Vitamin and Mineral Supplementation During Pregnancy on Maternal, Birth, Child Health and Development Outcomes in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Almost two billion people are deficient in key vitamins and minerals, mostly women and children in low- and middle-income countries (LMICs). Deficiencies worsen during pregnancy due to increased energy and nutritional demands, causing adverse outcomes in mother and child, but could be mitigated by interventions like micronutrient supplementation. To our knowledge, this is the first systematic review that aimed to compile evidence from both efficacy and effectiveness trials, evaluating different supplementation interventions on maternal, birth, child health, and developmental outcomes. We evaluated randomized controlled trials and quasi-experimental studies published since 1995 in peer-reviewed and grey literature that assessed the effects of calcium, vitamin A, iron, vitamin D, and zinc supplementation compared to placebo/no treatment; iron-folic (IFA) supplementation compared to folic acid only; multiple micronutrient (MMN) supplementation compared to IFA; and lipid-based nutrient supplementation (LNS) compared to MMN supplementation. Seventy-two studies, which collectively involved 314 papers (451,723 women), were included. Meta-analyses showed improvement in several key birth outcomes, such as preterm birth, small-for-gestational age (SGA) and low birthweight with MMN supplementation, compared to IFA. MMN also improved child outcomes, including diarrhea incidence and retinol concentration, which are findings not previously reported. Across all comparisons, micronutrient supplementation had little to no effect on mortality (maternal, neonatal, perinatal, and infant) outcomes, which is consistent with other systematic reviews. IFA supplementation showed notable improvement in maternal anemia and the reduction in low birthweight, whereas LNS supplementation had no apparent effect on outcomes; further research that compares LNS and MMN supplementation could help understand differences with these commodities. For single micronutrient supplementation, improvements were noted in only a few outcomes, mainly pre-eclampsia/eclampsia (calcium), maternal anemia (iron), preterm births (vitamin D), and maternal serum zinc concentration (zinc). These findings highlight that micronutrient-specific supplementation should be tailored to specific groups or needs for maximum benefit. In addition, they further contribute to the ongoing discourse of choosing antenatal MMN over IFA as the standard of care in LMICs.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".