Zhang Pei
Department of Gynaecology, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China.
Front Nutr. 2025 Jul 31;12:1619742. doi: 10.3389/fnut.2025.1619742. eCollection 2025.
BACKGROUND: Some studies have shown that dietary antioxidants may prevent the occurrence of Human Papillomavirus (HPV) infection. However, the relationship between the composite dietary antioxidant index (CDAI) and HPV infection among adult women in the United States remains unknown. METHODS: Participants from the National Health and Nutrition Examination Survey (NHANES) during 2003-2016 were included. Multivariable logistic regression, restricted cubic spline (RCS) regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were used to analyze the associations between CDAI and its sub-components and HPV infection. In addition, nine machine learning (ML) methods were employed to construct predictive models, and SHapley Additive exPlanations (SHAP) was used to further interpret the optimal model. RESULTS: This study enrolled 9,224 adult female participants. After adjusting for multiple confounding variables, CDAI was independently negatively associated with HPV infection (OR: 0.98, 95%CI: 0.97-0.99, = 0.01). RCS indicated an L-shaped association between CDAI and HPV infection. In the WQS model, the WQS index of CDAI was still robustly negatively associated with HPV infection (OR: 0.78, 95%CI: 0.71-0.86, < 0.0001). In the mixture effect, BKMR analysis confirmed the negative association between six antioxidants and HPV infection. Both WQS and BKMR confirmed that vitamin E had the strongest negative association with HPV infection. Additionally, among the nine machine-learning models, the Gradient Boosting Machine (GBM) showed the best predictive performance [area under curve (AUC) = 0.685]. SHAP analysis indicated that marital status, smoking, drinking, race, age, and CDAI had a significant impact on the model's prediction. CONCLUSION: Antioxidant-rich diets, especially increased intake of vitamin E, are significantly negatively associated with HPV infection. A GBM model with 12 features can effectively predict the occurrence of HPV infection, among which CDAI is an important factor in the model.
背景：一些研究表明，膳食抗氧化剂可能预防人乳头瘤病毒（HPV）感染的发生。然而，美国成年女性中复合膳食抗氧化指数（CDAI）与HPV感染之间的关系仍不清楚。 方法：纳入2003年至2016年期间参加美国国家健康与营养检查调查（NHANES）的参与者。采用多变量逻辑回归、受限立方样条（RCS）回归、加权分位数和（WQS）回归以及贝叶斯核机器回归（BKMR）分析CDAI及其子成分与HPV感染之间的关联。此外，采用九种机器学习（ML）方法构建预测模型，并使用夏普利值附加解释（SHAP）进一步解释最优模型。 结果：本研究纳入了9224名成年女性参与者。在调整多个混杂变量后，CDAI与HPV感染独立呈负相关（比值比：0.98，95%置信区间：0.97-0.99，P = 0.01）。RCS表明CDAI与HPV感染之间呈L形关联。在WQS模型中，CDAI的WQS指数仍与HPV感染呈显著负相关（比值比：0.78，95%置信区间：0.71-0.86，P < 0.0001）。在混合效应中，BKMR分析证实六种抗氧化剂与HPV感染呈负相关。WQS和BKMR均证实维生素E与HPV感染的负相关性最强。此外，在九种机器学习模型中，梯度提升机（GBM）表现出最佳的预测性能[曲线下面积（AUC）= 0.685]。SHAP分析表明婚姻状况、吸烟、饮酒、种族、年龄和CDAI对模型预测有显著影响。 结论：富含抗氧化剂的饮食，尤其是增加维生素E的摄入量，与HPV感染显著负相关。具有12个特征的GBM模型可以有效预测HPV感染的发生，其中CDAI是该模型中的一个重要因素。
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