Associations of parental internal migration with child growth and nutritional status in low- and middle-income countries: A systematic review
Bibliographic record
Abstract
Five to 50% of people in low- and middle-income countries (LMICs) report having ever migrated internally. Studies suggest internal (within-country) migration may influence health within and across generations. This review aims to collate evidence of associations of parental internal migration and child growth and nutritional status in LMICs. Observational studies of children with parents who had migrated internally within their resident country, with a non-migrant reference group and outcomes relating to child growth and nutritional status were eligible. Full research articles in peer-reviewed journals from 2000 onwards were included, with no country/setting/language restrictions. The search was conducted in June 2024 in Embase/Global Health/MEDLINE, WoS, Proquest Central, Global Index Medicus, and Google Scholar using relevant keywords. The Newcastle-Ottawa Scale assessed risk of bias. The protocol was registered on PROSPERO (CRD42023423895). Twelve studies were identified from China, India, Mexico, Peru, Tanzania, South Africa, and Turkey, most of which focussed on early childhood, and all but one found associations. Of studies comparing rural-urban migrants to rural non-migrants (n=5), migration was associated with reduced risk of child undernutrition and improved linear growth, particularly for children born at urban destination, but also increased weight growth and overweight. In comparison to urban non-migrants (n=11), findings were mixed and showed children of rural-urban migrants had greater/similar levels of undernutrition and poorer growth or greater levels of overweight in early life but better linear growth in late childhood/adolescence. This review identifies internal migration as a determinant of child health in LMICs and thus suggests it should be considered when designing policies and interventions to improve child health. • Internal migration may influence health within and across generations. • Notably, parent migration could influence child growth and nutritional status. • This review identified 12 studies from low- and middle-income countries. • Parent rural-urban migration was linked to greater child linear growth and obesity. • Limitations include varying definitions of migration and cross-sectional study 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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".