Nutrition And Exercise Lifestyle Intervention Program (NELIP) Prevents Excessive Pregnancy Weight Gain In Overweight Women.
Bibliographic record
Abstract
Excessive pregnancy weight gain and weight retention in the postpartum period have been linked to obesity and chronic disease risk. PURPOSE: To determine the effect of a Nutrition and Exercise Lifestyle Intervention Program (NELIP) for overweight and obese women on pregnancy weight gain, offspring birth weight and maternal weight retention at 2 months postpartum. METHODS: Case-control matched design by pre-pregnant body mass index (BMI), age, and parity; 4 controls per case. Cases had a pre-pregnancy BMI of ≥25.0 kg/m2 (N=65) and participated in a NELIP starting at 16-20 weeks of pregnancy, continuing until delivery. NELIP consisted of an individualized nutrition plan with total energy intake of approximately 2000 kcal/day (8360 kJ/day), and 40 - 55% of total energy intake from carbohydrate. Exercise consisted of a walking program (30% heart rate reserve), 3 - 4 times per week, using a pedometer to count steps. The Matched Cohort (MC; N=260) was from a large local perinatal database. RESULTS: Weight gained by women on the NELIP was 6.8±4.1 kg (0.38±0.2 kg/week), with a total pregnancy weight gain of 12.0±5.7 kg. Excessive weight gain occurred before NELIP began at 16 weeks gestation. Eighty percent of the women did not exceed recommended pregnancy weight gain on NELIP. Weight retention at 2 months postpartum was less compared to weight retention between pregnancies in the MC (2.2±5.6 kg vs 4.2±7.9 kg; respectively, p<0.05). Mean birth weight was not different between groups (3.59±0.5 kg vs 3.56±0.6 kg, respectively). CONCLUSIONS: NELIP prevented excessive pregnancy weight gain with minimal weight retention at 2 months postpartum in overweight and obese women. This intervention may assist overweight and obese women in successful weight control after childbirth. Funded by: CIHR-IAPH
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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".