Cardiorespiratory Fitness Associated to Teenagers’ Fat: Vo2max Cutoff Point

Abstract

Objective: To associate the Maximal Oxygen Uptake (VO2max) with body fat percentage (%BF), and to establish the best VO2max cutoff point for predicting risk %BF in teenagers.Methods: This study was carried out with 979 subjects aged 10 to 18.8 years, 556 (56.8%) girls. The 20 m shuttle run protocol determined the VO2max, which was analyzed in quintiles and in a numeric scale. Cutaneous fold equations determined the %BF, later classified as risk to health/obesity when >25 in girls and >20 in boys. Regression method was used - Odds Ratio (OR) and Receiver Operating Characteristics Curve (ROC curve) with α <5%.Results: From the total number of valid cases, 341 (65.6%) girls and 202 (53.2%) boys presented %BF of risk, and a larger proportion of %BF of risk was observed in the 1st quintile of the VO2max for both genders. There was inverse association between VO2max and %BF of risk from the 4th quintile (OR 1.84, 95%CI 1.05-3.24) until the 1st quintile (OR 4.74, 95%CI 2.44-9.19) for girls, and from the 2nd quintile (OR 2.99, 95%CI 1.48-6.00) until the 1st quintile (OR 5.60, 95%CI 2.64-11.87) for boys. As analytic highlights, VO2max Cutoff points for prediction of %BF of risk were ≤40.9 mL/kg-1/min-1 (AUC: 0.65; p<0.001) for girls and ≤44.8 mL/kg-1/min-1 (AUC: 0.66; p<0.001)for boys..Conclusions: VO2max was inversely associated to the %BF, and VO2max cutoff points for prediction of %BF of risk are important results to generate action to fight early obesity.

Health-Related Criterion-Referenced cut-Points for the 20 Meter Shuttle Run Test Among Children and Youth – An Exploration and Meta-Analysis

“…An overview of the characteristics of each study is provided in Table 1. The 13 studies included in the meta-analysis were all published in English between 2006 and 2019 and conducted using a cross-sectional design (Mesa et al, 2006;Boddy et al, 2012;Silva et al, 2012;Buchan et al, 2017;Nevill et al, 2018;Ramírez-Vélez et al, 2018;Silva et al, 2018;Buchan et al, 2019;Prieto-Benavides et al, 2019;Smouter et al, 2019). Together, these included 114,145 youth aged 6-18 years across 18 countries (17 low-income and 1 upper-middle-income countries [The World Bank, 2020] from 3/7 continents).…”

“…The table also shows the health outcome risk factors measured for each study along with the defined health criterion. Out of the 13 studies, six focused on cardiometabolic risk Silva et al, 2012;Buchan et al, 2017;Castro-Pinero et al, 2017;Ramirez-Velez et al, 2018;Buchan et al, 2019), three focused on obesity (Nevill et al, 2018;Silva et al, 2018;Prieto-Benavides et al, 2019), one focused on ideal cardiovascular health , one focused on body fat percentage (Smouter et al, 2019), one focused on ideal blood lipid profile (Mesa et al, 2006), and one focused on both obesity and body fat percentage (Boddy et al, 2012). It is important to note that no studies included the same health outcome risk factors, even if similar health definitions were used (e.g., 6 out of 13 studies defined high metabolic risk as ≥1 SD of a continuous standardized score computed with all CVD risk factors (Moreira et al, 2011;Silva et al, 2012;Buchan et al, 2017;Castro-Pinero et al, 2017;Ramirez-Velez et al, 2018;Buchan et al, 2019)).…”

“…These six studies are plotted in the SROC plots as red triangles (Ramirez-Velez et al, 2018 reports two different age groups and therefore has 2 data points per sex). No other studies had similar definitions of health risk (Mesa et al, 2006;Boddy et al, 2012;Nevill et al, 2018;Silva et al, 2018;Prieto-Benavides et al, 2019;Smouter et al, 2019). Having different criteria for determining health outcome risk is likely one of the reasons contributing to the significant heterogeneity displayed.…”