“As a JPB EH Fellow, I want to understand the interaction between psychosocial stress and toxicant exposure in determining the health and well-being of children growing up in socioeconomically disadvantaged communities. I am excited to join together with other JPB EH fellows to develop multidisciplinary research projects in partnership with local communities that will help improve the lives of children and families.”
As psychosocial stress and exposure to environmental contaminants tend to co-occur among disadvantaged groups, one project Allison will launch during her fellowship is a study of prenatal metal exposure and maternal experiences of racial discrimination and stress in relation to infant health among a racially and socioeconomically diverse community in Albany, NY. In particular, she will study epigenetic alterations as mechanisms that may help explain how prenatal stress and metal exposures can become biologically embodied and contribute to disparities in child growth and neurodevelopment.
Allison is a social epidemiologist with training in epigenetics, cardiovascular disease and neurodevelopment. She received her doctoral degree from the Harvard School of Public Health and completed postdoctoral fellowships at Harvard and also at the Geisel School of Medicine at Dartmouth. She brings her epidemiologic research skills and expertise in evaluating the psychosocial mechanisms linking social inequality to health outcomes to the fellowship. Through collaborative research and mentorship from the JPB EH Fellowship, Allison will build skills in community engagement and develop expertise around environmental exposure assessments for metals and air pollution.
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- Experience in the design, conduct, and analysis of cohort studies; and in developing psychosocial adversity and stress measures from archival data.
- Expertise in measuring stress, mental health, positive psychosocial factors, positive health, resiliency, and biomarker analysis, including epigenetics.
- Statistical expertise in testing mediation, effect modification, longitudinal analysis, and clustered/complex data structures.
This information is accurate as of the fellowship year indicated for each fellow.