72 Prevalence of Neurodevelopmental Disorder among Indigenous Children: A Systematic Review
Bibliographic record
Abstract
Abstract Background Neurodevelopment involves sensory-motor, cognitive, and social-emotional domains, which can be influenced by biological and psychosocial factors. Poor neurodevelopment can result in missing developmental milestones and neurodevelopmental disorders (NDs) that translate into negative consequences for long-term health and well-being. Indigenous children in countries with similar colonial histories face a disproportionate burden of infant mortality, chronic diseases, injuries, and disability compared to non-Indigenous children. However, there is no consensus on the prevalence of NDs among Indigenous children around the world. Objectives This systematic review (PROSPERO 2021 CRD42021238669) synthesized current evidence on the prevalence of NDs among Indigenous children in Australia, Canada, New Zealand, and the USA. Design/Methods Comprehensive searches of five databases from 2005 to Feb 15, 2021 were conducted to identify cohort and cross-sectional studies that assessed the objective. Two independent reviewers conducted study selection, data extraction/analysis, and risk of bias assessment. Risk of bias was assessed using the Newcastle-Ottawa scale for cohort and ecological studies (adapted), and the Quality Assessment Tool for Prevalence Studies by Hoy et al. for cross-sectional studies. Prevalence odds ratios (pOR) with 95% confidence intervals (CI) were calculated in random-effects meta-analyses for each ND outcome if there were two or more studies of the same study design. Results Of the 864 studies identified, 25 studies met the inclusion criteria. Twelve studies were conducted in Australia, one in Canada, four in New Zealand, and eight in the USA. Four studies evaluated attention-deficit/hyperactivity disorder (ADHD) prevalence, 13 for autism spectrum disorder (ASD), 10 for intellectual disability (ID), and five for motor disorders (MD). Most cohort studies (10/17) had high risk of bias. All cross-sectional studies (n=8) had low risk of bias. The prevalence of ADHD, ASD, ID, and MD for Indigenous children ranged from 2.7-3.9%, 0.07-3.0%, 1.1-3.9%, and 0.18-0.47%, respectively. Prevalence in non-Indigenous children ranged from 1.6-5.6%, 0.31-3.3%, 0.87-2.3%, and 0.22-0.37%. In cross-sectional studies, Indigenous children had decreased odds of ASD (three studies; pOR=0.80; 95% CI: 0.71-0.89) compared to non-Indigenous children. In cohort studies, higher odds of MD (two studies; pOR=1.57; 95%CI: 1.35-1.84) and lower odds of ASD (four studies; pOR=0.46; 95% CI: 0.28-0.76) were found in Indigenous children compared to non-Indigenous children. Conclusion Prevalence rates are greater in Indigenous children for MD and lower for ASD compared to their non-Indigenous counterparts. Differences in NDs prevalence between Indigenous and non-Indigenous children may be due to differences in access to health care services/assessment.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".