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Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents
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Nutrition, Metabolism & Cardiovascular Diseases (2012) xx, 1e7
Available online at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/nmcd
Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents M. Laguna a, S. Aznar a,*, M.T. Lara b, A. Lucı´a c, J.R. Ruiz d,e a
PAFS-UCLM Research Group, Faculty of Sports Sciences, University of Castilla-La Mancha, Avda. Carlos III, s/n. 45071, Toledo, Spain b Sport Medical Center, Juan Esplandiu´ Street, 1, 28007, Community of Madrid, Madrid, Spain c School of Doctoral Studies & Research, European University of Madrid, Tajo Street, s/n. 28670, Villaviciosa de Odo´n, Madrid, Spain d Department of physical education and sport, School of Sport Sciences, University of Granada, Alfacar Road, s/n. 18011 Granada, Spain e Department of Biosciences and Nutrition at NOVUM, Unit for Preventive Nutrition, Karolinska Institutet, Huddinge, Sweden Received 24 July 2012; received in revised form 20 September 2012; accepted 3 October 2012
KEYWORDS Adolescent; Autonomic function; Child; Heart rate recovery; Multiple linear regression; Physical activity
Abstract Background and aims: Increased vagal activity is associated with obesity and metabolic risk in children and adolescents. The aim of the present cross-sectional study was to examine the association of parasympathetic function, as assessed by heart rate recovery (HRR) from a maximal exercise cycle-ergometer test, with obesity traits and related cardiometabolic risk factors in Spanish children and adolescents. Methods and results: A sample of 437 Spanish 9-year-old-children and 235 15-year-old-adolescents participated in the study. The variables measured were anthropometric characteristics (height, body mass and waist circumference) and physical activity using the Actigraph accelerometer. Additional measured outcomes included fasting insulin, triglycerides, high-density lipoprotein cholesterol (HDLc) and blood pressure. A metabolic risk score was computed as the mean of the standardised outcomes scores. The HRR was calculated as the difference between peak heart rate and heart rate 1, 3 and 5 min after cessation of the maximal ergometer test. Diastolic blood pressure was associated with all the HRR parameters in 9-year-oldgirls. In 9-year-old-boys, the 3-min HRR was inversely associated with systolic blood pressure (p < 0.05) and Homeostasis Model Assessment (HOMA) (p < 0.05). Five minute HRR was inversely associated with waist circumference (p < 0.05), sum of five skinfolds (p < 0.01) and HOMA (p Z 0.004). There were no significant associations in adolescents. In 9-year-oldgirls, the adjusted 5-min HRR showed significant differences between quartile 2 and 4 of
* Corresponding author. Tel.: þ34 925 268 800x5521; fax: þ34 925 268 846. E-mail address: [email protected] (S. Aznar). 0939-4753/$ - see front matter ª 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.numecd.2012.10.002
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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M. Laguna et al. metabolic risk (p Z 0.011). In all samples, the adjusted HRR (1-, 3- and 5-min HRR) did not show significant differences across quartiles. Conclusion: HRR was inversely associated with obesity traits and related cardiometabolic risk factors mainly in healthy boys. ª 2012 Elsevier B.V. All rights reserved.
Recovery of the heart rate immediately after exercise is mediated by vagal reactivation [1,2]. Later recovery depends on a combination of vagal tone and withdrawal of sympathetic drive [1,2]. Reduced vagal activity is a powerful predictor of overall mortality [3,4] and has been associated with obesity [5] and metabolic risk [6] in children and adolescents. As the presence of childhood obesity conveys cardiometabolic complications such as insulin resistance and hypertension [7,8], it is possible that the adverse effects of childhood obesity on heart rate recovery (HRR) might also take place early in life. The central efferent parasympathetic control of heart rate is greater in children than in young adults and, thus, HRR after exercise is faster in children compared with young adults [2]. Several studies showed that 1-min HRR after exercise is attenuated with age [5,9], and having a slow HRR in early middle age is associated with traditional cardiovascular disease risk factors [9]. HRR is a marker independent of cardiovascular risk factors [4,10] which are not influenced by motivational factors. Other indicators may be influenced by several reasons (motivation, etc.) during a maximal exercise cycleergometer test because children and adolescents may not achieve the real VO2 peak. Assessing the association of HRR with obesity traits and related cardiometabolic risk factors in youth is of clinical interest because HRR is associated with all-cause mortality and sudden cardiac death in adults [3,4,10]. Several studies investigated the association of HRR with metabolic risk [6] and body mass index (BMI) [5] in adolescents, yet less is known regarding the association between HRR and other obesity traits and related cardiometabolic disease risk factors in adolescents as well as in younger populations. The aim of the present cross-sectional study was to examine the association of HRR from a maximal exercise cycle-ergometer test, with obesity traits and related cardiometabolic risk factors in Spanish children and adolescents.
Methods
sample was randomly selected using a two-stage cluster sample procedure, with schools in Madrid as primary sampling units. The secondary units were the children within the schools, and equal numbers of children were sampled randomly from each school. Data collection from the Spanish part of the EYHS took place in 2008e2010. Ethical approval was obtained by the Health Institute Carlos III in Madrid, Spain, and parental informed consent was obtained for each subject prior to data collection.
Measurement Anthropometric characteristics Height was measured using a Holtain stadiometer without shoes and recorded to the nearest millimetre. Body mass was measured to the nearest 0.1 kg with a calibrated beam balance scale in light clothing. BMI was calculated as body mass (kg) divided by height (m) squared. Skinfold thickness (biceps, triceps, subscapular, suprailiac and triceps surae) was measured to the nearest 0.2 mm in triplicate on the left side with a Holtain calliper [11]. The sum of five skinfold thicknesses was used as an indicator of body fat rather than BMI, because it has been suggested that BMI is not a good measurement of body fat in children [12]. Skinfold thickness has been shown to correlate highly with dualenergy X-ray absorptiometry-measured body fat percentage in children of similar ages [13]. Waist circumference was measured with an inelastic tape at the midpoint between the iliac crest and the lowest rib, using the mean of two measures for the analysis. Blood pressure Systolic and diastolic blood pressure (mmHg) were measured with an automatic oscillometric method (Dinamap model XL, Critikon, Inc., Tampa, FL, USA). The equipment has been validated in children and adolescents [14]. The subject was in a seated and relaxed position and the measurements were taken within a 10-min interval. The mean of the last three measurements of both diastolic and systolic blood pressure were used in the analysis.
Sample A total of 1395 children and adolescents from the Community of Madrid, Spain, participated in the European Youth Heart Study (EYHS). The EYHS is a school-based, cross-sectional study designed to examine the interactions between personal, environmental and lifestyle influences on the risk factor for future cardiovascular diseases in several European countries. All eligible schools were stratified according to location (urban, suburban and rural) and the socioeconomic profile of the uptake area (high, middle and low). The study
Blood samples The fasting venous (antecubital vein) samples were obtained after an overnight fast. Samples were stored at 80 C and analysed for serum high-density lipoprotein cholesterol (HDLc), triglyceride and insulin. HDLc was analysed using the homogeneous polyanion/cholesterol esterase/oxidase enzymatic method. Triglyceride levels were determined using the lipase/glycerol kinase/glycerol phosphate oxidase enzymatic method. Blood lipids were measured on an Olympus AU600 autoanalyser (Olympus Diagnostica, Hamburg, Germany). Insulin was analysed
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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Heart rate recovery vs. obesity traits/cardiometabolic risk factors using an enzyme immunoassay (microtitre plate format; Dako Diagnostics, Ely, U.K.). Glucose was analysed by the hexokinase method. Each of the above blood variables was measured on an Olympus autoanalyser (model AU600, Olympus Diagnostica GmbH, Hamburg, Germany). The homeostasis model assessment (HOMA) was calculated as (fasting insulin fasting glucose)/22.5, where fasting insulin is measured in mU l1 and fasting glucose is measured in mmol l1 [15]. Physical activity measurement Physical activity was measured during 6 consecutive days (from Thursday to Tuesday or from Friday to Wednesday) using the MTI accelerometer, model GT1M activity monitor. All children wore the accelerometer in an elastic waistband on the right hip during the daytime, except while bathing or during other aquatic activities. Verbal and written instructions for the care and placement of the monitor were given to both, children and their parents. GT1M is a lightweight (27 g) and small (4.5 3.5 1.0 cm), singleplane (vertical) accelerometer. Movement in a vertical plane is detected as a combined function of the frequency and the intensity of the movement, while an electronic filter rejects motion outside the range of normal human movement. Validation studies indicate that this accelerometer yields valid and reliable measurement of children’s physical activity, that is, a high correlation (r Z 0.86) with energy expenditure assessed by indirect calorimetry, as well as a high degree of inter-instrument reliability [16e18]. For data to be considered valid, two criteria were established: a minimum of data for a period of 4 days including one weekend day and a minimum of 10 registered h day1 [12]. To analyse the accelerometer data, Kinesoft software, developed specifically for the Actical and Actigraph accelerometers, was used. The outcome variables were expressed as average intensity (counts per min). Therefore, we calculated mean counts per min by dividing the sum of total counts per epoch (15 s) for a valid day by the number of min of wear time in that day across all valid days. We excluded from the analysis bouts of 20 continuous minutes of activity with intensity counts of 0, considering these periods to be non-wearing time [19]. Metabolic risk The metabolic risk score was computed from the following variables: waist circumference, insulin, HDLc, triglycerides/HDLc ratio and mean arterial pressure [20]. Each of these variables was standardised as follows: standardised value Z (value e mean)/SD. The metabolic risk score was calculated as the mean of the four standardised scores separately for boys and girls. Exercise testing All participants performed a maximum cycle-ergometer test. The workload was pre-programmed on a computerised cycle ergometer (Monark 829E, Ergomedic, Vansbro, Sweden) to increase after every 3 min until exhaustion. The cycle ergometer was electronically calibrated once every test day and mechanically calibrated after being moved between schools. Criteria for exhaustion were attaining a heart rate 185 beats per min or failure to maintain a pedalling frequency of at least 30 revolutions per min.
