Evidence map›Paper›PMID 30186782›Full record

ArticleIranian journal of public health2018

Influential Factors of Residents' Health in Regions of China: A Comparative Study.

Zhiguang Zhang, Haiqing Hu, Conghui Hao, Kaikai Zhang

Abstract read
In one paragraph

Article in Iranian journal of public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Zhiguang ZhangDept. of Business Administration, Xi'an University of Technology, Xi'an, China.
Haiqing HuDept. of Accounting and Finance, Xi'an University of Technology, Xi'an, China.
Conghui HaoDept. of Economy and Trade, Xi'an University of Technology, Xi'an, China.
Kaikai ZhangDept. of Student Affairs, Shaanxi University of Science and Technology, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the rapid growth of China's economy, the country's economic, social, and environmental development has also shown significant differences in various regions. Improving the health level of residents has gradually become a hot issue. We aimed to explore the difference of the health level of the residents in different regions of China and its influential factors.

methodsA panel regression model was established using statistical data from 31 provinces in the eastern, central, and western regions of China from the years 2000 and 2016 to examine the influence of economic, environmental, and social factors on the health level of residents in these regions and investigate the regulating role of public service factors.

resultsEnvironmental pollution significantly promotes human mortality in the eastern and central regions of China. The urbanization rate significantly reduces human mortality in the eastern and central regions. Per capita gross domestic product in the eastern and western regions has a significant U-shaped relationship with human mortality. The number of beds in health institutions per 10,000 persons, average years of schooling, and endowment insurance contribution service have varying degrees of influence on residents' health level in the three regions of China. In particular, endowment insurance contribution service significantly reduces human mortality in the eastern region, whereas its impact on the western region is insignificant.

conclusionDifferential policies in environmental pollution control, economic growth, and medical and public health should be formulated to reduce mortality in China, specifically in the eastern, central, and western regions.

Indexed as

Economic growthEnvironmental pollutionHuman mortalityPanel regression model

Identifiers

PMID30186782
PMCPMC6123580

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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.