Evidence map›Paper›PMID 32927631›Full record

ArticleInternational journal of environmental research and public health2020

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches.

Minxuan Zheng, Jiahua Zhang, Lamei Shi, Da Zhang, Til Prasad Pangali Sharma, Foyez Ahmed Prodhan

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Variations of Urban Thermal Risk with Local Climate Zones.International journal of environmental research and public health · 2023
    Article
  4. Review
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

6 authors.

Minxuan ZhengKey Laboratory of Digital Earth Sciences, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China.ORCID 0000-0002-1429-3276
Jiahua ZhangKey Laboratory of Digital Earth Sciences, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China.ORCID 0000-0002-2894-9627
Lamei ShiKey Laboratory of Digital Earth Sciences, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China.
Da ZhangKey Laboratory of Digital Earth Sciences, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China.
Til Prasad Pangali SharmaKey Laboratory of Digital Earth Sciences, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China.ORCID 0000-0002-9211-8238
Foyez Ahmed ProdhanKey Laboratory of Digital Earth Sciences, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China.ORCID 0000-0003-3109-0558

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches-Crichton's risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton's risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman's rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.

Indexed as

Geographic Information SystemsHot TemperatureChinaCitiesEnvironmental HealthHumansPublic HealthRisk AssessmentCrichton’s risk triangledeveloping countriesheat-health riskheat vulnerability index (HVI)spatial risk assessment

Identifiers

PMID32927631
PMCPMC7559026

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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.