Reference Standards of Cardiorespiratory Fitness Measured With the Cardiopulmonary Exercise Test Using the Treadmill in Chinese Adults Younger Than 60 Years

Author:

Huang Jia,Yin Lianhua,Li Xia,Xie Qiurong,He Youze,Wu Lijuan,Ni Xuling,Liu Zhizhen,Tao Liyuan,Tao Jing,Chen LidianORCID

Abstract

Purpose: Cardiorespiratory fitness (CRF) is a strong predictor of cardiorespiratory diseases and varies by race. The purpose of this study was to provide CRF reference standards and a prediction equation for peak oxygen uptake (V˙O2peak) from treadmill-based cardiopulmonary exercise testing (CPX) in Chinese individuals. Methods: Healthy participants (n = 4199) who completed a CPX using a treadmill were studied. The percentiles of V˙O2peak were determined for four age groups (decades). A regression prediction model was developed from the derivation cohort (n = 3361), validated in the independent validation cohort (n = 838), and compared with the widely used Wasserman equation and the Fitness Registry and the Importance of Exercise National Database (FRIEND) equation. Results: The mean V˙O2peak values of four age groups (20-29, 30-39, 40-49, and 50-59 yr) were 42.6, 41.2, 38.7, and 35.9 mL/kg/min, respectively, for men, and 37.1, 34.7, 32.0, and 30.3 mL/kg/min, respectively, for women. The 50th percentiles of relative V˙O2peak decreased with age for both sexes. The prediction equation was: Absolute V˙O2peak (mL/min) = 236.68 – (504.64 × sex [male = 0; female = 1]) + (21.23× weight [kg]) – (14.31 × age [yr]) + (9.46 × height [cm]) (standard error of the estimate = 379.59 mL/min, R 2 = 0.66, P < .001). Percentage predicted V˙O2peak for the validation sample was 100.2%. The novel equation performed better than the other two equations. Conclusion: This study reports the first CRF reference standards and prediction equation generated from treadmill CPX in China. These reference standards provide a framework for interpreting the CRF of the Chinese population and could be useful information for a global CRF database.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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