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Record W3183815414 · doi:10.1126/science.abe5017

Daily energy expenditure through the human life course

2021· article· en· W3183815414 on OpenAlexfundno aff
Herman Pontzer, Yosuke Yamada, Hiroyuki Sagayama, Philip N. Ainslie, Lene Frost Andersen, Liam Anderson, Lenore Arab, Issad Baddou, Kweku Bedu-Addo, Ellen E. Blaak, Stéphane Blanc, A. Bonomi, Carlijn V. C. Bouten, Pascal Bovet, Maciej S. Buchowski, Nancy F. Butte, Stefan Gerardus Camps, Graeme L. Close, Jamie A. Cooper, Richard Cooper, Sai Krupa Das, Lara R. Dugas, Ulf Ekelund, Sonja Entringer, Terrence Forrester, Barry W. Fudge, Annelies Goris, Michael Gurven, Catherine Hambly, Asmaa El Hamdouchi, Marjije B. Hoos, Sumei Hu, Noorjehan Joonas, Annemiek M. Joosen, Peter T. Katzmarzyk, Kitty P. Kempen, Misaka Kimura, William E. Kraus, Robert F. Kushner, Estelle V. Lambert, William R. Leonard, Nader Lessan, Corby K. Martin, Anine Christine Medin, Erwin P. Meijer, James C. Morehen, James P. Morton, Marian L. Neuhouser, Teresa A. Nicklas, Robert Ojiambo, Kirsi H. Pietiläinen, Yannis Pitsiladis, Jacob Plange‐Rhule, Guy Plasqui, Ross L. Prentice, Roberto Rabinovich, Susan B. Racette, David A. Raichlen, Éric Ravussin, Rebecca M. Reynolds, Susan B. Roberts, Albertine J. Schuit, Anders Sjödin, Eric Stice, Samuel S. Urlacher, Giulio Valenti, Ludo M. Van Etten, Edgar van Mil, Jonathan C. K. Wells, George Wilson, Brian M. Wood, Jack A. Yanovski, Tsukasa Yoshida, Xueying Zhang, Alexia J. Murphy‐Alford, Cornelia Loechl, Amy Luke, Jennifer Rood, Dale A. Schoeller, Klaas R. Westerterp, William W. Wong, John R. Speakman

Bibliographic record

VenueScience · 2021
Typearticle
Languageen
FieldEnergy
TopicEnergy, Environment, and Transportation Policies
Canadian institutionsnot available
FundersInstitute of GeneticsNational Cancer InstituteNational Institute on AgingInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesUniversity of California, IrvineFeinberg School of MedicineAgricultural Research ServiceUniversity of California, Los AngelesDuke Global Health Institute, Duke UniversityNational Institutes of HealthNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Biomedical Innovation, Health and NutritionBerlin Institute of HealthUniversitetet i AgderNovo Nordisk FondenNorges IdrettshøgskoleFreie Universität BerlinUniversity of Cape TownHumboldt-Universität zu BerlinUniversitetet i OsloUniversité de StrasbourgInternational Atomic Energy AgencyDavid Geffen School of Medicine, University of California, Los AngelesNational Science FoundationUniversity of AberdeenLiverpool John Moores UniversityUniversity of BrightonCentre National de la Recherche ScientifiqueChinese Academy of SciencesUniversity of TsukubaUniversity of GlasgowHelsingin ja Uudenmaan SairaanhoitopiiriDirectorate for Biological SciencesCentre Hospitalier Universitaire VaudoisImperial College LondonUniversity of WashingtonNational Center for Research ResourcesUniversiteit MaastrichtBaylor UniversityNorthwestern UniversityUniversity of Southern CaliforniaU.S. Department of AgricultureKwame Nkrumah University of Science and TechnologyVanderbilt University
KeywordsEnergy expenditureCourse (navigation)Life course approachEnergy metabolismPsychologyEnvironmental scienceBiologyEngineeringDevelopmental psychologyEndocrinology

Abstract

fetched live from OpenAlex

Total daily energy expenditure ("total expenditure") reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass-adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.273
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations585
Published2021
Admission routes1
Has abstractyes

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