Protective Effect of Daily Physical Activity Against COVID-19 in a Young Adult Population on Reunion Island
Bibliographic record
Abstract
The global fight against pandemics is a major public health issue. Epidemiological studies showed a reduced risk of the coronavirus disease 2019 (COVID-19) severity with the practice of regular physical activity (PA) in clinical populations. Here, we investigated the effect of PA against COVID-19 in a young general population. Methods: Two hundred ninety volunteers over 18 years old from Reunion Island responded to an online survey concerning sociodemographic, lifestyle and clinical information. Daily PA was studied using the International Physical Activity Questionnaire short version (IPAQ) and classified by overall score and intensities of PA. Results: Among 290 responders [179 women, median age = 27.5 years (interquartile range = 21.3 years)], 141 (48.6%) reported COVID-19 infection. Multivariate logistic analysis adjusted for age, sex, body mass index, chronic disease and alcohol consumption showed that the number of days per week of regular intense PA was independently associated with a low risk of COVID-19 infection [odds ratio (OR) 0.86; 95% confidence interval (CI) 0.24 to 0.99; p = 0.030], while regular moderate PA was not [OR 1.10; 95%CI 0.97 to 1.23; p = 0.137]. Conclusions: In a population of young adults, regular intense PA could offer a protective effect against COVID-19. Additional research is required to confirm this association in various viral infections and elucidate the fundamental mechanisms involved.
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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 | 0.001 |
| 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) | 0.002 | 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".