Evidence map›Paper›PMID 39818010›Full record

ArticleThe journal of nutrition, health & aging2025

Cognitive function differs across healthy lifestyle behavior profiles: a 10-year population-based prospective cohort study.

Huixiu Hu, Yajie Zhao, Di Guo, Ying Deng, Huanhuan Luo, Yuqing Hao, Chao Sun, Kang Yu

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In one paragraph

Article in The journal of nutrition, health & aging, 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.

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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

8 authors.

Huixiu HuDepartment of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; Department of Clinical Nutrition, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Yajie ZhaoDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Di GuoDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Ying DengDepartment of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Huanhuan LuoDepartment of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yuqing HaoDepartment of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Chao SunDepartment of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China. Electronic address: sunchaobjyy@163.com.
Kang YuDepartment of Clinical Nutrition, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China. Electronic address: yuk1997@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundModifiable lifestyle behaviors significantly influence the risk of cognitive impairment. However, the cumulative effects of multidimensional lifestyle profiles on cognitive function remain poorly understood, as most studies examine individual lifestyle behaviors in isolation. This study aimed to identify distinct profiles of individuals based on healthy lifestyle behaviors and to examine associations between these profiles and cognitive function in older Chinese adults.

methodsWe used a prospective cohort, including 5381 participants of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) between 2008 and 2018, aged 65 years and older with normal cognition at baseline. Questionnaires were used to collect self-reported data on healthy diet, sleep quality, physical activities, cognitive activities, and social activities. Repeated measures of the Mini-Mental State Examination (MMSE) were utilized to assess cognitive function. Latent Profile Analysis (LPA) was conducted to identify profiles characterized by similar characteristics of lifestyle behaviors. The resultant profiles, were then used to further explore associations with cognitive function using cox proportional hazard regression and linear mixed models.

resultsDuring a 10-year follow-up period, 2017 (37.5%) out of 5381 participants developed cognitive impairment. Three latent profiles were identified: (1) "active engagement" (n = 347, 6.4%); (2) "moderate engagement" (n = 627, 11.7%); and (3) "negative engagement" (n = 4407, 81.9%). Compared to negative engagement, the active profile had the lower risk of cognitive impairment (HR = 0.693, 95% CI: 0.553-0.868), longer years to develop cognitive impairment (mean = 7.818, range: 6.701, 8.935) and slower rate of annual cognitive decline (0.407 points per year). Similarly, the moderate engagement profile had the lower risk of cognitive impairment (HR = 0.781, 95% CI: 0.664-0.919), longer years to develop cognitive impairment (mean = 7.541, 95%CI: 6.464, 8.619) and slower rate of annual cognitive decline (0.297 points per year) compared to negative profile. Subgroup analysis revealed that there were no significant differences observed across any of the subgroups, including age, gender, year of schooling, marital status, residence, live alone, family economic status.

conclusionsThese findings imply the likelihood of an inverse correlation between the levels of engagement in healthy lifestyle behavior and the risk of cognitive impairment. Even adopting a few healthy lifestyle habits is superior to none at all, underscoring the value of lifestyle modifications for cognitive health.

Indexed as

CognitionCognitive DysfunctionHealth BehaviorHealthy LifestyleAgedAged, 80 and overChinaDiet, HealthyExerciseFemaleHumansLongitudinal StudiesMaleProspective StudiesSurveys and QuestionnairesCognitive impairmentCohort studyHealthy lifestyle behaviorsLatent profile analysis

Identifiers

PMID39818010
PMCPMC12180002

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.