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The peak power output was calculated as being equal to W1 þ (W2 $ t/180), where W1 is a work rate at fully completed stage, W2 is the work rate increment at final incomplete stage, and t is time in s at final incomplete stage [21]. Heart rate was monitored continuously (Polar Vantage, Kempele, Finland) throughout the test. The HRR was defined as the change from peak heart rate during exercise to that measured after 1, 3 or 5 min of recovery as stated in the EYHS protocol. Peak heart rate was the highest value obtained by the heart rate monitor set at 5-s interval, during the maximal exercise cycle-ergometer test.
Statistical analysis Tests of normality, symmetry and kurtosis were conducted. Mean SD was used to describe the physical characteristics and all physical activity variables. Independent t-tests were used to examine sex differences for continuous variables and the chi-squared test was used for nominal variables. The correlation of each HRR parameter (HRR 1 min, 3 min and 5 min) with obesity traits and related cardiometabolic risk factors were derived by Pearson correlation analysis. The strength of the association of each HRR parameter with obesity traits and related cardiometabolic risk factors was estimated by multiple linear regression models after controlling for age and physical activity. Finally, differences between HRR parameters according to quartiles of metabolic risk were analysed by one-way analysis of covariance (ANCOVA), with HRR variables as dependent variables (each in a separate model), quartiles of metabolic risk as fixed factor and age and total physical activity as covariates. Differences among quartiles were assessed by the post hoc Bonferroni test. The level of significance was set at p < 0.05. All analyses were performed by using the Statistical Package for Social Sciences (SPSS, v 19.0).
Results A total of 914 children and adolescents agreed to wear an accelerometer and 672 (437 children aged 9 years (range 8e10), and 235 adolescents aged 15 years (range 14e16)) returned the accelerometer after satisfying the aforementioned validity criteria. Participants who provided valid accelerometer recordings did not differ significantly in the study variables from children who did not provide valid recording (all p > 0.1). The characteristics of the study sample are shown in Table 1. In 9 year-old children, short-term HRR (1-min HRR) was negatively correlated with systolic blood pressure (r Z 0.136, p < 0.05) in boys and with diastolic blood pressure (r Z 0.172, p < 0.01) in girls (Table 2). Threemin HRR was negatively correlated with systolic blood pressure (r Z 0.155, p < 0.05) and with HOMA (r Z 0.176, p Z 0.011) in boys. In girls, 3-min HRR was negatively correlated with systolic blood pressure (r Z 0.169, p Z 0.011), diastolic blood pressure (r Z 0.219, p Z 0.001) and HDL (r Z 0.136, p < 0.05). Five-minute HRR was negatively correlated with waist circumference (r Z 0.150, p < 0.05), sum of five skinfolds (r Z 0.192, p Z 0.005) and HOMA (r Z 0.215, p Z 0.002) in boys and with diastolic blood pressure
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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M. Laguna et al. Table 1
Descriptive characteristics of the study sample. Children
Adolescents
Girls n Age (years) Height (cm) Body mass (kg) BMI (Kg/m2) Waist circumference (cm) Sum of 5 skinfolds (mm) SBP (mmHg) DBP (mmHg) Triglycerides (mg/dl) HDL (mg/dl) HOMA Total physical activity (cpm) Maximum heart rate (beats/min) Recovery 1 heart rate (per min) Recovery 3 heart rate (per min) Recovery 5 heart rate (per min) HRR 1 HRR 3 HRR 5
227 9.2 140.1 36.4 18.4 64.8 71.7 106.5 64.8 62.0 24.4 0.3 541.6 188.4 149.1 129.2 108.3 39.3 59.2 80.1
Boys
0.5 6.4 7.8 3.1 8.5 26.5 10.7 7.6 28.2 5.3 0.3 300.1 7.5 12.9 15.2 16.2 11.8 13.4 15.8
210 9.2 138.5 35.1 18.2 64.3 61.0 106.7 65.3 55.4 25.7 0.2 636.0 187.8 143.3 123.8 101.4 44.5 64.0 86.4
0.4 6.0 7.5 3.0 8.1 28.2 10.0 7.1 26.2 5.4 0.2 337.5 6.7 14.1 14.9 12.7 13.8 14.7 13.7
p
Girls
0.206 0.012 0.086 0.405 0.538 <0.001 0.824 0.505 0.012 0.013 0.001 0.002 0.356 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001
108 15.0 162.4 56.1 21.3 72.2 79.8 110.4 65.9 57.4 23.7 0.3 427.9 185.6 159.2 138.5 118.1 26.4 47.1 67.5
Boys
0.6 6.8 7.5 2.5 7.4 22.8 12.0 7.5 20.7 4.5 0.3 132.0 7.9 11.6 14.4 15.1 11.0 12.9 13.9
127 14.9 171.1 63.0 21.5 74.2 56.4 118.2 68.2 59.0 21.4 0.3 490.2 187.3 155.6 133.7 114.5 31.6 53.5 72.7
p
0.6 7.5 13.6 4.3 6.1 20.7 12.2 8.0 31.5 3.9 0.2 153.9 8.3 12.3 14.4 14.4 12.5 13.9 14.3
0.718 <0.001 <0.001 0.672 0.022 <0.001 <0.001 0.023 0.648 <0.001 0.109 0.001 0.119 0.025 0.012 0.062 0.001 <0.001 0.005
Data are mean SD. BMI Z Body mass index, cpm Z counts per minute, DBP Z Diastolic blood pressure, HDL Z High-density lipoprotein, HOMA Z Homeostasis model assessment, HRR Z Heart rate recovery, SBP Z Systolic blood pressure.
(r Z 0.156, p Z 0.019) in girls. In adolescents, we observed no significant correlations of any of the HRR parameters with obesity traits and related cardiometabolic risk factors. Multiple linear regression analysis (Table 3) showed that among the seven study components of obesity traits and related cardiometabolic risk factors, diastolic blood pressure was the only variable associated with all the HRR parameters in 9-year-old girls. In 9 year-old boys, 3-min HRR was inversely associated with systolic blood pressure (p < 0.05) and HOMA (p < 0.05). Five-minute HRR was inversely associated with waist circumference (p < 0.05), sum of five skinfolds (p < 0.01) and HOMA (p Z 0.004). There were no significant associations in adolescents. To consider the cardiometabolic risk factors as a whole, we calculated the metabolic risk to represent the severity of the cluster of the metabolic risk by a single value. In children, the adjusted 1-min HRR and 3-min HRR did not show significant differences across quartiles (Fig. 1). For 5min HRR, we observed a negative association in 9-year-old girls (p Z 0.021), and post hoc analysis showed that the 5min HRR adjusted-mean was significantly different between quartiles 2 and 4 of metabolic risk in 9-year-old girls (p Z 0.011) (Fig. 1). In adolescents, the adjusted HRR (1, 3 and 5 min) did not show significant differences across quartiles (Fig. 2).
