Background: Evaluating the long-term health consequences of migration requires longitudinal data on migrants and non-migrants to facilitate adjustment for time-varying confounder-mediators of the effect of migration on health. Methods: We merged harmonized data on subjects aged 50+ from the US-based Health and Retirement Study (HRS) and the Mexican Health and Aging Study (MHAS). Our exposed group includes MHAS-return migrants (n = 1555) and HRS Mexican-born migrants (n = 924). Our unexposed group includes MHAS-never migrants (n = 16,954). We constructed a lifecourse data set from birth (age 0) until either age at migration to the United States or age at study entry. To account for confounding via inverse probability of treatment weights (IPTW), we modeled the probability of migration at each year of life using time-varying pre-migration characteristics. We then evaluated the effect of migration on mortality hazard estimated with and without IPTW. Results: Mexico to the United States migration was predicted by time-varying factors that occurred before migration. Using measured covariates at time of enrollment to account for selective migration, we estimated that, for women, migrating reduces mortality risk by 13%, although this estimate was imprecise and results were compatible with either large protective or deleterious associations (hazard ratio [HR] =0.87, 95% confidence interval [CI]: 0.60, 1.27). When instead using IPTWs, the estimated effect on mortality was similarly imprecise (HR = 0.98, 95% CI: 0.77, 1.25). The relationship among men was similarly uncertain in both models. Conclusions: Although time-varying social factors predicted migration, IPTW weighting did not affect our estimates. Larger samples are needed to precisely estimate the health effects of migration.
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