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Nutritional epidemiology methods and related statistical challenges and opportunities

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  • Ross L. Prentice
  • Ying Huang

Abstract

The public health importance of nutritional epidemiology research is discussed, along with methodological challenges to obtaining reliable information on dietary approaches to chronic disease prevention. Measurement issues in assessing dietary intake need to be addressed to obtain reliable disease association information. Self-reported dietary data typically incorporate major random and systematic biases. Intake biomarkers offer potential for more reliable analyses, but biomarkers have been established only for a few dietary variables, and these may be too expensive to apply to all participants in large epidemiologic cohorts. A possible way forward involves additional nutritional biomarker development using high-dimensional metabolomic profiling, using blood and urine specimens, in conjunction with further development of statistical approaches for accommodating measurement error with failure time response data. Statisticians have the opportunity to contribute greatly to worldwide public health through the development of statistical methods to address these nutritional epidemiology research challenges, as is elaborated in this contribution.

Suggested Citation

  • Ross L. Prentice & Ying Huang, 2018. "Nutritional epidemiology methods and related statistical challenges and opportunities," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 2(1), pages 2-10, January.
    • Handle: RePEc:taf:tstfxx:v:2:y:2018:i:1:p:2-10
    DOI: 10.1080/24754269.2018.1466098
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    Cited by:

    1. S. Stanley Young & Warren B. Kindzierski, 2022. "Statistical Reliability of a Diet-Disease Association Meta-analysis," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 11(3), pages 1-40, May.
    2. Cheng Zheng & Yiwen Zhang & Ying Huang & Ross Prentice, 2023. "Using Controlled Feeding Study for Biomarker Development in Regression Calibration for Disease Association Estimation," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 57-113, April.

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