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 re-constructing 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® Accurint®, a commercial personal profile database, to develop a systematic and reliable methodology for constructing individual residential histories. Our analysis demonstrates that creating residential histories across diverse geographical contexts is feasible, and 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.