Evidence map›Paper›PMID 36293869›Full record

ArticleInternational journal of environmental research and public health2022

Global Population Exposure to Extreme Temperatures and Disease Burden.

Yajie Du, Ming Jing, Chunyu Lu, Jingru Zong, Lingli Wang, Qing Wang

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
1.1field-weighted citation impact, top 26% of its field
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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 12 citations in OpenAlex.

  1. Building the model: a review of input structures in extreme temperature-health.Environmental health : a global access science source · 2026
    Pooled it
  2. Pooled it
  3. Article
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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 at 2 institutions in 1 country.

Yajie DuDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
Ming JingSchool of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Science), Jinan 250353, China.
Chunyu LuDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
Jingru ZongDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
Lingli WangDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
Qing WangDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
Shandong University · CNQilu University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The frequency and duration of extreme temperature events continues to increase worldwide. However, the scale of population exposure and its quantitative relationship with health risks remains unknown on a global scale, limiting our ability to identify policy priorities in response to climate change. Based on data from 171 countries between 2010 and 2019, this study estimated the exposure of vulnerable populations to extreme temperatures, and their contemporary and lag associations with disease burden attributed to non-optimal temperatures. Fixed-effects models and dynamic panel models were applied. Increased vulnerable population exposure to extreme temperatures had adverse contemporary effects on the burden of disease attributed to non-optimal temperature. Health risks stemming from extreme cold could accumulate to a greater extent, exhibiting a larger lag effect. Population exposure to extreme cold was mainly distributed in high-income countries, while extreme heat occurred more in low-income and middle-income countries. However, the association between population exposure to extreme cold and burden of disease was much stronger in low-income and middle-income countries than in high-income countries, whereas the effect size of population exposure to extreme heat was similar. Our study highlighted that differential strategies should be determined and implemented according to the characteristics in different countries.

Indexed as

Extreme HeatHot TemperatureClimate ChangeCold TemperatureCost of IllnessTemperaturedisease burdenextreme temperaturelow-income and middle-income countriespopulation exposure

Identifiers

PMID36293869
PMCPMC9603138
OpenAlexW4306382006

What OpenQuestion holds

Textmetadata
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.