# Trajectories of Proactive Health Behaviors Among Chinese Middle-Aged and Older Adults with Multimorbidity: A Cohort Study Using Group-Based Trajectory Modeling

**Authors:** Jiaxuan Wang, Ziqi Wang, Fan Du, Jiaojiao Lv, Jiulong Kou, Jieting Chen, Mingxia Jing

PMC · DOI: 10.3390/ejihpe16030038 · European Journal of Investigation in Health, Psychology and Education · 2026-03-06

## TL;DR

This study examines how proactive health behaviors change over time in older Chinese adults with multiple chronic conditions, finding that most people's behaviors decline and that mental health and education are key factors.

## Contribution

The study introduces a novel approach to analyzing longitudinal proactive health behavior trajectories in multimorbid populations using group-based modeling and decomposition techniques.

## Key findings

- Two distinct behavioral trajectories were identified: a declining group (91.44%) and an improving group (8.56%).
- Education and depression were the strongest determinants of trajectory membership.
- Higher education and retirement indirectly supported proactive health behaviors by reducing depression.

## Abstract

(1) Background: Proactive health behaviors are key to reducing their burden and supporting healthy aging. (2) Methods: We analyzed five waves (2011–2020) of CHARLS data from 1343 middle-aged and older adults (≥45 years) with multimorbidity. An entropy weight method was used to create a composite score for proactive health behaviors, and group-based trajectory modeling identified behavioral trajectories. Multivariate logistic regression and Shapley value decomposition assessed determinants and their relative contributions. Generalized structural equation modeling and latent class analysis were applied to estimate direct and indirect effects across the full sample and key multimorbidity subgroups. (3) Results: Two trajectories emerged: a “declining group” (91.44%) and an “improving group” (8.56%). The improving group was more likely to include younger, urban individuals with higher education, retired status, smaller family size, and lower depression levels. Education (40.67%) and depressive symptoms (31.22%) were the strongest determinants of trajectory. Path analysis showed that higher education and retirement indirectly supported sustained proactive health behaviors by reducing depression. The direct and indirect effects varied across subgroups. (4) Conclusion: The proactive health behaviors of middle-aged and elderly patients with multimorbidity exhibit a declining trend. Future health policies and interventions should prioritize mental health.

## Full-text entities

- **Diseases:** lung diseases (MESH:D008171), diabetes (MESH:D003920), arthritis (MESH:D001168), mental illness (MESH:D001523), heart disease (MESH:D006331), Depression (MESH:D003866), kidney disease (MESH:D007674), stroke (MESH:D020521), dyslipidemia (MESH:D050171), injury to (MESH:D014947), COVID-19 (MESH:D000086382), anxiety (MESH:D001007), memory disorders (MESH:D008569), hypertension (MESH:D006973), asthma (MESH:D001249), liver disease (MESH:D008107), cardiometabolic (MESH:D024821), fatigue (MESH:D005221), Chronic Disease (MESH:D002908), cancer (MESH:D009369), gastric disease (MESH:D013272), osteoarticular and gastrointestinal symptoms (MESH:D012817), chronic non-communicable diseases (MESH:D000073296)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

56 references — full list in the complete paper: https://tomesphere.com/paper/PMC13026065/full.md

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Source: https://tomesphere.com/paper/PMC13026065