Discussion The main findings of the present study suggest an inverse association of HRR with obesity traits and related cardiometabolic risk factors mainly in boys. No association between HRR and obesity traits was observed in girls or
adolescents. Because the prevalence of obesity and associated metabolic disorders has increased over the past 3 decades among children of all ages [7,8], it is of clinical importance to investigate whether the link between impaired obesity traits and related cardiometabolic risk factors and HRR appears already in children and adolescents [6]. Moreover, enhanced central parasympathetic modulation may play an important role in protecting cardiac overload in children with frequent short intervals of physical activity [2]. Studies conducted up to now have established that the autonomic nervous system plays a central role in the development of obesity traits [22] and the metabolic syndrome [23e27] in adults. According to previous studies [25,28], decreased HRR occurs after, but not before, the presence of the metabolic syndrome. This association also seems to exist in children because we observed that most of the study variables (waist circumference, sum of five skinfolds, systolic blood pressure, diastolic blood pressure, HDL and HOMA) were associated with HRR parameters (1-, 3- and 5-min HRR). Our findings confirm that the association between HRR and metabolic risks operates early in young ages [6]. However, there were no associations of HRR with obesity traits and related cardiometabolic risk factors in adolescents and therefore, the association could not be confirmed in this group. One previous report [6] found that among 15-year-old adolescents, 1-, 2- and 3-min HRR was not associated with diastolic blood pressure, triglycerides and HDL, which concurs with our study results. It is biologically plausible that changes that occur during adolescence (hormonal and physiological) may mask the relationship of HRR with obesity traits and related cardiometabolic risk factors at these ages. Further studies are warranted.
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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Heart rate recovery vs. obesity traits/cardiometabolic risk factors Table 2 Correlation coefficients (r) showing the association between heart rate recovery at 1 (HRR 1), 3 (HRR 3) and 5 min post exercise (HRR 5) and obesity traits and related and cardiometabolic risk factors. Children Boys r
Adolescents Girls
p
r
Waist circumference (cm) HRR 1 0.019 NS 0.021 HRR 3 0.030 NS 0.031 HRR 3 0.150 0.029 0.022 Sum of 5 skinfolds (mm) HRR 1 0.119 NS 0.041 HRR 3 0.026 NS 0.033 HRR 5 0.192 0.005 0.088 SBP (mmHg) HRR 1 0.136 0.049 0.097 HRR 3 0.155 0.025 0.169 HRR 5 0.094 NS 0.034 DBP (mmHg) HRR 1 0.061 NS 0.172 HRR 3 0.076 NS 0.219 HRR 5 0.129 NS 0.156 Triglycerides (mg/dl) HRR 1 0.135 NS 0.116 HRR 3 0.026 NS 0.004 HRR 5 0.108 NS 0.087 HDL cholesterol (mg/dl) HRR 1 0.017 NS 0.003 HRR 3 0.000 NS 0.136 HRR 5 0.103 NS 0.020 HOMA HRR 1 0.133 NS 0.068 HRR 3 0.176 0.011 0.103 HRR 5 0.215 0.002 0.129
Boys
Girls
p
r
p
NS NS NS
0.077 NS 0.011 NS 0.016 NS
r
p
5
Table 3 Standardized correlation coefficients (b) from multiple linear regression analysis showing the association of heart rate recovery at 1 (HRR 1), 3 (HRR 3) and 5 min post exercise (HRR 5) with obesity traits and related cardiometabolic risk factors after controlling for age and physical activity. Children Boys
NS NS NS
0.125 NS 0.119 NS 0.088 NS
0.003 NS 0.029 NS 0.120 NS 0.131 NS 0.080 NS 0.024 NS
NS 0.058 NS 0.023 NS 0.011 0.068 NS 0.109 NS NS 0.028 NS 0.024 NS 0.009 0.014 NS 0.112 NS 0.001 0.018 NS 0.174 NS 0.019 0.018 NS 0.096 NS NS NS NS
0.042 NS 0.046 NS 0.027 NS 0.080 NS 0.020 NS 0.118 NS
NS 0.041 NS
0.074 NS 0.058 NS 0.002 NS 0.133 NS 0.030 NS 0.112 NS
NS NS NS
0.074 NS 0.154 NS 0.150 NS 0.156 NS 0.032 NS 0.109 NS
DBP Z Diastolic blood pressure, HDL Z High-density lipoprotein, HOMA Z Homeostasis model assessment, NS Z Not significant, SBP Z Systolic blood pressure.
We showed that the association between HRR and waist circumference was higher in boys. Our results concur with previous studies in adolescents that showed a strong relationship between HRR and waist circumference in both sexes [6]. However, we did not find a significant association in girls between these variables. In contrast, several cardiometabolic risk factors such as diastolic blood pressure and HDL related only in girls, which concur with the findings reported by Nilsson et al. [29] They showed that HRR is more closely associated with the metabolic syndrome in women than in men. However, these results were obtained in an elderly population and no data are still available in children. In the present study, multiple linear regression analysis showed that obesity traits and related cardiometabolic risk factors contribute more to the variation of the 3- or 5-min HRR compared with that of the 1-min HRR, similar to another recent study in American adolescents [6]. It has been suggested that short-term HRR indices (such as 1-min
b
Adolescents Girls
p
b
Waist circumference (cm) HRR 1 0.037 NS 0.019 HRR 3 0.011 NS 0.032 HRR 5 0.138 0.046 0.022 Sum of 5 skinfolds (mm) HRR 1 0.098 NS 0.044 HRR 3 0.011 NS 0.031 HRR 5 0.185 0.007 0.089 SBP (mmHg) HRR 1 0.126 NS 0.104 HRR 3 0.143 0.037 0.162 HRR 5 0.085 NS 0.037 DBP (mmHg) HRR 1 0.835 NS 0.167 HRR 3 0.063 NS 0.227 HRR 5 0.119 NS 0.154 Triglycerides (mg/dl) HRR 1 0.114 NS 0.118 0.009 HRR 3 0.010 NS HRR 5 0.099 NS 0.088 HDL (mg/dl) HRR 1 0.029 NS 0.000 HRR 3 0.014 NS 0.132 HRR 5 0.093 NS 0.021 HOMA HRR 1 0.108 NS 0.077 HRR 3 0.149 0.031 0.098 HRR 5 0.198 0.004 0.134
Boys
Girls
p
b
NS NS NS
0.072 NS 0.021 NS 0.006 NS
NS NS NS
p
b
p 0.137 NS 0.108 NS 0.080 NS
0.004 NS 0.045 NS 0.116 NS 0.123 NS 0.066 NS 0.031 NS
NS 0.062 NS 0.022 NS 0.015 0.071 NS 0.101 NS NS 0.022 NS 0.035 NS 0.012 0.009 NS 0.121 NS 0.001 0.025 NS 0.167 NS 0.021 0.035 NS 0.092 NS NS NS NS
0.033 NS 0.044 NS 0.023 NS 0.078 NS 0.010 NS 0.115 NS
NS 0.047 NS
0.095 NS 0.058 NS 0.010 NS 0.135 NS 0.049 NS 0.114 NS
NS 0.081 NS 0.153 NS NS 0.146 NS 0.154 NS 0.046 0.020 NS 0.107 NS
DBP Z Diastolic blood pressure, HDL Z High-density lipoprotein, HOMA Z Homeostasis model assessment, NS Z Not significant, SBP Z Systolic blood pressure.
Figure 1 Mean values of adjusted heart rate recovery among quartiles of metabolic risk for 9 yr-old boys (C) and girls (B). Symbol: p < 0.05 between quartile 2 and 4 in girls. Abbreviation: HRR Z heart rate recovery.
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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References
Figure 2 Mean values of adjusted heart rate recovery among quartiles of metabolic risk for 15 yr-old boys (C) and girls (B). Abbreviation: HRR Z heart rate recovery.
