Evidence map›Paper›PMID 41776461›Full record

ArticleBMC geriatrics2026

Dynamic evolution of multimorbidity patterns and association with medication adherence in Chinese older adults: a longitudinal analysis using latent transition analysis and semi-Markov models.

Qian Liu, Shuzhi Lin, Lin Yin, Xiaoying Zhu, Wei Liu, Yifang Shen, Zimeng Li, Bianling Feng

Abstract read
In one paragraph

Article in BMC geriatrics, 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

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2 · The registry

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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

8 authors.

Qian LiuThe Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
Shuzhi LinThe Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
Lin YinThe Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
Xiaoying ZhuThe Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
Wei LiuThe Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
Yifang ShenThe Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
Zimeng LiThe Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China.
Bianling FengThe Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, China. fengbianling@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultimorbidity is prevalent among the elderly, with long-term medication use posing increasing adherence challenges. This study examines the evolution of multimorbidity patterns and their dynamic association with medication adherence to generate empirical evidence for the design of personalized treatment strategies and targeted health interventions for older adults with multimorbidity.

methodsUsing data from 2,798 elderly individuals with multimorbidity in the 2011–2020 China Health and Retirement Longitudinal Study, this study employs latent transition analysis and a semi-Markov model to assess adherence transitions across four multimorbidity patterns. Relative Transition Rates (RTRs) were used to quantify differences in adherence improvement and deterioration probabilities.

resultsThe cardiovascular disease group remained relatively stable, with other patterns shifting toward it over time. Between 2013 and 2018, the incidence of adherence improvement (60.60%) was more frequent than deterioration (39.40%), especially in the multi-system disorders (62.08%) and respiratory diseases groups (67.59%), while deterioration was higher in the gastrointestinal metabolism (40.75%) and cardiovascular disease groups (39.64%). Compared to the multi-system disorders group, the gastrointestinal metabolism group was less likely to improve from low to moderate adherence (RTR = 0.63, 95% CI: 0.41–0.98), while both the gastrointestinal metabolism (RTR = 4.45, 95% CI: 1.92–10.18) and cardiovascular disease groups (RTR = 2.57, 95% CI: 1.07–6.11) had higher risks of declining from high to moderate adherence.

conclusionsCardiovascular diseases appear increasingly central in elderly multimorbidity, with gastrointestinal metabolism and respiratory conditions potentially serving as early or coexisting risk factors. Early cardiovascular risk monitoring may be beneficial in these groups, while long-term adherence support remains important for gastrointestinal and cardiovascular patterns.

Indexed as

Drug MonitoringMedication AdherenceMultimorbidityAgedAged, 80 and overCardiovascular DiseasesChinaEast Asian PeopleFemaleHumansLongitudinal StudiesMaleAging populationLatent transition analysisMedication adherenceMultimorbiditySemi-Markov model

Identifiers

PMID41776461
PMCPMC13067648

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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.