氧化平衡评分与绝经状态:来自流行病学分析和机器学习模型的见解
Oxidative balance score and menopausal status: insights from epidemiological analysis and machine learning models.
作者信息
Dong Chunlin, Ma Ding, Yu Jinjin, Gu Ke, Lin Yaying, Song Jing, Wang Yuan, Zhou Yanjun
机构信息
Department of Obstetrics and Gynecology, Affiliated Hospital of Jiangnan University, Wuxi, China.
Wuxi Medical College, Jiangnan University, Wuxi, China.
出版信息
Front Nutr. 2025 May 20;12:1586606. doi: 10.3389/fnut.2025.1586606. eCollection 2025.
BACKGROUND
Unhealthy lifestyle habits, such as smoking, can impact oxidative stress. During oxidative stress, unnaturalized free radicals can damage DNA, proteins, and lipids, leading to cellular damage and death. A comprehensive measurement of various pro-oxidative and antioxidative exposures can reflect an individual's oxidative stress burden. However, studies on assessing the association between dietary and lifestyle factors related to oxidative stress and menopause were previously lacking.
MATERIALS AND METHODS
A cohort of 2,813 women aged 40-60 years from the National Health and Nutrition Examination Survey conducted between 2003 and 2020 was identified as meeting the eligibility criteria. The associations of oxidative balance score (OBS) with the menopausal status were examined via weighted logistic regression models, and the odds ratios (ORs) of menopause onset were calculated with 95% confidence intervals (CIs). Machine learning models were developed and compared to classify the menopausal status based on the OBS and other epidemiological factors, with the interpretability of the models explored using the Shapley Additive Explanations method.
RESULTS
Following adjustment for various confounding factors, OBS was reversely associated with menopause (OR: 0.97, 95% CI: 0.94-0.99, = 0.010). When the OBS was categorized into quartiles, the association with menopause was still significant ( for trend = 0.009). The association of the OBS with menopause remained significant after excluding any each survey year cycles ( for trend < 0.050). The menopause classification models developed using TabFPN, Random Forest, CatBoost, and XGBoost achieved an area under the curve of 0.880, 0.884, 0.886, and 0.878, respectively. Based on the results from epidemiological analysis and machine learning models, the intake of magnesium, zinc, niacin, and vitamin B6 showed a decline in the early postmenopausal period and contributed in the model performance.
CONCLUSIONS
OBS were reversely associated with the menopausal status, and the OBS might serve as an indicator of an individual's oxidative stress status for lifestyle interventions during the menopausal transition.
背景
不健康的生活方式习惯,如吸烟,会影响氧化应激。在氧化应激期间,未被自然化的自由基会损害DNA、蛋白质和脂质,导致细胞损伤和死亡。对各种促氧化和抗氧化暴露进行全面测量可以反映个体的氧化应激负担。然而,此前缺乏关于评估与氧化应激和绝经相关的饮食及生活方式因素之间关联的研究。
材料与方法
从2003年至2020年进行的美国国家健康与营养检查调查中,确定了2813名年龄在40 - 60岁之间的女性队列符合纳入标准。通过加权逻辑回归模型检验氧化平衡评分(OBS)与绝经状态之间的关联,并计算绝经 onset 的优势比(OR)及95%置信区间(CI)。开发并比较了机器学习模型,以根据OBS和其他流行病学因素对绝经状态进行分类,并使用Shapley加法解释方法探索模型的可解释性。
结果
在对各种混杂因素进行调整后,OBS与绝经呈负相关(OR:0.97,95% CI:0.94 - 0.99,P = 0.010)。当将OBS分为四分位数时,与绝经的关联仍然显著(趋势P = 0.009)。在排除任何一个调查年份周期后,OBS与绝经的关联仍然显著(趋势P < 0.050)。使用TabFPN、随机森林、CatBoost和XGBoost开发的绝经分类模型的曲线下面积分别为0.880、0.884、0.886和0.878。基于流行病学分析和机器学习模型的结果,镁、锌、烟酸和维生素B6的摄入量在绝经后早期有所下降,并对模型性能有贡献。
结论
OBS与绝经状态呈负相关,并且OBS可能作为个体在绝经过渡期间进行生活方式干预的氧化应激状态指标。