Associations of changes in reported and estimated protein and energy intake with changes in insulin resistance, glycated hemoglobin, and BMI during the PREVIEW lifestyle intervention study
Bibliographic record
Abstract
BACKGROUND: Observed associations of high-protein diets with changes in insulin resistance are inconclusive. OBJECTIVES: We aimed to assess associations of changes in both reported and estimated protein (PRep; PEst) and energy intake (EIRep; EIEst) with changes in HOMA-IR, glycated hemoglobin (HbA1c), and BMI (in kg/m2), in 1822 decreasing to 833 adults (week 156) with overweight and prediabetes, during the 3-y PREVIEW (PREVention of diabetes through lifestyle intervention and population studies In Europe and around the World) study on weight-loss maintenance. Eating behavior and measurement errors (MEs) of dietary intake were assessed. Thus, observational post hoc analyses were applied. METHODS: Associations of changes in EIEst, EIRep, PEst, and PRep with changes in HOMA-IR, HbA1c, and BMI were determined by linear mixed-model analysis in 2 arms [high-protein-low-glycemic-index (GI) diet and moderate-protein-moderate-GI diet] of the PREVIEW study. EIEst was derived from energy requirement: total energy expenditure = basal metabolic rate × physical activity level; PEst from urinary nitrogen, and urea. MEs were calculated as [(EIEst - EIRep)/EIEst] × 100% and [(PRep - PEst)/PEst] × 100%. Eating behavior was determined using the Three Factor Eating Questionnaire, examining cognitive dietary restraint, disinhibition, and hunger. RESULTS: Increases in PEst and PRep and decreases in EIEst and EIRep were associated with decreases in BMI, but not independently with decreases in HOMA-IR. Increases in PEst and PRep were associated with decreases in HbA1c. PRep and EIRep showed larger changes and stronger associations than PEst and EIEst. Mean ± SD MEs of EIRep and PRep were 38% ± 9% and 14% ± 4%, respectively; ME changes in EIRep and En% PRep were positively associated with changes in BMI and cognitive dietary restraint and inversely with disinhibition and hunger. CONCLUSIONS: During weight-loss maintenance in adults with prediabetes, increase in protein intake and decrease in energy intake were not associated with decrease in HOMA-IR beyond associations with decrease in BMI. Increases in PEst and PRep were associated with decrease in HbA1c.This trial was registered at clinicaltrials.gov as NCT01777893.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".