Author
Listed:
- Soon-Won Jung
(Environmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea)
- Kyoungho Lee
(Occupational Epidemiology, Samsung Health Research Institute, Samsung Electronics, Giheung City 17113, Korea)
- Yong-Sung Cho
(Research Development and Education Division, National Institute of Chemical Safety, 90, Gajeonbuk-ro, Daejeon 34111, Korea)
- Ji-Hee Choi
(Department of Environmental Health Science, Soonchunhyang University, 22, Soonchunhyang-ro, Asan-si 336-745, Korea)
- Wonho Yang
(Department of Occupational Health, Catholic University of Daegu, 13-13, Hayang-ro, Daegu 38430, Korea)
- Tack-Shin Kang
(Environmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea)
- Choonghee Park
(Environmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea)
- Geun-Bae Kim
(Environmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea)
- Seung-Do Yu
(Environmental Health Research Division, National Institute of Environment Research, 42, Hwangyeong-ro, Incheon 22689, Korea)
- Bu-Soon Son
(Department of Environmental Health Science, Soonchunhyang University, 22, Soonchunhyang-ro, Asan-si 336-745, Korea)
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 (O 3 ) concentrations can give rise to adverse effects on respiratory symptoms and lung function, we investigated the association between O 3 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 O 3 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 O 3 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 O 3 levels and FVC and FEV 1 for most of the lag and methods in children. The largest effect of O 3 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.
Suggested Citation
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, 2016.
"Association by Spatial Interpolation between Ozone Levels and Lung Function of Residents at an Industrial Complex in South Korea,"
IJERPH, MDPI, vol. 13(7), pages 1-15, July.
Handle:
RePEc:gam:jijerp:v:13:y:2016:i:7:p:728-:d:74252
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