Journal of Physical Activity and Health, 2015, 12, 553 -560 http://dx.doi.org/10.1123/jpah.2013-0199 © 2015 Human Kinetics, Inc.
ORIGINAL RESEARCH
Improvements on Cardiovascular Diseases Risk Factors in Obese Adolescents: A Randomized Exercise Intervention Study Humberto José Gomes Silva, Lars Bo Andersen, Mara Cristina Lofrano-Prado, Mauro V.G. Barros, Ismael Fortes Freitas Jr., James Hill, and Wagner Luiz do Prado Background: It is unclear how different exercise intensities affect cardiovascular disease (CVD) risk factors in obese adolescents. The aim of this study was to compare the effects of high-intensity (HIT) vs. low-intensity (LIT) aerobic training on CVD risk factors in obese adolescents. Methods: Forty-three obese adolescents (age: 15.7 ± 1.3 years, BMI: 34.3 ± 4.1kg/m2) participated this study either HIT (corresponding to ventilatory threshold I; N = 20) or LIT (20% below ventilatory threshold I; N = 23) for 12 weeks. All sessions were isocaloric (350 kcal). All participants received the same nutritional, psychological, and clinical counseling. Subjects were assessed in fatness, fitness, lipid profile, and glucose at baseline and after 12 weeks. The CVD risk factors assessed were waist circumference (WC), total cholesterol (TC), high-density lipoprotein (HDL), glucose, and fitness, which were single and clustered analyzed (z scores sum). Results: Body mass, Body Mass Index, fatness, and WC were improved (P < .001) in both groups. The sum of z scores (WC + TC + glucose-fitness-HDL) improved in both HIT (12 weeks = –2.16 SD; Cohen’s d = .45) and LIT (12 weeks = –2.13 SD; Cohen’s d = .60) without groups differences. Changes in fitness were associated with changes in WC (r = –.48; P = .003). Conclusion: HIT does not promote any additional improvements in CVD risk factors than LIT in obese adolescents. Keywords: physical activity, health, obesity, multidisciplinary therapy
The presence of cardiovascular disease (CVD) risk factors, which in the past were usually observed later in life, have become common in children and adolescents.1 Cut-off points of single CVD risk factors are not well established in adolescents, so Andersen et al (2011)2 suggested using a continuous composite risk score to assess CVD risk in this group. Clustering of risk factors for CVD, including obesity, tracks from childhood to adulthood.3 Because treatment of obesity is more effective in children than adults,4 early identification of CVD risk factors is highly desirable. This can allow for early implementation of multidisciplinary therapy, composed of nutritional, psychological, clinical, and physical activity interventions to achieve the health goals in obese individuals. Physical exercise is considered a corner stone in obesity therapy, because it improves metabolic risk factors associated with obesity by decreasing fat mass and improving cardiorespiratory fitness.5 Noteworthy is the fact that both adiposity and fitness are strongly associated with clustering of CVD risk factors in children and adolescents.6 Previously, studies in adolescents have demonstrated that aerobic training can improve lipid profiles,7 glycemic control,8 body Silva, Lofrano-Prado, Barros, and Prado ([email protected]) are with the Post Graduate Program of Physical Education, University of Pernambuco, Recife, Brazil. Andersen is with the School of Research in Childhood Health, University of Southern Denmark, Odense, Denmark. Freitas is with the Dept of Physical Education, Universidade Estadual Paulista, São Paulo, Brazil. Hill is with the Center for Human Nutrition, University of Colorado, Denver, CO.
composition,9 and physical fitness.10 Noteworthy is that, in adults, the positive effects of aerobic training are intensity-dependent; indeed, high-intensity training (HIT) is associated with greater improvements in physical fitness,11 while low-intensity training (LIT) enhances fatty acids oxidation.12 Exercise at high intensity also seems to induce larger cardiovascular benefits.13 However, the safety and effectiveness of this type of training has not been evaluated in obese adolescents. The aim of this study was to compare the effects of high- versus low-intensity aerobic training on CVD risk factors in obese adolescents.
Methods Participants Obese adolescents were recruited from the urban area of Recife, in Pernambuco (northeast of Brazil) between January and February 2011 through local television announcement, newspapers, and radio. The inclusion criteria were age ranging from 13 to 18 years, pubertal stage 3 or 4,14 obesity,15 absence of hypertension and/or other metabolic diseases, no restriction to engaging in a regular physical exercise program, intrinsic motivation and agreement to participate in a weight loss multidisciplinary intervention. The exclusion criteria were pregnancy and less than 75% compliance in all nutritional, psychological, clinical, and/or exercise sessions. This study was carried out in accordance with the principles of the Declaration of Helsinki and was formally approved by the ethical committee of the University of Pernambuco (#154/09). Informed consent was obtained from all participants and/or their legal guardians.
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Study Design
Nutritional Counseling
A total of 229 adolescents volunteered for the study. At baseline, they visited the laboratory twice. During the first visit pubertal stage, height and weight were measured and participants underwent a confidential individual semistructured interview containing 8 questions aimed to assess personal motives for seeking weight loss treatment and barriers to losing weight was conducted by a psychologist in a quiet room (intrinsic motivation). Among these, 186 individuals did not meet the inclusion criteria. During the second visit, the participants performed a rest and exercise electrocardiogram and underwent a medical screening. At the end, 43 obese adolescents (14 boys and 29 girls) were included in the study. Following baseline testing, participants were randomized (coin-flip method) into either HIT (n = 20) or LIT (n = 23) groups for the 12-week intervention (Figure 1). All participants also received the same multidisciplinary nutritional, psychological, and clinical counseling, as previously described.16
Nutritional counseling included weekly small group (~9 participants) sessions of 1 hour and they were led by a trained nutritionist. Sessions addressed healthy eating behavior, the food pyramid, weight loss diets, diet versus reduced-calorie products, and recording energy intake and provided general nutrition information. Participants were not given specific diet prescriptions but were encouraged to reduce overall calorie intake of food and follow a balanced diet.
Clinical Counseling Medical follow-up was performed once/month by an endocrinologist. This included a physical examination to monitor clinical parameters and the overall compliance with the study. No medicine was prescribed for weight loss in the study participants.
