Prevalence and Risk Factors of Respiratory Symptoms in Rural Population
Bibliographic record
Abstract
Research has shown that respiratory symptoms, including chronic cough, chronic phlegm, shortness of breath, and wheeze, are important markers that contribute to hospitalization, lung function decline, and other respiratory illness. This report aims to estimate the prevalence of respiratory symptoms and associated environmental risk factors in farming and nonfarming rural-dwelling people. A baseline mail-out questionnaire to assess respiratory health outcomes as well as individual and contextual determinants in farm and small town cohorts was sent to 11,004 households within four geographical regions of Saskatchewan, Canada, in 2010. Completed questionnaires were received from 4624 households (8261 individuals). Outcome variables examined for this report were chronic cough, chronic phlegm, shortness of breath, and ever wheeze. Clustering effect within households was adjusted using generalized estimating equations. The prevalence of respiratory symptoms was chronic cough, 9.2% (farm vs. nonfarm: 8.1% vs. 10.0%); chronic phlegm, 8.2% (farm vs. nonfarm: 6.7% vs. 9.3%); shortness of breath, 29.1% (farm vs. nonfarm: 25.5% vs. 31.6%); and ever wheeze, 40.6% (farm vs. nonfarm: 38.1% vs. 42.5%). There was a significantly higher prevalence of each respiratory symptomin the nonfarming population compared with the farming population (P < .01). Respiratory symptoms were positively associated with smoking, allergic reaction to inhaled allergens, and other environmental factors for farming and nonfarming populations. The prevalence of respiratory symptoms was higher in the nonfarming rural population compared with the farming rural population. Environmental exposures such as work-related or home environment play an important role in the increased prevalence of respiratory symptoms in farming and nonfarming populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".