Detecting Early Life Exposures on Mid-Life Mortality in the US through Big Data

This project will trace the mid-life mortality of birth cohorts of the mid 20th century in the US by place, time, and family factors. Combining “big data” with a large array of contextual exposures, we substantially deepen our understanding of the complexities of how childhood exposures to disease, economic change, stress, and nutritional programs shape mid-life mortality profiles of cohorts born ~1940-1960. We fuse together hypothesis-driven tests and data driven discoveries; Our proposal combines the massive Numident/BUNMD and MLP data, which contains >3.5 million death records between 1988-2005 to test specific hypotheses as well as generate new hypotheses around the main, interactive, and cumulative effects of exposures during sensitive periods of development that may shape mid-life mortality experiences of these cohorts.
Our interdisciplinary group of demographers, economists, sociologists and others combines our expertise with the Census/Mortality data as well as with testing hypotheses from the Developmental Origins of Adult Health and Disease theories to pursue an interconnected set of specific aims to push forward the frontier of understanding the complex links between early life exposures and mid-life mortality.

Aim 1 leverages multiple “natural experiment” research designs to estimate causal main and interactive effects of specific early life exposures and how these effects vary by sex, geography, and family background. We focus particular attention on the impacts of WWII (parental loss, war mobilization activities), the 1957 Influenza Pandemic, and the 1946 National School Lunch Program on the mid-life mortality profiles of affected cohorts. We then make use of machine learning tools to synthesize estimates that may vary by age of exposure, sequence of exposures, and domain of exposures during early life. These models explore impacts of cumulative exposures, dynamic complementarity of exposures and potential for reversibility of early insults using well powered analysis not available elsewhere. Aim 2 extends the literature by focusing on the intergenerational consequences of early life exposures of the parents’ generation on the mid-life mortality of their children. Again, we focus on disease exposures and also public health interventions and educational expansions. Aim 3 explores mechanisms between particular exposures and mid-life mortality by focusing attention on the Project Talent cohort (born 1942-1947) as well as LIFE-M data that has deeper information to examine case studies of environmental and educational pathways in North Carolina and Ohio during this period.