Association of Early Interventions With Birth Outcomes and Child Linear Growth in Low-Income and Middle-Income Countries
Bibliographic record
Abstract
Importance: The first 1000 days of life represent a critical window for child development. Pregnancy, exclusive breastfeeding (EBF) period (0-6 months), and complementary feeding (CF) period (6-24 months) have different growth requirements, so separate considerations for intervention strategies are needed. No synthesis to date has attempted to quantify the associations of interventions under multiple domains of micronutrient and balanced energy protein and food supplements, deworming, maternal education, water sanitation, and hygiene across these 3 life periods with birth and growth outcomes. Objective: To determine the magnitude of association of interventions with birth and growth outcomes based on randomized clinical trials (RCTs) conducted in low-income and middle-income countries (LMICs) using Bayesian network meta-analyses. Data Sources: MEDLINE, Embase, and Cochrane databases were searched from their inception up to August 14, 2018. Study Selection: Included were LMIC-based RCTs of interventions provided to pregnant women, infants (0-6 months), and children (6-24 months). Data Extraction and Synthesis: Two independent reviewers used a standardized data extraction and quality assessment form. Random-effects network meta-analyses were performed for each life period. Effect sizes are reported as odds ratios (ORs) and mean differences (MeanDiffs) for dichotomous and continuous outcomes, with 95% credible intervals (CrIs). This study calculated probabilities of interventions being superior to standard of care by at least a minimal clinically important difference. Main Outcomes and Measures: The study compared ORs on preterm birth and MeanDiffs on birth weight for pregnancy, length for age (LAZ) for EBF, and height for age (HAZ) for CF. Results: Among 302 061 participants in 169 randomized clinical trials, the network meta-analyses found several nutritional interventions that demonstrated greater association with improved birth and growth outcomes compared with standard of care. For instance, compared with standard of care, maternal supplements of multiple micronutrients showed reduced odds for preterm birth (OR, 0.54; 95% CrI, 0.27-0.97) and improved mean birth weight (MeanDiff, 0.08 kg; 95% CrI, 0.00-0.17 kg) but not LAZ during EBF (MeanDiff, -0.02; 95% CrI, -0.18 to 0.14). Supplementing infants and children with multiple micronutrients showed improved LAZ (MeanDiff, 0.20; 95% CrI, 0.03-0.35) and HAZ (MeanDiff, 0.14; 95% CrI, 0.02-0.25). The study found that pregnancy interventions generally had higher probabilities of a minimal clinically importance difference than the interventions for the EBF or CF in the first 1000 days of life. Conclusions and Relevance: These analyses highlight the importance of intervening early for child development, during pregnancy if possible. Results of this study suggest that there is a need to combine interventions from multiple domains and test for their effectiveness as a package.
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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 | 0.001 |
| 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".