RESUMEN
Background: Cardio-respiratory fitness (CRF) is a strong predictor of overall health and is considered a key physiological measure in health care settings. Maximal oxygen uptake (VO2max) is considered the gold standard for measuring CRF. Non-exercise VO2max regression equations provide a safe, simple and relatively accurate means of measuring CRF in the general population. This study aimed to develop first native regression equations to predict of CRF without exercise test in Iranian healthy boys. Methods: Laboratory gold standard CRF and anthropometric variables were measured in 597 healthy boys (8-17 yr) in Hmadan City, Iran in 2019. Multiple regression analysis was used to generate CRF regression equations. Cross validation of the CRF regression equations was assessed using PRESS statistics, Pearson correlation, Bland-Althman plot and paired t-test. Results: CRF regression equations based on age, body mass index, body fat and resting heart rate were developed (R2=0.602 - 0.639, SEE = 3.42 - 3.73 ml/kg/min). PRESS statistics show that, shrinkage of the R2 (0.04 - 0.06) and the increment of SEE (0.18 - 0.25 ml/kg/min) is minor. There was strong correlation (R =0.847-0.883, P<0.001) and no significant difference (min diff= 0.09-0.18 ml/kg/min, P>0.05) between measured and predicted CRF. The Bland-Altman plot illustrates the strong agreement between the two values. Conclusion: We introduced simple and satisfactorily accurate CRF regression equations based in healthy boys. Prediction of CRF of the boys by regression equations would provide a simple tool for assessing cardiorespiratory fitness in large studies including Iranian boys.
RESUMEN
OBJECTIVE: To develop an equation to predict maximal oxygen uptake (VO2max) based on the 6-minute walk test (6MWT) and body composition in healthy boys. STUDY DESIGN: Direct VO2max, 6-minute walk distance, and anthropometric characteristics were measured in 349 healthy boys (12.49 ± 2.72 years). Multiple regression analysis was used to generate VO2max prediction equations. Cross-validation of the VO2max prediction equations was assessed with predicted residual sum of squares statistics. Pearson correlation was used to assess the correlation between measured and predicted VO2max. RESULTS: Objectively measured VO2max had a significant correlation with demographic and 6MWT characteristics (R = 0.11-0.723, P < .01). Multiple regression analysis revealed the following VO2max prediction equation: VO2max (mL/kg/min) = 12.701 + (0.06 × 6-minute walk distance m) - (0.732 × body mass indexkg/m2) (R2 = 0.79, standard error of the estimate [SEE] = 2.91 mL/kg/min, %SEE = 6.9%). There was strong correlation between measured and predicted VO2max (r = 0.875, P < .001). Cross-validation revealed minimal shrinkage (R2p = 0.78 and predicted residual sum of squares SEE = 2.99 mL/kg/min). CONCLUSIONS: This study provides a relatively accurate and convenient VO2max prediction equation based on the 6MWT and body mass index in healthy boys. This model can be used for evaluation of cardiorespiratory fitness of boys in different settings.