Elijah Watson, MA

Does prenatal exposure to acute political-economic crisis accelerate biological aging decades later? I examine this question in the Cebu Longitudinal Health and Nutrition Survey, which enrolled pregnant women across 33 metropolitan Cebu barangays from May 1983 to April 1984, bracketing the August 21 assassination of Benigno Aquino and the political-economic crisis that followed. Using a difference-in-differences design, I compare births before and after the crisis onset in central Cebu City, where post-assassination political mobilization and urban economic disruption were most acute, with births in peripheral barangays that shared broader national stressors, including a resolving El Niño drought, but experienced lower immediate local disruption. Prenatal exposure left no detectable mark on birth size, infant growth, cardiometabolic health through age 40, or epigenetic aging at age 21. By age 40, however, exposure predicted accelerated biological aging across multiple epigenetic clocks, suggesting that some forms of early-life stress may appear innocuous at birth yet leave a latent biological signature that becomes detectable only decades later through epigenetic biomarkers that anticipate future health risk.

As climate change increases exposure to extreme weather, studying its long-term consequences for human capital and health remains challenging. Building on prior work showing that typhoon-related housing damage in the Cebu Longitudinal Health and Nutrition Survey reduced household wealth and educational attainment, I extend the follow-up by nearly two decades to examine whether these early-life disadvantages persist into midlife and are accompanied by lasting biological consequences. Childhood housing damage predicted accelerated biological aging across multiple epigenetic clocks by age 40, higher blood pressure, greater food insecurity, lower household wealth, and a higher likelihood of experiencing housing damage again during Typhoon Odette in 2021. The findings suggest that childhood disaster exposure can leave enduring biological and socioeconomic consequences while reinforcing vulnerability across the life course.

Infectious disease epidemics require rapid population surveillance to identify high-risk communities and guide resources, but volunteer-based antibody surveys can misrepresent infection risk by oversampling ethnic majority, highly educated, and higher-income participants, potentially attenuating or even reversing true social and spatial disparities. Using a 2020 Chicago community antibody survey conducted before vaccine rollout, we estimated neighborhood-level SARS-CoV-2 infection risk with Bayesian multilevel regression and poststratification (MrP), incorporating American Community Survey demographic estimates, uncertainty in antibody test accuracy, and neighborhood racial-economic segregation measured using the Index of Concentration at the Extremes. Whereas unadjusted data suggested little variation in antibody prevalence across these gradients, MrP-adjusted estimates mirrored Chicago’s social and geographic gradients in COVID-19 burden: seroprevalence in the most economically deprived and predominantly Black neighborhoods was more than twice that of the most economically privileged and predominantly White neighborhoods. These findings show that unequal participation can conceal unequal exposure, making selection bias adjustment essential for estimating the social patterning of infection from imperfect crisis data.