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

Rania Bajunaid; Chaoqun Niu; Catherine Hambly; Zongfang Liu; Yosuke Yamada; Heliodoro Aleman-Mateo; Liam J Anderson; Lenore Arab; Issad Baddou; Linda Bandini; Kweku Bedu-Addo; Ellen E Blaak; Carlijn V C Bouten; Soren Brage; Maciej S Buchowski; Nancy F Butte; Stefan G J A Camps; Regina Casper; Graeme L Close; Jamie A Cooper; Richard Cooper; Sai Krupa Das; Peter S W Davies; Prasangi Dabare; Lara R Dugas; Simon Eaton; Ulf Ekelund; Sonja Entringer; Terrence Forrester; Barry W Fudge; Melanie Gillingham; Annelies H Goris; Michael Gurven; Asmaa El Hamdouchi; Hinke H Haisma; Daniel Hoffman; Marije B Hoos; Sumei Hu; Noorjehan Joonas; Annemiek M Joosen; Peter Katzmarzyk; Misaka Kimura; William E Kraus; Wantanee Kriengsinyos; Rebecca Kuriyan; Robert F Kushner; Estelle V Lambert; Pulani Lanerolle; Christel L Larsson; William R Leonard; Nader Lessan; Marie Löf; Corby K Martin; Eric Matsiko; Anine C Medin; James C Morehen; James P Morton; Aviva Must; Marian L Neuhouser; Theresa A Nicklas; Christine D Nyström; Robert M Ojiambo; Kirsi H Pietiläinen; Yannis P Pitsiladis; Jacob Plange-Rhule; Guy Plasqui; Ross L Prentice; Susan B Racette; David A Raichlen; Eric Ravussin; Leanne M Redman; John J Reilly; Rebecca Reynolds; Susan B Roberts; Dulani Samaranayakem; Luis B Sardinha; Analiza M Silva; Anders M Sjödin; Marina Stamatiou; Eric Stice; Samuel S Urlacher; Ludo M Van Etten; Edgar G A H van Mil; George Wilson; Jack A Yanovski; Tsukasa Yoshida; Xueying Zhang; Alexia J Murphy-Alford; Srishti Sinha; Cornelia U Loechl; 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

Rania Bajunaid, Chaoqun Niu, Catherine Hambly, Zongfang Liu, Yosuke Yamada, Heliodoro Aleman-Mateo, Liam J Anderson, Lenore Arab, Issad Baddou, Linda Bandini, Kweku Bedu-Addo, Ellen E Blaak, Carlijn V C Bouten, Soren Brage, Maciej S Buchowski, Nancy F Butte, Stefan G J A Camps, Regina Casper, Graeme L Close, Jamie A CooperRichard Cooper, Sai Krupa Das, Peter S W Davies, Prasangi Dabare, Lara R Dugas, Simon Eaton, Ulf Ekelund, Sonja Entringer, Terrence Forrester, Barry W Fudge, Melanie Gillingham, Annelies H Goris, Michael Gurven, Asmaa El Hamdouchi, Hinke H Haisma, Daniel Hoffman, Marije B Hoos, Sumei Hu, Noorjehan Joonas, Annemiek M Joosen, Peter Katzmarzyk, Misaka Kimura, William E Kraus, Wantanee Kriengsinyos, Rebecca Kuriyan, Robert F Kushner, Estelle V Lambert, Pulani Lanerolle, Christel L Larsson, William R Leonard, Nader Lessan, Marie Löf, Corby K Martin, Eric Matsiko, Anine C Medin, James C Morehen, James P Morton, Aviva Must, Marian L Neuhouser, Theresa A Nicklas, Christine D Nyström, Robert M Ojiambo, Kirsi H Pietiläinen, Yannis P Pitsiladis, Jacob Plange-Rhule, Guy Plasqui, Ross L Prentice, Susan B Racette, David A Raichlen, Eric Ravussin, Leanne M Redman, John J Reilly, Rebecca Reynolds, Susan B Roberts, Dulani Samaranayakem, Luis B Sardinha, Analiza M Silva, Anders M Sjödin, Marina Stamatiou, Eric Stice, Samuel S Urlacher, Ludo M Van Etten, Edgar G A H van Mil, George Wilson, Jack A Yanovski, Tsukasa Yoshida, Xueying Zhang, Alexia J Murphy-Alford, Srishti Sinha, Cornelia U Loechl, Amy H Luke, Herman Pontzer, Jennifer Rood, Hiroyuki Sagayama, Dale A Schoeller, Klaas R Westerterp, William W Wong, John R Speakman

Psychological Sciences And Health

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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.

