Nutrition and Exercise Prevent Excess Weight Gain in Overweight Pregnant Women
Bibliographic record
Abstract
PURPOSE: To determine the effect of a Nutrition and Exercise Lifestyle Intervention Program (NELIP) for overweight (OW) and obese (OB) pregnant women on pregnancy weight gain, birth weight, and maternal weight retention at 2 months postpartum. METHODS: This is a single-arm intervention matched by prepregnant body mass index, age, and parity to a historical cohort (4:1). Women with a prepregnancy body mass index of > or = 25.0 kg x m(-2) (N = 65) participated in a NELIP starting at 16-20 wk of pregnancy, continuing until delivery. NELIP consisted of an individualized nutrition plan with total energy intake of approximately 2000 kcal x d(-1) (8360 kJ x d(-1)) and 40%-55% of total energy intake from carbohydrate. Exercise consisted of a walking program (30% HR reserve), three to four times per week, using a pedometer to count steps. Matched historical 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 x wk(-1)), with a total pregnancy weight gain of 12.0 +/- 5.7 kg. Excessive weight gain occurred before NELIP began at 16 wk of gestation. Eighty percent of the women did not exceed recommended pregnancy weight gain on NELIP. Weight retention at 2 months postpartum was 2.2 +/- 5.6 kg with no difference between the OW and the OB women on NELIP. Mean birth weight was not different between NELIP (3.59 +/- 0.5 kg) and MC (3.56 +/- 0.6 kg, P > 0.05). CONCLUSIONS: NELIP reduces the risk of excessive pregnancy weight gain with minimal weight retention at 2 months postpartum in OW and OB women. This intervention may assist OW and OB women in successful weight control after childbirth.
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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".