Maternal Education and Home Environment Quality Protect Infants in Low Asset Families From Poor Growth
Bibliographic record
Abstract
OBJECTIVE Economic inequities are common in low and middle‐income countries, and are associated with poor growth among young children. To examine whether maternal education and home environment quality attenuate the association between economic inequities and children's growth. METHODS The sample included baseline data from 512 infants and 321 preschoolers in 26 villages in rural India (Project Grow Smart). Data collection included child growth (weight and length/height measured and converted to wt/age, ln/ht/age and BMI/age z‐scores, WAZ, LAZ/HAZ, BAZ) and hemoglobin (Hb); maternal education, wt/ht and Hb; and economic inequities measured by household assets (weighted score 0–8) and observations of home environment quality (HOME Inventory). Maternal education (completion of primary school or beyond) and home quality (top quartile) were combined into a 3‐level education/home protective factor (PF; high education and home quality, neither [0], either [1], both [2]). Data were analyzed using linear mixed models for infants and preschoolers separately, adjusted for gender and clustering within villages, and including asset by PF interactions. Interactions were interpreted at low/high assets (mean±SD). RESULTS Findings for infants/preschoolers: mean age 8.6/36.6 mo; underweight (WAZ<−2): 18.9%/45.9%; stunting (LAZ/HAZ<−2): 19.5%/40.6%; anemic (Hb<11.0 g/dL): 68.8%/48.6%. Findings for mothers of infants/preschoolers: mean age: 22.9/25.0 y; underweight (BMI<18.5): 37.8%/43.0%; anemic (Hb<12.0 g/dL): 43.7%/34.2%, primary school or beyond: 75.1%/55.2%. Among infants, relationships between assets and WAZ and LAZ are significantly attenuated by PF (p<0.01 for both) and relationships between assets and BAZ are marginally attenuated (p<0.10). Among infants, at low asset levels, PF accounts for 1.3 difference in WAZ (β= 0.65, p<0.01), a 1.38 difference in LAZ (β=0.69, p<0.01), and a 0.7 difference in BAZ (β=0.35, p<0.01). At high asset levels, the WAZ gap between children with/without PF narrows by 0.14 for 1 PF and 0.28 for both PFs (interaction β=0.14, p<0.01) (); the LAZ gap narrows by 0.13 for 1 PF and 0.26 for both PFs (interaction β=0.13, p<0.01); and the BAZ gap narrows by 0.08 for 1 PF and 0.16 for both PFs (interaction β=0.08, p<0.10). Among preschoolers, PF have a marginal independent association with BAZ (p<0.10), with no attenuation in relationships between assets and children's growth. CONCLUSIONS Maternal education and home environment quality may protect infants in low‐asset families from poor growth, illustrating the importance of the care giving context in offsetting the negative consequences of economic inequities on growth during infancy. Among preschoolers, maternal education and home environment quality do not provide growth protection from economic inequities in areas with high rates of stunting. To promote infant growth in low‐asset families, findings support early responsive care giving intervention. Support or Funding Information Micronutrient Initiative, The Mathile Institute for the Advancement of Human Nutrition
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".