Impact of the COVID-19 Pandemic on the Physical Activity Profile and Glycemic Control Among Qatari Adults With Type 1 Diabetes: Effect of Vaccination Status
Bibliographic record
Abstract
Objective To investigate the impact of COVID-19, as an influent barrier on physical activity (PA) patterns and glycemic control in Qatari adults with type 1 diabetes (T1D). As the COVID-19 vaccine may have a potential impact on an individual's lifestyle, we also considered this parameter. Methods Physical activity level, the exercise barriers (BAPAD1), anthropometric characteristics, the method of insulin administration, and the last glycated hemoglobin in % were completed by 102 Qatari adults with T1D. Moreover, all patients were asked whether they had “been vaccinated” or had a “fear of being infected by COVID-19”. Results For the unvaccinated group, weight, BMI and HbA1c (%) were significantly higher than those of vaccinated group (p < 0.01) and engaged in less moderate-to-vigorous PA (MVPA) (p < 0.01) per week and had less time in vigorous PA (VPA) (p < 0.01). A significant association between VPA levels and BMI (β = −0.36, p = 0.02) and HbA1C (%) (β = −0.22; p = 0.03) was reported, and “being vaccinated” was significantly associated with MVPA (β = 0.15; p = 0.021) and VPA (β = 0.28; p = 0.032). A higher “Fear of being infected by COVID-19” score was negatively correlated with reduced PA profiles (R2 = −0.71 for MVPA; R2 = −0.69 for VPA, p < 0.01, respectively). Conclusion Practicing VPA during the COVID-19 pandemic confer many health benefits for Qatari individual with T1D. As the “Fear of being affected by COVID-19” appeared as a potential barrier to PA practices this latter e.g. PA, could likely not be achieved without the participants being vaccinated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".