Stressors that age the body and impact overall health can be assessed in individuals and populations to understand how marginalized groups are collectively affected by a shared experience. This doctoral dissertation research project aims to explore the influence of social and environmental determinants of health on the discrepancies between biological age and chronological age using innovative AI models, comprehensive CT scan datasets, and skeletal data. The primary objective is to assess how factors such as race, ethnicity, socioeconomic status, geography, diet, and climate contribute to accelerated aging and associated health outcomes. The study leverages large datasets from the New Mexico Decedent Image Database, the University of Wisconsin Hospital and Clinics, and the Xoclán skeletal collection, encompassing diverse demographic samples to provide a broad understanding of how various stressors affect aging processes and health disparities. This project encompasses collaboration with international communities, inclusion of underrepresented individuals, public dissemination of research findings, and the use of multidisciplinary approaches.

The project consists of two main objectives. The first objective focuses on analyzing the discrepancies between biological age and chronological age by applying AI-based biological age models to CT scans from different populations, followed by statistical analyses to identify patterns related to social determinants of health. The second objective involves evaluating skeletal age against chronological age using standard forensic anthropology techniques on skeletal samples from Mérida, Yucatán, Mexico. This analysis will integrate a different cultural context and assess how sociocultural and environmental factors manifest in skeletal biology. Data collection will include skeletal and dental biomarkers, providing insights into the relationship between embodied stress and age discrepancies, with implications for bioarchaeology, forensic anthropology, and public health.