Psychological Counseling The study participants met with a psychologist weekly for 1-hour sessions in small groups of about 9. During these sessions themes related to body image, eating disorders (symptoms and consequences), relationship between food and feelings, family and social problems, mood, anxiety, and depression were discussed along with psychological motivation for compliance with the study protocol. The sessions were exactly the same for all groups, and always conducted by same psychologist.
Aerobic Exercise Training Participants in both HIT and LIT groups underwent personalized aerobic training on a treadmill, 3 times a week, under the supervision of an exercise instructor. The participants in the HIT group exercised at an intensity corresponding to the ventilatory threshold I, and those in the LIT group exercised at a speed 20% below the ventilatory threshold I. For both training groups, exercise sessions were isocaloric, with energy expenditure set at 350 Kcal (1050 Kcal/ week), estimated by indirect calorimetry. Once each participant had a set of specific and individualized work load, the duration of exercise sessions differed between participants to ensure that the preestablished energy expenditure was achieved. Based on the metabolic equivalent of task (MET)—and considering that for each liter of O2 consumed, the energy expenditure is 4.96 Kcal—exercise session duration was determined using the equation
Exercise session time (min) = 350 Kcal ÷ (VO2 on target intensity × 1 MET)
Measurements All volunteers were subjected to the same assessment protocol, before and after 12 weeks of a multidisciplinary therapy. The evaluations were performed in the same period of the day to avoid any circadian influence, and by the same evaluator.
Figure 1 — Experimental design. JPAH Vol. 12, No. 4, 2015
Exercise and CVD Risk in Obese Adolescents 555
Pubertal Maturation
Statistical Analysis
Each participant was given drawings of the 5 stages of breast, genital, and pubic hair development. In an isolated room, the adolescents were asked to look at the drawings, read the descriptions, think about how they looked in comparison with the drawings, and pick the 1 that most closely resembled them.17 For boys, the genitalia and pubic hair on each photograph were classified into 5 stages of development; for girls, the breasts and pubic hair on each photograph were classified into 5 stages of development.
Considering alpha = 0.05 and power = 0.80, the sample size in this study was sufficiently large to detect a significant differences greater than 0.67 in composite z score. Statistical analysis was performed using STATISTICA Version 8. Normality was verified by Shapiro Wilk test, and data were expressed as mean ± standard deviation and relative frequencies. Comparisons between time (baseline and 12 weeks) and groups (HIT and LIT) were made using ANOVA 2-way and Fischer’s post hoc test. Differences in percentage variation between groups were assessed by a student T test for independent groups. The withingroup effect size was calculated and is expressed as correlation when higher than moderate (Cohen’s d). The statistical power of the sample was determined a posteriori (power = 0.995). The significance level was set at P < .05.
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Anthropometry and Body Composition Participants were weighed wearing light clothing and no shoes on a Filizola scale (Model 160/300, Brazil) to the nearest 0.1 kg. Height was measured to nearest 0.5 cm by using a wall-mounted stadiometer (Filizola, Model 160/300, Brazil). Body Mass Index (BMI) was calculated dividing body weight (kg) by squared height (m2). Relative body fat (%) was estimated using a 2-site skinfold measurement (triceps and subscapular) by the equation of Slaughter et al,18 specific for each gender.
Serum Assays Blood samples were collected in the outpatient clinic at approximately 8:00 AM, after an overnight fast (12 hours). Spectrophotometry (Cobas Integra 400 Plus) was used to determine serum triglycerides (TG; coefficient of variation [CV] intra = 1.6% and inter = 1.9%), total cholesterol (TC; CVintra = 0.51%; CVinter = 1.9%), high-density lipoprotein (HDL; CVintra = 0.75%; CVinter = 2.1%) and glucose (CVintra = 0.41%; CVinter = 1.09%); using commercial kits (Roche), LDL was calculated indirectly using the Friedewald formula [LDL = TC – HDL – (TG / 5)].
Cardiorespiratory Fitness Peak oxygen uptake (VO2peak) was used to determine cardiovascular fitness. VO2 was measured directly in an open circuit respiratory metabolic system (Quark PFT, Cosmed, Italy), during a continuous incremental test on a treadmill (Cosmed T200, Italy). The initial load was set at 4 km/h (warm-up 3 minutes) and increased 1 Km/h each minute; inclination was kept constant at 1%.19 The termination criteria were volitional fatigue, Borg Scale higher than 18, and gas exchange ratio higher than 1.15. The greatest VO2 obtained before test interruption was considered as VO2peak. Before each test, the equipment (White Martins) was calibrated for gas composition (O2 = 12.2% and CO2 = 4.8%) and volume following all manufacturers’ recommendations.
Composite CVD Risk Factor Score Variables included in the composite CVD risk factor score were z scores of waist circumference (WC), TC, glucose, and inverse of cardiorespiratory fitness and HDL. WC was measured at the midpoint between the lower ribs and the iliac crest.20 Change in risk factor profile was also evaluated as the sum of changes in individual risk factors. The following criteria were adopted for categorizing the changes in individual risk factors: 1% change in TC,21 1.0 cm in WC,22 1.0 mg/dL in HDL,231 MET (3.5 mL×kg–1×min–1) in VO2peak,24 and fasting plasma glucose below 100 mg/dL.25 Thereafter, each individual variable was attributed +1 point for improvement, –1 point for worsening, or 0 points for maintenance.
Results Anthropometric Profile, Fitness, and Body Composition From a total of 43 patients (14 boys and 29 girls) included in the sample, 85% from HIT (6 boys and 11 girls) and 83% from LIT (7 boys and 12 girls) adhered to the 12 weeks of multidisciplinary therapy. The anthropometric characteristics of participants at baseline and after 12 weeks of intervention are presented in Table 1. Both groups reduced body weight, BMI, body fat (%) and WC; no differences were observed between groups at baseline and after 12 weeks.
Lipid and Glucose Profile After 12 weeks of intervention, LDL cholesterol was reduced only for adolescents enrolled in the LIT group, without changes for other blood lipids or glucose (Table 2). No differences were observed between training intensities.
Cardiorespiratory Fitness VO2peak improved from 25.6 ± 4.5 to 30.1 ± 4.5 mL×kg–1×min–1 (17.6%; P < .001) in the HIT group and from 26.5 ± 5.2 to 30.0 ± 5.6 mL×kg–1×min–1 (13.2%; P < .001) in the LIT group, with no difference between groups. In addition, results indicated a negative correlation between the change in WC (Δ%) andVO2peak (Δ%; r = –0.48; P = .003; both groups included in the analysis; Figure 2).
