Energy Intake and Food Habits between Weight Maintainers and Regainers, Five Years after Roux-en-Y Gastric Bypass
Bibliographic record
Abstract
We explored differences in dietary behaviours, energy, and macronutrient intake among individuals who had regained or maintained weight loss 5 or more years after Roux-en-Y gastric bypass (RYGB). This study assessed 27 adults who underwent RYGB an average of 12.1 ± 3.7 years before this study was conducted. Dietary assessment was performed using 3-day food records. Daily energy intake (kcal), protein (g), carbohydrate (g), fat (g), and alcohol intake (g) were computed using the ESHA’s Food Processor®. Participants were classified by percent weight loss, maintainers (≥38 %), and regainers (≤30 %). Daily carbohydrate consumption was greater in regainers (222 ± 84.3 g) compared with maintainers (162 ± 67.5 g), (P < 0.05). Thirty-seven percent of participants were not consuming the recommended amount of protein and 26% reported never taking vitamin supplements after surgery. Alcohol consumption was higher among regainers (18.5 ± 30.9 g) compared with maintainers (2.6 ± 6.5 g), (P < 0.05). Finally, 74% of the participants reported no contact with a Registered Dietitian, whereas 78 % were in contact with a health care professional once a year post-surgery. Differences were seen in carbohydrate intake and alcohol consumption between weight maintainers and regainers. These data suggest dietitians need to play a more active role in the long-term care of this medically complex population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".