Improving spatial exposure data for everyone - lifecourse social context and ascertaining residential history.

ABSTRACT

Measuring age-specific, contextual exposures is crucial for lifecourse epidemiology research. Longitudinal residential data offers a "golden ticket" to cumulative exposure metrics and can enhance our understanding of health disparities. Residential history can be linked to myriad spatiotemporal databases to characterize environmental, socioeconomic, and policy contexts that a person experienced throughout life. However, obtaining accurate residential history is challenging in the United States due to the limitations of administrative registries and self-reports. Xu et al. (Am J Epidemiol. 2024; 193(2)348-359) detail an approach to linking residential history sourced from LexisNexis ® Accurint ® to a Wisconsin-based research cohort, offering insights into challenges with residential history collection. Researchers must analyze the magnitude of selection and misclassification biases inherent to ascertaining residential history from cohort data. A lifecourse framework can provide insights into why the frequency and distance of moves is patterned by age, birth cohort, racial/ethnic identity, socioeconomic status, and urbanicity. Historic and contemporary migration patterns of marginalized people seeking economic and political opportunities must guide interpretations of residential history data. We outline methodologic priorities for use of residential history in health disparities research, including contextualizing residential history data with determinants of residential moves, triangulating spatial exposure assessment methods, and transparently quantifying measurement error.