Journal article
Spatio-temporal ozone variation in a case-crossover analysis of childhood asthma hospital visits in New York City
Environmental research, v 147, pp 108-114
May 2016
PMID: 26855129
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Childhood asthma morbidity has been associated with short-term air pollution exposure. To date, most investigations have used time-series models, and it is not well understood how exposure misclassification arising from unmeasured spatial variation may impact epidemiological effect estimates. Here, we develop case-crossover models integrating temporal and spatial individual-level exposure information, toward reducing exposure misclassification in estimating associations between air pollution and child asthma exacerbations in New York City (NYC).
Air pollution data included: (a) highly spatially-resolved intra-urban concentration surfaces for ozone and co-pollutants (nitrogen dioxide and fine particulate matter) from the New York City Community Air Survey (NYCCAS), and (b) daily regulatory monitoring data. Case data included citywide hospital records for years 2005–2011 warm-season (June–August) asthma hospitalizations (n=2353) and Emergency Department (ED) visits (n=11,719) among children aged 5–17 years. Case residential locations were geocoded using a multi-step process to maximize positional accuracy and precision in near-residence exposure estimates. We used conditional logistic regression to model associations between ozone and child asthma exacerbations for lag days 0–6, adjusting for co-pollutant and temperature exposures. To evaluate the effect of increased exposure specificity through spatial air pollution information, we sequentially incorporated spatial variation into daily exposure estimates for ozone, temperature, and co-pollutants.
Percent excess risk per 10ppb ozone exposure in spatio-temporal models were significant on lag days 1 through 5, ranging from 6.5 (95% CI: 0.2–13.1) to 13.0 (6.0–20.6) for inpatient hospitalizations, and from 2.9 (95% CI: 0.1–5.7) to 9.4 (6.3–12.7) for ED visits, with strongest associations consistently observed on lag day 2. Spatio-temporal excess risk estimates were consistently but not statistically significantly higher than temporal-only estimates on lag days 0–3.
Incorporating case-level spatial exposure variation produced small, non-significant increases in excess risk estimates. Our modeling approach enables a refined understanding of potential measurement error in temporal-only versus spatio-temporal air pollution exposure assessments. As ozone generally varies over much larger spatial scales than that observed within NYC, further work is necessary to evaluate potential reductions in exposure misclassification for populations spanning wider geographic areas, and for other pollutants.
•We examined ozone exposure and child asthma ED visits and hospitalizations.•We compared temporal-only and spatio-temporal exposure estimates.•We observed significant excess risk on lag days 1 through 5, highest risk on lag day 2.•Spatial exposure variation produced small increases in excess risk estimates.
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Details
- Title
- Spatio-temporal ozone variation in a case-crossover analysis of childhood asthma hospital visits in New York City
- Creators
- Jessie Loving Carr Shmool - University of PittsburghEllen Kinnee - University of PittsburghPerry Elizabeth Sheffield - Icahn School of Medicine at Mount SinaiJane Ellen Clougherty - University of Pittsburgh
- Publication Details
- Environmental research, v 147, pp 108-114
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Dana and David Dornsife School of Public Health; Drexel University; Environmental and Occupational Health
- Web of Science ID
- WOS:000374275700014
- Scopus ID
- 2-s2.0-84957797023
- Other Identifier
- 991020099049904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Environmental Sciences
- Public, Environmental & Occupational Health