Cluster of CVD Risk Factors The sum of the improvements (+1), worsening (–1), and maintenance (0) of individual changes in CVD risk factors demonstrated that none of the participants in the HIT group had worsening of risk factors, 12% of the adolescents had improvement in at least 1 risk factor, 36% improved 2 or 3 factors (36%), and 46% improved 4 or 5 factors, whereas only 6% had no changes in risk factors (Figure 3. In the LIT group, 21% had improvement in at least 1 risk factor, 5% in 2 risk factors, 21% in 3 risk factors, 11% in 4 risk factors, and 21% in 5 factors, while 5% worsened in at least 1 risk factors and 16% remained stable (Figure 3). Positive changes were seen in the sum of z scores (WC + TC + glucose-fitness-HDL) in HIT (baseline = 0.00; 12 weeks = –2.16; Cohen’s d = .45) and LIT (baseline = 0.00; 12 weeks = –2.13; Cohen’s d = .60; Figure 3).
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15.7 ± 1.3 1.62 ± 0.05 90.3 ± 11.3 34.3 ± 4.1 51.0 ± 5.9 96.7 ± 8.2
16.0 ± 1.3a 1.62 ± 0.05 87.7 ± 11.7a 33.4 ± 4.0a 44.8 ± 9.9a 92.8 ± 8.0a
12 weeks 2.29 –0.14 –2.90 –2.62 –12.20 –4.01
% 15.29 ± 1.63 1.63 ± 0.08 92.1 ± 11.4 34.6 ± 3.7 53.7 ± 9.4 94.6 ± 6.7
Baseline
LIT 15.6 ± 1.6a 1.63 ± 0.08 90.4 ± 12.4a 33.7 ± 3.9a 41.6 ± 6.4a 92.5 ± 8.4a
12 weeks 2.22 0.25 –1.96 –2.45 –20.24 –2.32
%
0.381 0.611 0.570 0.780 0.787 0.638
Group effect
0.001 0.671 0.001 0.001 0.001 0.001
Time effect
0.197 0.140 0.317 0.782 0.074 0.209
Interaction effect
Note. Data are expressed as mean ± SD. a Baseline vs 12 weeks. Abbreviations: HIT, high-intensity training; LIT, low-intensity training; ICC, intraclass correlation coefficient; BM, body mass; BMI, Body Mass Index; WC, waist circumference.
Age (yr) Height (m) BM (kg) BMI (kg/m2) Body fat (%) WC (cm)
Baseline
HIT
Table 1 Effects of Different Aerobic Training Intensities on Anthropometry and Body Composition in Obese Adolescents
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— 0.923 0.930 0.718 0.649 0.467
ICC
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169.8 ± 27.8 112.7 ± 24.7 34.5 ± 10.8 23.5 ± 15.3 117.4 ± 77.0 83.7 ± 9.6
164.6 ± 28.9 104.8 ± 20.2 36.8 ± 12.0 20.3 ± 7.3 116.8 ± 72.1 82.4 ± 10.0
12 weeks –3.44 –5.33 8.06 –1.43 3.22 –0.41
% 162.3 ± 30.2 106.3 ± 24.3 39.4 ± 13.5 23.0 ± 18.2 116.1 ± 90.7 86.5 ± 18.1
Baseline 159.1 ± 29.3 93.6 ± 27.6a 38.9 ± 11.0 21.8 ± 10.7 109.2 ± 53.7 78.9 ± 7.7
12 weeks
LIT –1.35 –10.36 1.84 6.23 4.52 –5.50
%
0.486 0.295 0.376 0.933 0.836 0.943
Group effect
0.144 0.024 0.310 0.319 0.575 0.166
Time effect
0.665 0.584 0.266 0.645 0.611 0.219
Interaction effect
ICC 0.546 0.649 0.274 0.632 0.116 0.978
Note. Data are expressed as mean ± SD. a Baseline vs 12 weeks. Abbreviations: HIT, high-intensity training; LIT, low-intensity training; ICC, intraclass correlation coefficient; TC, total cholesterol; LDL, low-density lipoprotein cholesterol; HDL, high-density lipoprotein cholesterol; VLDL, very-low-density lipoprotein cholesterol; TG, triglycerides.
