Associations between child and adolescent marriage and reproductive outcomes in Brazil, Ecuador, the United States and Canada
Bibliographic record
Abstract
BACKGROUND: Although marriage is associated with favourable reproductive outcomes among adult women, it is not known whether the marriage advantage applies to girls (< 18 years). The contribution of girl child marriage (< 18 years) to perinatal health is understudied in the Americas. METHODS: National singleton birth registrations were used to estimate the prevalence of girl child marriage among mothers in Brazil (2011-2018, N = 23,117,661), Ecuador (2014-2018, N = 1,519,168), the USA (2014-2018, N = 18,618,283) and Canada (2008-2018, N = 3,907,610). The joint associations between marital status and maternal age groups (< 18, 18-19 and 20-24 years) with preterm birth (< 37 weeks), small-for-gestational age (SGA < 10 percentile) and repeat birth were assessed with logistic regression. RESULTS: The proportion of births to < 18-year-old mothers was 9.9% in Ecuador, 8.9% in Brazil, 1.5% in the United States and 0.9% in Canada, and marriage prevalence among < 18-year-old mothers was 3.0%, 4.8%, 3.7% and 1.7%, respectively. In fully-adjusted models, marriage was associated with lower odds of preterm birth and SGA among 20-24-year-old mothers in the four countries. Compared to unmarried 20-24-year-old women, married and unmarried < 18-year-old girls had higher odds of preterm birth in the four countries, and slightly higher odds of SGA in Brazil and Ecuador but not in the USA and Canada. In comparisons within age groups, the odds of repeat birth among < 18-year-old married mothers exceeded that of their unmarried counterparts in Ecuador [AOR: 1.99, 95%CI: 1.82, 2.18], the USA [AOR: 2.96, 95%CI: 2.79, 3.14], and Canada [AOR: 2.17, 95%CI: 1.67, 2.82], although minimally in Brazil [AOR: 1.09, 95%CI: 1.07, 1.11]. CONCLUSIONS: The prevalence of births to < 18-year-old mothers varies considerably in the Americas. Girl child marriage was differentially associated with perinatal health indicators across countries, suggesting context-specific mechanisms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".