Obesity and Respiratory Hospitalizations During Influenza Seasons in Ontario, Canada: A Cohort Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Previous studies suggest that obesity may be a risk factor for complications from pandemic influenza A(H1N1) infection. We aimed to examine the association between obesity and respiratory hospitalizations during seasonal influenza epidemics and to determine the extent of this association among individuals without established risk factors for serious complications due to influenza infection. METHODS: We conducted a cohort study over 12 influenza seasons (1996-1997 through 2007-2008) of 82545 respondents to population health surveys in Ontario, Canada. We included individuals aged 18-64 years who had responded to a survey within 5 years prior to the start of an influenza season. We used logistic regression to examine the association between self-reported body mass index (BMI) and hospitalization for selected respiratory diseases (pneumonia and influenza, acute respiratory diseases, and chronic lung diseases), both in the entire cohort and stratified by chronic condition status. RESULTS: Obese class I (BMI, 30-34.9) (odds ratio [OR], 1.45 [95% confidence interval {CI}, 1.03-2.05]) and obese class II or III (BMI, ≥35) individuals (OR, 2.12 [95% CI, 1.45-3.10]) were more likely than normal weight individuals to have a respiratory hospitalization during influenza seasons. Among obese class II or III individuals, the association was present both for those without previously identified risk factors (OR, 5.10 [95% CI, 2.53-10.24]) and for those with 1 risk factor (OR, 2.11 [95% CI, 1.10-4.06]). CONCLUSIONS: Severely obese individuals with and without chronic conditions are at increased risk for respiratory hospitalizations during influenza seasons. They should be considered a priority group for preventive influenza measures, such as vaccination and treatment with antiviral medications.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it