Discovering Vitamin-D-Deficiency-Associated Factors in Korean Adults Using KNHANES Data Based on an Integrated Analysis of Machine Learning and Statistical Techniques.

ABSTRACT: Background/Objectives: Vitamin D deficiency (VDD) is a global health concern associated with metabolic disease and immune dysfunction. Despite known risk factors like limited sun exposure, diet, and lifestyle, few studies have explored these factors comprehensively on a large scale. This cross-sectional study aimed to identify VDD-associated factors in South Korea via an integrative approach of machine learning and statistical analyses using Korea National Health and Nutrition Examination Survey (KNHANES) IX-1 data. Methods: Using the KNHANES dataset, six machine learning algorithms were applied to evaluate VDD (serum 25[OH]D3 < 20 ng/mL)-associated factors through feature importance scores. Thereafter, multivariate linear and logistic regression models were applied to the da

SUBMITTER: Ahn H 

PROVIDER: S-EPMC11858147 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature