Relationship between maternal body composition during pregnancy and infant’s birth weight in Nairobi informal settlements, Kenya
Bibliographic record
Abstract
BACKGROUND: Maternal nutrition depletion during pregnancy compromises fetal programming, and is a cause of adverse birth outcomes. Maternal body composition measurement using direct body composition assessment methods such as the deuterium dilution technique provides better prediction of birth outcomes as compared with commonly used techniques like anthropometry. This study assessed body composition of pregnant mothers in urban informal settlements in Nairobi, Kenya, and established the relationship between maternal body composition and infant birth weight. METHODS: Deuterium dilution technique was used to determine body composition, including total body water (TBW), fat-free mass (FFM) and fat mass (FM), among 129 pregnant women who were enrolled into the study in their first or second trimester. Descriptive statistics and regression analysis were applied using Stata V.13. RESULTS: The mean TBW, FFM and FM were 33.3 L (±4.7), 45.7 kg (±6.5) and 17.01 kg (±7.4), respectively. Both TBW and FFM were significantly related to maternal age and gestation/pregnancy stage during body composition assessment while FM was significantly associated with gestation stage during body composition assessment. TBW and FFM were significantly lower in younger mothers (<20 years) compared with older mothers (≥20 years). The mean birth weight was 3.3 kg±0.42 kg. There was a positive association between infant birth weight and maternal TBW (p=0.031) and FFM (p=0.027), but not FM (p=0.88). CONCLUSION: Non-fat components of the body (TBW and FFM) have a positive association with birth weight. Therefore, interventions to improve optimal maternal feeding practices, to enhance optimal gains in FFM and TBW during pregnancy are recommended, especially among young mothers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".