Evidence map›Paper›PMID 31207896›Full record

ArticleInternational journal of environmental research and public health2019

Space-Time Relationship between Short-Term Exposure to Fine and Coarse Particles and Mortality in a Nationwide Analysis of Korea: A Bayesian Hierarchical Spatio-Temporal Model.

Dayun Kang, Yujin Jang, Hyunho Choi, Seung-Sik Hwang, Younseo Koo, Jungsoon Choi

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Dayun KangDepartment of Applied Statistics, Hanyang University, Seoul 04763, Korea. dayun4927@hanyang.ac.kr.
Yujin JangDepartment of Applied Statistics, Hanyang University, Seoul 04763, Korea. jennyujin@hanyang.ac.kr.
Hyunho ChoiDepartment of Applied Statistics, Hanyang University, Seoul 04763, Korea. gusgh4950@hanyang.ac.kr.
Seung-Sik HwangDepartment of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea. cyberdoc@snu.ac.kr.
Younseo KooDepartment of Environmental Engineering, Anyang University, Anyang 14028, Korea. koo@anyang.ac.kr.
Jungsoon ChoiDepartment of Mathematics, Hanyang University, Seoul 04763, Korea. jungsoonchoi@hanyang.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have shown an association between mortality and ambient air pollution in South Korea. However, these studies may have been subject to bias, as they lacked adjustment for spatio-temporal structures. This paper addresses this research gap by examining the association between air pollution and cause-specific mortality in South Korea between 2012 and 2015 using a two-stage Bayesian spatio-temporal model. We used 2012-2014 mortality and air pollution data for parameter estimation (i.e., model fitting) and 2015 data for model validation. Our results suggest that the relative risks of total, cardiovascular, and respiratory mortality were 1.028, 1.047, and 1.045, respectively, with every 10-µg/m

Indexed as

Models, TheoreticalMortalityAir PollutantsBayes TheoremEnvironmental ExposureHumansParticle SizeParticulate MatterRepublic of KoreaRiskTime FactorsAir PollutantsParticulate Matterair pollutionBayesian approachcardiovascular diseasemortalityPoisson modelrespiratory diseasespatio-temporal model

Identifiers

PMID31207896
PMCPMC6617003

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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.