Systematic review of rheumatic disease epidemiology in the indigenous populations of Canada, the United States, Australia, and New Zealand
Bibliographic record
Abstract
OBJECTIVE: Past publications have highlighted an excess rheumatic disease incidence and prevalence in indigenous populations of Canada (First Nations, Inuit, and Métis), and the United States of America (Alaska Native and American Indian). We have updated these reviews and expanded the scope to include New Zealand (Maori) and Australia (Aborigine) indigenous populations. METHODS: We performed a broad search using medical literature databases, indigenous specific online indexes, and government websites to identify publications reporting the incidence and/or prevalence of arthritis conditions (rheumatoid arthritis, spondyloarthropathies, gout, osteoarthritis, systemic autoimmune rheumatic diseases, and juvenile idiopathic arthritis) in the indigenous populations of Canada, America, New Zealand, and Australia. A narrative synthesis by type of arthritis was prepared given the heterogeneity of study designs used in the primary studies. RESULTS: Of 5269 titles and abstracts, 88 met inclusion criteria. Osteoarthritis was found to affect up to 17% of American Indian/Alaska Native women, 22% of Canadian First Nations, 32% of Australian Aborigine, and 6% of New Zealand Maori populations. The prevalence of rheumatoid arthritis, systemic lupus erythematosus, and juvenile idiopathic arthritis was consistently significantly higher in indigenous populations. Several studies describing the prevalence of spondyloarthropathy in North American northern populations were identified, but with no comparison populations the relative frequency could not be commented on. Gout was more prevalent in Maori compared to general population New Zealanders. CONCLUSIONS: This comprehensive summary describes rheumatic disease burden in indigenous populations in four countries with similar disparities in social determinants of health, to inform clinical service requirements to meet population need.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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".