HRR) could be considered as markers of cardiac parasympathetic outflow [2,30]. In contrast, the second slow heart rate decay phase is thought to be related to the gradual withdrawal of sympathetic activity and to the clearance of stress system metabolites [30]. It is unknown whether the sympathetic nervous system follows a different correlation pattern from the parasympathetic nervous system with metabolic risk. The strengths of our study included a relatively large sample of children and adolescents and an objective measure of PA. There were also a number of limitations. The cross-sectional study only provides suggestive evidence concerning causal relationships of obesity traits and related cardiometabolic risk factors and HRR. In this report, we were restricted to only one measure estimating autonomic function. Previous research has validated HRR as an estimate of parasympathetic reactivation after exercise [1], but it would be useful to confirm these findings using other markers that might estimate autonomic innervations or resting cardiovascular autonomic control in addition to response to provocation. The absence of internationally accepted and adopted exercise recovery protocols represents a major limitation in comparing reports [31]. In summary, the present findings indicated an inverse association of HRR with obesity traits and related cardiometabolic risk factors mainly in healthy boys. Longitudinal studies are needed to corroborate these findings.
Conflict of interest No conflict of interests.
Acknowledgements We would like to thank the ‘Viceconsejerı´a de Deportes’ through the Sports Medicine Center in the Community of Madrid in Spain for providing funding for this study. The study was also partially funded by the Spanish Ministry of Science and Innovation (RYC-2010-05957). We would also like to acknowledge all EYHS group leaders who assisted us in implementing the study. Finally to all participating schools, who made this study possible.
[1] Imai K, Sato H, Hori M, Kusuoka H, Ozaki H, Yokoyama H, et al. Vagally mediated heart rate recovery after exercise is accelerated in athletes but blunted in patients with chronic heart failure. J Am Coll Cardiol 1994;24:1529e35. [2] Ohuchi H, Suzuki H, Yasuda K, Arakaki Y, Echigo S, Kamiya T. Heart rate recovery after exercise and cardiac autonomic nervous activity in children. Pediatr Res 2000;47:329e35. [3] Schwartz PJ, La Rovere MT, Vanoli E. Autonomic nervous system and sudden cardiac death. Experimental basis and clinical observations for post-myocardial infarction risk stratification. Circulation 1992;85:I77e91. [4] Cole CR, Blackstone EH, Pashkow FJ, Snader CE, Lauer MS. Heart-rate recovery immediately after exercise as a predictor of mortality. N Engl J Med 1999;341:1351e7. [5] Singh TP, Rhodes J, Gauvreau K. Determinants of heart rate recovery following exercise in children. Med Sci Sports Exerc 2008;40:601e5. [6] Lin LY, Kuo HK, Lai LP, Lin JL, Tseng CD, Hwang JJ. Inverse correlation between heart rate recovery and metabolic risks in healthy children and adolescents: insight from the National Health and Nutrition Examination Survey 1999e2002. Diabetes Care 2008;31:1015e20. [7] Daniels SR, Jacobson MS, McCrindle BW, Eckel RH, Sanner BM. American heart association childhood obesity research summit: executive summary. Circulation 2009;119:2114e23. [8] Lee YS. Consequences of childhood obesity. Ann Acad Med Singapore 2009;38:75e7. [9] Carnethon MR, Sternfeld B, Liu K, Jacobs Jr DR, Schreiner PJ, Williams OD, et al. Correlates of heart rate recovery over 20 years in a healthy population sample. Med Sci Sports Exerc 2012;44:273e9. [10] Jouven X, Empana JP, Schwartz PJ, Desnos M, Courbon D, Ducimetiere P. Heart-rate profile during exercise as a predictor of sudden death. N Engl J Med 2005;352:1951e8. [11] Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Books; 1991. [12] Ekelund U, Sardinha LB, Anderssen SA, Harro M, Franks PW, Brage S, et al. Associations between objectively assessed physical activity and indicators of body fatness in 9- to 10-yold European children: a population-based study from 4 distinct regions in Europe (The European Youth Heart Study). Am J Clin Nutr 2004;80:584e90. [13] Gutin B, Litaker M, Islam S, Manos T, Smith C, Treiber F. Bodycomposition measurement in 9-11-y-old children by dualenergy X-ray absorptiometry, skinfold-thickness measurements, and bioimpedance analysis. Am J Clin Nutr 1996;63: 287e92. [14] Park MK, Menard SM. Accuracy of blood pressure measurement by the Dinamap monitor in infants and children. Pediatrics 1987;79:907e14. [15] Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412e9. [16] Brage S, Wedderkopp N, Franks PW, Andersen LB, Froberg K. Reexamination of validity and reliability of the CSA monitor in walking and running. Med Sci Sports Exerc 2003;35:1447e54. [17] Ekelund U, Yngve A, Sjostrom M, Westerterp K. Field evaluation of the Computer Science and Application’s Inc. activity monitor during running and skating training in adolescent athletes. Int J Sports Med 2000;21:586e92. [18] Trost SG, Ward DS, Moorehead SM, Watson PD, Riner W, Burke JR. Validity of the computer science and applications (CSA) activity monitor in children. Med Sci Sports Exerc 1998;30:629e33.
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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Heart rate recovery vs. obesity traits/cardiometabolic risk factors [19] Riddoch CJ, Bo Andersen L, Wedderkopp N, Harro M, KlassonHeggebo L, Sardinha LB, et al. Physical activity levels and patterns of 9- and 15-yr-old European children. Med Sci Sports Exerc 2004;36:86e92. [20] Martinez-Vizcaino V, Martinez MS, Aguilar FS, Martinez SS, Gutierrez RF, Lopez MS, et al. Validity of a single-factor model underlying the metabolic syndrome in children: a confirmatory factor analysis. Diabetes Care 2010;33:1370e2. [21] Kuipers H, Verstappen FT, Keizer HA, Geurten P, van Kranenburg G. Variability of aerobic performance in the laboratory and its physiologic correlates. Int J Sports Med 1985;6:197e201. [22] Kreier F, Fliers E, Voshol PJ, Van Eden CG, Havekes LM, Kalsbeek A, et al. Selective parasympathetic innervation of subcutaneous and intra-abdominal fatdfunctional implications. J Clin Invest 2002;110:1243e50. [23] Shishehbor MH, Hoogwerf BJ, Lauer MS. Association of triglyceride-to-HDL cholesterol ratio with heart rate recovery. Diabetes Care 2004;27:936e41. [24] Kreier F, Yilmaz A, Kalsbeek A, Romijn JA, Sauerwein HP, Fliers E, et al. Hypothesis: shifting the equilibrium from activity to food leads to autonomic unbalance and the metabolic syndrome. Diabetes 2003;52:2652e6.
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[25] Carnethon MR, Jacobs Jr DR, Sidney S, Liu K. Influence of autonomic nervous system dysfunction on the development of type 2 diabetes: the CARDIA study. Diabetes Care 2003;26:3035e41. [26] Grassi G. Sympathetic overdrive and cardiovascular risk in the metabolic syndrome. Hypertens Res 2006;29:839e47. [27] Landsberg L. Role of the sympathetic adrenal system in the pathogenesis of the insulin resistance syndrome. Ann N Y Acad Sci 1999;892:84e90. [28] Kizilbash MA, Carnethon MR, Chan C, Jacobs DR, Sidney S, Liu K. The temporal relationship between heart rate recovery immediately after exercise and the metabolic syndrome: the CARDIA study. Eur Heart J 2006;27:1592e6. [29] Nilsson G, Hedberg P, Jonason T, Lonnberg I, Ohrvik J. Heart rate recovery is more strongly associated with the metabolic syndrome, waist circumference, and insulin sensitivity in women than in men among the elderly in the general population. Am Heart J 2007;154(460):e1e7. [30] Buchheit M, Papelier Y, Laursen PB, Ahmaidi S. Noninvasive assessment of cardiac parasympathetic function: postexercise heart rate recovery or heart rate variability? Am J Physiol Heart Circulatory Physiol 2007;293:H8e10. [31] Lauer MS. Heart rate recovery: what now? J Intern Med 2011; 270:597e9.
