Evidence map›Paper›PMID 41243660›Full record

ArticleAnnals of medicine2025

Determinants of the onset and development of multimorbidity in different subpopulations of older Chinese adults: insights from the China Health and Retirement Longitudinal Study.

Changcong Wang, Shutong Wang, Haitao Yu, Xinyue Zhang, Meng Zhang, Dongmei Mu

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Article in Annals of medicine, 2025. 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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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Changcong WangDivision of Clinical Research, The First Hospital of Jilin University, Changchun, China.
Shutong WangDepartment of Medical Informatics, School of Public Health, Jilin University, Changchun, China.
Haitao YuDepartment of Medical Informatics, School of Public Health, Jilin University, Changchun, China.
Xinyue ZhangDepartment of Medical Informatics, School of Public Health, Jilin University, Changchun, China.
Meng ZhangDepartment of Medical Informatics, School of Public Health, Jilin University, Changchun, China.
Dongmei MuDivision of Clinical Research, The First Hospital of Jilin University, Changchun, China.

Funding

Integrting Information About Aging SurveysR01AG030153 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Sara Adar, Alden L. Gross · 2007 to 2026
$41.7M
Mega Meta Data Set of the Health and Retirement Surveys Around the WorldRC2AG036619 · NIA · RAND CORPORATION · PI KAPTEYN, ARIE · 2009 to 2010
$2.0M
Archiving & Creating User Friendly Data: the Longitudinal Aging Survey in IndiaR03AG043052 · NIA · RAND CORPORATION · PI LEE, JINKOOK · 2012 to 2012
$95k
NIA NIH HHS R01 AG030153NIA NIH HHS R03 AG043052NIA NIH HHS RC2 AG036619
6 · The paper itself

Abstract

BACKGROUND AND

objectivesMultimorbidity trajectories help to analyze the onset and development of multimorbidity over time and are an important public health matter. However, existing longitudinal studies have not adequately characterized trajectory differences nor their determinants across clinically distinct subpopulations stratified by baseline health status. This study explored and investigated evidence-based multimorbidity trajectories in populations with and without multimorbidity, and determined how factor trajectories and baseline factors impact multimorbidity trajectories.

methodsMultimorbidity trajectories and factor trajectories were estimated by group-based trajectory modeling (GBTM) using data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018) and the 2014 Life History Survey. Determinants of multimorbidity trajectories were explored using multinomial logistic regression.

resultsOur analysis revealed similar multimorbidity trajectories in the multimorbidity population and the full population, whereas in the Non-multimorbidity population, we found four diverse trajectories. Poor Center for Epidemiologic Studies Depression (CESD) trajectories and poor functional status (FS) trajectories were consistently associated with poor multimorbidity trajectories. It was in the presence of underlying disease at baseline that age and early life adversity were associated with the negative development of multimorbidity.

conclusionMultimorbidity trajectories were more complex in the non-multimorbidity population. Both CESD and FS were identified as important determinants of poor multimorbidity trajectories, underscoring the need for stratified interventions. For the non-multimorbidity population, primary prevention should integrate CESD/FS monitoring into primary care for early risk detection. For the multimorbidity population, secondary prevention requires integrated care models that concurrently manage depression and functional decline to curb progression.

Indexed as

MultimorbidityAgedAged, 80 and overChinaDepressionEast Asian PeopleFemaleFunctional StatusHealth StatusHumansLongitudinal StudiesMaleMiddle AgedRetirementRisk Factorschinese multimorbidity-weighted indexgroup-based trajectory modelMultimorbiditypublic health

Identifiers

PMID41243660
PMCPMC12624946

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