Environmental health research, whether involving experiments at the cellular level, investigations using laboratory animals, or studies of human populations, is becoming increasingly complex. There are several reasons for this added complexity. The valid quantification of human exposures to environmental hazards requires consideration of complicated time-dependent individual-specific multiple exposure profiles. Assessment of early biologic effects (e.g., biomarkers) requires elucidation of how these exposure profiles relate to multiple, intermediate, and often correlated endpoints. Assessment of exposure-disease relationships requires knowledge of the connections between exposure, early biological effects, and multiple correlated health outcomes. The further necessity of simultaneously considering the impact of gene-environment interactions and molecular-level mechanisms argues strongly for the use of innovative, well-designed, and appropriately analyzed environmental health research studies to insure the validity and precision of scientific conclusions. Such validity and precision requirements mandate that biostatisticians and bioinformaticians be involved as active research collaborators from the planning stages of environmental health studies through final analyses and dissemination of research conclusions via presentations and publications. Without state-of-the-art input from biostatisticians on study design and data analysis, there is no question that environmental health research studies can be severely biased and can suffer from a lack of sufficient precision to detect important exposure-response relationships. The Biostatistics and Bioinformatics Facility Core (BBFC) provides the CEHS with the needed expertise to apply state-of-the-art statistical methods to the design and analysis of all types of environmental health research studies, ranging from laboratory study design, analysis of multidimensional gene by environment interactions, and quantification of complex time-dependent exposures. BBFC personnel have expertise in essentially all state-of-the-art statistical methods required to address the most complex of study design and data analysis issues. It is fair to say that the CEHS cannot function effectively without making continued use of the BBFC, from study planning through data analysis and interpretation. It is an efficient and cost-effective allocation of resources to assign these important statistical design and data analysis activities to the BBFC. In the sections to follow, detailed descriptions of BBFC (formerly the Biostatitics and Epidemiological Methods Facility Core, or BEMFC) activities since April 2006 will be given. In particular, important functional changes will be highlighted, BBFC members and their unique expertise will be detailed, involvements of BBFC members in CEHS pilot and research projects will be described, and BBFC enrichment activities will be mentioned.

National Institute of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Center Core Grants (P30)
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Environmental Health Sciences Review Committee (EHS)
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University of North Carolina Chapel Hill
Chapel Hill
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Rummo, Pasquale E; Albrecht, Sandra S; Gordon-Larsen, Penny (2015) Field validation of food outlet databases: the Latino food environment in North Carolina, USA. Public Health Nutr 18:977-82
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Wen, Wanqing; Zheng, Wei; Okada, Yukinori et al. (2014) Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index. Hum Mol Genet 23:5492-504
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Bradshaw, Patrick T; Ibrahim, Joseph G; Khankari, Nikhil et al. (2014) Post-diagnosis physical activity and survival after breast cancer diagnosis: the Long Island Breast Cancer Study. Breast Cancer Res Treat 145:735-42
Stingone, Jeanette A; Luben, Thomas J; Daniels, Julie L et al. (2014) Maternal exposure to criteria air pollutants and congenital heart defects in offspring: results from the national birth defects prevention study. Environ Health Perspect 122:863-72
Harmon, Quaker E; Engel, Stephanie M; Wu, Michael C et al. (2014) Polymorphisms in inflammatory genes are associated with term small for gestational age and preeclampsia. Am J Reprod Immunol 71:472-84

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