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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Nutrition, Metabolism & Cardiovascular Diseases (2012) xx, 1e7
Available online at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/nmcd
Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents M. Laguna a, S. Aznar a,*, M.T. Lara b, A. Lucı´a c, J.R. Ruiz d,e a
PAFS-UCLM Research Group, Faculty of Sports Sciences, University of Castilla-La Mancha, Avda. Carlos III, s/n. 45071, Toledo, Spain b Sport Medical Center, Juan Esplandiu´ Street, 1, 28007, Community of Madrid, Madrid, Spain c School of Doctoral Studies & Research, European University of Madrid, Tajo Street, s/n. 28670, Villaviciosa de Odo´n, Madrid, Spain d Department of physical education and sport, School of Sport Sciences, University of Granada, Alfacar Road, s/n. 18011 Granada, Spain e Department of Biosciences and Nutrition at NOVUM, Unit for Preventive Nutrition, Karolinska Institutet, Huddinge, Sweden Received 24 July 2012; received in revised form 20 September 2012; accepted 3 October 2012
KEYWORDS Adolescent; Autonomic function; Child; Heart rate recovery; Multiple linear regression; Physical activity
Abstract Background and aims: Increased vagal activity is associated with obesity and metabolic risk in children and adolescents. The aim of the present cross-sectional study was to examine the association of parasympathetic function, as assessed by heart rate recovery (HRR) from a maximal exercise cycle-ergometer test, with obesity traits and related cardiometabolic risk factors in Spanish children and adolescents. Methods and results: A sample of 437 Spanish 9-year-old-children and 235 15-year-old-adolescents participated in the study. The variables measured were anthropometric characteristics (height, body mass and waist circumference) and physical activity using the Actigraph accelerometer. Additional measured outcomes included fasting insulin, triglycerides, high-density lipoprotein cholesterol (HDLc) and blood pressure. A metabolic risk score was computed as the mean of the standardised outcomes scores. The HRR was calculated as the difference between peak heart rate and heart rate 1, 3 and 5 min after cessation of the maximal ergometer test. Diastolic blood pressure was associated with all the HRR parameters in 9-year-oldgirls. In 9-year-old-boys, the 3-min HRR was inversely associated with systolic blood pressure (p < 0.05) and Homeostasis Model Assessment (HOMA) (p < 0.05). Five minute HRR was inversely associated with waist circumference (p < 0.05), sum of five skinfolds (p < 0.01) and HOMA (p Z 0.004). There were no significant associations in adolescents. In 9-year-oldgirls, the adjusted 5-min HRR showed significant differences between quartile 2 and 4 of
* Corresponding author. Tel.: þ34 925 268 800x5521; fax: þ34 925 268 846. E-mail address: [email protected] (S. Aznar). 0939-4753/$ - see front matter ª 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.numecd.2012.10.002
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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M. Laguna et al. metabolic risk (p Z 0.011). In all samples, the adjusted HRR (1-, 3- and 5-min HRR) did not show significant differences across quartiles. Conclusion: HRR was inversely associated with obesity traits and related cardiometabolic risk factors mainly in healthy boys. ª 2012 Elsevier B.V. All rights reserved.
Recovery of the heart rate immediately after exercise is mediated by vagal reactivation [1,2]. Later recovery depends on a combination of vagal tone and withdrawal of sympathetic drive [1,2]. Reduced vagal activity is a powerful predictor of overall mortality [3,4] and has been associated with obesity [5] and metabolic risk [6] in children and adolescents. As the presence of childhood obesity conveys cardiometabolic complications such as insulin resistance and hypertension [7,8], it is possible that the adverse effects of childhood obesity on heart rate recovery (HRR) might also take place early in life. The central efferent parasympathetic control of heart rate is greater in children than in young adults and, thus, HRR after exercise is faster in children compared with young adults [2]. Several studies showed that 1-min HRR after exercise is attenuated with age [5,9], and having a slow HRR in early middle age is associated with traditional cardiovascular disease risk factors [9]. HRR is a marker independent of cardiovascular risk factors [4,10] which are not influenced by motivational factors. Other indicators may be influenced by several reasons (motivation, etc.) during a maximal exercise cycleergometer test because children and adolescents may not achieve the real VO2 peak. Assessing the association of HRR with obesity traits and related cardiometabolic risk factors in youth is of clinical interest because HRR is associated with all-cause mortality and sudden cardiac death in adults [3,4,10]. Several studies investigated the association of HRR with metabolic risk [6] and body mass index (BMI) [5] in adolescents, yet less is known regarding the association between HRR and other obesity traits and related cardiometabolic disease risk factors in adolescents as well as in younger populations. The aim of the present cross-sectional study was to examine the association of HRR from a maximal exercise cycle-ergometer test, with obesity traits and related cardiometabolic risk factors in Spanish children and adolescents.
Methods
sample was randomly selected using a two-stage cluster sample procedure, with schools in Madrid as primary sampling units. The secondary units were the children within the schools, and equal numbers of children were sampled randomly from each school. Data collection from the Spanish part of the EYHS took place in 2008e2010. Ethical approval was obtained by the Health Institute Carlos III in Madrid, Spain, and parental informed consent was obtained for each subject prior to data collection.
Measurement Anthropometric characteristics Height was measured using a Holtain stadiometer without shoes and recorded to the nearest millimetre. Body mass was measured to the nearest 0.1 kg with a calibrated beam balance scale in light clothing. BMI was calculated as body mass (kg) divided by height (m) squared. Skinfold thickness (biceps, triceps, subscapular, suprailiac and triceps surae) was measured to the nearest 0.2 mm in triplicate on the left side with a Holtain calliper [11]. The sum of five skinfold thicknesses was used as an indicator of body fat rather than BMI, because it has been suggested that BMI is not a good measurement of body fat in children [12]. Skinfold thickness has been shown to correlate highly with dualenergy X-ray absorptiometry-measured body fat percentage in children of similar ages [13]. Waist circumference was measured with an inelastic tape at the midpoint between the iliac crest and the lowest rib, using the mean of two measures for the analysis. Blood pressure Systolic and diastolic blood pressure (mmHg) were measured with an automatic oscillometric method (Dinamap model XL, Critikon, Inc., Tampa, FL, USA). The equipment has been validated in children and adolescents [14]. The subject was in a seated and relaxed position and the measurements were taken within a 10-min interval. The mean of the last three measurements of both diastolic and systolic blood pressure were used in the analysis.
Sample A total of 1395 children and adolescents from the Community of Madrid, Spain, participated in the European Youth Heart Study (EYHS). The EYHS is a school-based, cross-sectional study designed to examine the interactions between personal, environmental and lifestyle influences on the risk factor for future cardiovascular diseases in several European countries. All eligible schools were stratified according to location (urban, suburban and rural) and the socioeconomic profile of the uptake area (high, middle and low). The study
Blood samples The fasting venous (antecubital vein) samples were obtained after an overnight fast. Samples were stored at 80 C and analysed for serum high-density lipoprotein cholesterol (HDLc), triglyceride and insulin. HDLc was analysed using the homogeneous polyanion/cholesterol esterase/oxidase enzymatic method. Triglyceride levels were determined using the lipase/glycerol kinase/glycerol phosphate oxidase enzymatic method. Blood lipids were measured on an Olympus AU600 autoanalyser (Olympus Diagnostica, Hamburg, Germany). Insulin was analysed
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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Heart rate recovery vs. obesity traits/cardiometabolic risk factors using an enzyme immunoassay (microtitre plate format; Dako Diagnostics, Ely, U.K.). Glucose was analysed by the hexokinase method. Each of the above blood variables was measured on an Olympus autoanalyser (model AU600, Olympus Diagnostica GmbH, Hamburg, Germany). The homeostasis model assessment (HOMA) was calculated as (fasting insulin fasting glucose)/22.5, where fasting insulin is measured in mU l1 and fasting glucose is measured in mmol l1 [15]. Physical activity measurement Physical activity was measured during 6 consecutive days (from Thursday to Tuesday or from Friday to Wednesday) using the MTI accelerometer, model GT1M activity monitor. All children wore the accelerometer in an elastic waistband on the right hip during the daytime, except while bathing or during other aquatic activities. Verbal and written instructions for the care and placement of the monitor were given to both, children and their parents. GT1M is a lightweight (27 g) and small (4.5 3.5 1.0 cm), singleplane (vertical) accelerometer. Movement in a vertical plane is detected as a combined function of the frequency and the intensity of the movement, while an electronic filter rejects motion outside the range of normal human movement. Validation studies indicate that this accelerometer yields valid and reliable measurement of children’s physical activity, that is, a high correlation (r Z 0.86) with energy expenditure assessed by indirect calorimetry, as well as a high degree of inter-instrument reliability [16e18]. For data to be considered valid, two criteria were established: a minimum of data for a period of 4 days including one weekend day and a minimum of 10 registered h day1 [12]. To analyse the accelerometer data, Kinesoft software, developed specifically for the Actical and Actigraph accelerometers, was used. The outcome variables were expressed as average intensity (counts per min). Therefore, we calculated mean counts per min by dividing the sum of total counts per epoch (15 s) for a valid day by the number of min of wear time in that day across all valid days. We excluded from the analysis bouts of 20 continuous minutes of activity with intensity counts of 0, considering these periods to be non-wearing time [19]. Metabolic risk The metabolic risk score was computed from the following variables: waist circumference, insulin, HDLc, triglycerides/HDLc ratio and mean arterial pressure [20]. Each of these variables was standardised as follows: standardised value Z (value e mean)/SD. The metabolic risk score was calculated as the mean of the four standardised scores separately for boys and girls. Exercise testing All participants performed a maximum cycle-ergometer test. The workload was pre-programmed on a computerised cycle ergometer (Monark 829E, Ergomedic, Vansbro, Sweden) to increase after every 3 min until exhaustion. The cycle ergometer was electronically calibrated once every test day and mechanically calibrated after being moved between schools. Criteria for exhaustion were attaining a heart rate 185 beats per min or failure to maintain a pedalling frequency of at least 30 revolutions per min.
