Developments in asthma incidence and prevalence in Alberta between 1995 and 2015
Bibliographic record
Abstract
BACKGROUND: Asthma is a chronic respiratory disease characterized by reversible bronchoconstriction and airway inflammation. According to Statistics Canada in 2014, 8.1% of Canadians aged 12 and older reported having asthma diagnosed by a health care professional. Therefore, in 2014 there were an estimated 274,661 persons with asthma in Alberta. Most epidemiological studies estimate prevalence and incidence using survey-based data, which has limitations. The Ontario Asthma Surveillance Information System (OASIS) group has developed and validated an algorithm for epidemiologic asthma studies using provincial health databases. In Alberta, there are some studies using provincial databases, but most are restricted to emergency department visits and do not represent the entire asthma population. Using the validated asthma definition for epidemiologic studies, we performed an analysis of the Alberta Health administrative databases to investigate and report province-wide asthma prevalence, incidence and mortality in Alberta from 1995 to 2015. METHODS: Data from administrative databases, provided by Alberta Health, was analyzed to determine age and sex specific prevalence, incidence and mortality of the asthma population. The population cohort was all individuals residing in the province of Alberta, ages 0 to 99 from 1995-2015. Kendall's Tau coefficient test was used to ascertain whether the observed trends were statistically significant. RESULTS: Between 1995 and 2015, the age-standardized incidence of asthma decreased by more than 50% in both males and females. Prevalence, however, increased threefold over the 20 years (for both genders) from 3.9 to 12.3% (Tau = 1.00, p < 0.0001) in females and from 3.5 to 11.6% (Tau = 1.00, p < 0.0001) in males. Thus, in 2015 there were 496,927 people with asthma in Alberta. All-cause mortality in the asthma population decreased over time, in both females (Tau = - 0.71, p < 0.0001) and males (Tau = - 0.69, p = 0.0001). For the last several years, all-cause mortality was higher in those with asthma. There were ~ 7 deaths/1000 in the population with asthma versus ~ 5 deaths/1000 in those without asthma. CONCLUSIONS: The incidence of asthma decreased in both females and males while prevalence continued to increase, although at a slower rate than previously. All-cause mortality in asthma patients was higher than in those without asthma, but both decreased over time.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".