Evidence map›Paper›PMID 31077197›Full record

ArticleBMC health services research2019

Factors associated with health literacy in rural areas of Central China: structural equation model.

Yaofei Xie, Mengdi Ma, Ya'nan Zhang, Xiaodong Tan

Abstract read
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Article in BMC health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

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28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

  1. Trial
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  14. Health Literacy Level and Comprehension of Prescription and Nonprescription Drug Information.International journal of environmental research and public health · 2022
    Article
  15. Article
  16. Sociodemographic correlates of knowledge about high sodium-related diseases among adults in Malaysia.Hypertension research : official journal of the Japanese Society of Hypertension · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. Health Literacy among Filipino Domestic Workers in Macao.Healthcare (Basel, Switzerland) · 2021
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Yaofei XieSchool of Health Sciences, Wuhan University, No.115 of Donghu Road, Wuhan, 430000, China.
Mengdi MaWuhan Blood Center, No.8 of Baofeng One Road, Wuhan, 430000, China.
Ya'nan ZhangSchool of Health Sciences, Wuhan University, No.115 of Donghu Road, Wuhan, 430000, China.
Xiaodong TanSchool of Health Sciences, Wuhan University, No.115 of Donghu Road, Wuhan, 430000, China. 00300469@whu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth literacy is a strong predictor of health status. This study develops and tests a structural equation model to explore the factors that are associated with the health literacy level of rural residents in Central China.

methodsThe participants were recruited from a county-level city in Central China (N = 1164). Face-to-face interviews were conducted to complete the self-designed questionnaire of each participant. The questionnaire included items for the (1) demographic information, (2) socioeconomic status, and (3) health literacy of the participants. Mplus analyses were performed to evaluate the proposed model.

resultsThe final model showed good fit for the data, and both demographic characteristics (i.e., age, BMI, and residence) and socioeconomic status (i.e., monthly income, occupation, and education level) were significantly associated with health literacy level. The effects of these two variables were - 0.277 (P < 0.05) and 0.615 (P < 0.001), respectively, and the model explained 70.2% of the variance in health literacy.

conclusionsHealth literacy was significantly associated with age, BMI, distance between residence and nearest medical institution, monthly income, occupation, and education level, whereas socioeconomic status was a dominant predictor of health literacy level. Targeting these factors might be helpful in allocating health resources rationally when performing health promotion work.

Indexed as

Health LiteracyAdolescentAdultAgedChinaCitiesCross-Sectional StudiesFemaleHealth PromotionHealth StatusHumansInterviews as TopicMaleMiddle AgedQualitative ResearchRural PopulationFactorHealth literacyRural areaStructural equation model

Identifiers

PMID31077197
PMCPMC6509858

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.