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Background <p>This study aimed to examine how community-level factors—particularly health resources and social capital—affect health literacy (HL) among residents in South Korea.</p> Methods <p>We used data from the 2021 Community Health Survey and the Korean Community Health Status Indicators, incorporating both individual- and community-level variables. Key predictors of HL were first identified using elastic net regression to address multicollinearity. Subsequently, we applied Multilevel (or Hierarchical) logistic regression models using SAS version 9.4, and accounted for clustering at the community level, to assess the combined influence of individual characteristics and community-level conditions.</p> Results <p>Multilevel analysis showed that individual characteristics including age, gender, income, occupation, and education were significantly associated with HL. Among the health resource variables, greater availability of healthcare professionals per 100,000 people (OR = 0.95, 95% CI = 0.94–0.99) and sports facilities (OR = 0.96, 95% CI = 0.94–0.98) were associated with higher HL. On the other hand, higher rates of unmet medical needs predicted lower HL (OR = 1.02, 95% CI = 1.01–1.04). Social capital indicators, such as mutual aid, religious participation, and social activities were also positively, yet marginally, linked to HL.</p> Conclusions <p>HL is shaped by both personal and community-level factors. Strategies to improve HL should simultaneously combine efforts to expand health infrastructure with measures to reduce social inequalities. Policymakers should prioritize vulnerable populations and strengthen community-based support systems that enhance access to and engagement with health information.</p>

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Exploring the association between community-level factors and health literacy using multilevel analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月29日

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  • Inhyung Cho,
  • Sung-il Cho

摘要

Background

This study aimed to examine how community-level factors—particularly health resources and social capital—affect health literacy (HL) among residents in South Korea.

Methods

We used data from the 2021 Community Health Survey and the Korean Community Health Status Indicators, incorporating both individual- and community-level variables. Key predictors of HL were first identified using elastic net regression to address multicollinearity. Subsequently, we applied Multilevel (or Hierarchical) logistic regression models using SAS version 9.4, and accounted for clustering at the community level, to assess the combined influence of individual characteristics and community-level conditions.

Results

Multilevel analysis showed that individual characteristics including age, gender, income, occupation, and education were significantly associated with HL. Among the health resource variables, greater availability of healthcare professionals per 100,000 people (OR = 0.95, 95% CI = 0.94–0.99) and sports facilities (OR = 0.96, 95% CI = 0.94–0.98) were associated with higher HL. On the other hand, higher rates of unmet medical needs predicted lower HL (OR = 1.02, 95% CI = 1.01–1.04). Social capital indicators, such as mutual aid, religious participation, and social activities were also positively, yet marginally, linked to HL.

Conclusions

HL is shaped by both personal and community-level factors. Strategies to improve HL should simultaneously combine efforts to expand health infrastructure with measures to reduce social inequalities. Policymakers should prioritize vulnerable populations and strengthen community-based support systems that enhance access to and engagement with health information.