Evidence map›Paper›PMID 35774578›Full record

ArticleFrontiers in public health2022

Study of the Economic, Environmental, and Social Factors Affecting Chinese Residents' Health Based on Machine Learning.

Hui Xu, Wei Pan, Meng Xin, Wulin Pan, Cheng Hu, Dai Wanqiang, Ge Huang

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Hui XuDong Fureng Institute of Economic and Social Development, Wuhan University, Wuhan, China.
Wei PanSchool of Applied Economics, Renmin University of China, Beijing, China.
Meng XinSchool of Economics and Management, North China Electric Power University, Beijing, China.
Wulin PanSchool of Economic and Management, Wuhan University, Wuhan, China.
Cheng HuSchool of Economic and Management, Wuhan University, Wuhan, China.
Dai WanqiangSchool of Economic and Management, Wuhan University, Wuhan, China.
Ge HuangSchool of Economic and Management, Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Healthy China Strategy puts realistic demands for residents' health levels, but the reality is that various factors can affect health. In order to clarify which factors have a great impact on residents' health, based on China's provincial panel data from 2011 to 2018, this paper selects 17 characteristic variables from the three levels of economy, environment, and society and uses the XG boost algorithm and Random forest algorithm based on recursive feature elimination to determine the influencing variables. The results show that at the economic level, the number of industrial enterprises above designated size, industrial added value, population density, and per capita GDP have a greater impact on the health of residents. At the environmental level, coal consumption, energy consumption, total wastewater discharge, and solid waste discharge have a greater impact on the health level of residents. Therefore, the Chinese government should formulate targeted measures at both economic and environmental levels, which is of great significance to realizing the Healthy China strategy.

Indexed as

Economic DevelopmentSocial FactorsChinaIndustryMachine Learningeconomic factorsenvironmental factorsmachine learningresidents' healthsocial factors

Identifiers

PMID35774578
PMCPMC9237364

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.