Individual exposure to air pollution and lung function in Korea: Spatial analysis using multiple exposure approaches

Son, Ji Young; Bell, Michelle L.; Lee, Jong Tae

doi:10.1016/j.envres.2010.08.003

Cited by 79 publications

(52 citation statements)

References 36 publications

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“…Some of these studies have reported evaluation of ordinary kriging models based on the leave-one-out cross-validation approach [17-19]. Leem et al [17] and Seo et al [18] reported good agreement between observed and cross-validation predicted PM 10 concentrations in Incheon and the seven major cities included in our study.…”

Section: Discussionsupporting

confidence: 65%

“…Many cohort studies into air pollution in South Korea have used ordinary kriging to estimate individual-level or fine-scale area-level concentrations of air pollution including PM 10 [15- 19]. Some of these studies have reported evaluation of ordinary kriging models based on the leave-one-out cross-validation approach [17-19].…”

Section: Discussionmentioning

confidence: 99%

“…When temporal variability was adjusted, cross-validated R 2 s dramatically decreased depending on the city and the PM2.5 component. In an assessment of annual average PM 10 concentrations in Ulsan, Son et al [19] compared MSEs from ordinary kriging with those obtained from area-averaging, nearest-monitor, and inverse-distance-weighting methods by using cross-validation. Although the MSE of the ordinary kriging model was smaller than the MSE of the other three approaches, all four methods produced large MSEs that were greater than the variance of the data, indicative of poor model performance.…”

Section: Discussionmentioning

confidence: 99%

“…Some of these studies used simple approaches such as area-averaging and inverse-distance-weighting methods [12-14]. Others adopted ordinary kriging to estimate spatially heterogeneous air pollution concentrations across individuals [15-19]. However, most of those studies limited their study areas to single cities.…”

Section: Introductionmentioning

confidence: 99%

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Ordinary kriging approach to predicting long-term particulate matter concentrations in seven major Korean cities

Kim

Eum

et al. 2014

Environ Health Toxicol

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ObjectivesCohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to 10 μm in diameter (PM10) concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability.MethodsWe obtained hourly PM10 data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average PM10 concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared (R2) statistics were computed.ResultsMean annual average PM10 concentrations in the seven major cities ranged between 45.5 and 66.0 μg/m3 (standard deviation=2.40 and 9.51 μg/m3, respectively). Cross-validated R2 values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had R2 values of zero. The national model produced a higher crossvalidated R2 (0.36) than those for the city-specific models.ConclusionsIn general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate PM10 source characteristics.

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Section: Discussionsupporting

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Ordinary kriging approach to predicting long-term particulate matter concentrations in seven major Korean cities

Kim

Eum

et al. 2014

Environ Health Toxicol

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“…Although levels of air pollutants including SO 2 , NO 2 , and PM 10 in major cities have not considerably increased in the last 10 years [31], air pollution in Seoul, particularly PM 10 , has increased more compared to other large cities such as Paris, Los Angeles, and London [32,33]. A small number of studies on allergic diseases conducted in Korea have taken into account spatial autocorrelation in ambient air pollutants [34,35], while others focus upon the prevalence of allergic diseases [36]. However, no studies simultaneously account for spatial autocorrelation in their bivariate analysis.…”

Section: Introductionmentioning

confidence: 99%

A Closer Look at the Bivariate Association between Ambient Air Pollution and Allergic Diseases: The Role of Spatial Analysis

Kim

Seo

Min

et al. 2018

IJERPH

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Although previous ecological studies investigating the association between air pollution and allergic diseases accounted for temporal or seasonal relationships, few studies address spatial non-stationarity or autocorrelation explicitly. Our objective was to examine bivariate correlation between outdoor air pollutants and the prevalence of allergic diseases, highlighting the limitation of a non-spatial correlation measure, and suggesting an alternative to address spatial autocorrelation. The 5-year prevalence data (2011–2015) of allergic rhinitis, atopic dermatitis, and asthma were integrated with the measures of four major air pollutants (SO2, NO2, CO, and PM10) for each of the 423 sub-districts of Seoul. Lee’s L statistics, which captures how much bivariate associations are spatially clustered, was calculated and compared with Pearson’s correlation coefficient for each pair of the air pollutants and allergic diseases. A series of maps showing spatiotemporal patterns of allergic diseases at the sub-district level reveals a substantial degree of spatial heterogeneity. A high spatial autocorrelation was observed for all pollutants and diseases, leading to significant dissimilarities between the two bivariate association measures. The local L statistics identifies the areas where a specific air pollutant is considered to be contributing to a type of allergic disease. This study suggests that a bivariate correlation measure between air pollutants and allergic diseases should capture spatially-clustered phenomenon of the association, and detect the local instability in their relationships. It highlights the role of spatial analysis in investigating the contribution of the local-level spatiotemporal dynamics of air pollution to trends and the distribution of allergic diseases.

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Particulate Matter Containing Environmentally Persistent Free Radicals and Adverse Infant Respiratory Health Effects: A Review

Saravia

Lee

Lomnicki

et al. 2012

J Biochem & Molecular Tox

103

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The health impacts of airborne particulate matter (PM) are of global concern, and the direct implications to the development/exacerbation of lung disease are immediately obvious. Most studies to date have sought to understand mechanisms associated with PM exposure in adults/adult animal models; however, infants are also at significant risk for exposure. Infants are affected differently than adults due to drastic immaturities, both physiologically and immunologically, and it is becoming apparent that they represent a critically understudied population. Highlighting our work funded by the ONES award, in this review we argue the understated importance of utilizing infant models to truly understand the etiology of PM-induced predisposition to severe, persistent lung disease. We also touch upon various mechanisms of PM-mediated respiratory damage, with a focus on the emerging importance of environmentally persistent free radicals (EPFRs) ubiquitously present in combustion-derived PM. In conclusion, we briefly comment on strengths/challenges facing current PM research, while giving perspective on how we may address these challenges in the future.

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Individual exposure to air pollution and lung function in Korea: Spatial analysis using multiple exposure approaches

Cited by 79 publications

References 36 publications

Ordinary kriging approach to predicting long-term particulate matter concentrations in seven major Korean cities

Ordinary kriging approach to predicting long-term particulate matter concentrations in seven major Korean cities

A Closer Look at the Bivariate Association between Ambient Air Pollution and Allergic Diseases: The Role of Spatial Analysis

Particulate Matter Containing Environmentally Persistent Free Radicals and Adverse Infant Respiratory Health Effects: A Review

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