142 Costs Associated with Fetal Alcohol Spectrum Disorder: A comparison of Indigenous and Non-Indigenous Children
Bibliographic record
Abstract
Abstract Primary Subject area Developmental Paediatrics Background The incidence of Fetal Alcohol Spectrum Disorder (FASD) is estimated to be 1 in 100 live births. Caused by prenatal exposure to alcohol, FASD is the leading cause of developmental and cognitive disabilities among Ontario’s children. No study has conducted a comparison of the costs associated with FASD among Indigenous children, and Non-Indigenous children. Objectives To calculate and compare an estimate of direct and indirect costs associated with FASD at the patient level among Indigenous children and Non-Indigenous children living in Ontario. Design/Methods A cross-sectional study design was used. Eight-hundred and thirty (830) participants completed the study tool. Participants included caregivers of children aged 3 months to 17.5 years, living in urban and rural communities throughout Ontario. Four-hundred and twelve (412) participants were Indigenous Ontarians, and 418 participants were Non-Indigenous Ontarians. Participants completed the Health Services Utilization Inventory (HSUI). Key cost components were elicited: direct costs (medical, education, social services, out-of-pocket costs); and indirect costs (productivity losses). Total average costs per child with FASD were calculated by summing the costs for each, in each cost component, and dividing by the sample size. Costs were extrapolated to one year. A t-test was used to compare costs associated with FASD in the two groups. A stepwise multiple regression analysis was used to identify significant determinants of costs. Results Total adjusted annual costs associated with FASD at the individual level was $51,543 (95% CI $46,825; $56,642) among Indigenous children compared to $36,435 (95% CI $31,935; $42,245), among Non-Indigenous children (p<0.01). Severity of the child’s condition and relationship of the child to the caregiver (biological, adoptive, foster) were significant determinants of costs in both groups (p < 0 .01). Age of diagnosis was a significant determinant of costs among the Indigenous group (p < 0.001) but was not a significant determinant in the Non-Indigenous group. On average, Indigenous children were diagnosed with FASD 3.9 years later than Non-Indigenous children. Conclusion Study results demonstrated the cost associated with FASD in Ontario was significantly greater among Indigenous children compared to Non-Indigenous children. Implications for practice, policy, and research are discussed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".