TC (mg/dL) LDL (mg/dL) HDL (mg/dL) VLDL (ml/dL) TG (ml/dL) Glucose (mg/dL)
Baseline
HIT
Table 2 Effects of Different Intensities of Aerobic Training on Blood Lipid and Glucose Profile in Obese Adolescents
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Discussion This is the first randomized trial conducted with obese adolescents testing the effects of high and low intensity of aerobic training on single and clustered CVD risk factors. These data provide evidence that both exercise intensities are effective in the control of CVD risk factors related to obesity in adolescents submitted to a multidisciplinary intervention. It is estimated that obesity was responsible for 365,000 avoidable deaths in 2000 in the United States,26 and those deaths were associated with alterations of cardiometabolic markers related to obesity.27 In Brazil, overweight and obesity has increased from 4% to 13% over the past 20 years.28 This is concerning given that obesity is associated with development of several other pathologies.29 Even small changes in body mass,30 TC and TG,31 WC,32 and improvements on physical fitness33 are related to lower likelihood to mortality in adulthood.34 Previous research reported no differences between intensities of aerobic exercise training on body composition.35 The results from the current study are in agreement with previous studies, as both training intensities were efficient to promote positive changes on body composition and physical fitness in obese adolescents engaged in a multidisciplinary therapy. According to the laws of thermodynamics, weight loss occurs only in response to negative energy balance, and the magnitude of weight loss is proportional with energetic deficit.36 The positive change over time in both groups (HIT and LIT) may had been influenced by other factors such as eating habits or free-living physical activity. The absence of a true control group (with no intervention) in the study design does not allow us to determine if the observed improvement is due to exercise training only. A high WC during adolescence is associated with increased mortality rate for all causes in adulthood, and an increase of 5 cm in WC raises the relative risk of death by 17% for men and 13% for women.37 Thus, it may be essential to reduce central adiposity in obese children, as a reduction of 1 cm in WC is related to 4% decrease in visceral fat.38 Noteworthy is the fact that increasing cardiorespiratory fitness is more impactful for reducing CVD risk factors and mortality than reducing body fat.33 You et al39 conducted an elegant study with obese women allocated to a diet group or a diet-plus-exercise group and found that both groups promoted similar changes on body fat
and visceral fat amount. However, only those who exercised presented decrease on inflammatory markers, such as tumor necrosis factor alpha, interleukin-6, and C-reactive protein. The authors suggested physical fitness as a possible mechanism linking health benefits to physical exercise. A study examining the influence of cardiorespiratory fitness on mortality and CVD verified that a 1 MET (3.5 mL×kg–1×min–1) increase in maximum oxygen uptake (VO2max; corresponding to approximately 1 km/h higher running/jogging speed or 10%) was associated with 13% and 15% risk reduction from all-cause mortality and CVD events, respectively. In the current study, both training intensities improved VO2peak more than 1 MET, reinforcing the positive effects of aerobic training on health related parameters, even with only small changes on fatness.40 In addition, our results show a relationship between changes on physical fitness and WC. Thus, we hypothesized that changes in physical fitness must be the key point to the improvements on a cluster of health risk factors observed in the adolescents submitted to exercise training. Duncan et al41 previously described that improvements in cardiorespiratory fitness can reverse the negatives effects of obesity on health parameters, independent of alterations on fat mass. The probable mechanism by which increased cardiorespiratory fitness confers reduction in risk factors is not completely understood. It is speculated that reduction in C-reactive protein, associated with down-regulation of tumor necrosis factor alpha and interleukin-6, entails vascular benefits conferring cardioprotection.42 The current study has some limitations that should be considered. For ethical reasons, we did not include a control nonintervention group. We were unable to assess circulating levels of cytokines and to obtain objective measures of body composition (eg, dualenergy X-ray absorptiometry). Free-living physical activities were not assessed and may also explain at least part of the results that cannot be entirely attributed to the exercise itself. A possible learning effect bias in relation to the cardiorespiratory fitness measurement should be considered for data interpretation. Most of previous studies that assessed the effects of exercise training intensity on cardiovascular risk factors have used relative exercise intensity based on VO2max or maximum heart rate, presuming that it would decrease the variability of the physiological response. This “normalization process” may not be the most appropriate because individuals could show different metabolic,
Figure 2 — Improvements, worsening, and maintenance of cardiovascular disease (CVD) risk factors in obese adolescents, according to training intensity. HIT = high-intensity training; LIT = low-intensity training; W = worsened; RF = risk factor. JPAH Vol. 12, No. 4, 2015
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Exercise and CVD Risk in Obese Adolescents 559
Figure 3 — Changes on sum of z scores (WC + TC + Glucose-FitnessHDL) of a cluster of cardiovascular disease (CVD) risk factors in obese adolescents, according to training intensity. HIT = high-intensity training; LIT = low-intensity training; WC = waist circumference; TC = total cholesterol; HDL = high-density lipoprotein.
cardiovascular, and hormonal changes at the same relative VO2max or maximum heart rate.43 The use of the anaerobic threshold to normalize exercise intensity is a better way to reduce variability between subjects. We can conclude HIT does not promote any additional improvements in CVD risk factors than LIT. However both high- and lowintensity aerobic exercise are equally effective for reducing CVD risk in obese adolescents. Further study is needed to determine the sustainability of these improvements after the end of therapy. Acknowledgments We would like to thank the Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (FACEPE) for the support. Thanks to the Nutrition and Exercise Research Group for the technical support in data collection. Special thanks to patients and their parents for participation in this study. This work was supported by a grant (477955/2009-6) from the Conselho Nacional de Desenvolvimento Científico e Tecnológico.
