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Journal article
Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology
International journal of environmental research and public health, v 17(16), pp 1-23
01 Aug 2020
PMID: 32806682
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Although environmental epidemiology studies often rely on geocoding procedures in the process of assigning spatial exposure estimates, geocoding methods are not commonly reported, nor are consequent errors in exposure assignment explored. Geocoding methods differ in accuracy, however, and, given the increasing refinement of available exposure models for air pollution and other exposures, geocoding error may account for an increasingly larger proportion of exposure misclassification. We used residential addresses from a reasonably large, dense dataset of asthma emergency department visits from all New York City hospitals (n= 21,183; 26.9 addresses/km(2)), and geocoded each using three methods (Address Point, Street Segment, Parcel Centroid). We compared missingness and spatial patterning therein, quantified distance and directional errors, and quantified impacts on pollution exposure estimates and assignment to Census areas for sociodemographic characterization. Parcel Centroids had the highest overall missingness rate (38.1%, Address Point = 9.6%, Street Segment = 6.1%), and spatial clustering in missingness was significant for all methods, though its spatial patterns differed. Street Segment geocodes had the largest mean distance error (mu = 29.2 (SD = 26.2) m; vs. mu = 15.9 (SD = 17.7) m for Parcel Centroids), and the strongest spatial patterns therein. We found substantial over- and under-estimation of pollution exposures, with greater error for higher pollutant concentrations, but minimal impact on Census area assignment. Finally, we developed surfaces of spatial patterns in errors in order to identify locations in the study area where exposures may be over-/under-estimated. Our observations provide insights towards refining geocoding methods for epidemiology, and suggest methods for quantifying and interpreting geocoding error with respect to exposure misclassification, towards understanding potential impacts on health effect estimates.
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Details
- Title
- Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology
- Creators
- Ellen J. Kinnee - University of PittsburghSheila Tripathy - Drexel UniversityLeah Schinasi - Drexel UniversityJessie L. C. Shmool - University of PittsburghPerry E. Sheffield - Icahn School of Medicine at Mount SinaiFernando Holguin - University of Colorado DenverJane E. Clougherty - Drexel University
- Publication Details
- International journal of environmental research and public health, v 17(16), pp 1-23
- Publisher
- Mdpi
- Number of pages
- 23
- Grant note
- R01HL114536 / National Heart Lung Blood Institute (NHLBI); United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Heart Lung & Blood Institute (NHLBI) R01ES030717 / National Institute of Environmental Health Sciences (NIEHS); United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Environmental Health Sciences (NIEHS)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Environmental and Occupational Health
- Web of Science ID
- WOS:000565080600001
- Scopus ID
- 2-s2.0-85089623016
- Other Identifier
- 991019167467004721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Environmental Sciences
- Public, Environmental & Occupational Health