Nutrition, growth, and other factors associated with early cognitive and motor development in Sub‐Saharan Africa: a scoping review
Bibliographic record
Abstract
BACKGROUND: Food insecurity, poverty and exposure to infectious disease are well-established drivers of malnutrition in children in Sub-Saharan Africa. Early development of cognitive and motor skills - the foundations for learning - may also be compromised by the same or additional factors that restrict physical growth. However, little is known about factors associated with early child development in this region, which limits the scope to intervene effectively. To address this knowledge gap, we compared studies that have examined factors associated with early cognitive and/or motor development within this population. METHODS: Predetermined criteria were used to examine four publication databases (PsycInfo, Embase, Web of Science and Medline) and identify studies considering the determinants of cognitive and motor development in children aged 0-8 years in Sub-Saharan Africa. RESULTS: In total, 51 quantitative studies met the inclusion criteria, reporting on 30% of countries across the region. Within these papers, factors associated with early child development were grouped into five themes: Nutrition, Growth and Anthropometry, Maternal Health, Malaria and HIV, and Household. Food security and dietary diversity were associated with positive developmental outcomes, whereas exposure to HIV, malaria, poor maternal mental health, poor sanitation, maternal alcohol abuse and stunting were indicators of poor cognitive and motor development. DISCUSSION: In this synthesis of research findings obtained across Sub-Saharan Africa, factors that restrict physical growth are also shown to hinder the development of early cognitive and motor skills, although additional factors also influence early developmental outcomes. The study also reviews the methodological limitations of conducting research using Western methods in sub-Saharan Africa.
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".