Evidence map›Paper›PMID 40078638›Full record

ArticleFrontiers in aging neuroscience2025

Protective and risk factors in daily life associated with cognitive decline of older adults.

Fang Tong, Hao Yang, Haidong Yu, Le-Wen Sui, Jing-Yuan Yao, Chen-Lei Shi, Qiao-Yuan Yao, Mei-Fang Shi, Cheng-Lang Qian, Gang Li and 2 more

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Fang Tong *Institute of Wound Prevention and Treatment, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Hao Yang *National Clinical Research Center for Aging and Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
Haidong Yu *Department of General Medicine, Youyi Road Community Health Service Centre for Baoshan District, Shanghai, China.
Le-Wen SuiDepartment of Physiology, School of Fundamental Medicine, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Jing-Yuan YaoDepartment of Physiology, School of Fundamental Medicine, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Chen-Lei ShiDepartment of Physiology, School of Fundamental Medicine, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Qiao-Yuan YaoDepartment of Physiology, School of Fundamental Medicine, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Mei-Fang ShiDepartment of General Medicine, Youyi Road Community Health Service Centre for Baoshan District, Shanghai, China.
Cheng-Lang QianNational Clinical Research Center for Aging and Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
Gang LiNational Clinical Research Center for Aging and Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
Chao ZhaoNational Clinical Research Center for Aging and Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
Hui-Jing WangInstitute of Wound Prevention and Treatment, Shanghai University of Medicine & Health Sciences, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

Indexed as

cognitive declinecognitive functionolder adultsprotective factorsrisk factors

Identifiers

PMID40078638
PMCPMC11897038

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.