Nonlinear Association Between Weekday Sleep Duration and COPD Risk: Evidence From NHANES 2017-2023

Chronic Obstructive Pulmonary Disease (COPD) is a major global health concern. Lifestyle factors play a pivotal role in its prevention. This research aims to explore the possible link between Weekday Sleep Duration (WSD) and the prevalence of COPD within the US population.

We employed data sourced from the NHANES during the 2017-2023 cycles. The research was centered around COPD. The primary exposure variable, WSD, was grouped by quartiles. Missing values were addressed using multiple imputation. Covariates related to WSD and COPD were pre-identified via a Directed Acyclic Graph (DAG), and highly collinear variables were removed using the Variance Inflation Factor (VIF). Least Absolute Shrinkage and Selection Operator (LASSO) regression further screened variables. Weighted logistic regression was employed to analyze the association between WSD and COPD. Sensitivity analysis tests the stability and reliability of results. Nonlinear relationships were evaluated using Restricted Cubic Splines (RCS) and threshold analysis, while subgroup analyses were performed to assess heterogeneity and validate results. Model performance was gauged by the Area Under the Receiver Operating Characteristic Curve (AUC).

After adjusting for all covariates in the weighted logistic regression analysis, we found that higher WSD was consistently correlated with increased prevalence of COPD (P=0.012; OR=1.740; 95% CI, 1.196-2.530). The sensitivity analysis confirms the reliability of our results. The RCS and threshold analysis results show a positive correlation between COPD and WSD (7.0-14.0 hours) (P=0.011; OR=1.12; 95% CI, 1.03-1.22). Subgroup analysis shows that among weekend catch-up sleep (P=0.000), there is a significant positive association between WSD and COPD prevalence. The ROC (AUC=0.811) results show that our model has good diagnostic performance.

WSD of 8.5-14 hours/day is associated with higher COPD risk. Prospective studies are needed to validate this novel insight for COPD prevention and treatment.