Tong Fang, Yang Hao, Yu Haidong, Sui Le-Wen, Yao Jing-Yuan, Shi Chen-Lei, Yao Qiao-Yuan, Shi Mei-Fang, Qian Cheng-Lang, Li Gang, Zhao Chao, Wang Hui-Jing
Institute of Wound Prevention and Treatment, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Department of Physiology, School of Fundamental Medicine, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Front Aging Neurosci. 2025 Feb 26;17:1496677. doi: 10.3389/fnagi.2025.1496677. eCollection 2025.
Cognitive decline is a chronic condition which is characterized by a loss of the ability to remember, learn, and pay attention to complex tasks. Many older people are now suffering from cognitive decline, which decreases life quality and leads to disability. This study aimed to identify the risk and protective factors for cognitive decline of the older people from daily life and establish a predictive model using logistic regression.
We investigated 3,790 older people with health examination and questionnaires which included information associated with physical condition, lifestyle factors, and cognitive status. Single-factor comparison, principal component analysis with a Manova-Wilk test, multiple linear regression, and logistic regression were performed to filter the risk and protective factors regarding cognitive decline of older individuals. Then a predictive model using logistic regression was established based on the most significant protective and risk factors.
We found a significant separation along the coordinate axis between people with normal and declined cognition by principal component analysis, as confirmed by the Manover-Wilk test. Single-factor comparison, multiple linear regression and logistic regression implied that gender, age, hypertension level, height, dietary habit, physical-exercise duration, physical-exercise history, and smoking history could be closely linked with cognitive decline. We also observed significant differences in height, physical exercise duration, physical-exercise years, and smoking years between the male and female of the participants. ROCs of the predictive model by logistic regression were plotted, with AUC values of 0.683 and 0.682, respectively, for the training and testing sets. Although an effective predictive model is thought to have AUC over 0.7, we still believe that the present model is acceptable because the value is close to the threshold.
The protective factors of cognitive decline for older people were male gender, height, keeping moderate exercising, and nicotine stimulation, and the risk factors included age, female gender, vegetarianism and hypertension. Except for the genetic factor, differences in lifestyle, such as smoking and exercise habits, may contribute to the observed differences in cognitive function between genders. The significant results could be utilized in the practice for the early intervention of cognitive decline in aged people.
认知功能衰退是一种慢性疾病,其特征是记忆、学习以及专注于复杂任务的能力丧失。现在许多老年人正遭受认知功能衰退的困扰,这降低了生活质量并导致残疾。本研究旨在从日常生活中识别老年人认知功能衰退的风险和保护因素,并使用逻辑回归建立预测模型。
我们对3790名老年人进行了健康检查和问卷调查,其中包括与身体状况、生活方式因素和认知状态相关的信息。进行单因素比较、主成分分析及多变量方差分析、多元线性回归和逻辑回归,以筛选出与老年人认知功能衰退相关的风险和保护因素。然后基于最显著的保护和风险因素建立逻辑回归预测模型。
通过主成分分析,我们发现在正常认知者和认知功能衰退者之间沿着坐标轴存在显著分离,多变量方差分析证实了这一点。单因素比较、多元线性回归和逻辑回归表明,性别、年龄、高血压水平、身高、饮食习惯、体育锻炼时长、体育锻炼史和吸烟史可能与认知功能衰退密切相关。我们还观察到参与者中男性和女性在身高、体育锻炼时长、体育锻炼年限和吸烟年限方面存在显著差异。绘制了逻辑回归预测模型的ROC曲线,训练集和测试集的AUC值分别为0.683和0.682。尽管一般认为有效的预测模型AUC应超过0.7,但我们仍然认为当前模型是可接受的,因为该值接近阈值。
老年人认知功能衰退的保护因素为男性性别、身高、保持适度锻炼和尼古丁刺激,风险因素包括年龄、女性性别、素食主义和高血压。除了遗传因素外,生活方式的差异,如吸烟和运动习惯,可能导致观察到的性别之间认知功能的差异。这些显著结果可用于老年人认知功能衰退早期干预的实践中。