The perinatal epidemiology of child and adolescent marriage in Brazil, 2011–2018
Bibliographic record
Abstract
Brazil is one of the top contributors of girl child marriages in the world and one of the United Nations' members that committed to end child marriage by 2030 as part of the Sustainable Development Goals. Child marriage is an indicator of gender inequality associated with poor health outcomes. However, the perinatal epidemiology of minor mothers (<18 years) according to marital status has been insufficiently studied. We used 23,163,209 birth registrations (2011-2018) to describe the sociodemographic distribution of births to minor mothers. The association between adverse outcomes and marital status and maternal age was restricted to 7,953,739 births of mothers aged ≤15, 16-17, 18-19, 20-24 years. Multinomial logistic models were used for very (24-31 weeks) and moderately preterm birth (32-36 weeks), and severe (<3rd percentile) and moderately small-for-gestational age (SGA) (3rd to <10th percentile). Logistic models were used for binary outcomes. The proportion of births to minor mothers in the study period was 8.9%, composed of those of single (6.1%), common-law (2.4%) and married girls (0.4%). Births to minor mothers decreased over time (p-value <0.001), were more common in the North Region (13.2%) and among Indigenous (17.4%). Very and moderately preterm birth increased with decreasing age but within each age group, rates were highest among single, followed by common-law and lowest among married mothers. A similar pattern was observed for SGA, low Apgar and late prenatal care initiation. Repeat birth and low age-appropriate education were less common among married compared to single mothers in all age groups, except among ≤15-year-olds [Adjusted Odds Ratio (AOR): 2.56; 95% Confidence Interval (95%CI): 2.40, 2.74 and AOR: 1.30; 95%CI: 1.03, 1.64, respectively]. The association between perinatal indicators and marital status among adolescents is strongly modified by decreasing maternal age. Marital status is relevant for the understanding of early pregnancies.
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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 | 0.001 | 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".