Evidence map›Paper›PMID 41724508›Full record

ArticleBMJ open2026

Typology of ageing and its associations with the end of life and death among older adults in China: a longitudinal person-centred study.

Jing Li, Liangjun Song

Abstract read
In one paragraph

Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Jing LiSchool of Social Development and Public Policy, Fudan University, Shanghai, China fd_lijing@fudan.edu.cn.ORCID http://orcid.org/0000-0001-9961-9433
Liangjun SongFudan Development Institute, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesStudies on ageing trajectories typically foreground intrinsic capacities and focus on frailty and mortality outcomes. Instead, research capturing aspects of people's living environment alongside individuals' capacities is limited. This study aimed to identify qualitatively distinctive ageing profiles among deceased older adults in China using individual-based and environment-based indicators. It further examined sociodemographic correlates of profile membership and investigated associations between these profiles and end-of-life and death-related outcomes.

designThis is a retrospective cohort study.

settingIndividual level, longitudinal data from the Chinese Longitudinal Healthy Longevity Study (CLHLS) between 2008 and 2018 were analysed.

participantsThe study included older participants of the CLHLS (2008-2018) who died between survey waves (N=9755). OUTCOME MEASURES: Ageing profiles were categorised using latent class modelling based on individuals' intrinsic capacity (functional, physical, cognitive, mental and social dimensions; 20 indicators) and environment characteristics (healthcare-related, financial and social aspects; 10 items). Sociodemographic correlates of profile membership included age, sex, education, marital status, living arrangement and residence location. End-of-life and death experiences were assessed by length of survival and functional status measured at the wave prior to death, pain at death and terminal delirium.

resultsWithin the study sample, four profiles emerged: healthy-and-supported (57%), cognitively-competent-but-functionally-dependent (12%), functionally-capable-but-cognitively-challenged (18%) and frail-and-support-lacking (13%). While profiles were primarily distinguished by functional and cognitive capacities and financial status, social participation was insufficient across all groups. Sociodemographic disparities (sex, education, marital status, living arrangement and residence) were associated with profile membership. The first and third profiles enjoyed a better quality of life in their final months. The healthy-and-supported adults were most prone to painful deaths in hospitals. The functionally capable participants most often died at home. The frail-and-support-lacking individuals were at the highest risk of terminal delirium.

conclusionsThe heterogeneity of ageing revolved around functional and cognitive capacities and economic/financial characteristics, the latter particularly salient for the frail-and-support-lacking group. The uniformly low social engagement observed across profiles highlighted the need for boosting overall social participation and developing community-level social services. Distinct end-of-life patterns emphasise the importance of targeted care strategies for rural and urban residents and interventions for delirium prevention.

Indexed as

AgingDeathAgedAged, 80 and overChinaFemaleFunctional StatusHumansLongitudinal StudiesMaleRetrospective StudiesSocioeconomic FactorsAgingDeathPublic health

Identifiers

PMID41724508
PMCPMC12927367

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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.