Evidence map›Paper›PMID 27489155›Full record

ArticleBMJ open2016

Long-term changes in the heat-mortality relationship according to heterogeneous regional climate: a time-series study in South Korea.

Seulkee Heo, Eunil Lee, Bo Yeon Kwon, Suji Lee, Kyung Hee Jo, Jinsun Kim

Abstract read
In one paragraph

Article in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 3 pooled it
–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

18 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  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. Association between moderately cold temperature and mortality in China.Environmental science and pollution research international · 2020
    Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Research Trends in Agenda-setting for Climate Change Adaptation Policy in the Public Health Sector in Korea.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2020
    Review
  12. Heat waves in South Korea: differences of heat wave characteristics by thermal indices.Journal of exposure science & environmental epidemiology · 2019
    Article
  13. Article
  14. Article
  15. Article
  16. The Use of a Quasi-Experimental Study on the Mortality Effect of a Heat Wave Warning System in Korea.International journal of environmental research and public health · 2019
    Article
  17. Article
  18. Public perceptions of the health risks of extreme heat across US states, counties, and neighborhoods.Proceedings of the National Academy of Sciences of the United States of America · 2019
    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

6 authors.

Seulkee HeoDepartment of Public Health, Graduate School, Korea University, Seoul, South Korea.
Eunil LeeDepartment of Public Health, Graduate School, Korea University, Seoul, South Korea Department of Preventive Medicine, College of Medicine, Korea University, Seoul, Korea Graduate School of Public Health, Graduate School, Korea University, Seoul, Korea.
Bo Yeon KwonDepartment of Public Health, Graduate School, Korea University, Seoul, South Korea.
Suji LeeDepartment of Preventive Medicine, College of Medicine, Korea University, Seoul, Korea.
Kyung Hee JoGraduate School of Public Health, Graduate School, Korea University, Seoul, Korea.
Jinsun KimGraduate School of Public Health, Graduate School, Korea University, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSeveral studies identified a heterogeneous impact of heat on mortality in hot and cool regions during a fixed period, whereas less evidence is available for changes in risk over time due to climate change in these regions. We compared changes in risk during periods without (1996-2000) and with (2008-2012) heatwave warning forecasts in regions of South Korea with different climates.

methodsStudy areas were categorised into 3 clusters based on the spatial clustering of cooling degree days in the period 1993-2012: hottest cluster (cluster H), moderate cluster (cluster M) and cool cluster (cluster C). The risk was estimated according to increases in the daily all-cause, cardiovascular and respiratory mortality per 1°C change in daily temperature above the threshold, using a generalised additive model.

resultsThe risk of all types of mortality increased in cluster H in 2008-2012, compared with 1996-2000, whereas the risks in all-combined regions and cooler clusters decreased. Temporal increases in mortality risk were larger for some vulnerable subgroups, including younger adults (<75 years), those with a lower education and blue-collar workers, in cluster H as well as all-combined regions. Different patterns of risk change among clusters might be attributable to large increases in heatwave frequency or duration during study periods and the degree of urbanisation in cluster H.

conclusionsPeople living in hotter regions or with a lower socioeconomic status are at higher risk following an increasing trend of heat-related mortality risks. Continuous efforts are needed to understand factors which affect changes in heat-related mortality risks.

Indexed as

AdolescentAdultAgedAged, 80 and overAir PollutantsAir PollutionChildChild, PreschoolClimate ChangeCluster AnalysisEnvironmental ExposureExtreme HeatFemaleForecastingHumansInfantAir PollutantsEPIDEMIOLOGYOCCUPATIONAL & INDUSTRIAL MEDICINEPUBLIC HEALTH

Identifiers

PMID27489155
PMCPMC4985795

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.