Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake.
Nature food 2025 ; 6: 58-71.
Bajunaid R, Niu C, Hambly C, Liu Z, Yamada Y, Alemán-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, Speakman JR
DOI : 10.1038/s43016-024-01089-5
PubMed ID : 39806218
PMCID : PMC11772230
URL : https://www.nature.com/articles/s43016-024-01089-5
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.