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560 Silva et al 22. Kanhai DA, Kappelle LJ, Van der Graaf Y, Uiterwaal CSPM, Visseren FLJ. The risk of general and abdominal adiposity in the occurrence of new vascular events and mortality in patients with various manifestations of vascular disease. Int J Obes (Lond). 2012;36(5):695–702. PubMed doi:10.1038/ijo.2011.115 23. Hausenloy DJ, Yellon DM. Targeting residual cardiovascular risk: raising high-density lipoprotein cholesterol levels. Postgrad Med J. 2008;84(997):590–598. PubMed 24. Lee D-C, Sui X, Church TS, Lavie CJ, Jackson AS, Blair SN. Changes in fitness and fatness on the development of cardiovascular disease risk factors hypertension, metabolic syndrome, and hypercholesterolemia. J Am Coll Cardiol. 2012;59(7):665–672. PubMed doi:10.1016/j. jacc.2011.11.013 25. Seshasai SR, Kaptoge S, Thompson A, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364(9):829–841. PubMed doi:10.1056/NEJMoa1008862 26. Catenacci VA, Hill JO, Wyatt HR. The obesity epidemic. Clin Chest Med. 2009;30:415–444. PubMed doi:10.1016/j.ccm.2009.05.001 27. Ekelund U, Luan J, Sherar LB, Esliger DW, Griew P, Cooper A. Moderate to vigorous physical activity and sedentary time and cardiometabolic risk factors in children and adolescents. JAMA. 2012;307(7):704–712. PubMed doi:10.1001/jama.2012.156 28. da Veiga GV, Da Cunha AS, Sichieri R. Trends in overweight among adolescents living in the poorest and richest regions of Brazil. Am J Public Health. 2004;94(9):1544–1548. PubMed doi:10.2105/AJPH.94.9.1544 29. Walls HL, Backholer K, Proietto J, McNeil JJ. Obesity and trends in life expectancy. J Obes. 2012;2012:107989 . 30. Garanty-Bogacka B, Syrenicz M, Goral J, et al. Changes in inflammatory biomarkers after successful lifestyle intervention in obese children. Endokrynol Pol. 2011;62(6):499–505. PubMed 31. Thorogood A, Mottillo S, Shimony A, et al. Isolated aerobic exercise and weight loss: a systematic review and meta-analysis of randomized controlled trials. Am J Med. 2011;124(8):747–755. PubMed doi:10.1016/j.amjmed.2011.02.037 32. Kahn HS, Bullard KM, Barker LE, Imperatore G. Differences between adiposity indicators for predicting all-cause mortality in a representative sample of United States non-elderly adults. PLoS ONE. 2012;7(11):e50428. PubMed doi:10.1371/journal.pone.0050428
33. Hamer M. The relative influences of fitness and fatness on inflammatory factors. Prev Med. 2007;44(1):3–11. PubMed doi:10.1016/j. ypmed.2006.09.005 34. Lloyd LJ, Langley-Evans SC, McMullen S. Childhood obesity and risk of the adult metabolic syndrome: a systematic review. Int J Obes (Lond). 2012;36(1):1–11. PubMed doi:10.1038/ijo.2011.186 35. Lafortuna CL, Resnik M, Galvani C, Sartorio A. Effects of non-specific vs individualized exercise training protocols on aerobic, anaerobic and strength performance in severely obese subjects during a short-term body mass reduction program. J Endocrinol Invest. 2003;26(3):197– 205. PubMed doi:10.1007/BF03345157 36. Mai K, Schwarz F, Bobbert T, et al. Relation between fibroblast growth factor-21, adiposity, metabolism, and weight reduction. Metabolism. 2011;60(2):306–311. PubMed doi:10.1016/j.metabol.2010.02.016 37. Baker JL, Olsen LW, Sørensen TIA. Childhood body-mass index and the risk of coronary heart disease in adulthood. N Engl J Med. 2007;357(23):2329–2337. PubMed doi:10.1056/NEJMoa072515 38. Kushner RF, Bessenen DH, eds. Treatment of the obese patient. Totowa, NJ: Humana Press. 2007. 39. You T, Berman DM, Ryan AS, Nicklas BJ. Effects of hypocaloric diet and exercise training on inflammation and adipocyte lipolysis in obese postmenopausal women. J Clin Endocrinol Metab. 2004;89(4):1739– 1746. PubMed doi:10.1210/jc.2003-031310 40. Kodama S, Saito K, Tanaka S, et al. Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA. 2009(19);301:2024– 2035. PubMed doi:10.1001/jama.2009.681 41. Duncan GE. The “fit but fat” concept revisited: population-based stimates using NHANES. Int J Behav Nutr Phys Act. 2010;7:47. PubMed doi:10.1186/1479-5868-7-47 42. Wong PC, Chia MY, Tsou IY, et al. Effects of a 12-week exercise training programme on aerobic fitness, body composition, blood lipids and C-reactive protein in adolescents with obesity. Ann Acad Med Singapore. 2008;37(4):286–293. PubMed 43. Baldwin J, Snow RJ, Febraio MA. Effect of training status and relative exercise intensity on physiological responses in men. Med Sci Sports Exerc. 2000;32(9):1648–1654. PubMed doi:10.1097/00005768200009000-00020
JPAH Vol. 12, No. 4, 2015
ORIGINAL RESEARCH
Improvements on Cardiovascular Diseases Risk Factors in Obese Adolescents: A Randomized Exercise Intervention Study Humberto José Gomes Silva, Lars Bo Andersen, Mara Cristina Lofrano-Prado, Mauro V.G. Barros, Ismael Fortes Freitas Jr., James Hill, and Wagner Luiz do Prado Background: It is unclear how different exercise intensities affect cardiovascular disease (CVD) risk factors in obese adolescents. The aim of this study was to compare the effects of high-intensity (HIT) vs. low-intensity (LIT) aerobic training on CVD risk factors in obese adolescents. Methods: Forty-three obese adolescents (age: 15.7 ± 1.3 years, BMI: 34.3 ± 4.1kg/m2) participated this study either HIT (corresponding to ventilatory threshold I; N = 20) or LIT (20% below ventilatory threshold I; N = 23) for 12 weeks. All sessions were isocaloric (350 kcal). All participants received the same nutritional, psychological, and clinical counseling. Subjects were assessed in fatness, fitness, lipid profile, and glucose at baseline and after 12 weeks. The CVD risk factors assessed were waist circumference (WC), total cholesterol (TC), high-density lipoprotein (HDL), glucose, and fitness, which were single and clustered analyzed (z scores sum). Results: Body mass, Body Mass Index, fatness, and WC were improved (P < .001) in both groups. The sum of z scores (WC + TC + glucose-fitness-HDL) improved in both HIT (12 weeks = –2.16 SD; Cohen’s d = .45) and LIT (12 weeks = –2.13 SD; Cohen’s d = .60) without groups differences. Changes in fitness were associated with changes in WC (r = –.48; P = .003). Conclusion: HIT does not promote any additional improvements in CVD risk factors than LIT in obese adolescents. Keywords: physical activity, health, obesity, multidisciplinary therapy
The presence of cardiovascular disease (CVD) risk factors, which in the past were usually observed later in life, have become common in children and adolescents.1 Cut-off points of single CVD risk factors are not well established in adolescents, so Andersen et al (2011)2 suggested using a continuous composite risk score to assess CVD risk in this group. Clustering of risk factors for CVD, including obesity, tracks from childhood to adulthood.3 Because treatment of obesity is more effective in children than adults,4 early identification of CVD risk factors is highly desirable. This can allow for early implementation of multidisciplinary therapy, composed of nutritional, psychological, clinical, and physical activity interventions to achieve the health goals in obese individuals. Physical exercise is considered a corner stone in obesity therapy, because it improves metabolic risk factors associated with obesity by decreasing fat mass and improving cardiorespiratory fitness.5 Noteworthy is the fact that both adiposity and fitness are strongly associated with clustering of CVD risk factors in children and adolescents.6 Previously, studies in adolescents have demonstrated that aerobic training can improve lipid profiles,7 glycemic control,8 body Silva, Lofrano-Prado, Barros, and Prado ([email protected]) are with the Post Graduate Program of Physical Education, University of Pernambuco, Recife, Brazil. Andersen is with the School of Research in Childhood Health, University of Southern Denmark, Odense, Denmark. Freitas is with the Dept of Physical Education, Universidade Estadual Paulista, São Paulo, Brazil. Hill is with the Center for Human Nutrition, University of Colorado, Denver, CO.
composition,9 and physical fitness.10 Noteworthy is that, in adults, the positive effects of aerobic training are intensity-dependent; indeed, high-intensity training (HIT) is associated with greater improvements in physical fitness,11 while low-intensity training (LIT) enhances fatty acids oxidation.12 Exercise at high intensity also seems to induce larger cardiovascular benefits.13 However, the safety and effectiveness of this type of training has not been evaluated in obese adolescents. The aim of this study was to compare the effects of high- versus low-intensity aerobic training on CVD risk factors in obese adolescents.
