Prevalence and temporal trends in prepregnancy nutritional status and gestational weight gain of adult women followed in the Brazilian Food and Nutrition Surveillance System from 2008 to 2018
Bibliographic record
Abstract
Prepregnancy body mass index (BMI) and gestational weight gain (GWG) are the most investigated indicators of maternal nutritional status, which is a modifiable factor that plays a vital role in maternal and infant health. This study describes prepregnancy BMI and GWG of 840,243 women with 2,087,765 weight observations in the Brazilian Food and Nutrition Surveillance System from 2008 to 2018. Prepregnancy BMI was classified according to the World Health Organization cut-offs. Total GWG was calculated from weight measurements taken after 36 weeks of pregnancy and classified according to the Institute of Medicine guidelines. Temporal trends in prepregnancy BMI status were examined, and maps were used to evaluate changes in excessive GWG in each Brazilian federation unit. On overall, prepregnancy overweight and obesity increased from 22.6% to 28.8% and from 9.8% to 19.8%, respectively, between 2008 and 2018. The prevalence of excessive GWG rose from 34.2% to 38.7% during the same period and in 11 of the 27 Brazilian federation units between 2008 and 2016. Women with underweight showed the highest values for mean total GWG for all the compared years (overall variation from 12.3 to 13.1 kg), followed by those with normal weight (11.9 to 12.5 kg), overweight (10.1 to 10.9 kg) and obesity (from 8.2 to 8.9 kg). Within each BMI group, values remained fairly stable throughout the studied period for first- and second-trimester GWG and total GWG. These results help to fill a significant gap in understanding the distribution of prepregnancy BMI and GWG in Brazilian women.
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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".