Self-reported nutrition intake (NI) data are prone to reporting bias that may induce bias in estimands in nutrition studies; however, they are used anyway due to high feasibility. We examined whether applying Goldberg cutoffs to remove “implausible” self-reported NI could reliably reduce bias compared to biomarkers for energy, sodium, potassium, and protein. Using IDATA data, significant bias in mean NI was removed with Goldberg cutoffs (120 among 303 participants excluded). Associations between NI and outcomes (weight, waist circumference, heart rate, systolic/diastolic blood pressure, and VO2 max) were estimated, but sample size was insufficient to evaluate bias reductions. We therefore simulated data based on IDATA. Significant bias in simulated associations using self-reported NI was reduced but not eliminated by Goldberg cutoffs in 14 of 24 nutrition-outcome pairs; bias was not reduced for remaining cases. 95% coverage probabilities were improved by applying Goldberg cutoffs in most cases but underperformed compared with biomarker data. Although Goldberg cutoffs may achieve bias elimination in estimating mean NI, bias in estimates of associations between NI and outcomes will not necessarily be reduced or eliminated after application of Goldberg cutoffs. Whether one uses Goldberg cutoffs should therefore be decided based on research purposes and not general rules.

AWB declares: in the past three years (since 2019-09-19), Dr. Brown has received travel expenses from International Food Information Council; speaking fees from Eastern North American Region of the International Biometric Society, Purchaser Business Group on Health, Purdue University, and University of Arkansas for the Medical Sciences; monetary awards from American Society for Nutrition; consulting fees from LA NORC, Pennington Biomedical Research Center, and Soy Nutrition Institute Global; and grants through his institution from Alliance for Potato Research & Education, American Egg Board, National Cattlemen's Beef Association, NIH/NHLBI, NIH/NIDDK, and NIH/NIGMS. In addition, he has been involved in research for which his institution or colleagues have received grants or contracts from Center for Open Science, Gordon and Betty Moore Foundation, Hass Avocado Board, Indiana CTSI, NIH/NCATS, NIH/NCI, NIH/NHLBI, NIH/NIA, NIH/NIGMS, NIH/NLM, and Sloan Foundation. His wife is employed by Reckitt Benckiser. NY, KE, and RZ declare that they have no competing interests.

NIH grants R25HL124208, R25DK099080, R25GM141507, 1R01DK132385-01, U01-CA057030-29S1. Japan Society for Promotion of Science (JSPS) KAKENHI grant 18K18146. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or any other organization.

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Code book and analytic code will be made publicly and freely available without restriction at http://doi.org/10.5281/zenodo.7013204. Data described in the manuscript are available through the National Cancer Institute per their terms of use (https://biometry.nci.nih.gov/cdas/idata/).

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