Using Internal Migration to Estimate the Causal Effect of Neighborhood Socioeconomic Context on Health: A Longitudinal Analysis, England, 1995–2008

There is long-standing evidence for the existence of geographical inequalities in health. Multiple conceptual frameworks have been proposed to explain why such patterns persist. The methodological design for these studies is often not appropriate for identifying causal effects of neighborhood context, however. It is possible that findings that show the importance of neighborhoods could be subject to confounding of individual-level factors, neighborhood sorting effects (i.e., health-selective migration), or both. We present an approach to investigating neighborhood-level factors that provides a stronger examination for causal effects, as well as addressing issues of confounding and sorting. We use individual-level data from the British Household Panel Survey (1995–2008). Individuals were grouped into quintiles based on the median house price of an individual's lower super output area as our measure of neighborhood socioeconomic context. Multivariate propensity scores were used to match individuals to control for confounding factors, and logistic regression models were used to estimate the association between destination of migration and risk of poor health (up to ten years following migration). Initially, we found some evidence that poorer neighborhoods were associated with an increased risk of poor health. Following controlling for an individual's health status prior to migration, the influence of neighborhood socioeconomic context was statistically nonsignificant. Our findings suggest that health-selective migration might help to explain the association between neighborhood-level factors and individual-level health. Our study design appears useful for both identifying causal effects of neighborhoods and accounting for health-selective migration.