RESUMO
Background: Identifying at-risk children with optimal specificity and sensitivity to allow for the appropriate intervention strategies to be implemented is crucial to improving the health and well-being of children. We determined relationships of body mass indexes for age and sex percentile (BMI%) classifications to actual body composition using validated and convenient methodologies and compared fat and non-fat mass estimates to normative cut-off reference values to determine guideline reliability. We hypothesized that we would achieve an improved ability to identify at-risk children using simple, non-invasive body composition and index measures. Methods: Cross-sectional study of a volunteer convenience sample of 1,064 (537 boys) young children comparing Body Fat Percentage (BF%), Fat Mass Index (FMI), Fat-Free Mass Index (FFMI), determined via rapid bioimpedance methods vs. BMI% in children. Comparisons determined among weight classifications and boys vs. girls. Results: Amongst all subjects BMI% was generally correlated to body composition measures and indexes but nearly one quarter of children in the low-risk classifications (healthy weight or overweight BMI%) had higher BF% and/or lower FFMI than recommended standards. Substantial evidence of higher than expected fatness and or sarcopenia was found relative to risk status. Inaccuracies were more common in girls than boys and girls were found to have consistently higher BF% at any BMI%. Conclusions: The population studied raises concerns regarding actual risks for children of healthy or overweight categorized BMI% since many had higher than expected BF% and potential sarcopenia. When body composition and FMI and FFMI are used in conjunction with BMI% improved sensitivity, and accuracy of identifying children who may benefit from appropriate interventions results. These additional measures could help guide clinical decision making in settings of disease-risks stratifications and interventions.
RESUMO
PURPOSE: The purpose of this study was to examine differences in heart rate recovery (HRRec) and oxygen consumption recovery (VO2 recovery) between young healthy-weight children and children with obesity following a maximal volitional graded exercise test (GXTmax). METHOD: Twenty healthy-weight children and 13 children with obesity completed body composition testing and performed a GXTmax. Immediately after the GXTmax, HRRec and VO2 recovery were measured each minute for 5 consecutive minutes. RESULTS: There were no statistically significant group differences in HRRec for the 5 min following maximal exercise, Wilks's Lambda = .885, F(4, 28) = 0.911, p = .471, between the healthy-weight children and children with obesity despite statistically significant differences in body fat percentage (BF%; healthy-weight children, 18.5 ± 6.1%; children with obesity, 41.1 ± 6.9%, p < .001) and aerobic capacity relative to body mass (VO2 peak; healthy-weight children, 46.8 ± 8.2 mL/kg/min; children with obesity, 31.9 ± 4.7 mL/kg/min, p < .001). There were statistically significant differences in VO2 recovery for the 5 min following exercise, Wilks's Lambda = .676, F(4, 26) = 3.117, p = .032. There were no statistically significant correlations between HRRec and body mass index (BMI), BF%, VO2peak, or physical activity. CONCLUSIONS: In a healthy pediatric population, obesity alone does not seem to significantly impact HRRec, and because HRRec was not related to obesity status, BMI, or BF%, it should not be used as the sole indicator of aerobic capacity or health status in children. Using more than one recovery variable (i.e., HRRec and VO2 recovery) may provide greater insight into cardiorespiratory fitness in this population.