Original language	English
Article number	100203
Pages (from-to)	58-71
Number of pages	14
Journal	Nature food
Volume	6
Issue number	1
DOIs	https://doi.org/10.1038/s43016-024-01089-5
Publication status	Published - 13 Jan 2025

Funding

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

Nutritional epidemiology
total energy expenditure
dietary reports
misreporting
bias

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s43016-024-01089-5Licence: CC BY 4.0

Bajunaid-etal-2025-Predictive-equation-derived-from-6,497-doubly-labelled-water-measurements-enables-the-detection-of-erroneous-self-reported-energy-intakeFinal published version, 1.68 MBLicence: CC BY 4.0

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Bajunaid, R., Niu, C., Hambly, C., Liu, Z., Yamada, Y., Aleman-Mateo, H., Anderson, L. J., Arab, L., Baddou, I., Bandini, L., Bedu-Addo, K., Blaak, E. E., Bouten, C. V. C., Brage, S., Buchowski, M. S., Butte, N. F., Camps, S. G. J. A., Casper, R., Close, G. L., ... 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. Article 100203. https://doi.org/10.1038/s43016-024-01089-5

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

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.",

keywords = "Nutritional epidemiology, total energy expenditure, dietary reports, misreporting, bias",

author = "Rania Bajunaid and Chaoqun Niu and Catherine Hambly and Zongfang Liu and Yosuke Yamada and Heliodoro Aleman-Mateo and Anderson, {Liam J} and Lenore Arab and Issad Baddou and Linda Bandini and Kweku Bedu-Addo and Blaak, {Ellen E} and Bouten, {Carlijn V C} and Soren Brage and Buchowski, {Maciej S} and Butte, {Nancy F} and Camps, {Stefan G J A} and Regina Casper and Close, {Graeme L} and Cooper, {Jamie A} and Richard Cooper and Das, {Sai Krupa} and Davies, {Peter S W} and Prasangi Dabare and Dugas, {Lara R} and Simon Eaton and Ulf Ekelund and Sonja Entringer and Terrence Forrester and Fudge, {Barry W} and Melanie Gillingham and Goris, {Annelies H} and Michael Gurven and {El Hamdouchi}, Asmaa and Haisma, {Hinke H} and Daniel Hoffman and Hoos, {Marije B} and Sumei Hu and Noorjehan Joonas and Joosen, {Annemiek M} and Peter Katzmarzyk and Misaka Kimura and Kraus, {William E} and Wantanee Kriengsinyos and Rebecca Kuriyan and Kushner, {Robert F} and Lambert, {Estelle V} and Pulani Lanerolle and Larsson, {Christel L} and Leonard, {William R} and Nader Lessan and Marie L{\"o}f and Martin, {Corby K} and Eric Matsiko and Medin, {Anine C} and Morehen, {James C} and Morton, {James P} and Aviva Must and Neuhouser, {Marian L} and Nicklas, {Theresa A} and Nystr{\"o}m, {Christine D} and Ojiambo, {Robert M} and Pietil{\"a}inen, {Kirsi H} and Pitsiladis, {Yannis P} and Jacob Plange-Rhule and Guy Plasqui and Prentice, {Ross L} and Racette, {Susan B} and Raichlen, {David A} and Eric Ravussin and Redman, {Leanne M} and Reilly, {John J} and Rebecca Reynolds and Roberts, {Susan B} and Dulani Samaranayakem and Sardinha, {Luis B} and Silva, {Analiza M} and Sj{\"o}din, {Anders M} and Marina Stamatiou and Eric Stice and Urlacher, {Samuel S} and {Van Etten}, {Ludo M} and {van Mil}, {Edgar G A H} and George Wilson and Yanovski, {Jack A} and Tsukasa Yoshida and Xueying Zhang and Murphy-Alford, {Alexia J} and Srishti Sinha and Loechl, {Cornelia U} and Luke, {Amy H} and Herman Pontzer and Jennifer Rood and Hiroyuki Sagayama and Schoeller, {Dale A} and Westerterp, {Klaas R} and Wong, {William W} and Speakman, {John R}",

