Evidence map›Paper›PMID 36408058›Full record

ArticleFrontiers in public health2022

The impact of public health education on people's demand for commercial health insurance: Empirical evidence from China.

Lifei Gao, Ying Nie, Guojun Wang, Fei Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

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

9 citing papers in PubMed.

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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

4 authors.

Lifei GaoSchool of Economics, Beijing Technology and Business University, Beijing, China.
Ying NieSchool of Insurance and Economics, University of International Business and Economics, Beijing, China.
Guojun WangSchool of Insurance and Economics, University of International Business and Economics, Beijing, China.
Fei LiChina Life Reinsurance Company Ltd., Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Public health education is gaining significance globally, and it is important for managing health risks. This study empirically analyzed the effect of public health education on people's demand for commercial health insurance. And we used the fixed effects and the mediating effect models, and instrumental variables regression in our research based on panel data of 31 provinces (including municipalities and autonomous regions) in China from year 2009 to 2019. The findings show that public health education significantly increases people's demand for commercial health insurance, and this effect remains significant when considering endogeneity and robustness. We further analyzed and found that the increased demand for commercial health insurance is caused by health literacy, health risk perceptions and health risk attitudes. Through heterogeneity analysis, we found that there were significant differences in the effects of public health education in regions with different demographic and socioeconomic characteristics. We found that the effect of health education on promoting people's demand for commercial health insurance is more obvious in regions with high levels of urbanization, proportion of men, education, economic development, medical resources, and social medical insurance coverage. Governments are supposed to take further measures to enhance the effectiveness of public health education, develop high-quality commercial health insurance, and continuously improve health risk coverage.

Indexed as

Health EducationInsurance, HealthChinaEconomic DevelopmentEducational StatusHumansMalecommercial health insurancehealth literacyhealth risk attitudehealth risk perceptionpublic health education

Identifiers

PMID36408058
PMCPMC9669966

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Registered trials

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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.