Machine learning research on the correlation between lifestyles and ovarian aging
10.3760/cma.j.issn.0254-9026.2025.11.017
- VernacularTitle:机器学习研究生活习惯与卵巢衰老的相关性
- Author:
Gaohui CAO
1
;
Liangliang FAN
;
Jieyi LONG
;
Yanmei SUN
;
Jishi LIU
Author Information
1. 中南大学生命科学学院，长沙 410013
- Publication Type:Journal Article
- Keywords:
Lifestyle habits;
Ovarian health;
Factor analysis
- From:
Chinese Journal of Geriatrics
2025;44(11):1585-1589
- CountryChina
- Language:Chinese
-
Abstract:
Objective:With the aging of the population, the health of women's ovarian in China has received increasing attention.Ovarian aging not only affects reproductive health but also increases the risk of chronic diseases.This study aims to systematically explore the relationship between living habits and ovarian aging.Methods:Based on the data from the China Health and Retirement Longitudinal Study(CHARLS)from 2011 to 2018, 8 287 postmenopausal women were included.A retrospective cohort study was conducted using statistical analysis and machine learning methods to evaluate the impact of lifestyle factors such as smoking, drinking, sleep, and dietary patterns on the age of menopause.Results:It was found that adverse lifestyle factors such as reduced daily meal frequency [the early menopause group(2.85±0.38)times/day vs.the normal group(2.89±0.38)times/day, P=0.002], smoking [the smoking rate of the early menopause group(7.75%) vs.that of the normal group(6.15%), P=0.004], and high-frequency drinking [the early menopause rate of people who drink daily(19.76%(33/167)) vs.that of people who rarely or never drink(14.62%(1 162/7 949)), P=0.047]were associated with accelerated ovarian aging. Conclusions:Reasonable adjustment of living habits maybe help to delay the age of menopause and reduce related health risks.This study provides a scientific basis for optimizing women's healthy lifestyles, which is conducive to improving the quality of life and happiness of middle-aged and elderly women in China.