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doi = "10.1038/s43016-024-01089-5",

language = "English",

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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 & 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, 100203, pp. 58-71. https://doi.org/10.1038/s43016-024-01089-5

TY - JOUR

T1 - Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake

AU - Bajunaid, Rania

AU - Niu, Chaoqun

AU - Hambly, Catherine

AU - Liu, Zongfang

AU - Yamada, Yosuke

AU - Aleman-Mateo, Heliodoro

AU - Anderson, Liam J

AU - Arab, Lenore

AU - Baddou, Issad

AU - Bandini, Linda

AU - Bedu-Addo, Kweku

AU - Blaak, Ellen E

AU - Bouten, Carlijn V C

AU - Brage, Soren

AU - Buchowski, Maciej S

AU - Butte, Nancy F

AU - Camps, Stefan G J A

AU - Casper, Regina

AU - Close, Graeme L

AU - Cooper, Jamie A

AU - Cooper, Richard

AU - Das, Sai Krupa

AU - Davies, Peter S W

AU - Dabare, Prasangi

AU - Dugas, Lara R

AU - Eaton, Simon

AU - Ekelund, Ulf

AU - Entringer, Sonja

AU - Forrester, Terrence

AU - Fudge, Barry W

AU - Gillingham, Melanie

AU - Goris, Annelies H

AU - Gurven, Michael

AU - El Hamdouchi, Asmaa

AU - Haisma, Hinke H

AU - Hoffman, Daniel

AU - Hoos, Marije B

AU - Hu, Sumei

AU - Joonas, Noorjehan

AU - Joosen, Annemiek M

AU - Katzmarzyk, Peter

AU - Kimura, Misaka

AU - Kraus, William E

AU - Kriengsinyos, Wantanee

AU - Kuriyan, Rebecca

AU - Kushner, Robert F

AU - Lambert, Estelle V

AU - Lanerolle, Pulani

AU - Larsson, Christel L

AU - Leonard, William R

AU - Lessan, Nader

AU - Löf, Marie

AU - Martin, Corby K

AU - Matsiko, Eric

AU - Medin, Anine C

AU - Morehen, James C

AU - Morton, James P

AU - Must, Aviva

AU - Neuhouser, Marian L

AU - Nicklas, Theresa A

AU - Nyström, Christine D

AU - Ojiambo, Robert M

AU - Pietiläinen, Kirsi H

AU - Pitsiladis, Yannis P

AU - Plange-Rhule, Jacob

AU - Plasqui, Guy

AU - Prentice, Ross L

AU - Racette, Susan B

AU - Raichlen, David A

AU - Ravussin, Eric

AU - Redman, Leanne M

AU - Reilly, John J

AU - Reynolds, Rebecca

AU - Roberts, Susan B

AU - Samaranayakem, Dulani

AU - Sardinha, Luis B

AU - Silva, Analiza M

AU - Sjödin, Anders M

AU - Stamatiou, Marina

AU - Stice, Eric

AU - Urlacher, Samuel S

AU - Van Etten, Ludo M

AU - van Mil, Edgar G A H

AU - Wilson, George

AU - Yanovski, Jack A

AU - Yoshida, Tsukasa

AU - Zhang, Xueying

AU - Murphy-Alford, Alexia J

AU - Sinha, Srishti

AU - Loechl, Cornelia U

AU - Luke, Amy H

AU - Pontzer, Herman

AU - Rood, Jennifer

AU - Sagayama, Hiroyuki

AU - Schoeller, Dale A

AU - Westerterp, Klaas R

AU - Wong, William W

AU - Speakman, John R

PY - 2025/1/13

Y1 - 2025/1/13

N2 - 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.

AB - 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.

KW - Nutritional epidemiology

KW - total energy expenditure

KW - dietary reports

KW - misreporting

KW - bias

UR - https://doubly-labelled-water-database.iaea.org/home

UR - http://www.dlwdatabase.org

UR - https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2017

U2 - 10.1038/s43016-024-01089-5

DO - 10.1038/s43016-024-01089-5

M3 - Article

C2 - 39806218

VL - 6

SP - 58

EP - 71

JO - Nature food

JF - Nature food

IS - 1

M1 - 100203

ER -

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

Abstract

Funding

Keywords

UN SDGs

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