Fractures in indigenous compared to non-indigenous populations: A systematic review of rates and aetiology
Bibliographic record
Abstract
BACKGROUND: Compared to non-indigenous populations, indigenous populations experience disproportionately greater morbidity, and a reduced life expectancy; however, conflicting data exist regarding whether a higher risk of fracture is experienced by either population. We systematically evaluate evidence for whether differences in fracture rates at any skeletal site exist between indigenous and non-indigenous populations of any age, and to identify potential risk factors that might explain these differences. METHODS: On 31 August 2016 we conducted a comprehensive computer-aided search of peer-reviewed literature without date limits. We searched PubMed, OVID, MEDLINE, CINAHL, EMBASE, and reference lists of relevant publications. The protocol for this systematic review is registered in PROSPERO, the International Prospective Register of systematic reviews (CRD42016043215). Using the World Health Organization reference population as standard, hip fracture incidence rates were re-standardized for comparability between countries. RESULTS: Our search yielded 3227 articles; 283 potentially eligible articles were cross-referenced against predetermined criteria, leaving 27 articles for final inclusion. Differences in hip fracture rates appeared as continent-specific, with lower rates observed for indigenous persons in all countries except for Canada and Australia where the opposite was observed. Indigenous persons consistently had higher rates of trauma-related fractures; the highest were observed in Australia where craniofacial fracture rates were 22-times greater for indigenous compared to non-indigenous women. After adjustment for socio-demographic and clinical risk factors, approximately a three-fold greater risk of osteoporotic fracture and five-fold greater risk of craniofacial fractures was observed for indigenous compared to non-indigenous persons; diabetes, substance abuse, comorbidity, lower income, locality, and fracture history were independently associated with an increased risk of fracture. CONCLUSIONS: The observed paucity of data and suggestion of continent-specific differences indicate an urgent need for further research regarding indigenous status and fracture epidemiology and aetiology. Our findings also have implications for communities, governments and healthcare professionals to enhance the prevention of trauma-related fractures in indigenous persons, and an increased focus on modifiable lifestyle behaviours to prevent osteoporotic fractures in all populations.
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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 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".