aged ≥30 years without diabetes from the 2022 Korea National Health and Nutrition Examination Survey. Seven lifestyle factors were assessed: body weight, alcohol consumption, smoking, physical activity, sleep duration, vegetable intake, and breakfast consumption. Prediabetes was defined as fasting blood glucose of 100-125 mg/dL or hemoglobin A1c levels of 5.7-6.4%. Complex survey-adjusted logistic regression was used to identify significant lifestyle risk factors, and their PAFs were estimated using a regression-based sequential method. RESULTS: Five lifestyle factors were significantly associated with prediabetes: abnormal body weight (odds ratio [OR], 2.05; 95% confidence interval [CI], 1.68 to 2.50), excessive alcohol consumption (OR, 1.27; 95% CI, 1.00 to 1.62), smoking (OR, 1.35; 95% CI, 1.07 to 1.71), insufficient exercise (OR, 1.26; 95% CI, 1.05 to 1.51), and irregular breakfast consumption (OR, 1.31; 95% CI, 1.08 to 1.59). In sequential PAF estimation, abnormal body weight had the largest contribution (22.2%; 95% CI, 16.2 to 28.2), followed by smoking (6.4%; 95% CI, 1.1 to 11.6), insufficient exercise (5.8%; 95% CI, 1.2 to 10.5), irregular breakfast consumption (4.9%; 95% CI, 0.5 to 9.2), and excessive alcohol consumption (3.6%; 95% CI, 0.1 to 7.4). These results remained consistent in sensitivity analyses including undiagnosed diabetes cases. CONCLUSIONS: Abnormal body weight emerged as the largest contributor to prediabetes (PAF>20%). Diabetes prevention programs in Korea should prioritize weight management within a comprehensive approach to lifestyle modification.