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Record W4416202541 · doi:10.1016/s2468-2667(25)00253-1

The effect of healthy lifestyles and social determinants on independent life expectancy and sex differences in China: evidence from a 13-year cohort study

2025· article· en· W4416202541 on OpenAlexaff
Longbing Ren, Ying Zhou, Keyang Liu, Hao Zhang, Shaojie Li, Yang Hu, Kokoro Shirai, Yuling Jiang, Yifei Wu, Mingzhi Yu, Jiakang Huo, Jie Li, Yan Zhang, Jing Sun, Bo Hu, David Bishai, Yi Zeng, Erdan Dong, Yao Yao

Bibliographic record

VenueThe Lancet Public Health · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsInstitute of Aging
FundersChinese Academy of Medical SciencesNational Natural Science Foundation of China
KeywordsLife expectancyCohort studySocial determinants of healthCohortMEDLINEExpectancy theory

Abstract

fetched live from OpenAlex

BACKGROUND: Functional independence is the basis for healthy ageing and quality of late life. However, evidence on how healthy lifestyle factors and social determinants of health affect longevity in independence remains limited, particularly regarding sex differences. We aimed to examine the associations of these factors with life expectancy with and without dependency, and to assess whether such effects differ by sex. METHODS: This cohort study used data from the nationally representative Chinese Longitudinal Healthy Longevity Study (CLHLS), which collected data from 2008 to 2021. Participants aged 65-100 years were included if they had at least one follow-up or death record. Healthy lifestyle factors (ie, diet, physical activity, smoking, and alcohol use) and social determinants of health (ie, financial status, education, health-care access, built environment, and social context) were assessed at baseline. Functional independence was determined by self-reported need for assistance with activities of daily living and instrumental activities of daily living at each survey wave. A continuous-time three-state Markov model was applied to estimate hazard ratios and 95% CIs between independence, dependence, and death, yielding total and independent life expectancy by sex, adjusted for covariates. FINDINGS: 11 804 participants were included in the study. At age 65 years, females had longer total life expectancy than males (18·18 years [95% CI 17·74-18·49] vs 15·50 years [15·10-15·89]) but shorter independent life expectancy (10·35 years [10·13-10·55] vs 11·29 years [11·05-11·54]). The gain in independent life expectancy was greater for males with 3-4 healthy lifestyle factors versus males with 0-1 healthy lifestyle factors (2·45 years [2·24-2·67]) compared with females with 3-4 healthy lifestyle factors versus females with 0-1 healthy lifestyle factors (2·09 years [1·90-2·29], p=0·015). However, females had greater gains in independent life expectancy from favourable social determinants of health. Those with 4-5 positive social determinants of health indicators lived 1·95 (1·74-2·16) more years independently compared with those with 0-1, surpassing the 1·67 year (1·49-1·85) gain observed in males (p=0·047). The combination of both favourable lifestyle behaviours and supportive social conditions produced the largest improvement in independent life expectancy, with gains of 3·94 (3·73-4·15) years for males and 3·89 (3·68-4·11) years for females. INTERPRETATION: Pathways to healthy ageing differ between sexes in China: males benefit more from lifestyle modifications whereas females gain more from improved social conditions. These results underscore the importance of sex-specific public health strategies that focus on reducing unhealthy behaviours among males and improving social support for females. FUNDING: National Natural Science Foundation of China and Chinese Academy of Medical Sciences Innovation Fund. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.388
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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