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The peak power output was calculated as being equal to W1 þ (W2 $ t/180), where W1 is a work rate at fully completed stage, W2 is the work rate increment at final incomplete stage, and t is time in s at final incomplete stage [21]. Heart rate was monitored continuously (Polar Vantage, Kempele, Finland) throughout the test. The HRR was defined as the change from peak heart rate during exercise to that measured after 1, 3 or 5 min of recovery as stated in the EYHS protocol. Peak heart rate was the highest value obtained by the heart rate monitor set at 5-s interval, during the maximal exercise cycle-ergometer test.
Statistical analysis Tests of normality, symmetry and kurtosis were conducted. Mean SD was used to describe the physical characteristics and all physical activity variables. Independent t-tests were used to examine sex differences for continuous variables and the chi-squared test was used for nominal variables. The correlation of each HRR parameter (HRR 1 min, 3 min and 5 min) with obesity traits and related cardiometabolic risk factors were derived by Pearson correlation analysis. The strength of the association of each HRR parameter with obesity traits and related cardiometabolic risk factors was estimated by multiple linear regression models after controlling for age and physical activity. Finally, differences between HRR parameters according to quartiles of metabolic risk were analysed by one-way analysis of covariance (ANCOVA), with HRR variables as dependent variables (each in a separate model), quartiles of metabolic risk as fixed factor and age and total physical activity as covariates. Differences among quartiles were assessed by the post hoc Bonferroni test. The level of significance was set at p < 0.05. All analyses were performed by using the Statistical Package for Social Sciences (SPSS, v 19.0).
Results A total of 914 children and adolescents agreed to wear an accelerometer and 672 (437 children aged 9 years (range 8e10), and 235 adolescents aged 15 years (range 14e16)) returned the accelerometer after satisfying the aforementioned validity criteria. Participants who provided valid accelerometer recordings did not differ significantly in the study variables from children who did not provide valid recording (all p > 0.1). The characteristics of the study sample are shown in Table 1. In 9 year-old children, short-term HRR (1-min HRR) was negatively correlated with systolic blood pressure (r Z 0.136, p < 0.05) in boys and with diastolic blood pressure (r Z 0.172, p < 0.01) in girls (Table 2). Threemin HRR was negatively correlated with systolic blood pressure (r Z 0.155, p < 0.05) and with HOMA (r Z 0.176, p Z 0.011) in boys. In girls, 3-min HRR was negatively correlated with systolic blood pressure (r Z 0.169, p Z 0.011), diastolic blood pressure (r Z 0.219, p Z 0.001) and HDL (r Z 0.136, p < 0.05). Five-minute HRR was negatively correlated with waist circumference (r Z 0.150, p < 0.05), sum of five skinfolds (r Z 0.192, p Z 0.005) and HOMA (r Z 0.215, p Z 0.002) in boys and with diastolic blood pressure
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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M. Laguna et al. Table 1
Descriptive characteristics of the study sample. Children
Adolescents
Girls n Age (years) Height (cm) Body mass (kg) BMI (Kg/m2) Waist circumference (cm) Sum of 5 skinfolds (mm) SBP (mmHg) DBP (mmHg) Triglycerides (mg/dl) HDL (mg/dl) HOMA Total physical activity (cpm) Maximum heart rate (beats/min) Recovery 1 heart rate (per min) Recovery 3 heart rate (per min) Recovery 5 heart rate (per min) HRR 1 HRR 3 HRR 5
227 9.2 140.1 36.4 18.4 64.8 71.7 106.5 64.8 62.0 24.4 0.3 541.6 188.4 149.1 129.2 108.3 39.3 59.2 80.1
Boys
0.5 6.4 7.8 3.1 8.5 26.5 10.7 7.6 28.2 5.3 0.3 300.1 7.5 12.9 15.2 16.2 11.8 13.4 15.8
210 9.2 138.5 35.1 18.2 64.3 61.0 106.7 65.3 55.4 25.7 0.2 636.0 187.8 143.3 123.8 101.4 44.5 64.0 86.4
0.4 6.0 7.5 3.0 8.1 28.2 10.0 7.1 26.2 5.4 0.2 337.5 6.7 14.1 14.9 12.7 13.8 14.7 13.7
p
Girls
0.206 0.012 0.086 0.405 0.538 <0.001 0.824 0.505 0.012 0.013 0.001 0.002 0.356 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001
108 15.0 162.4 56.1 21.3 72.2 79.8 110.4 65.9 57.4 23.7 0.3 427.9 185.6 159.2 138.5 118.1 26.4 47.1 67.5
Boys
0.6 6.8 7.5 2.5 7.4 22.8 12.0 7.5 20.7 4.5 0.3 132.0 7.9 11.6 14.4 15.1 11.0 12.9 13.9
127 14.9 171.1 63.0 21.5 74.2 56.4 118.2 68.2 59.0 21.4 0.3 490.2 187.3 155.6 133.7 114.5 31.6 53.5 72.7
p
0.6 7.5 13.6 4.3 6.1 20.7 12.2 8.0 31.5 3.9 0.2 153.9 8.3 12.3 14.4 14.4 12.5 13.9 14.3
0.718 <0.001 <0.001 0.672 0.022 <0.001 <0.001 0.023 0.648 <0.001 0.109 0.001 0.119 0.025 0.012 0.062 0.001 <0.001 0.005
Data are mean SD. BMI Z Body mass index, cpm Z counts per minute, DBP Z Diastolic blood pressure, HDL Z High-density lipoprotein, HOMA Z Homeostasis model assessment, HRR Z Heart rate recovery, SBP Z Systolic blood pressure.
(r Z 0.156, p Z 0.019) in girls. In adolescents, we observed no significant correlations of any of the HRR parameters with obesity traits and related cardiometabolic risk factors. Multiple linear regression analysis (Table 3) showed that among the seven study components of obesity traits and related cardiometabolic risk factors, diastolic blood pressure was the only variable associated with all the HRR parameters in 9-year-old girls. In 9 year-old boys, 3-min HRR was inversely associated with systolic blood pressure (p < 0.05) and HOMA (p < 0.05). Five-minute HRR was inversely associated with waist circumference (p < 0.05), sum of five skinfolds (p < 0.01) and HOMA (p Z 0.004). There were no significant associations in adolescents. To consider the cardiometabolic risk factors as a whole, we calculated the metabolic risk to represent the severity of the cluster of the metabolic risk by a single value. In children, the adjusted 1-min HRR and 3-min HRR did not show significant differences across quartiles (Fig. 1). For 5min HRR, we observed a negative association in 9-year-old girls (p Z 0.021), and post hoc analysis showed that the 5min HRR adjusted-mean was significantly different between quartiles 2 and 4 of metabolic risk in 9-year-old girls (p Z 0.011) (Fig. 1). In adolescents, the adjusted HRR (1, 3 and 5 min) did not show significant differences across quartiles (Fig. 2).
