Evidence map›Paper›PMID 42800871›Full record

Observational studyBMC geriatrics2026

Associations of cognitive impairment and physical disability with the risk and reversibility of depressive symptoms in Chinese older adults.

Rui Zhang, Chengzhi Jiang, Zhijie Guan, Xueqin Sun, Guanzhong Caotian, Wenjie Teng

Abstract readObservational Study
In one paragraph

Observational study 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

What it found

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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

6 authors.

Rui ZhangShandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China.
Chengzhi JiangShandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China.
Zhijie GuanShandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China.
Xueqin SunShandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China.
Guanzhong CaotianShandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China.
Wenjie TengShandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China. 13583650668@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCognitive impairment (CI) and physical disability (PD) frequently co-occur in older adults and are both significant risk factors for depressive symptoms. However, their combined impact on the risk and reversibility across different depressive symptom states remains unclear.

methodsUtilizing data from five waves (2011-2020) of the China Health and Retirement Longitudinal Study (CHARLS), we included 8,473 adults aged 60 and above. A continuous-time multi-state Markov model was used to analyze transition probabilities and intensities among states of no (NDS), mild (MDS), and severe depressive symptoms (SDS), and to examine the effects of CI and PD on these transitions. Cox proportional hazards models were employed to estimate hazard ratios (HRs) for the associations of CI and PD with the risk and reversibility of depressive symptoms. Restricted cubic splines (RCS) were further applied to assess dose-response relationships.

resultsAmong 8,473 older participants (mean age 67.91 ± 6.59 years; 49.3% female), 14.0% had CI, 17.5% had PD, and 6.5% had both at baseline. Multi-state Markov models showed dynamic transitions of depressive symptoms, with reversion generally exceeding progression. Both CI and PD were associated with increased progression risk and reduced likelihood of reversion, with PD showing stronger associations and a lower likelihood of symptom reversal. Their co-occurrence showed the strongest effects (NDS → MDS: HR = 1.76, 95% CI: 1.42-2.18; MDS → SDS: HR = 1.79, 95% CI: 1.30-2.46), alongside reduced reversion probabilities (MDS → NDS: HR = 0.82, 95% CI: 0.66-0.92; SDS → MDS: HR = 0.74, 95% CI: 0.57-0.91). Additive interactions were observed across all transition pathways (all P < 0.05). Findings were consistent in prospective analyses, and restricted cubic spline analyses supported dose-response relationships.

conclusionThis study highlights the dynamic nature of depressive symptoms in older Chinese adults. CI and PD were independently associated with a higher likelihood of symptom progression and jointly associated with a lower probability of reversion. These findings suggest that approaches focusing on cognitive and physical function may hold promise for informing strategies to modify depressive symptom trajectories.

Indexed as

Cognitive DysfunctionDepressionPersons with DisabilitiesAgedChinaFemaleHumansLongitudinal StudiesMaleMarkov ChainsMiddle AgedRisk FactorsCognitive impairmentDepressive symptomsMulti-state Markov modelOlder adultsPhysical disability

Identifiers

PMID42800871
PMCPMC13615622

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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.