Associations between household air pollution and early child development among children aged 36–59 months in Bangladesh
Bibliographic record
Abstract
BACKGROUND: Household air pollution (HAP) from solid fuel use (SFU) for cooking may impact child health in low-resources countries. This study examined the associations between HAP and early childhood development (ECD) outcomes among children under 5 years of age in Bangladesh and explored potential effect modification by sex and urbanicity. METHODS: The study sample consisted of 9395 children aged 36-59 months in the households from the Bangladesh Multiple Indicator Cluster Survey 2019. SFU and levels of exposure to SFU (unexposed, moderately exposed and highly exposed) were used as proxies of HAP exposure. We estimated the covariate-adjusted prevalence ratios (aPRs) and 95% CIs for the associations between HAP and ECD outcomes using multilevel mixed-effects Poisson regression models with a robust variance estimator. RESULTS: 81.4% of children were exposed to SFU, and the prevalence of developmental delay (in Early Childhood Development Index) was 25.3%. Children exposed to SFU were 1.47 times more likely to have developmental delays (95% CI: 1.25, 1.73; p<0.001) compared with children with no SFU exposure. SFU was significantly associated with developmental delay in socioemotional (aPR: 1.17; 95% CI: 1.01, 1.36; p=0.035) and learning-cognitive (aPR: 1.90; 95% CI: 1.39, 2.60; p<0.001) domains. Similarly, children moderately exposed and highly exposed to HAP had higher prevalence of developmental delays than unexposed children. We did not observe effect modification by sex or urbanicity. CONCLUSION: Public health policies should promote the use of clean cooking fuels and cookstoves to reduce the high burden of HAP exposure in low-resource countries for helping younger children to meet their developmental milestones.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".