# Latent class analysis of intrinsic capacity among rural older adults in China and its influencing factors

**Authors:** Zhihui Wang, Hu Jiang, Yue Peng, Jianxia Luo, Weiping Yan

PMC · DOI: 10.3389/fpubh.2025.1708977 · Frontiers in Public Health · 2026-01-14

## TL;DR

This study identifies different patterns of physical and cognitive decline in rural older adults in China and finds factors that influence these patterns.

## Contribution

The study introduces a classification of intrinsic capacity profiles and their associated factors in rural Chinese older adults using latent class analysis.

## Key findings

- Three distinct intrinsic capacity profiles were identified: physically weak, balanced, and cognitive-motor impaired.
- Factors like living alone, low income, and frailty significantly influence these profiles.
- Tailored healthcare interventions are recommended based on these patterns to improve outcomes.

## Abstract

The decline of intrinsic capacity (IC) is especially pronounced among rural older adults and significantly impacts their health outcomes. However, the heterogeneity of IC profiles in this population and its associations with factors like self-care ability are not well understood.

This study aimed to identify latent classes of IC among rural older adults in China and examine their influencing factors.

Using convenience sampling method, 607 rural older adults in Guizhou Province were recruited between January to June, 2025. Data were collected through questionnaires including a general information survey, self-care ability scale, frailty assessment tool, and intrinsic capacity evaluation instrument. Latent class analysis was performed to identify patterns of intrinsic capacity, followed by multivariate logistic regression to determine influencing factors.

The intrinsic capacity of rural older adults was classified into three latent classes: “Physically Weak and Lacking Vitality Group” (38.71%), “Balanced and Stable Group” (22.41%), and “Cognitive-Motor Impairment Group” (38.88%). Multivariate logistic regression analysis revealed that living alone, low monthly household income, advanced age, frailty status, self-care ability, current work participation, rural residence, and multiple medication use were significant influencing factors for the latent classes of intrinsic capacity (p < 0.05).

The deterioration of intrinsic capacity among rural older adult populations exhibits distinct categorical patterns. Healthcare providers should implement tailored and individualized nursing interventions based on these differential influencing factors to enhance the intrinsic capacity levels of rural older adults.

## Full-text entities

- **Diseases:** frailty (MESH:D000073496), Cognitive-Motor Impairment (MESH:D003072)

## Full text

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## Figures

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## References

39 references — full list in the complete paper: https://tomesphere.com/paper/PMC12848799/full.md

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Source: https://tomesphere.com/paper/PMC12848799