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Record W2102848237 · doi:10.1017/s0007114509992984

Increased meal frequency does not promote greater weight loss in subjects who were prescribed an 8-week equi-energetic energy-restricted diet

2009· article· en· W2102848237 on OpenAlexafffund
Jameason D. Cameron, Marie-Josée Cyr, Éric Doucet

Bibliographic record

VenueBritish Journal Of Nutrition · 2009
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMealWeight lossAnimal scienceBody weightFood scienceBiologyChemistryEndocrinologyObesity

Abstract

fetched live from OpenAlex

There have been reports of an inverse relationship between meal frequency (MF) and adiposity. It has been postulated that this may be explained by favourable effects of increased MF on appetite control and possibly on gut peptides as well. The main goal of the present study was to investigate whether using a high MF could lead to a greater weight loss than that obtained with a low MF under conditions of similar energy restriction. Subjects were randomised into two treatment arms (high MF = 3 meals+3 snacks/d or low MF = 3 meals/d) and subjected to the same dietary energy restriction of - 2931 kJ/d for 8 weeks. Sixteen obese adults (n 8 women and 8 men; age 34.6 (sd 9.5); BMI 37.1 (sd 4.5) kg/m2) completed the study. Overall, there was a 4.7 % decrease in body weight (P < 0.01); similarly, significant decreases were noted in fat mass ( - 3.1 (sd 2.9) kg; P < 0.01), lean body mass ( - 2.0 (sd 3.1) kg; P < 0.05) and BMI ( - 1.7 (sd 0.8) kg/m2; P < 0.01). However, there were NS differences between the low- and high-MF groups for adiposity indices, appetite measurements or gut peptides (peptide YY and ghrelin) either before or after the intervention. We conclude that increasing MF does not promote greater body weight loss under the conditions described in the present study.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.241
Teacher spread0.227 · 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 teacher head, 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

Citations94
Published2009
Admission routes2
Has abstractyes

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