Garner, David M.Vanderlei, Franciele Marques [UNESP]Vanderlei, Luiz Carlos Marques [UNESP]2019-10-062019-10-062018-01-01Journal of Human Growth and Development, v. 28, n. 3, p. 298-306, 2018.2175-35980104-1282http://hdl.handle.net/11449/188495Introduction: Heart rate variability (HRV) can be assessed from RR-intervals. These are derived from an electrocardiographic PQRST-signature and can deviate in a chaotic or irregular manner. In the past, techniques from statistical physics have allowed researchers to study such systems. Objective: This study planned to assess the heart rate dynamics in young obese subjects by nonlinear metrics to heart rate variability. Method: 86 subjects were split equally according to status. Heart rate was recorded with the subjects resting in a dorsal (prone) position for 30 minutes. The complexity of the RR-intervals was assessed by five Entropies, Detrended Fluctuation Analysis, Higuchi and Katz's fractal dimensions Following inconclusive tests of normality we calculated the One-Way Analysis of Variance, Kruskal-Wallis, and the Effect Sizes by Cohen's d significances. Results: It was established that Shannon, Renyi and Tsallis Entropies and the Higuchi and Katz's fractal dimensions could significantly discriminate the two groups. The three entropies were higher in obese youths, suggesting less predictable sets of RR intervals (p < 0.0001; d≈1.0). Whilst the Higuchi (p < 0.003; d ≈0.76) and Katz's (p≈0.02; d≈0.57) fractal dimensions were lower in obese youths. Conclusion: As with chaotic globals an increase in response was detected by three measures of entropy in young obese. This is counter to the decreasing response detected by fractal dimensions. Chaotic globals and entropies are more dependable than fractal dimensions when assessing the responses to obesity.298-306engDetrended fluctuation analysisEntropyFractal dimensionsYouth obesityArtigo10.7322/jhgd.152180Acesso restrito2-s2.0-850584330385860525135106995