Association between monocyte-to-high-density lipoprotein-cholesterol ratio and chronic obstruc tive pulmonary disease findings from the National Health and Nutrition Examination Survey 2001–2023

Background: Chronic obstructive pulmonary disease (COPD) is a global public health challenge, with its pathogenesis driven by complex inflammatory pathways. This study aimed to investigate the potential association between MHR and COPD risk while evaluating its utility as a predictive marker for COPD progression. Methods: This study utilized data from the National Health and Nutrition Survey (NHANES) spanning from 2001 to 2023. Control for con-founders by the propensity score matching (PSM) method. The relationship between monocyte-to-high-density lipoprotein-cholesterol ratio (MHR) and chronic obstructive pulmonary disease (COPD) was analyzed using multivariate logistic regression models. A restricted cubic spline（RCS）model was applied to explore the dose-response relationship between MHR and COPD risk. Subgroup analyses revealed significant heterogeneity in the associations across different predefined groups, indicating varying degrees of correlation between MHR and COPD depending on specific subgroup characteristics. To evaluate the relative contribution of MHR as a predictor of COPD risk, an XGBoost model was constructed to assess its predictive importance. Results: The cross-sectional analysis included a total of 15,047 participants, among whom 582 were diagnosed with chronic obstructive pulmonary disease (COPD). The monocyte-to-high-density lipoprotein-cholesterol ratio (MHR) of COPD patients was significantly higher compared to non-COPD participants (0.58 ± 0.38 vs. 0.49 ± 0.25, P < 0.001). Multivariate logistic regression analysis revealed that MHR was an independent risk factor for COPD diagnosis (odds ratio = 2.134; 95% confidence interval: 1.115–4.378; P = 0.0327). The restricted cubic spline (RCS) model demonstrated a significant linear trend in the association between MHR and COPD risk (P for overall trend < 0.001), as well as a similarly significant nonlinear relationship (P for non-linear term = 0.02). Furthermore, the XGBoost model identified MHR as an important predictor of COPD diagnosis, with an average SHAP score of 0.0174. Conclusions: There was an association between MHR and COPD, indicating its potential utility as a clinical marker in assessing disease risk.