Maternal anthropometry: trends and inequalities in four population-based birth cohorts in Pelotas, Brazil, 1982–2015
Bibliographic record
Abstract
BACKGROUND: Pre-pregnancy nutritional status and weight gain during pregnancy have short- and long-term consequences for the health of women and children. This study was aimed at evaluating maternal height,- and overweight or obesity at the beginning of the pregnancy and gestational weight gain, according to socioeconomic status and maternal skin colour of mothers in Pelotas, a southern Brazilian city, in 1982, 1993, 2004 and 2015. METHODS: In 1982, 1993, 2004 and 2015, the maternity hospitals in Pelotas were visited daily, all deliveries were identified and mothers who lived in the urban area of the city were interviewed. Maternal weight at the beginning of the pregnancy was self-reported by the mother or obtained from the antenatal card. Maternal height was collected from the maternity records or measured by the research team. Overweight or obesity was defined by a body mass index ≥25 kg/m2. Gestational weight gain was evaluated according to the Institute of Medicine guidelines. RESULTS: In the four cohorts, we evaluated 19 931 women. From 1982 to 2015, the prevalence of overweight or obesity at the beginning of the pregnancy increased from 22.1% to 47.0% and height increased by an average of 5.2 cm, whereas gestational weight gain did not change. Socioeconomic status was positively associated with maternal height, and the difference between the poorest and the wealthiest decreased. Overweight or obesity was lower among those mothers in the extreme categories of family income. CONCLUSIONS: Over the 33-year span, mothers were taller at the beginning of the pregnancy, but the prevalence of overweight or obesity more than doubled.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".