Anthropometric, metabolic, psychosocial and dietary factors associated with dropout in overweight and obese postmenopausal women engaged in a 6-month weight loss programme: a MONET study
Bibliographic record
Abstract
The objective of the present study was to examine anthropometric, metabolic, psychosocial and dietary factors associated with dropout in a 6-month weight loss intervention aimed at reducing body weight by 10 %. The study sample included 137 sedentary, overweight and obese postmenopausal women, participating in a weight loss intervention that consisted of either energy restriction (ER) or ER with resistance training (ER+RT). Anthropometric (BMI, percent lean body mass, percent fat mass, visceral adipose tissue and waist circumference), metabolic (total energy expenditure, RMR, insulin sensitivity and fasting plasma levels of leptin and ghrelin), psychosocial (body esteem, self-esteem, stress, dietary restraint, disinhibition, hunger, quality of life, self-efficacy, perceived benefits for controlling weight and perceived risk) and dietary (3-d food record) variables were measured. Thirty subjects out of 137 dropped out of the weight loss programme (22 %), with no significant differences in dropout rates between those in the ER and the ER+RT groups. Overall, amount of weight loss was significantly lower in dropouts than in completers ( - 1.7 (sd 3.5) v. - 5.6 (sd 4.3) kg, P < 0.05); weekly weight loss during the first 4 weeks was also significantly lower. Dropouts consumed fewer fruit servings than completers (1.7 (sd 1.1) v. 2.7 (sd 1.53), P < 0.05) and had higher insulin sensitivity levels (12.6 (sd 3.8) v. 11.1 (sd 2.8) mg glucose/min per kg fat-free mass, P < 0.05). The present results suggest that the rate of weight loss during the first weeks of an intervention plays an important role in the completion of the programme. Thus, participants with low rates of initial weight loss should be monitored intensely to undertake corrective measures to increase the likelihood of completion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".