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Cancer Epidemiol Biomarkers Prev. 2017 Sep;26(9):1370-1380. doi: 10.1158/1055-9965.EPI-17-0459. Epub 2017 Jul 14.

Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies.

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Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts.
Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California.
Department of Preventive Medicine, University of Southern California, Los Angeles, California.
Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan.
Department of Epidemiology, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California.
Department of Biostatistics and Department of Oncology, Johns Hopkins University, Baltimore, Maryland.
Division of Neonatology, Department of Pediatrics, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.
Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire.
Susceptibility and Population Health Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, North Carolina.
Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, Maryland.
Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland.
Center of Excellence in Environmental Toxicology and Penn SRP Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.
Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth College, Lebanon, New Hampshire.


A growing number and increasing diversity of factors are available for epidemiological studies. These measures provide new avenues for discovery and prevention, yet they also raise many challenges for adoption in epidemiological investigations. Here, we evaluate 1) designs to investigate diseases that consider heterogeneous and multidimensional indicators of exposure and behavior, 2) the implementation of numerous methods to capture indicators of exposure, and 3) the analytical methods required for discovery and validation. We find that case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective and two-phase designs are required but must balance extended data collection with follow-up of study participants. We discuss innovations in assessments including the microbiome; mass spectrometry and metabolomics; behavioral assessment; dietary, physical activity, and occupational exposure assessment; air pollution monitoring; and global positioning and individual sensors. We claim the the availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. In conclusion, new high-dimensional exposure assessments offer many new opportunities for environmental assessment in cancer development. Cancer Epidemiol Biomarkers Prev; 26(9); 1370-80. ©2017 AACR.

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