Under‐five children's acute respiratory infection dropped significantly in Bangladesh: An evidence from Bangladesh demographic and health survey, 1996–2018
Bibliographic record
Abstract
AIM: This study aims to systematically identify and review the most significant risk factors and the trends that follow acute respiratory infection (ARI) among children under five in Bangladesh. METHODS: A total of 6863 under-five children were eligible for our analysis, retrieved from Bangladesh Demographic and Health Survey (BDHS), 2014. ARI cases were defined if a child experienced coughing with short and rapid breathing at the chest that occurred during 2 weeks prior to the study. Logistic regression and systematic review methods were appraised to explore the various risk factors involving ARI in Bangladesh. Furthermore, a trend analysis was performed to overlook the historical trend of ARI prevalence and affiliated determinants from 1996/97 to 2017/18 in Bangladesh. RESULTS: Over the past two decades, Bangladesh experienced a significant drop in ARI prevalence from 12.8% in 1996 to only 3.0% in 2018. The cross-sectional findings revealed that boys (OR = 1.35, 95% CI: 1.03-1.78), stunted children (OR = 1.35, 95% CI: 1.03-1.78) and mothers with primary or no education (OR = 2.53, 95% CI: 1.43-4.90) and secondary education (OR = 1.77, 95% CI: 1.00-3.44) have the higher odds of ARI than their counterparts. CONCLUSION: Acute respiratory infection prevalence significantly declined in Bangladesh, while boys, stunted children and uneducated or primary educated mothers were identified as potential risk factors.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".