Methods Participants Obese adolescents were recruited from the urban area of Recife, in Pernambuco (northeast of Brazil) between January and February 2011 through local television announcement, newspapers, and radio. The inclusion criteria were age ranging from 13 to 18 years, pubertal stage 3 or 4,14 obesity,15 absence of hypertension and/or other metabolic diseases, no restriction to engaging in a regular physical exercise program, intrinsic motivation and agreement to participate in a weight loss multidisciplinary intervention. The exclusion criteria were pregnancy and less than 75% compliance in all nutritional, psychological, clinical, and/or exercise sessions. This study was carried out in accordance with the principles of the Declaration of Helsinki and was formally approved by the ethical committee of the University of Pernambuco (#154/09). Informed consent was obtained from all participants and/or their legal guardians.
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Study Design
Nutritional Counseling
A total of 229 adolescents volunteered for the study. At baseline, they visited the laboratory twice. During the first visit pubertal stage, height and weight were measured and participants underwent a confidential individual semistructured interview containing 8 questions aimed to assess personal motives for seeking weight loss treatment and barriers to losing weight was conducted by a psychologist in a quiet room (intrinsic motivation). Among these, 186 individuals did not meet the inclusion criteria. During the second visit, the participants performed a rest and exercise electrocardiogram and underwent a medical screening. At the end, 43 obese adolescents (14 boys and 29 girls) were included in the study. Following baseline testing, participants were randomized (coin-flip method) into either HIT (n = 20) or LIT (n = 23) groups for the 12-week intervention (Figure 1). All participants also received the same multidisciplinary nutritional, psychological, and clinical counseling, as previously described.16
Nutritional counseling included weekly small group (~9 participants) sessions of 1 hour and they were led by a trained nutritionist. Sessions addressed healthy eating behavior, the food pyramid, weight loss diets, diet versus reduced-calorie products, and recording energy intake and provided general nutrition information. Participants were not given specific diet prescriptions but were encouraged to reduce overall calorie intake of food and follow a balanced diet.
Clinical Counseling Medical follow-up was performed once/month by an endocrinologist. This included a physical examination to monitor clinical parameters and the overall compliance with the study. No medicine was prescribed for weight loss in the study participants.
Psychological Counseling The study participants met with a psychologist weekly for 1-hour sessions in small groups of about 9. During these sessions themes related to body image, eating disorders (symptoms and consequences), relationship between food and feelings, family and social problems, mood, anxiety, and depression were discussed along with psychological motivation for compliance with the study protocol. The sessions were exactly the same for all groups, and always conducted by same psychologist.
Aerobic Exercise Training Participants in both HIT and LIT groups underwent personalized aerobic training on a treadmill, 3 times a week, under the supervision of an exercise instructor. The participants in the HIT group exercised at an intensity corresponding to the ventilatory threshold I, and those in the LIT group exercised at a speed 20% below the ventilatory threshold I. For both training groups, exercise sessions were isocaloric, with energy expenditure set at 350 Kcal (1050 Kcal/ week), estimated by indirect calorimetry. Once each participant had a set of specific and individualized work load, the duration of exercise sessions differed between participants to ensure that the preestablished energy expenditure was achieved. Based on the metabolic equivalent of task (MET)—and considering that for each liter of O2 consumed, the energy expenditure is 4.96 Kcal—exercise session duration was determined using the equation
Exercise session time (min) = 350 Kcal ÷ (VO2 on target intensity × 1 MET)
Measurements All volunteers were subjected to the same assessment protocol, before and after 12 weeks of a multidisciplinary therapy. The evaluations were performed in the same period of the day to avoid any circadian influence, and by the same evaluator.
Figure 1 — Experimental design. JPAH Vol. 12, No. 4, 2015
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Pubertal Maturation
Statistical Analysis
Each participant was given drawings of the 5 stages of breast, genital, and pubic hair development. In an isolated room, the adolescents were asked to look at the drawings, read the descriptions, think about how they looked in comparison with the drawings, and pick the 1 that most closely resembled them.17 For boys, the genitalia and pubic hair on each photograph were classified into 5 stages of development; for girls, the breasts and pubic hair on each photograph were classified into 5 stages of development.
Considering alpha = 0.05 and power = 0.80, the sample size in this study was sufficiently large to detect a significant differences greater than 0.67 in composite z score. Statistical analysis was performed using STATISTICA Version 8. Normality was verified by Shapiro Wilk test, and data were expressed as mean ± standard deviation and relative frequencies. Comparisons between time (baseline and 12 weeks) and groups (HIT and LIT) were made using ANOVA 2-way and Fischer’s post hoc test. Differences in percentage variation between groups were assessed by a student T test for independent groups. The withingroup effect size was calculated and is expressed as correlation when higher than moderate (Cohen’s d). The statistical power of the sample was determined a posteriori (power = 0.995). The significance level was set at P < .05.
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Anthropometry and Body Composition Participants were weighed wearing light clothing and no shoes on a Filizola scale (Model 160/300, Brazil) to the nearest 0.1 kg. Height was measured to nearest 0.5 cm by using a wall-mounted stadiometer (Filizola, Model 160/300, Brazil). Body Mass Index (BMI) was calculated dividing body weight (kg) by squared height (m2). Relative body fat (%) was estimated using a 2-site skinfold measurement (triceps and subscapular) by the equation of Slaughter et al,18 specific for each gender.
Serum Assays Blood samples were collected in the outpatient clinic at approximately 8:00 AM, after an overnight fast (12 hours). Spectrophotometry (Cobas Integra 400 Plus) was used to determine serum triglycerides (TG; coefficient of variation [CV] intra = 1.6% and inter = 1.9%), total cholesterol (TC; CVintra = 0.51%; CVinter = 1.9%), high-density lipoprotein (HDL; CVintra = 0.75%; CVinter = 2.1%) and glucose (CVintra = 0.41%; CVinter = 1.09%); using commercial kits (Roche), LDL was calculated indirectly using the Friedewald formula [LDL = TC – HDL – (TG / 5)].
