Comparison of Residential Geocoding Methods in Population-Based Study of Air Quality and Birth Defects

Citation

Gilboa, Suzanne M.; Mendola, Pauline; Olshan, Andrew F.; Harness, Catherine; Loomis, Dana P.; Langlois, Peter H.; Savitz, David A.; & Herring, Amy H. (2006). Comparison of Residential Geocoding Methods in Population-Based Study of Air Quality and Birth Defects. Environmental Research, 101(2), 256-262.

Abstract

Our population-based case–control study of air quality and birth defects in Texas relied on the geocoding of maternal residence from vital records for the assignment of air pollution exposures during early pregnancy. We attempted to geocode the maternal addresses for 5338 birth defect cases and 4574 frequency-matched controls using an automated procedure with standard matching criteria in ArcGIS 8.2 and 8.3. Initially, we matched 7266 observations (73%). To increase the proportion of successful matches, we used an interactive procedure for the 2646 addresses that were initially not geocoded by the software. This yielded an additional 985 matches (37%). Using the same 2646 initially unmatched addresses, we compared the results of this interactive procedure to those of an automated procedure using lower standards. The automated procedure with lower standards yielded more matches (n=1559, 59%) but with questionable accuracy. We included the interactively geocoded observations in our final data set. Their inclusion did not affect the estimates of air pollution exposure but increased our statistical power to detect associations between air quality and risk of selected birth defects. The geocoded and not geocoded populations differed in the distribution of Latino ethnicity (51% vs 59%) and ethnicity was independently associated with air pollution exposures (P<0.05). Geocoding status also appeared to modify the association between ethnicity and risk of birth defects; Latina women appeared to have a slightly lower risk of birth defects than non-Latina women in the geocoded population and to have a slightly higher risk in the not geocoded population. Incomplete geocoding may have resulted in a selection bias because of the underrepresentation of Latinas in our study population.

URL

http://dx.doi.org/10.1016/j.envres.2006.01.004

Reference Type

Journal Article

Year Published

2006

Journal Title

Environmental Research

Author(s)

Gilboa, Suzanne M.
Mendola, Pauline
Olshan, Andrew F.
Harness, Catherine
Loomis, Dana P.
Langlois, Peter H.
Savitz, David A.
Herring, Amy H.

ORCiD

Olshan - 0000-0001-9115-5128