This multidisciplinary five-year program provides integrated training in Environmental Biostatistics, Environmental Epidemiology, and Environmental Health Science, with the goal of preparing scientists to address emerging challenges in modern environmental health research. By constructing a training program that involves collaboration across three critical scientific areas, we have a unique opportunity to advance environmental health in ways that could not be achieved if the training were conducted via three separate programs. Funding is requested for 23 predoctoral (9 BIOS, 7 EPID, 7 ENVR) and 5 postdoctoral trainees (1 BIOS, 2 EPID, 2 ENVR). Assessment of exposure-disease relationships requires understanding connections between exposure, early biological effects, host-factors, and potential interactions with the environment. Thus current environmental health research, whether involving experiments with laboratory animals or observational studies of human populations, is becoming increasingly complex. Across the lifespan, individuals are exposed to multiple contaminants at varying windows of development. These windows may differ in their sensitivities to toxic insults, potentially resulting in different health outcomes. Understanding the relationship between environmental toxicants and disease susceptibility therefore requires sophistication in the measurement of biological markers of exposure and disease processes. New technologies that allow investigators to obtain a more comprehensive estimate of exposure (the exposome), in combination with `omics- scale biological markers (genomes, epigenomes, microbiomes, proteomes and metabolomes) present both opportunities and challenges to the next generation of environmental science researchers. The ability to incorporate these data into a sophisticated systems biological framework is essential and requires cross-disciplinary training in exposure science, epidemiology, and biostatistics. A program that prepares and trains students to integrate these next-generation tools in the ?big data? era is essential to environmental health science research.

Public Health Relevance

This multidisciplinary five-year program provides integrated training in Environmental Biostatistics, Environmental Epidemiology, and Environmental Health Science, with the goal of preparing scientists to address emerging challenges in modern environmental health research. The program provides necessary training to allow new sciences to integrate skills across multiple disciplines as they work to understand and solve major public health challenges related to the complex interactions of environmental exposures, genetic and biologic factors, and human health outcomes. A major focus is training in development and use of next-generation analytical tools in the ?Big Data? era.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Institutional National Research Service Award (T32)
Project #
5T32ES007018-44
Application #
9977195
Study Section
Environmental Health Sciences Review Committee (EHS)
Program Officer
Shreffler, Carol A
Project Start
1977-07-01
Project End
2022-06-30
Budget Start
2020-07-01
Budget End
2021-06-30
Support Year
44
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Cronk, Ryan; Bartram, Jamie (2018) Environmental conditions in health care facilities in low- and middle-income countries: Coverage and inequalities. Int J Hyg Environ Health 221:409-422
Parada Jr, Humberto; Gammon, Marilie D; Chen, Jia et al. (2018) Urinary Phthalate Metabolite Concentrations and Breast Cancer Incidence and Survival following Breast Cancer: The Long Island Breast Cancer Study Project. Environ Health Perspect 126:047013
Urrutia, Eugene; Chen, Hao; Zhou, Zilu et al. (2018) Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny. Bioinformatics 34:2126-2128
Keil, Alexander P; Daza, Eric J; Engel, Stephanie M et al. (2018) A Bayesian approach to the g-formula. Stat Methods Med Res 27:3183-3204
Keil, Alexander P; Richardson, David B (2018) Quantifying Cancer Risk from Radiation. Risk Anal 38:1474-1489
McClure, Elizabeth; Feinstein, Lydia; Ferrando-Martínez, Sara et al. (2018) The Great Recession and Immune Function. RSF 4:62-81
Martin, Chantel L; Haan, Mary N; Fernandez-Rhodes, Lindsay et al. (2018) Association Between Immigration History and Inflammatory Marker Profiles Among Older Adult Mexican Americans. Biodemography Soc Biol 64:30-42
Hoffman, Kate; Stapleton, Heather M; Lorenzo, Amelia et al. (2018) Prenatal exposure to organophosphates and associations with birthweight and gestational length. Environ Int 116:248-254
Richardson, David B; Keil, Alexander P; Cole, Stephen R et al. (2018) Asbestos standards: Impact of currently uncounted chrysotile asbestos fibers on lifetime lung cancer risk. Am J Ind Med 61:383-390
Rudolph, Jacqueline E; Cole, Stephen R; Edwards, Jessie K et al. (2018) At-Risk Alcohol Use Among HIV-Positive Patients and the Completion of Patient-Reported Outcomes. AIDS Behav 22:1313-1322

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