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Influence of the Spatial Resolution of the Exposure Estimate in Determining the Association between Heat Waves and Adverse Health Outcomes

Bibliographic Data

ID3775767
AuthorsConnor Y H Wu (0000-0003-1943-9841, Troy University), Benjamin F Zaitchik (0000-0002-0698-0658, Planetary Science Institute), Samarth Swarup (0000-0003-3615-1663, Biocom), Julia M Gohlke (0000-0002-6984-2893, Virginia–Maryland College of Veterinary Medicine, corresponding author)
Year2019
Volume109
Issue3
Pages875-886
Publication date2019-05-04
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAnnals of the American Association of Geographers (JOURNAL)
Journal identifiersISSN: 2469-4452 • E-ISSN: 2469-4460
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/24694452.2018.1511411
PMID31555750
OpenAlexW2915076041
LanguageEN
Citations received5
References cited36

BACKGROUND: Area-level estimates of temperature may lead to exposure misclassification in studies examining associations between heat waves and health outcomes. Our study compared the association between heat waves and preterm birth (PTB) or non-accidental death (NAD) using exposure metrics at varying levels of spatial resolution: ZIP codes, 12.5 km, and 1 km. METHOD: Using geocoded residential addresses on birth (1990-2010) and death (1997-2010) records from Alabama, USA, we implemented a time-stratified case-crossover design to examine the association between heat waves and PTB or NAD. ZIP code- and 12.5 km heat wave indices (HIs) were derived using air temperatures from Phase 2 of the North American Land Data Assimilation System (NLDAS-2). We downscaled NLDAS-2 data, using land surface temperatures (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) product, to estimate fine spatial resolution HIs (1 km). RESULTS: The association between heat waves and PTB or NAD was significant and positive using ZIP code-, 12.5 km, and 1 km exposure metrics. Moreover, results show that these three-exposure metric analyses produced similar effect estimates. Urban heat islands were evident with the 1 km metric. When analyses were stratified by rurality, we found associations in urban areas were more positive than in rural areas. CONCLUSIONS: Comparing results of models with a varying spatial resolution of the exposure metric allows for examination of potential bias associated with exposure misclassification

Climate change · Environmental health · Geography · Heat wave · Climate Change and Health Impacts · Environmental Science · Medicine · Psychology · Thermal Regulation in Medicine · Urban Heat Island Mitigation · Geology

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Unique citing works5
Citations per year0,83
Citation span2020 - 2023 (4)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 4
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