Tao Xinxin, Ye Xianwei
School of Clinical Medicine, Guizhou Medical University, Guiyang, Guizhou, China.
Department of Respiratory and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Front Nutr. 2025 May 15;12:1563692. doi: 10.3389/fnut.2025.1563692. eCollection 2025.
This research aims to explore the possible link between Vitamin C Intake (VCI) and the incidence of Chronic Obstructive Pulmonary Disease (COPD) in Americans aged over 20.
This study analyzed data from 10,757 participants with or without COPD from NHANES (2017-2023). The primary exposure variable, VCI, was grouped by quartiles. Missing data were handled via multiple imputations. A Directed Acyclic Graph (DAG) was used to pre-identify VCI -and COPD-related covariates. Variance Inflation Factor (VIF) eliminated highly collinear variables. Machine learning methods (LASSO, Random Forest, and XGBoost) screened variables. A weighted multivariate logistic regression model explored the VCI-COPD relationship. Restricted Cubic Spline (RCS) and threshold analysis examined non-linear relationships. Subgroup analysis and interaction tests ensured reliability. A nomogram showed the predictive factors' importance for COPD. Model performance was reported using the Area Under the Receiver Operating Characteristic Curve (AUC).
In all models, we found that there was a negative correlation between VCI (≥50.1 mg/day) and the prevalence of COPD. The RCS and threshold analysis results show a negative correlation between COPD and VCI (≤135.6 mg/day). Subgroup analysis shows a negative association between VCI and the prevalence of COPD, specifically among females and individuals with dietary fiber intake in the second quartile (Q2). The AUC results show that our model has good diagnostic performance.
The cross-sectional design limits causal inference and lacks external validation.
An elevated VCI within 50.1-135.6 is linked to a decreased risk for COPD.
本研究旨在探讨20岁以上美国人的维生素C摄入量（VCI）与慢性阻塞性肺疾病（COPD）发病率之间的潜在联系。
本研究分析了来自美国国家健康与营养检查调查（NHANES，2017 - 2023年）的10757名有或无慢性阻塞性肺疾病参与者的数据。主要暴露变量VCI按四分位数分组。通过多重插补处理缺失数据。使用有向无环图（DAG）预先识别与VCI和COPD相关的协变量。方差膨胀因子（VIF）消除高度共线变量。机器学习方法（LASSO、随机森林和XGBoost）进行变量筛选。采用加权多变量逻辑回归模型探讨VCI与COPD的关系。使用受限立方样条（RCS）和阈值分析检查非线性关系。亚组分析和交互作用检验确保结果的可靠性。列线图显示了预测因素对COPD的重要性。使用受试者工作特征曲线下面积（AUC）报告模型性能。
在所有模型中，我们发现VCI（≥50.1毫克/天）与COPD患病率之间存在负相关。RCS和阈值分析结果显示COPD与VCI（≤135.6毫克/天）之间存在负相关。亚组分析显示VCI与COPD患病率之间存在负相关，特别是在女性和膳食纤维摄入量处于第二四分位数（Q2）的个体中。AUC结果表明我们的模型具有良好的诊断性能。
横断面设计限制了因果推断，且缺乏外部验证。
VCI在50.1 - 135.6范围内升高与COPD风险降低相关。
