Constructing Residential Histories in a General Population-Based Representative Sample

Research on neighborhoods and health typically measures neighborhood context at a single point in time. However, neighborhood exposures accumulate over the life course, influenced by both residential mobility and neighborhood change, with potential implications for estimating the impact of neighborhoods on health. Commercial databases offer fine-grained longitudinal residential address data that can enrich life-course spatial epidemiology research, and validated methods for reconstructing residential histories from these databases are needed. Our study draws on unique data from a geographically diverse, population-based representative sample of adult Wisconsin residents and the LexisNexis (New York, New York) Accurint, a commercial personal profile database, to develop a systematic and reliable methodology for constructing individual residential histories. Our analysis demonstrated that creating residential histories across diverse geographical contexts is feasible, and it highlights differences in the information obtained from available residential histories by age, education, race/ethnicity, and rural/urban/suburban residency. Researchers should consider potential address data availability and information biases favoring socioeconomically advantaged individuals and their implications for studying health inequalities. Despite these limitations, LexisNexis data can generate varied residential exposure metrics and be linked to contextual data to enrich research into the contextual determinants of health at varied geographic scales.