Cardiorespiratory Fitness Peak oxygen uptake (VO2peak) was used to determine cardiovascular fitness. VO2 was measured directly in an open circuit respiratory metabolic system (Quark PFT, Cosmed, Italy), during a continuous incremental test on a treadmill (Cosmed T200, Italy). The initial load was set at 4 km/h (warm-up 3 minutes) and increased 1 Km/h each minute; inclination was kept constant at 1%.19 The termination criteria were volitional fatigue, Borg Scale higher than 18, and gas exchange ratio higher than 1.15. The greatest VO2 obtained before test interruption was considered as VO2peak. Before each test, the equipment (White Martins) was calibrated for gas composition (O2 = 12.2% and CO2 = 4.8%) and volume following all manufacturers’ recommendations.
Composite CVD Risk Factor Score Variables included in the composite CVD risk factor score were z scores of waist circumference (WC), TC, glucose, and inverse of cardiorespiratory fitness and HDL. WC was measured at the midpoint between the lower ribs and the iliac crest.20 Change in risk factor profile was also evaluated as the sum of changes in individual risk factors. The following criteria were adopted for categorizing the changes in individual risk factors: 1% change in TC,21 1.0 cm in WC,22 1.0 mg/dL in HDL,231 MET (3.5 mL×kg–1×min–1) in VO2peak,24 and fasting plasma glucose below 100 mg/dL.25 Thereafter, each individual variable was attributed +1 point for improvement, –1 point for worsening, or 0 points for maintenance.
Results Anthropometric Profile, Fitness, and Body Composition From a total of 43 patients (14 boys and 29 girls) included in the sample, 85% from HIT (6 boys and 11 girls) and 83% from LIT (7 boys and 12 girls) adhered to the 12 weeks of multidisciplinary therapy. The anthropometric characteristics of participants at baseline and after 12 weeks of intervention are presented in Table 1. Both groups reduced body weight, BMI, body fat (%) and WC; no differences were observed between groups at baseline and after 12 weeks.
Lipid and Glucose Profile After 12 weeks of intervention, LDL cholesterol was reduced only for adolescents enrolled in the LIT group, without changes for other blood lipids or glucose (Table 2). No differences were observed between training intensities.
Cardiorespiratory Fitness VO2peak improved from 25.6 ± 4.5 to 30.1 ± 4.5 mL×kg–1×min–1 (17.6%; P < .001) in the HIT group and from 26.5 ± 5.2 to 30.0 ± 5.6 mL×kg–1×min–1 (13.2%; P < .001) in the LIT group, with no difference between groups. In addition, results indicated a negative correlation between the change in WC (Δ%) andVO2peak (Δ%; r = –0.48; P = .003; both groups included in the analysis; Figure 2).
Cluster of CVD Risk Factors The sum of the improvements (+1), worsening (–1), and maintenance (0) of individual changes in CVD risk factors demonstrated that none of the participants in the HIT group had worsening of risk factors, 12% of the adolescents had improvement in at least 1 risk factor, 36% improved 2 or 3 factors (36%), and 46% improved 4 or 5 factors, whereas only 6% had no changes in risk factors (Figure 3. In the LIT group, 21% had improvement in at least 1 risk factor, 5% in 2 risk factors, 21% in 3 risk factors, 11% in 4 risk factors, and 21% in 5 factors, while 5% worsened in at least 1 risk factors and 16% remained stable (Figure 3). Positive changes were seen in the sum of z scores (WC + TC + glucose-fitness-HDL) in HIT (baseline = 0.00; 12 weeks = –2.16; Cohen’s d = .45) and LIT (baseline = 0.00; 12 weeks = –2.13; Cohen’s d = .60; Figure 3).
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15.7 ± 1.3 1.62 ± 0.05 90.3 ± 11.3 34.3 ± 4.1 51.0 ± 5.9 96.7 ± 8.2
16.0 ± 1.3a 1.62 ± 0.05 87.7 ± 11.7a 33.4 ± 4.0a 44.8 ± 9.9a 92.8 ± 8.0a
12 weeks 2.29 –0.14 –2.90 –2.62 –12.20 –4.01
% 15.29 ± 1.63 1.63 ± 0.08 92.1 ± 11.4 34.6 ± 3.7 53.7 ± 9.4 94.6 ± 6.7
Baseline
LIT 15.6 ± 1.6a 1.63 ± 0.08 90.4 ± 12.4a 33.7 ± 3.9a 41.6 ± 6.4a 92.5 ± 8.4a
12 weeks 2.22 0.25 –1.96 –2.45 –20.24 –2.32
%
0.381 0.611 0.570 0.780 0.787 0.638
Group effect
0.001 0.671 0.001 0.001 0.001 0.001
Time effect
0.197 0.140 0.317 0.782 0.074 0.209
Interaction effect
Note. Data are expressed as mean ± SD. a Baseline vs 12 weeks. Abbreviations: HIT, high-intensity training; LIT, low-intensity training; ICC, intraclass correlation coefficient; BM, body mass; BMI, Body Mass Index; WC, waist circumference.
Age (yr) Height (m) BM (kg) BMI (kg/m2) Body fat (%) WC (cm)
Baseline
HIT
Table 1 Effects of Different Aerobic Training Intensities on Anthropometry and Body Composition in Obese Adolescents
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— 0.923 0.930 0.718 0.649 0.467
ICC
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169.8 ± 27.8 112.7 ± 24.7 34.5 ± 10.8 23.5 ± 15.3 117.4 ± 77.0 83.7 ± 9.6
164.6 ± 28.9 104.8 ± 20.2 36.8 ± 12.0 20.3 ± 7.3 116.8 ± 72.1 82.4 ± 10.0
12 weeks –3.44 –5.33 8.06 –1.43 3.22 –0.41
% 162.3 ± 30.2 106.3 ± 24.3 39.4 ± 13.5 23.0 ± 18.2 116.1 ± 90.7 86.5 ± 18.1
Baseline 159.1 ± 29.3 93.6 ± 27.6a 38.9 ± 11.0 21.8 ± 10.7 109.2 ± 53.7 78.9 ± 7.7
12 weeks
LIT –1.35 –10.36 1.84 6.23 4.52 –5.50
%
0.486 0.295 0.376 0.933 0.836 0.943
Group effect
0.144 0.024 0.310 0.319 0.575 0.166
Time effect
0.665 0.584 0.266 0.645 0.611 0.219
Interaction effect
ICC 0.546 0.649 0.274 0.632 0.116 0.978
Note. Data are expressed as mean ± SD. a Baseline vs 12 weeks. Abbreviations: HIT, high-intensity training; LIT, low-intensity training; ICC, intraclass correlation coefficient; TC, total cholesterol; LDL, low-density lipoprotein cholesterol; HDL, high-density lipoprotein cholesterol; VLDL, very-low-density lipoprotein cholesterol; TG, triglycerides.
