Body mass index and diet-related inflammation as predictors of sleep disorders: A cross-sectional study

作者：Yiren Bao, Bo Liang, Heran Zhou, Xueyan Huang, Yankai Dong, Rui Wang · 发表于：Medicine · 年份：2026 · DOI：10.1097/md.0000000000047924 · 研究领域：Sleep and related disorders、Nutritional Studies and Diet、Obstructive Sleep Apnea Research

This study examines diet as a key risk factor for sleep disorders and integrates physiological indicators to develop a machine learning (ML)-based model for targeted public health interventions. Data from 5158 2011 to 2014 National Health and Nutrition Examination Survey (NHANES) participants were analyzed. Dietary, lifestyle, and physiological variables used to build sleep disorder prediction models with random forest, extreme gradient boosting, light gradient boosting machine, and logistic regression. Model interpretability was assessed using Shapley additive explanations (SHAP). Key predictors were further analyzed using progressive modeling and least absolute shrinkage and selection operator (LASSO) regression. All ML models showed acceptable-to-excellent discrimination (area under the receiver operating characteristic curve: 0.744-1.000), with light gradient boosting machine achieving the highest performance (area under the receiver operating characteristic curve = 1.000). SHAP analysis showed that dietary inflammatory index (DII), body mass index (BMI), and age were positively associated with sleep disorder risk, while mean arterial pressure was negatively associated. In progressively adjusted logistic regression models, BMI was consistently positively associated with sleep disorders (model 3 odds ratio [OR] = 1.065, 95% confidence interval [CI]: 1.050-1.080; P < .001), whereas DII was associated with sleep disorders primarily in less-adjusted models (model 1 OR = 1.099...