Individual-level socioeconomic status is associated with worse asthma morbidity in patients with asthma
Bibliographic record
Abstract
BACKGROUND: Low socioeconomic status (SES) has been linked to higher morbidity in patients with chronic diseases, but may be particularly relevant to asthma, as asthmatics of lower SES may have higher exposures to indoor (e.g., cockroaches, tobacco smoke) and outdoor (e.g., urban pollution) allergens, thus increasing risk for exacerbations. METHODS: This study assessed associations between adult SES (measured according to educational level) and asthma morbidity, including asthma control; asthma-related emergency health service use; asthma self-efficacy, and asthma-related quality of life, in a Canadian cohort of 781 adult asthmatics. All patients underwent a sociodemographic and medical history interview and pulmonary function testing on the day of their asthma clinic visit, and completed a battery of questionnaires (Asthma Control Questionnaire, Asthma Quality of Life Questionnaire, and Asthma Self-Efficacy Scale). General Linear Models assessed associations between SES and each morbidity measure. RESULTS: Lower SES was associated with worse asthma control (F = 11.63, p < .001), greater emergency health service use (F = 5.09, p = .024), and worse asthma self-efficacy (F = 12.04, p < .01), independent of covariates. Logistic regression analyses revealed that patients with <12 years of education were 55% more likely to report an asthma-related emergency health service visit in the last year (OR = 1.55, 95%CI = 1.05-2.27). Lower SES was not related to worse asthma-related quality of life. CONCLUSIONS: Results suggest that lower SES (measured according to education level), is associated with several indices of worse asthma morbidity, particularly worse asthma control, in adult asthmatics independent of disease severity. Results are consistent with previous studies linking lower SES to worse asthma in children, and add asthma to the list of chronic diseases affected by individual-level SES.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".