Incorporating residential histories into assessment of cancer risk

There is growing recognition that area-level biological and physical exposures associated with residential location across the life-course must be considered for more precise cancer risk and outcomes. Yet many cohort studies lack comprehensive residential history information or limit analyses to the residence at enrollment or cancer diagnosis, a critical limitation in assessment of exposure causation potentially leading to misclassification or biased associations. Residential histories derived from commercial vendors offer an exciting opportunity to integrate the neighborhood environment into cancer research. Little research has been conducted incorporating life-course residential history information into cohort studies, particularly in poverty regions such as in the Southeast.

Populations living in the Southeast have the highest cancer risk and some of the poorest health outcomes among all U.S. populations. To address gaps in knowledge of how best to integrate geospatial data via life-course residential histories into cancer research cohort studies, we propose to evaluate residential histories in a well-resourced and large-scale observational prospective cohort of adults, with the following specific aims: 1) collect and describe self-reported adult life-course residential histories, 2) develop algorithms to reconstruct temporal residential histories, and 3) evaluate residential mobility and spatiotemporal changes in area-level life-course exposures and cancer risk. We hypothesize concordance of residential history between vendor and self-report varies by population group and incorporating residential mobility improves exposure assessment and reduces bias in cancer research. We propose to construct residential histories, link residential histories to geospatial exposures, and test associations between geospatial exposures across the life-course and cancer risk.

We will focus on the four most common cancers (breast, lung, colorectal, prostate) in over 84,000 participants recruited across 12 Southern states. Our design focuses on robust methods to identify factors predictive of residential history patterns, including those living in poverty regions, and novel translation of residential history information into an interpretable context. Our project then examines neighborhoods which can influence cancer risk over space and time. Our project fosters innovative collaborations among a multidisciplinary team with scientific expertise in cancer epidemiology, survey design, geospatial analyses, small area estimation, and biostatistics.

Findings from our multidisciplinary approach will have sustained impact since it will reveal pathways for improved precision to incorporate area-level exposures across the life-course.

Grant Number: 4R01CA276266-03
NIH Institute/Center: NIH
Principal Investigator: Melinda Aldrich