Frontiers in public health · 2026
Factors influencing chronic disease self-management behaviors: a national multilevel analysis in China.
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Li Kai, Chen Yufan
Аннотация
OBJECTIVE: This study employed multilevel analysis to examine the impact of the prefecture-level city level variable (number of physicians per 1,000 population) on chronic disease self-management behavior (CDSMB) among Chinese adults, while also investigating the effects of individual-level control variables on CDSMB.
METHODS: A cross-sectional survey of 1,916 adults across 120 cities, using data from the "Psychology and Behavior Investigation of Chinese Residents" (PBICR), evaluated Chronic Disease Self-Management Behavior (CDSMB) via CDSMS. Key predictors included individual-level control variables: health literacy (HLS-SF12), self-efficacy (NGSES), family health (FHS-SF), and the prefecture-level city level variable of physicians per 1,000 population. Hierarchical linear modeling (HLM) was used to analyze the nested data, with adjustments for demographic covariates.
RESULTS: Vulnerable groups (older adults, rural residents, low-income, education individuals) exhibited significantly poorer self-management (p < 0.001). At the individual level control variables, health literacy (β = 3.075, p < 0.001) and self-efficacy (β = 1.891, p < 0.001) positively predicted CDSMB, while family health showed an unexpected negative effect (β = -1.784, p < 0.001). At the prefecture-level city level, physicians per 1,000 population (β = 0.077, p < 0.05) explained 17% of between prefecture-level city level variance in CDSMB.
CONCLUSION: Based on the findings highlighting the influence of physicians per 1,000 population and individual-level control variables on chronic disease self-management, targeted optimization of medical resource allocation and focused support for vulnerable groups are needed to improve chronic disease management.
METHODS: A cross-sectional survey of 1,916 adults across 120 cities, using data from the "Psychology and Behavior Investigation of Chinese Residents" (PBICR), evaluated Chronic Disease Self-Management Behavior (CDSMB) via CDSMS. Key predictors included individual-level control variables: health literacy (HLS-SF12), self-efficacy (NGSES), family health (FHS-SF), and the prefecture-level city level variable of physicians per 1,000 population. Hierarchical linear modeling (HLM) was used to analyze the nested data, with adjustments for demographic covariates.
RESULTS: Vulnerable groups (older adults, rural residents, low-income, education individuals) exhibited significantly poorer self-management (p < 0.001). At the individual level control variables, health literacy (β = 3.075, p < 0.001) and self-efficacy (β = 1.891, p < 0.001) positively predicted CDSMB, while family health showed an unexpected negative effect (β = -1.784, p < 0.001). At the prefecture-level city level, physicians per 1,000 population (β = 0.077, p < 0.05) explained 17% of between prefecture-level city level variance in CDSMB.
CONCLUSION: Based on the findings highlighting the influence of physicians per 1,000 population and individual-level control variables on chronic disease self-management, targeted optimization of medical resource allocation and focused support for vulnerable groups are needed to improve chronic disease management.