Matching participant address with public records database in a US national longitudinal cohort study

Marquita S Brooks; Aleena Bennett; Gina S Lovasi; Philip M Hurvitz; Natalie Colabianchi; Virginia J Howard; Jennifer Manly; Suzanne E Judd

doi:10.1016/j.ssmph.2021.100887

Matching participant address with public records database in a US national longitudinal cohort study

SSM Popul Health. 2021 Aug 3:15:100887. doi: 10.1016/j.ssmph.2021.100887. eCollection 2021 Sep.

Authors

Marquita S Brooks¹, Aleena Bennett¹, Gina S Lovasi², Philip M Hurvitz³, Natalie Colabianchi⁴, Virginia J Howard⁵, Jennifer Manly⁶, Suzanne E Judd¹

Affiliations

¹ Department of Biostatistics, University of Alabama at Birmingham (UAB), Birmingham, AL, USA.
² Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
³ Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, USA.
⁴ Environment and Policy Lab, University of Michigan School of Kinesiology, Ann Arbor, MI, USA.
⁵ Department of Epidemiology, UAB, Birmingham, AL, USA.
⁶ Neurology at Gertrude H. Sergievsky Center and the Taub Institute for Research in Aging and Alzheimer's Disease, Columbia University, New York, NY, USA.

Abstract

Background: Epidemiological studies utilize residential histories to assess environmental exposure risk. The validity from using commercially-sourced residential histories within national longitudinal studies remains unclear. Our study assessed predictors of non-agreement between baseline addresses from the commercially-sourced LexisNexis database and participants in the national longitudinal study, REasons for Geographic and Racial Differences in Stroke (REGARDS). Additionally, we assessed differences in stroke risk by neighborhood socioeconomic score (nSES) based on participant reported address compared to nSES from LexisNexis/REGARDS matched baseline address.

Methods: From January 2003-October 2007, REGARDS enrolled 30,239 black and white adults aged 45 and older within the continental United States and collected their baseline address. ArcGIS Desktop 10.5.1 with ESRI 2016 Business Analyst Data was used to geocode baseline addresses from LexisNexis and REGARDS. Logistic regression was used to estimate the likelihood that LexisNexis address matched REGARDS baseline address for each participant. Survival analysis was used to estimate association between nSES and incident stroke.

Results: Approximately 91% of REGARDS participants had a LexisNexis address. Of these geocoded addresses, 93% of REGARDS baseline addresses matched LexisNexis addresses. Odds of agreement between LexisNexis and REGARDS was higher for older-aged participants (OR = 1.02 per year, 95% CI: 1.01, 1.02), blacks compared to whites (OR = 1.16, 95% CI: 1.05, 1.29), females compared to males (OR = 1.15, 95% CI: 1.04, 1.26), participants with an income of $34k-74k compared to an income less than $20k (OR = 1.62, 95% CI: 1.39, 1.89). Odds of agreement were lower for residents in Midwest compared to residents in the south (OR = 0.82, 95% CI: 0.73, 0.94). No significant differences in nSES-stroke associations were observed between REGARDS only and LexisNexis/REGARDS matched addresses; however, differences in interactions were observed.

Conclusion: Agreement between LexisNexis and REGARDS addresses varied by sociodemographic groups, potentially introducing bias in studies reliant on LexisNexis alone for residential address data.

Keywords: Environmental exposure; Residential address; Residential history.

Published by Elsevier Ltd.

Abstract

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