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Background <p>Physical activity patterns have reverted to pre-pandemic norms as social distancing measures have improved. However, the understanding of the impact of the COVID-19 pandemic on adult cardiorespiratory fitness (CRF) remains limited. Our questions were as follows: Has the COVID-19 pandemic continued to affect adults’ CRF even after 2 years? Is a longitudinal study-based equation more suitable than a cross-sectional analysis for estimating the pandemic’s impact on CRF? We aimed to develop non-exercise cross-sectional and longitudinal equations for predicting treadmill maximal oxygen uptake (<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\:\dot{V}\)</EquationSource> </InlineEquation>O<sub>2max</sub>) that incorporate cardiovascular risk factors (CVRFs). We then compared CRF changes during the pandemic using these approaches, providing crucial insights into the long-term effects of the pandemic on cardiorespiratory fitness.</p> Methods <p>Data from 1,295 Epidemiology and Human Movement Study participants were analyzed, with 498 who underwent at least two cardiopulmonary exercise tests over a median of 2 years. Linear multivariate hierarchical and mixed-effects models were used to develop the equations. The best models were applied to estimate CRF changes during the pandemic in 405 adults who completed a survey.</p> Results <p>Age, weight, height, sex, hypertension, diabetes, dyslipidemia, obesity, insufficient physical activity, smoking status, and beta-blocker usage were key determinants of <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\:\dot{V}\)</EquationSource> </InlineEquation>O<sub>2max</sub>. The predictors explained 72% and 56% of the <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\:\dot{V}\)</EquationSource> </InlineEquation>O<sub>2max</sub> total variability in the best cross-sectional and longitudinal equations, respectively. <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\:\dot{V}\)</EquationSource> </InlineEquation>O<sub>2max</sub> during the pandemic, obtained from the questionnaire, was significantly lower than pre-pandemic values (<i>P</i> &lt; 0.05) in both models. However, the decrease adjusted for age was more pronounced (<i>P</i> &lt; 0.05) in the cross-sectional model (-0.82 mL kg-1&#xa0;min-1) than in the longitudinal model (-0.63 mLO2 kg-1&#xa0;min-1).</p> Conclusion <p>Our findings demonstrate that demographic and anthropometric factors, CVRFs, and beta-blockers can reasonably estimate <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(\:\dot{V}\)</EquationSource> </InlineEquation>O<sub>2max</sub> in both equation types. Importantly, both approaches effectively captured the pandemic’s detrimental impact on Brazilian adults’ CRF, with the cross-sectional model showing significantly greater changes. This underscores the importance of promoting individual physical exercise during pandemic-related restrictions, given the observed associations with cardiovascular health.</p>

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Adult cardiorespiratory fitness changes during the COVID-19 pandemic estimated by non-exercise \(\:\dot{V}\)O2max equations

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  • 发表日期：

    2026年7月1日

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  • Vinícius Lauria,
  • Maria do Socorro Simões,
  • Marcello Romiti,
  • Rodolfo Arantes,
  • Rosana Poggio,
  • Victor Dourado

摘要

Background

Physical activity patterns have reverted to pre-pandemic norms as social distancing measures have improved. However, the understanding of the impact of the COVID-19 pandemic on adult cardiorespiratory fitness (CRF) remains limited. Our questions were as follows: Has the COVID-19 pandemic continued to affect adults’ CRF even after 2 years? Is a longitudinal study-based equation more suitable than a cross-sectional analysis for estimating the pandemic’s impact on CRF? We aimed to develop non-exercise cross-sectional and longitudinal equations for predicting treadmill maximal oxygen uptake ( \(\:\dot{V}\) O2max) that incorporate cardiovascular risk factors (CVRFs). We then compared CRF changes during the pandemic using these approaches, providing crucial insights into the long-term effects of the pandemic on cardiorespiratory fitness.

Methods

Data from 1,295 Epidemiology and Human Movement Study participants were analyzed, with 498 who underwent at least two cardiopulmonary exercise tests over a median of 2 years. Linear multivariate hierarchical and mixed-effects models were used to develop the equations. The best models were applied to estimate CRF changes during the pandemic in 405 adults who completed a survey.

Results

Age, weight, height, sex, hypertension, diabetes, dyslipidemia, obesity, insufficient physical activity, smoking status, and beta-blocker usage were key determinants of \(\:\dot{V}\) O2max. The predictors explained 72% and 56% of the \(\:\dot{V}\) O2max total variability in the best cross-sectional and longitudinal equations, respectively. \(\:\dot{V}\) O2max during the pandemic, obtained from the questionnaire, was significantly lower than pre-pandemic values (P < 0.05) in both models. However, the decrease adjusted for age was more pronounced (P < 0.05) in the cross-sectional model (-0.82 mL kg-1 min-1) than in the longitudinal model (-0.63 mLO2 kg-1 min-1).

Conclusion

Our findings demonstrate that demographic and anthropometric factors, CVRFs, and beta-blockers can reasonably estimate \(\:\dot{V}\) O2max in both equation types. Importantly, both approaches effectively captured the pandemic’s detrimental impact on Brazilian adults’ CRF, with the cross-sectional model showing significantly greater changes. This underscores the importance of promoting individual physical exercise during pandemic-related restrictions, given the observed associations with cardiovascular health.