Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies
Authors:
Open Access
- 31 August 2017
- journal article
- review article
- Published by American Association for Cancer Research (AACR) in Cancer Epidemiology, Biomarkers & Prevention
- Vol. 26 (9) , 1370-1380
Abstract
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.Keywords
Funding Information
- NIH (R00ES023504 and R21ES025052)
- NIH (R01CA17997)
- NIH (P01CA1956569)
- NIH (R01ES023541 and R21ES025573)
- NIH (P30CA023108)
- NIH (P20GM104416 and P01ES022832)
- NIH (U01DD00046, R01ES025216, and R01ES025531)
- NIH (P30ES013508 and P42ES023720)
- NIH (U2CES026555)
- NIH (U01CA196386, R21CA191651, R01CA186566, and GM103534)
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