Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake

+25 authors; Yosuke Yamada; Carlijn V.C. Bouten; Guy Plasqui; Amy H. Luke; Herman Pontzer; Jennifer Rood; Hiroyuki Sagayama; Dale A. Schoeller; Klaas R. Westerterp; William W. Wong; John R. Speakman

doi:10.1038/s43016-024-01089-5

Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake

+25 authors
, Yosuke Yamada (Corresponding author)
, Carlijn V.C. Bouten
, Guy Plasqui
, Amy H. Luke (Corresponding author)
, Herman Pontzer (Corresponding author)
, Jennifer Rood (Corresponding author)
, Hiroyuki Sagayama (Corresponding author)
, Dale A. Schoeller (Corresponding author)
, Klaas R. Westerterp (Corresponding author-nrf)
, William W. Wong (Corresponding author)
, John R. Speakman (Corresponding author)

Research output: Contribution to journal › Article › Academic › peer-review

34 Citations (Scopus)

Abstract

Nutritional epidemiology aims to link dietary exposures to chronic disease, but the instruments for evaluating dietary intake are inaccurate. One way to identify unreliable data and the sources of errors is to compare estimated intakes with the total energy expenditure (TEE). In this study, we used the International Atomic Energy Agency Doubly Labeled Water Database to derive a predictive equation for TEE using 6,497 measures of TEE in individuals aged 4 to 96 years. The resultant regression equation predicts expected TEE from easily acquired variables, such as body weight, age and sex, with 95% predictive limits that can be used to screen for misreporting by participants in dietary studies. We applied the equation to two large datasets (National Diet and Nutrition Survey and National Health and Nutrition Examination Survey) and found that the level of misreporting was >50%. The macronutrient composition from dietary reports in these studies was systematically biased as the level of misreporting increased, leading to potentially spurious associations between diet components and body mass index.

Original language	English
Pages (from-to)	58-71
Number of pages	14
Journal	Nature food
Volume	6
Issue number	1
Early online date	13 Jan 2025
DOIs	https://doi.org/10.1038/s43016-024-01089-5
Publication status	Published - Jan 2025
Externally published	Yes

Bibliographical note

Funding

We are grateful to the IAEA, Taiyo Nippon Sanso and SERCON for their support and to T. Oono for his tremendous efforts at fundraising on our behalf. We are grateful to D. Tobias for many insightful comments on a previous draft of this paper. We also acknowledge contributors to the database whose data were not used in this compilation or who indicated they did not wish to be authors or who could not be contacted. A list of these contributors is provided in the Supplementary Information. We also gratefully acknowledge funding from the Chinese Academy of Sciences (grant no. CAS 153E11KYSB20190015) and Shenzhen Key Laboratory of Metabolic Health (ZDSYS20210427152400001) awarded to J.R.S. and from the US National Science Foundation (BCS-1824466) awarded to H.P. The funders played no role in the content of this paper. The IAEA Doubly Labeled Water (DLW) Database is generously supported by the IAEA, Taiyo Nippon Sanso and SERCON. The NDNS is a UK government-commissioned rolling programme funded by Public Health England and the UK Food Standards Agency. The rolling programme from 2008 to 2019 is a continuous cross-sectional survey that assesses the diet, nutritional status and nutrient intake of individuals in the UK (England, Scotland, Wales and Northern Ireland) living in private households. The survey aims to collect around 1,000 samples each year, equally divided into 500 children and 500 adults, children aged 1.5\u201318\u2009years and adults aged 19\u2009years and over. There are two main stages of the survey, namely, interviewer visits and a nurse visit; all nutritional data are collected during the interviewer visits. This study used data from years 1\u201311 (2008\u20132009 to 2008\u20132019) for the population aged 4 and over between April 2008 and August 2019. The total number of eligible individuals included in this study was 12,694. We are grateful to the IAEA, Taiyo Nippon Sanso and SERCON for their support and to T. Oono for his tremendous efforts at fundraising on our behalf. We are grateful to D. Tobias for many insightful comments on a previous draft of this paper. We also acknowledge contributors to the database whose data were not used in this compilation or who indicated they did not wish to be authors or who could not be contacted. A list of these contributors is provided in the . We also gratefully acknowledge funding from the Chinese Academy of Sciences (grant no. CAS 153E11KYSB20190015) and Shenzhen Key Laboratory of Metabolic Health (ZDSYS20210427152400001) awarded to J.R.S. and from the US National Science Foundation (BCS-1824466) awarded to H.P. The funders played no role in the content of this paper. The IAEA Doubly Labeled Water (DLW) Database is generously supported by the IAEA, Taiyo Nippon Sanso and SERCON.

Keywords

Energy Metabolism/physiology
Body Mass Index
Water
Nutrition Surveys
Humans
Middle Aged
Self Report
Child, Preschool
Male
Energy Intake
Young Adult
Diet
Adolescent
Aged, 80 and over
Adult
Female
Aged
Child

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10.1038/s43016-024-01089-5

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+25 authors, Yamada, Y., Bouten, C. V. C., Plasqui, G., Luke, A. H., Pontzer, H., Rood, J., Sagayama, H., Schoeller, D. A., Westerterp, K. R., Wong, W. W., & Speakman, J. R. (2025). Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake. Nature food, 6(1), 58-71. https://doi.org/10.1038/s43016-024-01089-5

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abstract = "Nutritional epidemiology aims to link dietary exposures to chronic disease, but the instruments for evaluating dietary intake are inaccurate. One way to identify unreliable data and the sources of errors is to compare estimated intakes with the total energy expenditure (TEE). In this study, we used the International Atomic Energy Agency Doubly Labeled Water Database to derive a predictive equation for TEE using 6,497 measures of TEE in individuals aged 4 to 96 years. The resultant regression equation predicts expected TEE from easily acquired variables, such as body weight, age and sex, with 95\% predictive limits that can be used to screen for misreporting by participants in dietary studies. We applied the equation to two large datasets (National Diet and Nutrition Survey and National Health and Nutrition Examination Survey) and found that the level of misreporting was >50\%. The macronutrient composition from dietary reports in these studies was systematically biased as the level of misreporting increased, leading to potentially spurious associations between diet components and body mass index.",

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+25 authors, Yamada, Y, Bouten, CVC, Plasqui, G, Luke, AH, Pontzer, H, Rood, J, Sagayama, H, Schoeller, DA, Westerterp, KR, Wong, WW & Speakman, JR 2025, 'Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake', Nature food, vol. 6, no. 1, pp. 58-71. https://doi.org/10.1038/s43016-024-01089-5

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AU - Luke, Amy H.

AU - Pontzer, Herman

AU - Rood, Jennifer

AU - Sagayama, Hiroyuki

AU - Schoeller, Dale A.

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AU - Speakman, John R.

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ER -

Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake

Abstract

Bibliographical note

Funding

Keywords

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Author Correction: Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake (Nature Food, (2025), 6, 1, (58-71), 10.1038/s43016-024-01089-5)

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