Discussion The main findings of the present study suggest an inverse association of HRR with obesity traits and related cardiometabolic risk factors mainly in boys. No association between HRR and obesity traits was observed in girls or
adolescents. Because the prevalence of obesity and associated metabolic disorders has increased over the past 3 decades among children of all ages [7,8], it is of clinical importance to investigate whether the link between impaired obesity traits and related cardiometabolic risk factors and HRR appears already in children and adolescents [6]. Moreover, enhanced central parasympathetic modulation may play an important role in protecting cardiac overload in children with frequent short intervals of physical activity [2]. Studies conducted up to now have established that the autonomic nervous system plays a central role in the development of obesity traits [22] and the metabolic syndrome [23e27] in adults. According to previous studies [25,28], decreased HRR occurs after, but not before, the presence of the metabolic syndrome. This association also seems to exist in children because we observed that most of the study variables (waist circumference, sum of five skinfolds, systolic blood pressure, diastolic blood pressure, HDL and HOMA) were associated with HRR parameters (1-, 3- and 5-min HRR). Our findings confirm that the association between HRR and metabolic risks operates early in young ages [6]. However, there were no associations of HRR with obesity traits and related cardiometabolic risk factors in adolescents and therefore, the association could not be confirmed in this group. One previous report [6] found that among 15-year-old adolescents, 1-, 2- and 3-min HRR was not associated with diastolic blood pressure, triglycerides and HDL, which concurs with our study results. It is biologically plausible that changes that occur during adolescence (hormonal and physiological) may mask the relationship of HRR with obesity traits and related cardiometabolic risk factors at these ages. Further studies are warranted.
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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Heart rate recovery vs. obesity traits/cardiometabolic risk factors Table 2 Correlation coefficients (r) showing the association between heart rate recovery at 1 (HRR 1), 3 (HRR 3) and 5 min post exercise (HRR 5) and obesity traits and related and cardiometabolic risk factors. Children Boys r
Adolescents Girls
p
r
Waist circumference (cm) HRR 1 0.019 NS 0.021 HRR 3 0.030 NS 0.031 HRR 3 0.150 0.029 0.022 Sum of 5 skinfolds (mm) HRR 1 0.119 NS 0.041 HRR 3 0.026 NS 0.033 HRR 5 0.192 0.005 0.088 SBP (mmHg) HRR 1 0.136 0.049 0.097 HRR 3 0.155 0.025 0.169 HRR 5 0.094 NS 0.034 DBP (mmHg) HRR 1 0.061 NS 0.172 HRR 3 0.076 NS 0.219 HRR 5 0.129 NS 0.156 Triglycerides (mg/dl) HRR 1 0.135 NS 0.116 HRR 3 0.026 NS 0.004 HRR 5 0.108 NS 0.087 HDL cholesterol (mg/dl) HRR 1 0.017 NS 0.003 HRR 3 0.000 NS 0.136 HRR 5 0.103 NS 0.020 HOMA HRR 1 0.133 NS 0.068 HRR 3 0.176 0.011 0.103 HRR 5 0.215 0.002 0.129
Boys
Girls
p
r
p
NS NS NS
0.077 NS 0.011 NS 0.016 NS
r
p
5
Table 3 Standardized correlation coefficients (b) from multiple linear regression analysis showing the association of heart rate recovery at 1 (HRR 1), 3 (HRR 3) and 5 min post exercise (HRR 5) with obesity traits and related cardiometabolic risk factors after controlling for age and physical activity. Children Boys
NS NS NS
0.125 NS 0.119 NS 0.088 NS
0.003 NS 0.029 NS 0.120 NS 0.131 NS 0.080 NS 0.024 NS
NS 0.058 NS 0.023 NS 0.011 0.068 NS 0.109 NS NS 0.028 NS 0.024 NS 0.009 0.014 NS 0.112 NS 0.001 0.018 NS 0.174 NS 0.019 0.018 NS 0.096 NS NS NS NS
0.042 NS 0.046 NS 0.027 NS 0.080 NS 0.020 NS 0.118 NS
NS 0.041 NS
0.074 NS 0.058 NS 0.002 NS 0.133 NS 0.030 NS 0.112 NS
NS NS NS
0.074 NS 0.154 NS 0.150 NS 0.156 NS 0.032 NS 0.109 NS
DBP Z Diastolic blood pressure, HDL Z High-density lipoprotein, HOMA Z Homeostasis model assessment, NS Z Not significant, SBP Z Systolic blood pressure.
We showed that the association between HRR and waist circumference was higher in boys. Our results concur with previous studies in adolescents that showed a strong relationship between HRR and waist circumference in both sexes [6]. However, we did not find a significant association in girls between these variables. In contrast, several cardiometabolic risk factors such as diastolic blood pressure and HDL related only in girls, which concur with the findings reported by Nilsson et al. [29] They showed that HRR is more closely associated with the metabolic syndrome in women than in men. However, these results were obtained in an elderly population and no data are still available in children. In the present study, multiple linear regression analysis showed that obesity traits and related cardiometabolic risk factors contribute more to the variation of the 3- or 5-min HRR compared with that of the 1-min HRR, similar to another recent study in American adolescents [6]. It has been suggested that short-term HRR indices (such as 1-min
b
Adolescents Girls
p
b
Waist circumference (cm) HRR 1 0.037 NS 0.019 HRR 3 0.011 NS 0.032 HRR 5 0.138 0.046 0.022 Sum of 5 skinfolds (mm) HRR 1 0.098 NS 0.044 HRR 3 0.011 NS 0.031 HRR 5 0.185 0.007 0.089 SBP (mmHg) HRR 1 0.126 NS 0.104 HRR 3 0.143 0.037 0.162 HRR 5 0.085 NS 0.037 DBP (mmHg) HRR 1 0.835 NS 0.167 HRR 3 0.063 NS 0.227 HRR 5 0.119 NS 0.154 Triglycerides (mg/dl) HRR 1 0.114 NS 0.118 0.009 HRR 3 0.010 NS HRR 5 0.099 NS 0.088 HDL (mg/dl) HRR 1 0.029 NS 0.000 HRR 3 0.014 NS 0.132 HRR 5 0.093 NS 0.021 HOMA HRR 1 0.108 NS 0.077 HRR 3 0.149 0.031 0.098 HRR 5 0.198 0.004 0.134
Boys
Girls
p
b
NS NS NS
0.072 NS 0.021 NS 0.006 NS
NS NS NS
p
b
p 0.137 NS 0.108 NS 0.080 NS
0.004 NS 0.045 NS 0.116 NS 0.123 NS 0.066 NS 0.031 NS
NS 0.062 NS 0.022 NS 0.015 0.071 NS 0.101 NS NS 0.022 NS 0.035 NS 0.012 0.009 NS 0.121 NS 0.001 0.025 NS 0.167 NS 0.021 0.035 NS 0.092 NS NS NS NS
0.033 NS 0.044 NS 0.023 NS 0.078 NS 0.010 NS 0.115 NS
NS 0.047 NS
0.095 NS 0.058 NS 0.010 NS 0.135 NS 0.049 NS 0.114 NS
NS 0.081 NS 0.153 NS NS 0.146 NS 0.154 NS 0.046 0.020 NS 0.107 NS
DBP Z Diastolic blood pressure, HDL Z High-density lipoprotein, HOMA Z Homeostasis model assessment, NS Z Not significant, SBP Z Systolic blood pressure.
Figure 1 Mean values of adjusted heart rate recovery among quartiles of metabolic risk for 9 yr-old boys (C) and girls (B). Symbol: p < 0.05 between quartile 2 and 4 in girls. Abbreviation: HRR Z heart rate recovery.
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
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M. Laguna et al.
References
Figure 2 Mean values of adjusted heart rate recovery among quartiles of metabolic risk for 15 yr-old boys (C) and girls (B). Abbreviation: HRR Z heart rate recovery.
