Adaptations to a diet‐based weight‐reducing programme in obese women resistant to weight loss
Bibliographic record
Abstract
The aim of this study was to assess energy intake, resting metabolic rate (RMR), appetite sensations, eating behaviours and sleep duration and quality in obese women resistant to body weight loss when subjected to a diet-based weight-reducing programme. A pooled cohort of obese women (n = 75; aged 39 ± 8 years; body mass index: 33 ± 4 kg m(-2)) participated in a 12-16-week diet-based weight loss programme targeting a daily energy deficit of 500-700 kcal d(-1). Women were classified in tertiles a posteriori based on the response of their body weight to dietary supervision (high, moderate and low responders). Post-intervention, mean weight loss was 3.3 ± 2.8 kg and explained by the 2.9 ± 2.6 kg reduction in fat mass. Mean weight loss was 6.2 ± 1.6, 3.4 ± 0.6 and 0.2 ± 1.4 kg in participants classified in the high, middle and low tertiles, respectively. Women in the low tertile reduced their daily energy intake and susceptibility to hunger during the programme to a lesser extent than those in the high tertile and had higher fasting hunger in response to the dietary intervention. Women in the high tertile maintained their RMR, which was in contrast to the significant decrease predicted by their weight loss. They also reported a significant improvement in sleep quality and an increase in sleep duration compared with other tertiles. The differences in the response of body weight to dietary supervision may be explained, in part, by variations in energy intake, eating behaviours, appetite sensations and sleep duration and quality.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".