Evidence map›Paper›PMID 31810235›Full record

ArticleHealthcare (Basel, Switzerland)2019

Maternal Health and Green Spaces in China: A Longitudinal Analysis of MMR Based on Spatial Panel Model.

Ping Jin, Yushu Gao, Lingbo Liu, Zhenghong Peng, Hao Wu

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Understanding Barriers and Facilitators of Maternal Health Care Utilization in Central Myanmar.International journal of environmental research and public health · 2020
    Article
  5. 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

5 authors.

Ping JinDepartment of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China.
Yushu GaoDepartment of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China.
Lingbo LiuDepartment of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China.
Zhenghong PengDepartment of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China.
Hao WuDepartment of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China.

Funding

China National Science Fund 51978535Humanities and Social Science 263 project of Ministry of Education 19YJCZH187Wuhan University Experiment Technology Project Funding WHU-2019-SYJS-14
6 · The paper itself

Abstract

The positive impact of green spaces on public health has attracted increasing attention, and maternal health has also been shown to be related to green spaces. However, there are different kinds of green space indicators that represent different mechanisms for mitigating maternal health, and few studies have investigated the different relevance amongst them with longitudinal data. This study explores the correlation between various green space indicators and maternal health using spatial panel models with provincial data from China from 2007 to 2016. The results indicate that all kinds of green spaces could decrease maternal mortality, wherein public green spaces may play a key role. In terms of spatial correlation, an increase in green space coverage in adjacent provinces may also result in a slight decline in maternal mortality. This paper provides valuable insight into the correlation between maternal health and green spaces.

Indexed as

Green Space CoverageMaternal healthMaternal Mortality RatioPublic Green SpaceSpatial Panel Model

Identifiers

PMID31810235
PMCPMC6956252

What OpenQuestion holds

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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.