Measuring Women’s Cumulative Neighborhood Deprivation Exposure Using Longitudinally Linked Vital Records: A Method for Life Course MCH Research
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A life course conceptual framework for MCH research demands new tools for understanding population health and measuring exposures. We propose a method for measuring population-based socio-environmental trajectories for women of reproductive age. We merged maternal longitudinally-linked births to Georgia-resident women from 1994 to 2007 with census economic and social measures using residential geocodes to create woman-centered socio-environmental trajectories. We calculated a woman’s neighborhood deprivation index (NDI) at the time of each of her births and, from these, we calculated a cumulative NDI. We fit Loess curves to describe average life course NDI trajectories and binomial regression models to test specific life course theory hypotheses relating cumulative NDI to risk for preterm birth. Of the 1,815,944 total live births, we linked 1,000,437 live births to 413,048 unique women with two or more births. Record linkage had high specificity but relatively low sensitivity which appears non-differential with respect to maternal characteristics. Georgia women on average experienced upward mobility across the life course, although differences by race, early life neighborhood quality, and age at first birth produced differences in cumulative NDI. Adjusted binomial models found evidence for modification of the effect of history of prior preterm birth and advancing age on risk for preterm birth by cumulative NDI. The creation of trajectories from geocoded maternal longitudinally-linked vital records is one method to carry out life course MCH research. We discuss approaches for investigating the impact of truncation of the life course, selection bias from migration, and misclassification of cumulative exposure.
KeywordsNeighborhood environment Pregnancy outcomes Preterm birth Health disparities Record linkage
Life course theory
Maternal and Child Health
Preterm, low birth weight
This study was supported by grant R40MC17180 from the Maternal and Child Health Bureau (Title V, Social Security Act), Health Resources and Services Administration, Department of Health and Human Services. The authors also wish to acknowledge the cooperation of the Office of Health Indicators for Planning of the Georgia Department of Public Health.
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