Evidence map›Paper›PMID 40594574›Full record

ArticleScientific reports2025

Risk factors associated with health literacy among community residents in China based on multiple correspondence analysis and ordinal logistic regression.

Mengqian Gao, Shuo Yang, Hongtao Zhang, Ying Huang, Hui Xiao, Zhanming He, Chao Qiu, Jianyun Lu

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Mengqian Gao *Department of Health Education and Promotion, Guangzhou Baiyun Center for Disease Control and Prevention, Guangzhou, 510440, China.
Shuo Yang *Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, 510310, China.
Hongtao ZhangGuangzhou Baiyun Center for Disease Control and Prevention, Guangzhou, 510440, China.
Ying HuangSchool of Public Health, Guangdong Pharmaceutical University, Guangzhou, 510006, Guangdong, China.
Hui XiaoDepartment of Health Education and Promotion, Guangzhou Baiyun Center for Disease Control and Prevention, Guangzhou, 510440, China.
Zhanming HeDepartment of Health Education and Promotion, Guangzhou Baiyun Center for Disease Control and Prevention, Guangzhou, 510440, China.
Chao QiuSchool of Medicine, Lishui University, No.1 Xueyuan Road, Liandu District, Lishui City, 323000, Zhejiang Province, China. qcim@163.com.
Jianyun LuGuangzhou Baiyun Center for Disease Control and Prevention, Guangzhou, 510440, China. 258506273@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health literacy is crucial in individuals' ability to make informed health decisions and manage chronic conditions. This study aimed to assess the levels of health literacy and identify socio-demographic factors associated with health literacy among residents aged 15-69 years in Baiyun District, Guangzhou. A cross-sectional survey was conducted among 2630 participants using the China Health Literacy Survey (CHLS) questionnaire between 2019 and 2024. Ordinal logistic regression (OLR) was performed to identify factors associated with health literacy. Multiple Correspondence Analysis (MCA) was used to explore the interrelationships between categorical variables such as age, education, and health literacy. The mean health literacy score was 47.31 (SD = 11.41), with 34.5% of participants having adequate health literacy. The OLR results showed that lower education levels were significantly associated with a reduced likelihood of having adequate health literacy. Participants with less than junior high school education ([Formula: see text] = -1.71, 95% CI: -2.06, -1.37, P < 0.001) and those with junior or senior high school education ([Formula: see text] = -1.24, 95% CI: -1.40, -1.07, P < 0.001) were less likely to have adequate health literacy compared to those with college or higher education. Age was also significantly associated with health literacy, with younger participants (aged 15-44 years) having a higher likelihood of adequate health literacy ([Formula: see text] = 0.82, 95% CI: 0.58, 1.06, P < 0.001). MCA further revealed that younger, higher-educated individuals clustered in the upper-left quadrant, reflecting higher health literacy, while older, less-educated individuals were positioned in the lower-right quadrant, indicating lower health literacy. Education and age were significant determinants of health literacy in Baiyun District, Guangzhou. These findings emphasize the need for targeted health literacy interventions, particularly for older and less-educated populations. Public health policies should focus on improving educational opportunities and providing tailored health education programs to enhance health literacy, thereby reducing health disparities.

Indexed as

Health LiteracyAdolescentAdultAgedChinaCross-Sectional StudiesEducational StatusFemaleHumansLogistic ModelsMaleMiddle AgedRisk FactorsSurveys and QuestionnairesYoung AdultHealth literacyMultiple correspondence analysis.Ordinal logistic regressionSocio-demographic factors

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PMID40594574
PMCPMC12214547

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