DO MODIFIABLE HOUSEHOLD BEHAVIORS AND EARLY INFANT FEEDING PRACTICES CONTRIBUTE TO VARIATIONS IN INFANT LINEAR GROWTH? EVIDENCE FROM A BIRTH COHORT IN DHAKA, BANGLADESH
Bibliographic record
Abstract
Abstract BACKGROUND Numerous postnatal risk factors have been associated with child length/height in cross-sectional studies in low- and middle-income countries. However, there have been few longitudinal studies of the effects of modifiable risk factors on postnatal linear growth during discrete developmental windows of infancy. OBJECTIVES We aimed to assess associations between modifiable household behaviours and conditional growth from birth to 1 year of life. DESIGN/METHODS We conducted a longitudinal cohort study using data from women and their infants (n=1162 pairs) in the Maternal Vitamin D and Infant Growth trial in Dhaka, Bangladesh. Infant length was measured tri-monthly from birth to 12 months, and infant feeding patterns were ascertained at weekly visits from 0 to 6 months of age. Confounder-adjusted associations of selected modifiable household factors (i.e., household air quality, sanitation/hygiene) or early infant feeding with change in length-for-age z-score (LAZ) were estimated in five intervals: birth to 3 months, 3 to 6 months, birth to 6 months, 6 to 12 months and birth to 12 months. In primary analyses, the outcome was conditional growth in LAZ (cLAZ) in each interval, derived as model residuals from regression of end-interval LAZ on initial LAZ. Effect estimates were expressed as mean difference in cLAZ (95% confidence interval) between the exposed versus referent group. RESULTS LAZ was symmetrically distributed, with mean (± standard deviation) LAZ of -0.95 (± 1.02) at birth and -1.00 (± 1.04) at 12 months. In multivariable-adjusted linear regression models, indicators of household air quality and sanitation/hygiene were not significantly associated with cLAZ in any interval. No breastfeeding and partial breastfeeding (versus exclusive breastfeeding), and any infant formula use (versus no formula use) were associated with slower growth in the 0–3 month interval: -0.11 (95% CI: -0.20, -0.02), -0.30 (95% CI: -0.52, -0.08), and -0.13 (95% CI: -0.22, -0.05), respectively, but not in later intervals. Several non-modifiable factors (maternal height, paternal education, and household wealth) were associated with cLAZ and LAZ in multivariable models. CONCLUSION Compared to international standards, the length distribution of infants in Dhaka, Bangladesh was harmonically shifted down at birth and throughout the first year of life, suggesting that observed infant length deficits relative to international norms were primarily caused by ubiquitous factors. Infant feeding practices explained some between-child variation in linear growth in the early postnatal period (0–3 months). Behaviors related to cooking or sanitation/hygiene were not related to infant linear growth trajectories.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".