Investigating the role of depression in obstructive sleep apnea and predicting risk factors for OSA in depressed patients: machine learning-assisted evidence from NHANES.

ABSTRACT:

Objective

The relationship between depression and obstructive sleep apnea (OSA) remains controversial. Therefore, this study aims to explore their association and utilize machine learning models to predict OSA among individuals with depression within the United States population.

Methods

Cross-sectional data from the American National Health and Nutrition Examination Survey were analyzed. The sample included 14,492 participants. Weighted logistic regression analysis was performed to examine the association between OSA and depression.Additionally, interaction effect analyses were conducted to assess potential interactions between each subgroup and the depressed population.Multiple machine learning models were constructed within the depressed population to predict the risk of

SUBMITTER: Cheng X 

PROVIDER: S-EPMC12512373 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature