Eating behavior traits and sleep as determinants of weight loss in overweight and obese adults
Bibliographic record
Abstract
OBJECTIVE: To examine the associations between eating behavior traits and weight loss according to sleep quality and duration in adults enrolled in common weight-loss interventions. METHODS: Participants included overweight and obese men and women (n=150) (mean±s.d. age, 38.8±8.6 years; mean±s.d. body mass index (BMI), 33.3±3.5 kg m(-2)) who were subjected to a dietary intervention over a period of 12-16 weeks. Anthropometric measurements, eating behavior traits (Three-Factor Eating Questionnaire), sleep quality (total Pittsburgh Sleep Quality Index (PSQI) score) and sleep duration (hours per night, self-reported from the PSQI) were assessed at both baseline and post intervention. Linear regression analysis was used to quantify the relationships between eating behavior traits and changes in anthropometric markers for all subjects and by sleep categories (short sleep: <7 h per night vs recommended sleep: ⩾7 h per night; poor sleep quality: ⩾5 PSQI score vs good sleep quality: <5 PSQI score). We adjusted for age, sex and baseline BMI in analyses. RESULTS: Baseline eating behavior traits were modest predictors of weight-loss success, but they were all significantly associated with their changes over the weight-loss intervention (P<0.01). The diet intervention induced significant changes in eating behavior traits and even more for those having a non-favorable eating behavior profile at baseline. We observed that changes in flexible control and strategic dieting behavior were constantly negatively associated with changes in body weight and fat mass (P<0.05) for recommended duration sleepers. The change in situational susceptibility to disinhibition was positively associated with the change in fat mass and body weight for those having healthy sleeping habits (P<0.05). For poor quality sleepers, the change in avoidance of fattening foods was negatively associated with changes in adiposity (P<0.05). CONCLUSION: Eating behavior traits and sleep may act together to influence the outcome of weight-loss programs.
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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 | 0.000 | 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".