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Assessing diet in epidemiologic studies

Nature Food volume 6, pages 927–929 (2025)Cite this article

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The Original Article was published on 13 January 2025

arising from R. Bajunaid et al. Nature Food https://doi.org/10.1038/s43016-024-01089-5 (2025)

Studies of diet and disease risk require assessments of long-term intake that inevitably have measurement error and typically underestimate energy intake. Using doubly labelled water (DLW) methodology to develop predictive equations for energy intake and cross-sectional correlations between macronutrients and body mass index (BMI), Bajunaid et al.1 conclude that “radical approaches” are needed in epidemiologic studies of diet. However, they confuse requirements for estimation of metabolic needs, population surveys and epidemiologic studies, which was the stated focus of their report. Their predictive equations are not a major advance, and their cross-sectional associations may themselves be biased and do not invalidate widely used dietary assessment in nutritional epidemiology.

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Further information, including the procedures to obtain and access data from the Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII) and Health Professionals Follow-Up Study (HPFS), is described at https://www.nurseshealthstudy.org/researchers (contact email: nhsaccess@channing.harvard.edu) and https://hsph.harvard.edu/research/health-professionals/resources/for-external-collaborators/. Owing to participant confidentiality and privacy concerns, data cannot be shared publicly and requests to access NHS/NHSII/HPFS data must be submitted in writing. According to standard access procedures, applications to use NHS/NHSII/HPFS resources will be reviewed by our External Collaborations Committee to verify that the proposed use maintains the protection of the privacy of participants and the confidentiality of the data. Investigators wishing to use NHS/NHSII/HPFS data are asked to submit a brief description of the proposed project to the email address above.

References

  1. Bajunaid, R. et al. Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake. Nat. Food 6, 58–71 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Bajunaid, R. et al. Author Correction: Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake. Nat. Food 6, 523–524 (2025).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Mendez, M. A. et al. Alternative methods of accounting for underreporting and overreporting when measuring dietary intake–obesity relations. Am. J. Epidemiol. 173, 448–458 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Rhee, J. J. et al. Comparison of methods to account for implausible reporting of energy intake in epidemiologic studies. Am. J. Epidemiol. 181, 225–233 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Smith, J. D. et al. A comparison of different methods for evaluating diet, physical activity, and long-term weight gain in 3 prospective cohort studies. J. Nutr. 145, 2527–2534 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Prentice, R. L. Measurement error and results from analytic epidemiology: dietary fat and breast cancer. J. Natl Cancer Inst. 88, 1738–1747 (1996).

    Article  CAS  PubMed  Google Scholar 

  7. Hunter, D. J., Spiegelman, D. & Willett, W. Dietary fat and breast cancer. J. Natl Cancer Inst. 90, 1303–1305 (1998).

    Article  CAS  PubMed  Google Scholar 

  8. Willett, W. Nutritional Epidemiology (Oxford Univ. Press, 2013).

    Google Scholar 

  9. Satija, A., Yu, E., Willett, W. C. & Hu, F. B. Understanding nutritional epidemiology and its role in policy. Adv. Nutr. 6, 5–18 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Al-Shaar, L. et al. Reproducibility and validity of a semiquantitative food frequency questionnaire in men assessed by multiple methods. Am. J. Epidemiol. 190, 1122–1132 (2021).

    Article  PubMed  Google Scholar 

  11. Yuan, C. et al. Relative validity of nutrient intakes assessed by questionnaire, 24-hour recalls, and diet records as compared with urinary recovery and plasma concentration biomarkers: findings for women. Am. J. Epidemiol. 187, 1051–1063 (2018).

    Article  PubMed  Google Scholar 

  12. Yuan, C. et al. Validity of a dietary questionnaire assessed by comparison with multiple weighed dietary records or 24-hour recalls. Am. J. Epidemiol. 185, 570–584 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Speakman, J. R. et al. A standard calculation methodology for human doubly labeled water studies. Cell Rep. Med. 2, 100203 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Roberts, S. B., Dietz, W., Sharp, T., Dallal, G. E. & Hill, J. O. Multiple laboratory comparison of the doubly labeled water technique. Obes. Res. 3, 3–13 (1995).

    Article  PubMed  Google Scholar 

  15. Neuhouser, M. L. et al. Use of recovery biomarkers to calibrate nutrient consumption self-reports in the Women’s Health Initiative. Am. J. Epidemiol. 167, 1247–1259 (2008).

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Walter C. Willett, Frank B. Hu & Xiao Gu

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  1. Walter C. Willett
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  2. Frank B. Hu
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  3. Xiao Gu
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All authors contributed to the writing of this paper. The authors received no funding for this work.

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Correspondence to Walter C. Willett.

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Nature Food thanks James Hébert, Diana Thomas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Willett, W.C., Hu, F.B. & Gu, X. Assessing diet in epidemiologic studies. Nat Food 6, 927–929 (2025). https://doi.org/10.1038/s43016-025-01245-5

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