Association Between Physical Activity And Olfaction Function - The Importance Of Frequency And Moderate Intensity
Bibliographic record
Abstract
PURPOSE: Olfactory function can have a significant impact on one’s quality of life, where a decrease in the sense of smell can both influence physical and mental health. Recently, the practice of physical activity (PA) has been associated with decrease in olfactory dysfunction throughout life and could even be used to improve olfactory function. This study aimed to determine the association between duration, frequency, and intensity PA parameters and olfactory function in adults. METHODS: This study included 3,527 participants from the National Health and Nutrition Examination Survey (NHANES) 2013-2014 for which their duration, frequency, and intensity of PA performed on a weekly basis were assessed. Also, their sense of smell was assessed through a test which monitored chocolate, strawberry, grape, onion, smoke, natural gas, leather, and soap smells. The association between PA parameters and olfaction was assessed using correlations and binary logistic regressions on SPSSTM. P-value ≤0.05 was considered statistically significant. RESULTS: Total smell score showed small and positive significant correlations with the duration, frequency, and volume of moderate PA (coefficients of correlation ranging between 0.05 and 0.08; all p≤ 0.05) and frequency of vigorous PA (coefficient of correlation of 0.05; p<0.05). For moderate PA, the duration, frequency, and volume were significantly and positively associated with the chance of correctly detecting the smell of grapes while the frequency was significantly and positively associated with the capacity to identify smoke and leather odors (odds ratios ranging from 1.01 to 1.07; p<0.05). For vigorous PA, the frequency PA was positively associated with the detection of grape smell (odds ratio of 1.05; p<0.05). CONCLUSIONS: Adopting an active lifestyle could increase the odds of accurately identify smells by up to 7.4%. The duration, frequency, and volume of moderate PA were all associated with higher scores in olfactory function while high intensity PA had a more limited impact. Interestingly, frequency of PA appears more important than duration and volume for the preservation of smell integrity. A-C. G holds a doctoral scholarship and FDM a research scholar from the Fonds de recherche du Québec – Santé. M-E. M. holds a Canada Research Chair (Tier 2) on Physical activity and juvenile obesity. The funders had no role in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".