Burden of Acute Respiratory Infections Among Under-Five Children in Relation to Household Wealth and Socioeconomic Status in Bangladesh
Bibliographic record
Abstract
Acute respiratory infections (ARIs), as a group of diseases and symptoms, are a leading cause of morbidity and mortality among under-five children in tropical countries like Bangladesh. Currently, no clear evidence has been published on the prevalence and socioeconomic correlates of ARIs in Bangladesh. In this regard, we carried out this study with the aim of assessing the prevalence and the socioeconomic predictors of ARIs among children aged 0⁻59 months, with a special focus on socioeconomic status and wealth-related indicators. Cross-sectional data on 32,998 mother-child (singleton) pairs were collected from six rounds of Bangladesh Demographic and Health Surveys (BDHS 1997⁻2014). The outcome variable were presence of the common symptoms of ARIs, fever and dyspnea, during the previous two weeks, which were measured based on mothers' reports about the symptoms of these conditions. Explanatory variables included maternal demographic and socioeconomic factors such as age, education, occupation, wealth quintile, and child's age and sex. The prevalence and predictors of ARIs were measured using descriptive and multivariate regression methods. The prevalence of both fever (31.00% in 1997 vs. 36.76% in 2014) and dyspnea (39.27% in 1997 vs. 43.27% in 2014) has increased gradually since 1997, and tended to be higher in households in the lower wealth quintiles. Multivariable analysis revealed that higher maternal educational status, access to improved water and sanitation facilities, and living in households in higher wealth quintiles had protective effects against both fever and dyspnea. Findings suggested a significantly negative association between lacking access to improved water and sanitation and use of biomass fuel with ARI symptoms. However, no sex difference was observed in these associations. Based on the findings, childhood ARI prevention strategies should address the risk factors stemming from parental socioeconomic marginalisation, household water and sanitation poverty, and use of unclean fuel.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".