Asthma in First Nations Adults: Prevalence and Associated Factors
Bibliographic record
Abstract
Background: Asthma is a significant cause of morbidity worldwide. Research suggests that Indigenous people experience a higher asthma burden than non-Indigenous Canadians. However, few studies have examined the prevalence of asthma and associated factors in adult First Nations people by phenotype and through a sex/gender lens. The study aimed to determine the prevalence of atopic and non-atopic asthma in First Nations women and men and whether the correlates of asthma varied by atopic status and by sex/gender. Methods: The data source was the First Nations Lung Health Project (FNLHP), a community-based participatory study in two First Nation communities in rural Saskatchewan, Canada. Participants were 648 women and 647 men 18 years of age and older. Data were obtained via interviewer-administered questionnaires and clinical testing. The dependent variable, asthma phenotype, was a categorical variable with three response options (no asthma, atopic asthma, non-atopic asthma) and derived from a combination of self-reported asthma and allergy testing. The independent variables included personal, environmental, and social/economic factors. Multinomial logistic regression was the primary analysis. Results: Atopic and nonatopic asthma prevalence was 11.4% and 5%, respectively. There were no significant sex differences in asthma prevalence; however, the results of the multivariable analysis indicated a significantly higher occurrence of non-atopic asthma in women 40 years of age and older compared to same-age men. Only one variable was associated with atopic asthma: those with depression had 2.9 times higher odds of atopic asthma than those without depression (95%CI: 1.38, 6.20). Statistically significantly associated with an elevated odds of non-atopic asthma were home dampness (OR=1.83, 95%CI: 1.08-3.11), ever alcohol use (OR=2.21, 95%CI: 1.09-4.48) and the presence of a co-morbidity (OR=1.77, 95% CI: 1.17, 2.68). Financial strain was related to an increased odds of nonatopic asthma in women and decreased odds in men. Conclusion: The results from this study suggest the possibility of intriguing differences in the correlates of asthma by phenotype and sex. Future research incorporating a longitudinal design and enhanced measurement is required to advance understanding of the complex interrelationships between sex, asthma phenotype, and various risk factors in First Nations adults.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".