Does Nutrition And Exercise Intervention Delivery (simultaneously Or Sequentially) Prevent Early/late Excessive Gestational Weight Gain?
Bibliographic record
Abstract
PURPOSE: Excessive gestational weight gain (EGWG) can lead to increased risk of obesity and type 2 diabetes for mother and offspring. We evaluated the effectiveness of either simultaneous or sequential introduction of nutrition and exercise components at preventing early and late EGWG. We hypothesized that introducing exercise first followed by nutrition would prevent early and late EGWG by improving adherence compared to the introduction of nutrition followed by exercise or introducing both components together. METHODS: Eighty-four healthy pregnant individuals (mean age: 32.4 ± 3.4 years; pre-pregnancy body mass index: 26.0 ± 5.1 kg/m2) were randomly allocated at 12-18 weeks gestational age (GA; baseline) to either NE (nutrition and exercise delivered simultaneously; n = 25), N + E (nutrition first and exercise added at 25 weeks’ GA; n = 29) or E + N (exercise first and nutrition added at 25 weeks’ GA; n = 30). Early weight gain was analysed weekly from baseline up to 25 weeks’ GA (midpoint) and later from midpoint to 36 weeks’ GA. RESULTS: From baseline to 25 weeks, no differences were found for weight gain (NE: 4.4 ± 1.9 kg, N + E: 3.8 ± 2.1 kg, E + N: 3.8 ± 1.6 kg; p = 0.87) or for those who gained excessively (p = 0.38). However, from midpoint to final assessment, N + E gained more weight (6.2 ± 2.1 kg; NE 4.8 ± 1.9 kg; E + N 4.3 ± 1.6 kg; p = 0.002, respectively) with more participants (n = 21; p = 0.03) gaining excessively than NE (n = 11) and E + N (n = 12). Total overall adherence showed that E + N was significantly (p = 0.03) more adherent (76.5 ± 16.3%) than NE (62.1 ± 18.5%) and N + E (69.8 ± 13.5%). CONCLUSIONS: Delivering the components of a nutrition and exercise intervention sequentially or simultaneously equally influences early EGWG. After 25 weeks’ GA, introducing nutrition sequentially into an exercise program (E + N) (with the highest program adherence) or the continuation of a combined nutrition and exercise program (NE) showed less EGWG than adding exercise sequentially to a nutrition program (N + E). Introduction order of nutrition and/or exercise components either before or after 25 weeks’ GA may be an important factor to consider for intervention success. TRIAL REGISTRATION: ClinicalTrials.gov NCT02804061
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".