Maternal Micronutrient Status During Pregnancy and Its Neurodevelopmental Implications for Infants in South Asia: Protocol for a Scoping Review
Bibliographic record
Abstract
Background: Pregnancy is a crucial stage characterized by an increased demand for various nutrients. The role of micronutrients becomes especially important during pregnancy and infancy to support neurodevelopment. Micronutrient deficiencies are prevalent in low- and middle-income countries due to socioeconomic disparities, limited dietary diversity, and barriers to quality antenatal care. This results in women of reproductive age and developing offspring being disproportionately affected. Despite extensive research, evidence remains fragmented, leading to a lack of comprehensive synthesis. Objective: This scoping review aims to explore the existing evidence on the role of maternal micronutrient status during pregnancy influencing neurodevelopmental outcomes in infants. Additionally, it will assess the prevalence and distribution of specific micronutrient deficiencies and identify their sociodemographic determinants within South Asian countries. Methods: This scoping review uses an iterative, three-step search strategy to identify both published and gray literature. Initially, a targeted search using relevant keywords was developed for PubMed to locate studies investigating maternal micronutrient status or supplementation during pregnancy (women aged 15-49 y) and associated neurodevelopmental outcomes in offspring up to two years of age. The search was sequentially narrowed by geographic region (South Asian countries), study design, human studies, English-language publications, and clinical trials. In the second stage, this search strategy will be adapted and implemented across additional electronic databases, including MEDLINE, Embase, Google Scholar, Cochrane Library, OpenGrey, JSTOR, and Wiley, as well as trial registries such as ClinicalTrials.gov and PROSPERO. Further, supplementary hand-searching of relevant journals will be conducted. The third step involves applying a snowballing technique to review the bibliographies of initially identified papers. Two reviewers will independently conduct study selection and data extraction using standardized forms. Quality assessment will use Joanna Briggs Institute critical appraisal checklists. Quantitative findings (study characteristics, exposure definitions, outcome measures) will be summarized with descriptive statistics and visualized in structured tables and charts, and qualitative findings will be coded inductively to develop themes pertinent to the review questions. We will integrate evidence through a convergent narrative synthesis to contextualize how maternal micronutrient deficiencies are influenced by sociodemographic factors and how these relate to infant neurodevelopment. The review will adhere to PRISMA-ScR reporting guidelines. Results: The initial database search was completed on July 3, 2025. Title and abstract screening is in progress, and final synthesis and reporting are anticipated by January 2026. Conclusions: This review aims to summarize the available evidence on maternal micronutrients and infant neurodevelopment in South Asia, identify major gaps and inconsistencies in the data, and highlight opportunities for focused research and multisectoral action. The findings will help guide the next phases of the South Asia Collaborative for Maternal Micronutrients and Infant Neurodevelopment (SACMIND) collaborative project, which will include qualitative studies, biomarker assessments, and designing interventions.
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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 | 0.069 | 0.056 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.016 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.055 | 0.009 |
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".