Evidence map›Paper›PMID 27447653›Full record

ArticleInternational journal of environmental research and public health2016

Association by Spatial Interpolation between Ozone Levels and Lung Function of Residents at an Industrial Complex in South Korea.

Soon-Won Jung, Kyoungho Lee, Yong-Sung Cho, Ji-Hee Choi, Wonho Yang, Tack-Shin Kang, Choonghee Park, Geun-Bae Kim, Seung-Do Yu, Bu-Soon Son

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 19% 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, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Article
  5. Article
  6. 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

10 authors at 4 institutions in 1 country.

Soon-Won JungEnvironmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea. melon777@korea.kr.
Kyoungho LeeOccupational Epidemiology, Samsung Health Research Institute, Samsung Electronics, Giheung City 17113, Korea. khlee3789@gmail.com.
Yong-Sung ChoResearch Development and Education Division, National Institute of Chemical Safety, 90, Gajeonbuk-ro, Daejeon 34111, Korea. yscho72@korea.kr.
Ji-Hee ChoiDepartment of Environmental Health Science, Soonchunhyang University, 22, Soonchunhyang-ro, Asan-si 336-745, Korea. jhchoi@sch.ac.kr.
Wonho YangDepartment of Occupational Health, Catholic University of Daegu, 13-13, Hayang-ro, Daegu 38430, Korea. whyang@korea.kr.
Tack-Shin KangEnvironmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea. lm8080@korea.kr.
Choonghee ParkEnvironmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea. whoispch@korea.kr.
Geun-Bae KimEnvironmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea. mykgb@korea.kr.
Seung-Do YuEnvironmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea. sdyu@korea.kr.
Bu-Soon SonDepartment of Environmental Health Science, Soonchunhyang University, 22, Soonchunhyang-ro, Asan-si 336-745, Korea. sonbss@sch.ac.kr.
National Institute of Environmental Research · KRSoonchunhyang University · KRDaegu Catholic University · KRSamsung (South Korea) · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spatial interpolation is employed to improve exposure estimates and to assess adverse health effects associated with environmental risk factors. Since various studies have reported that high ozone (O₃) concentrations can give rise to adverse effects on respiratory symptoms and lung function, we investigated the association between O₃ levels and lung function using a variety of spatial interpolation techniques and evaluated how different methods for estimating exposure may influence health results for a cohort from an industrial complex (Gwangyang Bay) in South Korea in 2009. To estimate daily concentrations of O₃ in each subject, four different methods were used, which include simple averaging, nearest neighbor, inverse distance weighting, and kriging. Also, to compare the association between O₃ levels and lung function by age-groups, we explored ozone's impacts on three age-related groups: children (9-14 years), adults (15-64 years), and the elderly (≥65 years). The overall change of effect size on lung function in each age group tended to show similar patterns for lag and methods for estimating exposure. A significant negative association was only observed between O₃ levels and FVC and FEV₁ for most of the lag and methods in children. The largest effect of O₃ levels was found at the average for the lung function test day and last 2 days (0-2 days). In conclusions, the spatial interpolation methods may benefit in providing individual-level exposure with appropriate temporal resolution from ambient monitors. However, time-activity patterns of residents, monitoring site locations, methodological choices, and other factors should be considered to minimize exposure misclassification.

Indexed as

AdolescentAdultAgedAir PollutantsAir PollutionChildFemaleHumansLungMaleOzoneRepublic of KoreaRespiratory Function TestsRisk FactorsSpatial AnalysisAir PollutantsOzonekriginglung functionozonespatial interpolation

Identifiers

PMID27447653
PMCPMC4962269
OpenAlexW2482173034

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.