Prevalence of Asthma and Chronic Obstructive Pulmonary Disease in Aboriginal and Non-Aboriginal Populations: A Systematic Review and Meta-Analysis of Epidemiological Studies
Bibliographic record
Abstract
BACKGROUND: Asthma and chronic obstructive pulmonary disease (COPD) have considerable potential for inequities in diagnosis and treatment, thereby affecting vulnerable groups. OBJECTIVE: To evaluate differences in asthma and COPD prevalence between adult Aboriginal and non-Aboriginal populations. METHODS: MEDLINE, Embase, specialized databases and the grey literature up to October 2011 were searched to identify epidemiological studies comparing asthma and COPD prevalence between Aboriginal and non-Aboriginal adult populations. Prevalence ORs (PORs) and 95% CIs were calculated in a random-effects meta-analysis. RESULTS: Of 132 studies, eight contained relevant data. Aboriginal populations included Native Americans, Canadian Aboriginals, Australian Aboriginals and New Zealand Maori. Overall, Aboriginals were more likely to report having asthma than non-Aboriginals (POR 1.41 [95% CI 1.23 to 1.60]), particularly among Canadian Aboriginals (POR 1.80 [95% CI 1.68 to 1.93]), Native Americans (POR 1.41 [95% CI 1.13 to 1.76]) and Maori (POR 1.64 [95% CI 1.40 to 1.91]). Australian Aboriginals were less likely to report asthma (POR 0.49 [95% CI 0.28 to 0.86]). Sex differences in asthma prevalence between Aboriginals and their non-Aboriginal counterparts were not identified. One study compared COPD prevalence between Native and non-Native Americans, with similar rates in both groups (POR 1.08 [95% CI 0.81 to 1.44]). CONCLUSIONS: Differences in asthma prevalence between Aboriginal and non-Aboriginal populations exist in a variety of countries. Studies comparing COPD prevalence between Aboriginal and non-Aboriginal populations are scarce. Further investigation is needed to identify and account for factors associated with respiratory health inequalities among Aboriginal peoples.
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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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.041 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".