The Association of Contraceptive Use, Non-Use, and Failure with Child Health
Bibliographic record
Abstract
Objective: To examine the association of contraceptive use in the interpregnancy interval with subsequent child health outcomes in low- and middle-income countries. Design: A cross-sectional analysis of nationally representative household samples was performed. A modified Poisson regression model was used to estimate unadjusted and adjusted relative risk ratios for high prevalence outcomes. Setting: Low- and middle-income countries. Population: Births to women aged 12-49 years for which this birth occurred 12-79 months prior to the interview were included. The sample for analysing infant mortality was comprised of 453,795 children from 35 low- and middle-income countries across 67 Demographic and Health Surveys conducted between 1990 and 2011. Main Outcome Measures: Infant mortality, stunting, underweight, wasting, diarrhoea, and anaemia. Results: Contraceptive use in the interpregnancy interval, even if contraceptive failure resulted in birth, had a positive effect on all child health outcomes compared to non-use of contraception in the interpregnancy interval. The positive effect of contraceptive use was the lengthening of the interpregnancy interval, but it also had a direct positive effect on child health, independent of birth interval. Conclusions: Extending the interval between births had a positive effect on child health outcomes, and contraceptive use had a positive effect on child health independent of the birth spacing effect. Additionally, contraceptive failure did not adversely affect child health outcomes.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".