Evidence map›Paper›PMID 39680440›Full record

ArticleJMIR public health and surveillance2024

Effect of Health Literacy on Antiviral Treatment of Hepatitis B: Instrumental Variable Analysis.

Hanchao Cheng, Shiyang Liu, Zhitao Wang, Qiyou Wu, Xin Wang, Polin Chan, Zhongdan Chen, Simon Luo, Yinghua Li, Jing Sun

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Hanchao Cheng *School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID 0000-0003-4551-4614
Shiyang Liu *Medical School of Chinese People's Liberation Army, The Fifth Medical Center of People's Liberation Army General Hospital, Beijing, China.ORCID 0000-0001-9311-4020
Zhitao WangSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID 0000-0002-9730-5382
Qiyou WuSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID 0000-0002-9730-5382
Xin WangTongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, China.ORCID 0009-0007-8103-7778
Polin ChanHepatitis/Tuberculosis/HIV/STI, World Health Organization Regional Office for the South East Asia, Dehli, India.ORCID 0000-0003-1708-5170
Zhongdan ChenHepatitis/TB/HVI/STI, World Health Organization Representative Office in China, Beijing, China.ORCID 0000-0002-2514-7661
Simon LuoIQVIA, China, Beijing, China.ORCID 0009-0006-4612-5070
Yinghua LiChina Health Education Center, Beijing, China.ORCID 0000-0002-0371-8304
Jing SunSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID 0000-0002-4646-1174

Funding

World Health Organization 001
6 · The paper itself

Abstract

Background: China is a country with a high burden of hepatitis B (Hep B) but a low treatment rate. One of the key reasons for the low treatment rate is the inadequate health literacy (HL) of the people, which may affect the awareness and knowledge of Hep B and its treatment, as well as the ability to actively and correctly seek medical resources. Objective: This study analyzed how HL contributed to the scale-up of antiviral treatment of Hep B in China. We expect that the findings of this study could be used to inform resource allocation for health education and other approaches intending to improve the HL of the Chinese population, thus facilitating the nationwide scale-up of Hep B treatment and contributing to the achievement of the 2030 goal of eliminating viral hepatitis as a major public health threat in China. Methods: We used the two-stage least squares regression method and adopted the mobile phone penetration rate as the instrumental variable to estimate the effect of improved HL on the number of 12-month standard Hep B antiviral treatments in China based on the panel data of 31 provinces from 2013 to 2020. Results: In the cross-sectional dimension, the higher the HL, the higher the number of treatments in the provinces in a specific year. In the time series dimension, the number of treatments in a specific province increased with the improvement of HL over time. After controlling the time-invariant inherent attributes of provinces, the instrumental variable estimation with two-stage least squares regression based on the province fixed effect model found that for every 1% increase of HL in each province, the number of treatments increased by 7.15% (0.0715 = e0.0691 - 1; P<.001). Such an increase turned to 5.19% (0.0519 = e0.0506 - 1; P<.001) for the analysis targeting the observation time from 2013 to 2019, as the data of 2020 were removed when the COVID-19 pandemic started. The study found no statistically significant effect of HL on the number of Hep B treatments in the provinces with higher newly reported Hep B incidence and lower gross domestic product per capita. Conclusions: Our findings suggest that improved HL of the population is an important favorable facilitator for the scale-up of Hep B treatment in China. Building awareness and knowledge of Hep B and its treatment can help individuals understand their health status, ensuring a healthier lifestyle and appropriate health care-seeking behaviors and health care service utilization, so that people can be diagnosed and treated timely and appropriately. Enhancing resource allocation to improve the overall HL of the population and sending Hep B-specific messages to the infected people would be a feasible and effective approach to scale-up the treatment of Hep B in low- and middle-income settings with limited resources, and contribute to achieving the 2030 global goal of eliminating viral hepatitis as a major public health threat.

Indexed as

Antiviral AgentsHealth LiteracyHepatitis BChinaCross-Sectional StudiesHumansMaleAntiviral Agentsantiviral treatmentChinahealth literacyhepatitis Binstrumental variablelongitudinal study

Identifiers

PMID39680440
PMCPMC11665480

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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.