Trained in biosocial anthropology and epidemiology, I center my work on the biological and social demography of population health, development, and aging.
I am a sixth-year PhD candidate in Anthropology and an MPH student in Epidemiology at Northwestern University, supported by an NIH F31 Predoctoral Fellowship from the National Institute on Aging and a previous National Science Foundation Graduate Research Fellowship (GRFP). I will complete both degrees in spring 2026.
My research integrates biomarkers of aging—especially epigenetic clocks—with causal inference methods and ecosocial theory to understand how social and environmental conditions become embodied across the life course. I am also interested in integrating, translating, and applying causal inference frameworks from biostatistics, econometrics, and epidemiology to questions concerning population health and aging .
Drawing on the Cebu Longitudinal Health and Nutrition Survey (CLHNS) and Demographic and Health Surveys (DHS) in the Philippines, my dissertation examines how political, environmental, and institutional exposures shape human development and health across the life course.
This study uses the 1983 Philippine political–economic crisis as a natural experiment to test whether prenatal exposure to worsening conditions shapes life-course physiology and biological aging. Leveraging variation in gestational timing from the Cebu Longitudinal Health and Nutrition Survey, we exploit two discrete shocks — a currency devaluation and severe flooding in June 1983, followed by the assassination of Benigno Aquino in August — to identify third-trimester cohorts with no exposure (born May–June, before the shocks), mild exposure (June shocks only), or moderate exposure (both shocks). We compare individuals who entered the same adverse postnatal environment with versus without prenatal signals of the crisis onset. Prenatal exposure was associated with smaller birth size, but by age 2 a higher BMI and lower risk of wasting, and by age 40 slower epigenetic aging — patterns consistent with the idea that informative prenatal signals can calibrate later-life metabolic and aging trajectories. A second analysis restricts to the prenatally exposed and asks whether the severity of the prenatal signal matters: those additionally exposed to the political shock of the Aquino assassination show accelerated biological aging at midlife relative to the June-only group, pointing to biological costs when prenatal stress exceeds what the postnatal environment demands.
This project uses data from the Cebu Longitudinal Health and Nutrition Survey (CLHNS), a population-based birth cohort from the Philippines that has followed individuals from birth in 1983–84 through midlife. I examine how socioeconomic conditions across childhood and adulthood shape biological aging, measured using DNA methylation–based epigenetic clocks at ages 21 and 40. Childhood wealth was measured prospectively across multiple time points, allowing for a detailed assessment of early-life socioeconomic conditions. To understand how educational attainment contributes to inequality in biological aging, I apply modern causal decomposition methods that combine epidemiologic theory with machine-learning approaches to flexibly model complex relationships between socioeconomic factors, education, and aging biomarkers. The results show that large socioeconomic disparities in biological aging are already present by early adulthood, but that these disparities partially attenuate by midlife. By age 40, remaining inequalities are shaped less by persistent early-life differences and more by unequal biological returns to education, with educational attainment conferring greater protective benefits among individuals from more advantaged childhood backgrounds.
This study considers institutional reform as a protective shock that redistributes the social resources buffering women from violence. Leveraging the 1988 Free Public Secondary Education Act, which eliminated tuition fees for public secondary schools, I use instrumental variables methods with national DHS data to assess whether expanded schooling reduced women’s lifetime risk of intimate partner violence. Among rural women, each additional year of schooling lowered IPV risk by roughly four percentage points, in part by delaying union formation and enabling more-educated partner selection.
This study used Bayesian multilevel regression with poststratification to analyze data from a 2020 community antibody survey and estimate neighborhood-level infection risk prior to vaccine rollout. Population estimates from the American Community Survey were used for poststratification, and racialized economic segregation was measured using an Index of Concentration at the Extremes (ICE) for race, ethnicity, and income, capturing the spatial polarization of advantage and disadvantage across the city. While the raw seroprevalence data erroneously suggested that exposure burdens were similar across Chicago neighborhoods, adjusted estimates revealed pronounced disparities, with higher infection risk in poorer, predominantly Black neighborhoods and lower risk in wealthier, predominantly white areas. The findings demonstrate how serological data and careful modeling to mitigate sampling bias can uncover inequities in infection exposure that routine surveillance based on case counts and hospitalizations cannot reveal.
To learn more about my research and publications, see my CV or my Google Scholar.