Respiratory Health and Housing for University Undergraduate Students
Bibliographic record
Abstract
Background: Diverse factors affect the overall health of undergraduate students.These factors pertain to multiple physical and social environmental exposures, individual behaviours, and genetic predispositions.Research generally recognizes that the most common illnesses experienced by this population are respiratory-related.Within the home, exposures may include indoor air pollutants including environmental tobacco smoke and other ubiquitous chemicals, mould from water damage, and allergens.Although individuals may engage in behaviours to reduce these exposures, these exposures persist and can negatively impact respiratory health.Objectives: To assess the prevalence of wheezing and whistling symptoms, dry cough, and difficulties breathing, in relation to environmental exposures from housing accommodations among the undergraduate university population; and to explore predictors on these health outcomes, as well as the role of three housing types (on-campus, off campus, with family). Methods:We developed an online health questionnaire to collect data related to the sociodemographic and respiratory health of the study population.Spirometry was also conducted to collect lung function (FVC, FEV1, PEF, and FEV1%).Results: A total sample of 213 participants completed the questionnaire, of which 180 also underwent spirometry testing.Overall, 40% of university undergraduate students reported being sick within the last 30 days with 36% reporting that their sickness was respiratory-related.Type of housing accommodation did not appear to affect wheezing and whistling symptoms or difficulties breathing, however participants who indicated living in a housing accommodation older than 11 years were 3.28 times more likely to experience dry cough at night than those living in a housing accommodation 1-10 years old.Based on spirometry, no participants had restrictive or obstructive lung disease.Conclusions: This study suggests there are no significant differences in respiratory health based on type of housing accommodation.However, this study suggests the age of the housing accommodation is a predictor of dry cough.Furthermore, the prevalence of wheezing/whistling symptoms, dry cough, and difficulties breathing does not appear to be correlated with the type of housing accommodation resided in.This implies that the type of housing accommodation does not have an impact on respiratory health symptoms for this population.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".