Prenatal, perinatal, and environmental risk factors contribute to the high prevalence of autism spectrum disorder in northeastern Bangladesh
Bibliographic record
Abstract
Objectives Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide, including in Bangladesh. This study investigated prenatal, perinatal, and environmental risk factors associated with ASD in northeastern Bangladesh, where data on the disorder is scarce.Methods A cross-sectional study was conducted with 168 children diagnosed with ASD (CWA), 167 typically developing children (TDC), and 185 unaffected siblings (Sib), recruited from five government-approved specialized schools in Sylhet, northeastern Bangladesh. Diagnoses were confirmed using a modified ADI-R/ADOS, and logistic regression was used to analyze associated risk factors.Results Advanced maternal age, firstborn status, and a history of consanguinity were significant prevalence of prenatal/perinatal complications, including birth asphyxia and blood Rh incompatibility, compared to TDC and Sib. A considerable gap in scientific awareness was noted, with many parents attributing their child’s condition to associated with ASD. Parental exposure to mercury-based dental amalgam was also strongly linked to ASD. CWA had a higher generational or religious belief.Conclusions We identified critical risk factors contributing to the high prevalence of ASD in northeastern Bangladesh, underscoring the need for enhanced diagnostic, educational, and healthcare strategies to ensure good health and well-being and to provide quality education for individuals with ASD.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".