HRR) could be considered as markers of cardiac parasympathetic outflow [2,30]. In contrast, the second slow heart rate decay phase is thought to be related to the gradual withdrawal of sympathetic activity and to the clearance of stress system metabolites [30]. It is unknown whether the sympathetic nervous system follows a different correlation pattern from the parasympathetic nervous system with metabolic risk. The strengths of our study included a relatively large sample of children and adolescents and an objective measure of PA. There were also a number of limitations. The cross-sectional study only provides suggestive evidence concerning causal relationships of obesity traits and related cardiometabolic risk factors and HRR. In this report, we were restricted to only one measure estimating autonomic function. Previous research has validated HRR as an estimate of parasympathetic reactivation after exercise [1], but it would be useful to confirm these findings using other markers that might estimate autonomic innervations or resting cardiovascular autonomic control in addition to response to provocation. The absence of internationally accepted and adopted exercise recovery protocols represents a major limitation in comparing reports [31]. In summary, the present findings indicated an inverse association of HRR with obesity traits and related cardiometabolic risk factors mainly in healthy boys. Longitudinal studies are needed to corroborate these findings.
Conflict of interest No conflict of interests.
Acknowledgements We would like to thank the ‘Viceconsejerı´a de Deportes’ through the Sports Medicine Center in the Community of Madrid in Spain for providing funding for this study. The study was also partially funded by the Spanish Ministry of Science and Innovation (RYC-2010-05957). We would also like to acknowledge all EYHS group leaders who assisted us in implementing the study. Finally to all participating schools, who made this study possible.
[1] Imai K, Sato H, Hori M, Kusuoka H, Ozaki H, Yokoyama H, et al. Vagally mediated heart rate recovery after exercise is accelerated in athletes but blunted in patients with chronic heart failure. J Am Coll Cardiol 1994;24:1529e35. [2] Ohuchi H, Suzuki H, Yasuda K, Arakaki Y, Echigo S, Kamiya T. Heart rate recovery after exercise and cardiac autonomic nervous activity in children. Pediatr Res 2000;47:329e35. [3] Schwartz PJ, La Rovere MT, Vanoli E. Autonomic nervous system and sudden cardiac death. Experimental basis and clinical observations for post-myocardial infarction risk stratification. Circulation 1992;85:I77e91. [4] Cole CR, Blackstone EH, Pashkow FJ, Snader CE, Lauer MS. Heart-rate recovery immediately after exercise as a predictor of mortality. N Engl J Med 1999;341:1351e7. [5] Singh TP, Rhodes J, Gauvreau K. Determinants of heart rate recovery following exercise in children. Med Sci Sports Exerc 2008;40:601e5. [6] Lin LY, Kuo HK, Lai LP, Lin JL, Tseng CD, Hwang JJ. Inverse correlation between heart rate recovery and metabolic risks in healthy children and adolescents: insight from the National Health and Nutrition Examination Survey 1999e2002. Diabetes Care 2008;31:1015e20. [7] Daniels SR, Jacobson MS, McCrindle BW, Eckel RH, Sanner BM. American heart association childhood obesity research summit: executive summary. Circulation 2009;119:2114e23. [8] Lee YS. Consequences of childhood obesity. Ann Acad Med Singapore 2009;38:75e7. [9] Carnethon MR, Sternfeld B, Liu K, Jacobs Jr DR, Schreiner PJ, Williams OD, et al. Correlates of heart rate recovery over 20 years in a healthy population sample. Med Sci Sports Exerc 2012;44:273e9. [10] Jouven X, Empana JP, Schwartz PJ, Desnos M, Courbon D, Ducimetiere P. Heart-rate profile during exercise as a predictor of sudden death. N Engl J Med 2005;352:1951e8. [11] Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Books; 1991. [12] Ekelund U, Sardinha LB, Anderssen SA, Harro M, Franks PW, Brage S, et al. Associations between objectively assessed physical activity and indicators of body fatness in 9- to 10-yold European children: a population-based study from 4 distinct regions in Europe (The European Youth Heart Study). Am J Clin Nutr 2004;80:584e90. [13] Gutin B, Litaker M, Islam S, Manos T, Smith C, Treiber F. Bodycomposition measurement in 9-11-y-old children by dualenergy X-ray absorptiometry, skinfold-thickness measurements, and bioimpedance analysis. Am J Clin Nutr 1996;63: 287e92. [14] Park MK, Menard SM. Accuracy of blood pressure measurement by the Dinamap monitor in infants and children. Pediatrics 1987;79:907e14. [15] Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412e9. [16] Brage S, Wedderkopp N, Franks PW, Andersen LB, Froberg K. Reexamination of validity and reliability of the CSA monitor in walking and running. Med Sci Sports Exerc 2003;35:1447e54. [17] Ekelund U, Yngve A, Sjostrom M, Westerterp K. Field evaluation of the Computer Science and Application’s Inc. activity monitor during running and skating training in adolescent athletes. Int J Sports Med 2000;21:586e92. [18] Trost SG, Ward DS, Moorehead SM, Watson PD, Riner W, Burke JR. Validity of the computer science and applications (CSA) activity monitor in children. Med Sci Sports Exerc 1998;30:629e33.
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002
+
MODEL
Heart rate recovery vs. obesity traits/cardiometabolic risk factors [19] Riddoch CJ, Bo Andersen L, Wedderkopp N, Harro M, KlassonHeggebo L, Sardinha LB, et al. Physical activity levels and patterns of 9- and 15-yr-old European children. Med Sci Sports Exerc 2004;36:86e92. [20] Martinez-Vizcaino V, Martinez MS, Aguilar FS, Martinez SS, Gutierrez RF, Lopez MS, et al. Validity of a single-factor model underlying the metabolic syndrome in children: a confirmatory factor analysis. Diabetes Care 2010;33:1370e2. [21] Kuipers H, Verstappen FT, Keizer HA, Geurten P, van Kranenburg G. Variability of aerobic performance in the laboratory and its physiologic correlates. Int J Sports Med 1985;6:197e201. [22] Kreier F, Fliers E, Voshol PJ, Van Eden CG, Havekes LM, Kalsbeek A, et al. Selective parasympathetic innervation of subcutaneous and intra-abdominal fatdfunctional implications. J Clin Invest 2002;110:1243e50. [23] Shishehbor MH, Hoogwerf BJ, Lauer MS. Association of triglyceride-to-HDL cholesterol ratio with heart rate recovery. Diabetes Care 2004;27:936e41. [24] Kreier F, Yilmaz A, Kalsbeek A, Romijn JA, Sauerwein HP, Fliers E, et al. Hypothesis: shifting the equilibrium from activity to food leads to autonomic unbalance and the metabolic syndrome. Diabetes 2003;52:2652e6.
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[25] Carnethon MR, Jacobs Jr DR, Sidney S, Liu K. Influence of autonomic nervous system dysfunction on the development of type 2 diabetes: the CARDIA study. Diabetes Care 2003;26:3035e41. [26] Grassi G. Sympathetic overdrive and cardiovascular risk in the metabolic syndrome. Hypertens Res 2006;29:839e47. [27] Landsberg L. Role of the sympathetic adrenal system in the pathogenesis of the insulin resistance syndrome. Ann N Y Acad Sci 1999;892:84e90. [28] Kizilbash MA, Carnethon MR, Chan C, Jacobs DR, Sidney S, Liu K. The temporal relationship between heart rate recovery immediately after exercise and the metabolic syndrome: the CARDIA study. Eur Heart J 2006;27:1592e6. [29] Nilsson G, Hedberg P, Jonason T, Lonnberg I, Ohrvik J. Heart rate recovery is more strongly associated with the metabolic syndrome, waist circumference, and insulin sensitivity in women than in men among the elderly in the general population. Am Heart J 2007;154(460):e1e7. [30] Buchheit M, Papelier Y, Laursen PB, Ahmaidi S. Noninvasive assessment of cardiac parasympathetic function: postexercise heart rate recovery or heart rate variability? Am J Physiol Heart Circulatory Physiol 2007;293:H8e10. [31] Lauer MS. Heart rate recovery: what now? J Intern Med 2011; 270:597e9.
Please cite this article in press as: Laguna M, et al., Heart rate recovery is associated with obesity traits and related cardiometabolic risk factors in children and adolescents, Nutrition, Metabolism & Cardiovascular Diseases (2012), http://dx.doi.org/10.1016/ j.numecd.2012.10.002