Associations of appetite sensations and metabolic characteristics with weight retention in postpartum women
Bibliographic record
Abstract
Postpartum weight retention (PPWR) is an important risk factor for long-term obesity. Appetite may be a key factor regulating PPWR. The objectives of this study were to determine the associations between (i) PPWR and appetite; and (ii) appetite, lactation, and metabolic characteristics. Data from 49 women at 9 months postpartum contributed to this cross-sectional analysis. Energy expenditure was assessed in a whole-body calorimetry unit for 24 h. Appetite sensations were rated using visual analogue scales. Lactation (min/day) was measured using a 3-day breastfeeding diary. PPWR was negatively associated with fullness (β ± SE; R2 = –2.97 ± 0.72; 0.661; P < 0.001), and satiety (–2.75 ± 0.81; 0.617; P = 0.002), and was positively associated with hunger (2.19 ± 1.02; 0.548; P = 0.039), prospective food consumption (PFC; 2.19 ± 0.91; 0.562; P = 0.021), and composite appetite score (CAS; 0.34 ± 0.09; 0.632; P = 0.001). Lactation was associated with higher CAS (39.68 ± 15.56; 0.365; P = 0.015), hunger (3.56 ± 1.61; 0.308; P = 0.033), and PFC (4.22 ± 1.78; 0.314; P = 0.023), and with reduced sensations of fullness (–4.18 ± 1.94; 0.358; P = 0.038) and satiety (–3.83 ± 1.87; 0.295; P = 0.048). Lactation was associated with appetite, which in turn was related to PPWR. Appetite control should be explored to support postpartum weight management strategies. Novelty Postpartum weight retention was associated with appetite sensations, which were assessed throughout the day under conditions in which energy intake and expenditure were precisely matched. Lactation and other maternal metabolic factors, including carbohydrate oxidation and physical activity level may play a role in controlling appetite during the postpartum period.
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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".