Acceptability of Antenatal Multiple Micronutrient Supplementation (MMS) Compared to Iron and Folic Acid (IFA) Supplementation in Pregnant Individuals: A Narrative Review
Bibliographic record
Abstract
Background/Objectives: Antenatal multiple micronutrient supplementation (MMS) improves birth outcomes more effectively than iron and folic acid (IFA) supplementation alone. However, the acceptability of MMS among pregnant individuals, a critical factor for adherence and program success, remains poorly defined and inconsistently assessed. This narrative review proposes a comprehensive definition of “acceptability” in the context of nutritional supplementation and evaluates the evidence on the acceptability of MMS compared to IFA in low- and middle-income countries (LMICs). Methods: We conducted a systematic literature search across Embase, Medline, and Scopus to identify studies (including grey literature) reporting on acceptability-related outcomes for MMS versus IFA among pregnant individuals. Studies exploring dimensions such as organoleptic properties, ease of consumption, side effects, cultural appropriateness, and socioeconomic factors were included. Results: Out of 1056 screened studies, five informed a novel multi-dimensional definition of acceptability. Six studies assessed acceptability-related characteristics. MMS was generally accepted across most organoleptic domains. Most studies reported fewer or comparable adverse side effects for MMS as compared to IFA. Studies consistently reported more perceived benefits for MMS than IFA. Facilitating factors included trust in health professionals, free provision, and family support. Barriers included poor taste or smell, fear of side effects, misconceptions, cost, and lack of family support. Conclusions: Antenatal MMS is widely acceptable in LMICs. Addressing socio-cultural, sensory, and socioeconomic factors is essential to increase uptake and adherence. This review provides a clear, standardized definition of acceptability to guide future research and inform effective program design.
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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 | 0.009 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".