Socio-demographic factors associated with normal linear growth among pre-school children living in better-off households: A multi-country analysis of nationally representative data
Bibliographic record
Abstract
This study examined the socio-demographic factors associated with normal linear growth among pre-school children living in better-off households, using survey data from Ghana, Kenya, Nigeria, Mozambique and Democratic Republic of Congo (DRC). The primary outcome variable was child height-for-age z-scores (HAZ), categorised into HAZ≥-2SD (normal growth/not stunted) and HAZ<-2 (stunted). Using logistic regression, we estimated adjusted odds ratios (aORs) of the factors associated with normal growth. Higher maternal weight (measured by body mass index) was associated with increased odds of normal growth in Mozambique, DRC, Kenya and Nigeria. A unit increase in maternal years of education was associated with increased odds in normal growth in DRC (aOR = 1.06, 95% CI = 1.03, 1.09), Ghana (aOR = 1.08, 95% CI = 1.04, 1.12), Mozambique (aOR = 1.08, 95% CI = 1.05, 1.11) and Nigeria (aOR = 1.07, 95% CI = 1.06, 1.08). A year increase in maternal age was positively associated with normal growth in all the five countries. Breastfeeding was associated with increased odds of normal growth in Nigeria (aOR = 1.30, 95% CI = 1.16, 1.46) and Kenya (aOR = 1.37, 95% CI = 1.05, 1.79). Children of working mothers had 25% (aOR = 0.75, 95% CI = 0.60, 0.93) reduced odds of normal growth in DRC. A unit change in maternal parity was associated with 10% (aOR = 0.90, 95% CI = 0.84, 0.97), 23% (aOR = 0.77, 95% CI = 0.63, 0.93), 25% (aOR = 0.75, 95% CI = 0.69, 0.82), 6% (aOR = 0.94, 95% CI = 0.89, 0.99) and 5% (aOR = 0.95, 95% CI = 0.92, 0.99) reduced odds of normal growth in DRC, Ghana, Kenya, Mozambique and Nigeria, respectively. A child being a male was associated with 18% (aOR = 0.82, 95% CI = 0.68, 0.98), 40% (aOR = 0.60, 95% CI = 0.40, 0.89), 37% (aOR = 0.63, 95% CI = 0.51, 0.77) and 21% (aOR = 0.79, 95% CI = 0.71, 0.87) reduced odds of normal child growth in DRC, Ghana, Kenya and Nigeria, respectively. In conclusion, maternal education, weight, age, breastfeeding and antenatal care are positively associated with normal child growth. In contrast, maternal parity, employment, and child sex and age are associated negatively with normal growth. Interventions to improve child growth should take into account these differential effects.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".