Maternal reproductive history: trends and inequalities in four population-based birth cohorts in Pelotas, Brazil, 1982–2015
Bibliographic record
Abstract
BACKGROUND: Brazil experienced important progress in maternal and child health in recent decades. We aimed at describing secular trends as well as socioeconomic and ethnic inequalities in reproductive history indicators (birth spacing, previous adverse perinatal outcome, parity and multiple births) over a 33-year span. METHODS: Four population-based birth cohort studies included all hospital births in 1982, 1993, 2004 and 2015 in Pelotas, Southern Brazil. Information on reproductive history was collected through interviews. Indicators were stratified by family income quintiles and skin colour. Absolute and relative measures of inequality were calculated. RESULTS: From 1982 to 2015, the proportion of primiparae increased from 39.2% to 49.6%, and median birth interval increased by 23.2 months. Poor women were more likely to report short intervals and higher parity, although reductions were observed in all income and ethnic groups. History of previous low birthweight was inversely related to income and increased by 7.7% points (pp) over time-more rapidly in the richest (12.1 pp) than in the poorest quintile (0.4 pp). Multiple births increased from 1.7% to 2.7%, with the highest increase observed among the richest quintile and for white women (220% and 70% increase, respectively). Absolute and relative income and ethnic-related inequalities for short birth intervals increased, whereas inequalities for previous low birthweight decreased over time. CONCLUSIONS: In this 33-year period there were increases in birth intervals, multiple births and reports of previous low-birthweight infants. These trends may be explained by increased family planning coverage, assisted reproduction and a rise in preterm births, respectively. Our results show that socioeconomic and ethnic inequalities in health are dynamic and vary over time, within the same location.
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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 | 0.001 |
| 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".