TC (mg/dL) LDL (mg/dL) HDL (mg/dL) VLDL (ml/dL) TG (ml/dL) Glucose (mg/dL)
Baseline
HIT
Table 2 Effects of Different Intensities of Aerobic Training on Blood Lipid and Glucose Profile in Obese Adolescents
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Discussion This is the first randomized trial conducted with obese adolescents testing the effects of high and low intensity of aerobic training on single and clustered CVD risk factors. These data provide evidence that both exercise intensities are effective in the control of CVD risk factors related to obesity in adolescents submitted to a multidisciplinary intervention. It is estimated that obesity was responsible for 365,000 avoidable deaths in 2000 in the United States,26 and those deaths were associated with alterations of cardiometabolic markers related to obesity.27 In Brazil, overweight and obesity has increased from 4% to 13% over the past 20 years.28 This is concerning given that obesity is associated with development of several other pathologies.29 Even small changes in body mass,30 TC and TG,31 WC,32 and improvements on physical fitness33 are related to lower likelihood to mortality in adulthood.34 Previous research reported no differences between intensities of aerobic exercise training on body composition.35 The results from the current study are in agreement with previous studies, as both training intensities were efficient to promote positive changes on body composition and physical fitness in obese adolescents engaged in a multidisciplinary therapy. According to the laws of thermodynamics, weight loss occurs only in response to negative energy balance, and the magnitude of weight loss is proportional with energetic deficit.36 The positive change over time in both groups (HIT and LIT) may had been influenced by other factors such as eating habits or free-living physical activity. The absence of a true control group (with no intervention) in the study design does not allow us to determine if the observed improvement is due to exercise training only. A high WC during adolescence is associated with increased mortality rate for all causes in adulthood, and an increase of 5 cm in WC raises the relative risk of death by 17% for men and 13% for women.37 Thus, it may be essential to reduce central adiposity in obese children, as a reduction of 1 cm in WC is related to 4% decrease in visceral fat.38 Noteworthy is the fact that increasing cardiorespiratory fitness is more impactful for reducing CVD risk factors and mortality than reducing body fat.33 You et al39 conducted an elegant study with obese women allocated to a diet group or a diet-plus-exercise group and found that both groups promoted similar changes on body fat
and visceral fat amount. However, only those who exercised presented decrease on inflammatory markers, such as tumor necrosis factor alpha, interleukin-6, and C-reactive protein. The authors suggested physical fitness as a possible mechanism linking health benefits to physical exercise. A study examining the influence of cardiorespiratory fitness on mortality and CVD verified that a 1 MET (3.5 mL×kg–1×min–1) increase in maximum oxygen uptake (VO2max; corresponding to approximately 1 km/h higher running/jogging speed or 10%) was associated with 13% and 15% risk reduction from all-cause mortality and CVD events, respectively. In the current study, both training intensities improved VO2peak more than 1 MET, reinforcing the positive effects of aerobic training on health related parameters, even with only small changes on fatness.40 In addition, our results show a relationship between changes on physical fitness and WC. Thus, we hypothesized that changes in physical fitness must be the key point to the improvements on a cluster of health risk factors observed in the adolescents submitted to exercise training. Duncan et al41 previously described that improvements in cardiorespiratory fitness can reverse the negatives effects of obesity on health parameters, independent of alterations on fat mass. The probable mechanism by which increased cardiorespiratory fitness confers reduction in risk factors is not completely understood. It is speculated that reduction in C-reactive protein, associated with down-regulation of tumor necrosis factor alpha and interleukin-6, entails vascular benefits conferring cardioprotection.42 The current study has some limitations that should be considered. For ethical reasons, we did not include a control nonintervention group. We were unable to assess circulating levels of cytokines and to obtain objective measures of body composition (eg, dualenergy X-ray absorptiometry). Free-living physical activities were not assessed and may also explain at least part of the results that cannot be entirely attributed to the exercise itself. A possible learning effect bias in relation to the cardiorespiratory fitness measurement should be considered for data interpretation. Most of previous studies that assessed the effects of exercise training intensity on cardiovascular risk factors have used relative exercise intensity based on VO2max or maximum heart rate, presuming that it would decrease the variability of the physiological response. This “normalization process” may not be the most appropriate because individuals could show different metabolic,
Figure 2 — Improvements, worsening, and maintenance of cardiovascular disease (CVD) risk factors in obese adolescents, according to training intensity. HIT = high-intensity training; LIT = low-intensity training; W = worsened; RF = risk factor. JPAH Vol. 12, No. 4, 2015
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Exercise and CVD Risk in Obese Adolescents 559
Figure 3 — Changes on sum of z scores (WC + TC + Glucose-FitnessHDL) of a cluster of cardiovascular disease (CVD) risk factors in obese adolescents, according to training intensity. HIT = high-intensity training; LIT = low-intensity training; WC = waist circumference; TC = total cholesterol; HDL = high-density lipoprotein.
cardiovascular, and hormonal changes at the same relative VO2max or maximum heart rate.43 The use of the anaerobic threshold to normalize exercise intensity is a better way to reduce variability between subjects. We can conclude HIT does not promote any additional improvements in CVD risk factors than LIT. However both high- and lowintensity aerobic exercise are equally effective for reducing CVD risk in obese adolescents. Further study is needed to determine the sustainability of these improvements after the end of therapy. Acknowledgments We would like to thank the Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (FACEPE) for the support. Thanks to the Nutrition and Exercise Research Group for the technical support in data collection. Special thanks to patients and their parents for participation in this study. This work was supported by a grant (477955/2009-6) from the Conselho Nacional de Desenvolvimento Científico e Tecnológico.
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