Evidence map›Paper›PMID 32290451›Full record

ArticleInternational journal of environmental research and public health2020

Event-Based Heat-Related Risk Assessment Model for South Korea Using Maximum Perceived Temperature, Wet-Bulb Globe Temperature, and Air Temperature Data.

Misun Kang, Kyu Rang Kim, Ju-Young Shin

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Misun KangApplied Meteorology Research Division, National Institute of Meteorological Sciences, Seohobuk-ro 33, Seogwipo 63568, Korea.
Kyu Rang KimApplied Meteorology Research Division, National Institute of Meteorological Sciences, Seohobuk-ro 33, Seogwipo 63568, Korea.
Ju-Young ShinApplied Meteorology Research Division, National Institute of Meteorological Sciences, Seohobuk-ro 33, Seogwipo 63568, Korea.ORCID 0000-0002-1520-3965

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to assess the heat-related risk (excess mortality rate) at six cities, namely, Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan, in South Korea using the daily maximum perceived temperature (PTmax), which is a physiology-based thermal comfort index, the wet-bulb globe temperature, which is meteorology-based thermal comfort index, and air temperature. Particularly, the applicability of PTmax was evaluated using excess mortality rate modeling. An event-based heat-related risk assessment model was employed for modeling the excess mortality rate. The performances of excess mortality rate models using those variables were evaluated for two data sets that were used (training data, 2000-2016) and not used (test data, 2017-2018) for the construction of the assessment models. Additionally, the excess mortality rate was separately modeled depending on regions and ages. PTmax is a good temperature indicator that can be used to model the excess mortality rate in South Korea. The application of PTmax in modeling the total mortality rate yields the best performances for the test data set, particularly for young people. From a forecasting perspective, PTmax is the most appropriate temperature indicator for assessing the heat-related excess mortality rate in South Korea.

Indexed as

Hot TemperatureCitiesEnvironmental ExposureRepublic of KoreaRisk AssessmentSeoulTemperatureheat-related mortalityheatwavemaximum temperatureperceived temperaturewet-bulb globe temperature

Identifiers

PMID32290451
PMCPMC7215463

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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.