Evidence map›Paper›PMID 38238587›Full record

ArticleScientific reports2024

Geodetector analysis of individual and joint impacts of natural and human factors on maternal and child health at the provincial scale.

Jialu Chen, Shuyuan Wang, Ying Han, Yongjin Zhang, Yuansheng Li, Beibei Zhang, Xiang Li, Junhui Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

8 authors.

Jialu Chen *Department of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Road, Longmatan District, Luzhou, 646000, Sichuan, People's Republic of China.
Shuyuan Wang *Department of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Road, Longmatan District, Luzhou, 646000, Sichuan, People's Republic of China.
Ying HanDepartment of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Road, Longmatan District, Luzhou, 646000, Sichuan, People's Republic of China.
Yongjin ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Road, Longmatan District, Luzhou, 646000, Sichuan, People's Republic of China.
Yuansheng LiDepartment of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Road, Longmatan District, Luzhou, 646000, Sichuan, People's Republic of China.
Beibei ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Road, Longmatan District, Luzhou, 646000, Sichuan, People's Republic of China.
Xiang LiDepartment of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Road, Longmatan District, Luzhou, 646000, Sichuan, People's Republic of China.
Junhui ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Road, Longmatan District, Luzhou, 646000, Sichuan, People's Republic of China. zjh960500@swmu.edu.cn.

Funding

the National Statistical Science Research Project of China No.2021LZ31the Scientific Research Project of Southwest Medical University No.2021ZKMS002
6 · The paper itself

Abstract

This ecological study examined the individual and joint impacts of natural-human factors on the spatial patterns of maternal and child health status in China at the provincial scale in 2020. We considered natural factors (forest coverage, average temperature, and total sulfur dioxide and particulate matter emissions) and human factors (economic development, urbanization, healthcare access, and education level). We combined maternal, infant, and under-five mortality rates into a composite maternal and child health index using the entropy method. The spatial autocorrelation analysis of this index highlighted distinct health patterns across provinces, whereas the geodetector method assessed the effects of natural-human factors on the patterns. A notable east-central-west stepwise decline in health status was observed. Global Moran's I showed positive spatial clustering, with high-high clustering areas in the Yangtze River Delta and low-low clustering areas in western regions. Factor detection identified eight significant natural-human factors impacting maternal and child health, with total sulfur dioxide emission density having the greatest impact. The interaction between average schooling years and total sulfur dioxide emission notably affected maternal and child health patterns. The study concludes that natural-human factors critically affect the spatial distribution of maternal and child health.

Indexed as

Child HealthSulfur DioxideChildChinaForestsHumansInfantSocioeconomic FactorsSpatial AnalysisSulfur Dioxide

Identifiers

PMID38238587
PMCPMC10796915

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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.