ArticleEnvironmental health and toxicology2014
Spatial analysis of PM10 and cardiovascular mortality in the Seoul metropolitan area.
Article in Environmental health and toxicology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Spatial Analysis of Ambient Air Pollution and Cardiovascular Disease (CVD) Hospitalization Across Sweden.GeoHealth · 2021Article
- Spatial-Temporal Modelling of Disease Risk Accounting for PM2.5 Exposure in the Province of Pavia: An Area of the Po Valley.International journal of environmental research and public health · 2021Article
- Current State of Research on the Risk of Morbidity and Mortality Associated with Air Pollution in Korea.Yonsei medical journal · 2019Review
- Spatial patterns of childhood diarrhea in Ethiopia: data from Ethiopian demographic and health surveys (2000, 2005, and 2011).BMC infectious diseases · 2017Article
- A survey-based study on the protocols for therapeutic hypothermia in cardiac arrest patients in Korea: focusing on the differences between level 1 and 2 centers.Clinical and experimental emergency medicine · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesNumerous studies have revealed the adverse health effects of acute and chronic exposure to particulate matter less than 10 μm in aerodynamic diameter (PM10). The aim of the present study was to examine the spatial distribution of PM10 concentrations and cardiovascular mortality and to investigate the spatial correlation between PM10 and cardiovascular mortality using spatial scan statistic (SaTScan) and a regression model.
methodsFrom 2008 to 2010, the spatial distribution of PM10 in the Seoul metropolitan area was examined via kriging. In addition, a group of cardiovascular mortality cases was analyzed using SaTScan-based cluster exploration. Geographically weighted regression (GWR) was applied to investigate the correlation between PM10 concentrations and cardiovascular mortality.
resultsAn examination of the regional distribution of the cardiovascular mortality was higher in provincial districts (gu) belonging to Incheon and the northern part of Gyeonggido than in other regions. In a comparison of PM10 concentrations and mortality cluster (MC) regions, all those belonging to MC 1 and MC 2 were found to belong to particulate matter (PM) 1 and PM 2 with high concentrations of air pollutants. In addition, the GWR showed that PM10 has a statistically significant relation to cardiovascular mortality.
conclusionsTo investigate the relation between air pollution and health impact, spatial analyses can be utilized based on kriging, cluster exploration, and GWR for a more systematic and quantitative analysis. It has been proven that cardiovascular mortality is spatially related to the concentration of PM10.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.