Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake
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| Title: | Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake |
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| Authors: | 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 |
| Contributors: | HUS Abdominal Center, Department of Medicine, Clinicum, University of Helsinki, CAMM - Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, DSpace at Cambridge pro (8.1), Apollo - University of Cambridge Repository, University of Aberdeen.Biological Sciences, University of Aberdeen.Energetics Research Group, University of Aberdeen.Medical Sciences, University of Aberdeen.Applied Medicine, University of Aberdeen.Physical Sciences, University of Aberdeen.Environment and Food Security |
| Source: | Nat Food 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, Cooper, J A, Cooper, R, Das, S K, Davies, P S W, Dabare, P, Dugas, L R, Eaton, S, Ekelund, U, Entringer, S, Forrester, T, Fudge, B W, Gillingham, M, Goris, A H, Gurven, M, El Hamdouchi, A, Haisma, H H, Hoffman, D, Hoos, M B, Hu, S, Joonas, N, Joosen, A M, Katzmarzyk, P, Kimura, M, Kraus, W E, Kriengsinyos, W, Kuriyan, R, Kushner, R F, Lambert, E V, Lanerolle, P, Larsson, C L, Leonard, W R, Lessan, N, Löf, M, Martin, C K, Matsiko, E, Medin, A C, Morehen, J C, Morton, J P, Must, A, Neuhouser, M L, Nicklas, T A, Nyström, C D, Ojiambo, R M, Pietiläinen, K H, Pitsiladis, Y P, Plange-Rhule, J, Plasqui, G, Prentice, R L, Racette, S B, Raichlen, D A, Ravussin, E, Redman, L M, Reilly, J J, Reynolds, R, Roberts, S B, Samaranayakem, D, Sardinha, L B, Silva, A M, Sjödin, A M, Stamatiou, M, Stice, E, Urlacher, S S, Van Etten, L M, van Mil, E G A H, Wilson, G, Yanovski, J A, Yoshida, T, Zhang, X, Murphy-Alford, A J, Sinha, S, Loechl, C U, 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, vol. 6, no. 1, pp. 58-71 . https://doi.org/10.1038/s43016-024-01089-5 Nature Food, vol 6, iss 1 |
| Publisher Information: | Springer Science and Business Media LLC, 2025. |
| Publication Year: | 2025 |
| Subject Terms: | Questionnaires, Adult, Male, Adolescent, Supplementary Data, QH301 Biology, America, Obese, Energy Metabolism/physiology, Article, Body Mass Index, QH301, Young Adult, Validation, 80 and over, Humans, including exercise, Preschool, Child, Nutrition, Aged, Aged, 80 and over, Nutrition and Dietetics, Expenditure, Water, Habitual food-intake, Middle Aged, Nutrition Surveys, Dietary data, Diet, nutrition, 416 Food Science, Life-style, Child, Preschool, Metabolic-rate, Personal health and hygiene, Female, Self Report, Energy Intake, Energy Metabolism, Näringslära och dietkunskap |
| Description: | 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 27.4%. 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. |
| Document Type: | Article Other literature type |
| File Description: | application/pdf; text/xml; text |
| Language: | English |
| ISSN: | 2662-1355 |
| DOI: | 10.1038/s43016-024-01089-5 |
| Access URL: | https://pubmed.ncbi.nlm.nih.gov/39806218 https://cris.maastrichtuniversity.nl/en/publications/d07c6afa-62ba-4e78-b036-052f82cb876e https://doi.org/10.1038/s43016-024-01089-5 http://hdl.handle.net/10138/592488 https://curis.ku.dk/ws/files/427561489/s43016_024_01089_5.pdf http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-211614 https://escholarship.org/content/qt35c8p3h2/qt35c8p3h2.pdf https://escholarship.org/uc/item/35c8p3h2 |
| Rights: | CC BY |
| Accession Number: | edsair.doi.dedup.....c9d672e565be2e5a668e634c49127789 |
| Database: | OpenAIRE |
Nájsť tento článok vo Web of Science | 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 27.4%. 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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| ISSN: | 26621355 |
| DOI: | 10.1038/s43016-024-01089-5 |