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Background: Protection against airborne infection is currently, due to the COVID-19-associated restrictions, ubiquitously applied during public transport use, work and leisure time. Increased carbon dioxide re-inhalation and breathing resistance may result thereof and, in turn, may negatively impact metabolism and performance.
Objectives: To deduce the impact of the surgical mask and filtering face piece type 2 (FFP2) or N95 respirator application on gas exchange (pulse-derived oxygen saturation (SpO2), carbon dioxide partial pressure (PCO2), carbon dioxide exhalation (VCO2) and oxygen uptake (VO2)), pulmonary function (respiratory rate and ventilation) and physical performance (heart rate HR, peak power output Wpeak).
Methods: Systematic review with meta-analysis. Literature available in Medline/Pubmed, the Cochrane Library and the Web of Knowledge with the last search on the 6th of May 2021. Eligibility criteria: Randomised controlled parallel group or crossover trials (RCT), full-text availability, comparison of the acute effects of ≥ 1 intervention (surgical mask or FFP2/N95 application) to a control/comparator condition (i.e. no mask wearing). Participants were required to be healthy humans and > 16 years of age without conditions or illnesses influencing pulmonary function or metabolism. Risk of bias was rated using the crossover extension of the Cochrane risk of bias assessment tool II. Standardised mean differences (SMD, Hedges' g) with 95% confidence intervals (CI) were calculated, overall and for subgroups based on mask and exercise type, as pooled effect size estimators in our random-effects meta-analysis.
Results: Of the 1499 records retrieved, 14 RCTs (all crossover trials, high risk of bias) with 25 independent intervention arms (effect sizes per outcome) on 246 participants were included. Masks led to a decrease in SpO2 during vigorous intensity exercise (6 effect sizes; SMD = − 0.40 [95% CI: − 0.70, − 0.09], mostly attributed to FFP2/N95) and to a SpO2-increase during rest (5 effect sizes; SMD = 0.34 [95% CI: 0.04, 0.64]); no general effect of mask wearing on SpO2 occurred (21 effect sizes, SMD = 0.34 [95% CI: 0.04, 0.64]). Wearing a mask led to a general oxygen uptake decrease (5 effect sizes, SMD = − 0.44 [95% CI: − 0.75, − 0.14]), to slower respiratory rates (15 effect sizes, SMD = − 0.25 [95% CI: − 0.44, − 0.06]) and to a decreased ventilation (11 effect sizes, SMD = − 0.43 [95% CI: − 0.74, − 0.12]). Heart rate (25 effect sizes; SMD = 0.05 [95% CI: − 0.09, 0.19]), Wpeak (9 effect sizes; SMD = − 0.12 [95% CI: − 0.39, 0.15]), PCO2 (11 effect sizes; SMD = 0.07 [95% CI: − 0.14, 0.29]) and VCO2 (4 effect sizes, SMD = − 0.30 [95% CI: − 0.71, 0.10]) were not different to the control, either in total or dependent on mask type or physical activity status.
Conclusion: The number of crossover-RCT studies was low and the designs displayed a high risk of bias. The within-mask- and -intensity-homogeneous effects on gas exchange kinetics indicated larger detrimental effects during exhausting physical activities. Pulse-derived oxygen saturation was increased during rest when a mask was applied, whereas wearing a mask during exhausting exercise led to decreased oxygen saturation. Breathing frequency and ventilation adaptations were not related to exercise intensity. FFP2/N95 and, to a lesser extent, surgical mask application negatively impacted the capacity for gas exchange and pulmonary function but not the peak physical performance.
Registration: Prospero registration number: CRD42021244634
The spread of the COVID-19 virus was met by a strict lockdown in many countries around the world, with the closure of all physical activity (PA) facilities and limitations on moving around freely. The aim of the present online survey was to assess the effect of lockdown on physical activity in Italy. Physical activity was assessed using the European Health Interview Survey questionnaire. A total of 1500 datasets were analyzed. Differences between conditions were tested with a chi2-based (χ2) test for categorical variables, and with the Student’s t-test for paired data. A fixed effects binary logistic regression analysis was conducted to identify relevant predictor variables to explain the compliance with World Health Organisation (WHO) recommendations. We found a substantial decline in all physical activity measures. Mean differences in walking and cycling metabolic equivalent of task minutes per week (METmin/week), respectively, were 344.4 (95% confidence interval (95% CI): 306.6–382.2; p < 0.001) and 148.5 (95% CI: 123.6–173.5; p < 0.001). Time spent in leisure time decreased from 160.8 to 112.6 min/week (mean difference 48.2; 95% CI: 40.4–56.0; p < 0.001). Compliance with WHO recommendations decreased from 34.9% to 24.6% (chi2 (1, 3000) = 38.306, p < 0.001, V = 0.11). Logistic regression showed a reduced chance (OR 0.640, 95% CI: 0.484–0.845; p = 0.001) to comply with WHO PA recommendations under lockdown conditions. Measures to promote physical activity should be intensified to limit detrimental health effects.