Associations between contraception and stunting in Guatemala: secondary analysis of the 2014–2015 Demographic and Health Survey
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: There has been limited research on the relationship between contraception and child growth in low-income and middle-income countries (LMICs). This study examines the association between contraception and child linear growth in Guatemala, an LMIC with a very high prevalence of child stunting. We hypothesise that contraceptive use is associated with better child linear growth and less stunting in Guatemala. METHODS: Using representative national data on 12 440 children 0-59 months of age from the 2014-2015 Demographic and Health Survey in Guatemala, we constructed multivariable linear and Poisson regression models to assess whether child linear growth and stunting were associated with contraception variables. All models were adjusted for a comprehensive set of prespecified confounding variables. RESULTS: Contraceptive use was generally associated with modest, statistically significant greater height-for-age z-score. Current use of a modern method for at least 15 months was associated with a prevalence ratio of stunting of 0.87 (95% CI 0.81 to 0.94; p<0.001), and prior use of a modern method was associated with a prevalence ratio of stunting of 0.93 (95% CI 0.87 to 0.98; p<0.05). The severe stunting models found generally similar associations with modern contraceptive use as the stunting models. There was no significant association between use of a modern method for less than 15 months and the prevalence ratio of stunting or severe stunting. CONCLUSIONS: Contraceptive use was associated with better child linear growth and less child stunting in Guatemala. In addition to the human rights imperative to expand contraceptive access and choice, family planning merits further study as a strategy to improve child growth in Guatemala and other countries with high prevalence of stunting.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 it