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

Bajunaid, R, Niu, C, Hambly, C, Liu, Z, Yamada, Y, Aleman-Mateo, H, Anderson, LJ, Arab, L, Baddou, I, Bandini, L, Bedu-Addo, K, Blaak, EE, Bouten, CVC, Brage, S, Buchowski, MS, Butte, NF, Camps, SGJA, Casper, R, Close, GL, Cooper, JA , Cooper, R, Das, SK, Davies, PSW, Dabare, P, Dugas, LR, Eaton, S, Ekelund, U, Entringer, S, Forrester, T, Fudge, BW, Gillingham, M, Goris, AH, Gurven, M, El Hamdouchi, A, Haisma, HH, Hoffman, D, Hoos, MB, Hu, S, Joonas, N, Joosen, AM, Katzmarzyk, P, Kimura, M, Kraus, WE, Kriengsinyos, W, Kuriyan, R, Kushner, RF, Lambert, EV, Lanerolle, P, Larsson, CL, Leonard, WR, Lessan, N, Löf, M, Martin, CK, Matsiko, E, Medin, AC, Morehen, JC, Morton, JP, Must, A, Neuhouser, ML, Nicklas, TA, Nyström, CD, Ojiambo, RM, Pietiläinen, KH, Pitsiladis, YP, Plange-Rhule, J, Plasqui, G, Prentice, RL, Racette, SB, Raichlen, DA, Ravussin, E, Redman, LM, Reilly, JJ, Reynolds, R, Roberts, SB, Samaranayakem, D, Sardinha, LB, Silva, AM, Sjödin, AM, Stamatiou, M, Stice, E, Urlacher, SS, Van Etten, LM, van Mil, EGAH, Wilson, G, Yanovski, JA, Yoshida, T, Zhang, X, Murphy-Alford, AJ, Sinha, S, Loechl, CU, Luke, AH, Pontzer, H, Rood, J, Sagayama, H, Schoeller, DA, Westerterp, KR, Wong, WW and Speakman, JR (2025) Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake. Nature Food.

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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.

Item Type: Article
Subjects: T Technology > TX Home economics > TX341 Nutrition. Foods and food supply
R Medicine > RC Internal medicine > RC1200 Sports Medicine
Divisions: Sport and Exercise Sciences
Publisher: Springer Nature
SWORD Depositor: A Symplectic
Date Deposited: 17 Jan 2025 11:48
Last Modified: 17 Jan 2025 12:00
DOI or ID number: 10.1038/s43016-024-01089-5
URI: https://researchonline.ljmu.ac.uk/id/eprint/25310
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