The association between obesity and self‐reported sinus infection in non‐smoking adults: a cross‐sectional study
Bibliographic record
Abstract
The aim of this article was to examine the associations between having had a sinus infection (SI) and BMI and physical activity (PA), diet quality, stress and/or sleep. A total of 2915 adults from the National Health and Nutrition Examination Survey 2005-2006 were examined. Logistic regression analysis was used to examine the association between having had an SI with BMI and PA, diet quality, stress or sleep. As these factors are known to influence one another, a fully adjusted model with PA, diet quality, stress and sleep was also constructed to examine their independent associations with having had an SI. Overall, 15.5 ± 1.2% of the population report having had an SI in the past year. In all models, individuals with obesity were approximately twice as likely to have had an SI compared to those of normal weight (P < 0.05). While PA and diet quality were not significantly associated with having had an SI (P > 0.05), individuals with stress and sleep troubles were also twice as likely to have had an SI (P < 0.05) independent of BMI. In the fully adjusted model, only the associations for BMI and sleep troubles remained significant (P < 0.05). Results from this study suggest that obesity and sleep troubles, but not PA, quality of diet and stress, are associated with having had an SI. As interactions exist between obesity, immune system factors and exposure to infectious disease(s), more research is necessary to understand the directionality of these relationships.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".