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Iranian Journal of Public Health، جلد ۵۲، شماره ۱۲، صفحات ۲۶۶۳-۲۶۷۲
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عنوان انگلیسی Developing First Native Regression Equations to Predict of Cardiorespiratory Fitness in Healthy Boys
چکیده انگلیسی مقاله 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.
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نویسندگان مقاله | Majid Jalili
Department of Physical Education and Sport Sciences, Bu-Ali Sina University, Hamedan, Iran


| Farzad Nazem
Department of Physical Education and Sport Sciences, Bu-Ali Sina University, Hamedan, Iran


| Arian Qaragozlou
Department of Computer Science, Faculty of Mathematics and Statistics Sciences, Malayer University, Malayer, Iran
نشانی اینترنتی https://ijph.tums.ac.ir/index.php/ijph/article/view/26711
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