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Original article
Associations between objectively measured physical activity intensity in childhood and measures of subclinical cardiovascular disease in adolescence: prospective observations from the European Youth Heart Study
  1. Mathias Ried-Larsen1,
  2. Anders Grøntved1,
  3. Niels Christian Møller1,
  4. Kristian Traberg Larsen1,
  5. Karsten Froberg1,
  6. Lars Bo Andersen1,2
  1. 1Research Unit for Exercise Epidemiology, Institute of Sport Science and Clinical Biomechanics, Centre of Research in Childhood Health, University of Southern Denmark, Odense M, Denmark
  2. 2Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway
  1. Correspondence to Mathias Ried-Larsen, Research Unit for Exercise Epidemiology, Institute of Sports Science and Clinical Biomechanics, Centre of Research in Childhood Health, University of Southern Denmark, Campusvej 55, Odense M 5230, Denmark; mried-Larsen{at}health.sdu.dk

Abstract

Background and aim No prospective studies have investigated the association between physical activity (PA) and carotid subclinical cardiovascular disease across childhood. Therefore, the primary aim was to investigate the association between PA intensity across childhood and carotid intima media thickness (cIMT) and stiffness in adolescence. Second, we included a clustered cardiovascular disease risk score as outcome.

Methods This was a prospective study of a sample of 254 children (baseline age 8–10 years) with a 6-year follow-up. The mean exposure and the change in minutes of moderate-and-vigorous and vigorous PA intensity were measured using the Actigraph activity monitor. Subclinical cardiovascular disease was expressed as cIMT, carotid arterial stiffness and secondarily as a metabolic risk z-score including the homoeostasis model assessment score of insulin resistance, triglycerides, total cholesterol to high-density lipoprotein ratio, inverse of cardiorespiratory fitness, systolic blood pressure and the sum of four skinfolds.

Results No associations were observed between PA intensity variables and cIMT or carotid arterial stiffness (p>0.05). Neither change in PA intensity (moderate-and-vigorous nor vigorous) nor mean minutes of moderate-and-vigorous PA intensity was associated to the metabolic risk z-score in adolescence (p>0.05). However, a significant inverse association was observed between mean minutes of vigorous PA and the metabolic risk z-score in adolescence independent of gender and biological maturity (standard β=–0.19 p=0.007).

Conclusions A high mean exposure to, or changes in, minutes spent at higher PA intensities across childhood was not associated to cIMT or stiffness in the carotid arteries in adolescence. Our observations suggest that a high volume of vigorous PA across childhood independently associated with lower metabolic cardio vascular disease risk in adolescence.

  • Cardiovascular epidemiology
  • Children's health and exercise
  • Health promotion through physical activity

https://doi.org/10.1136/bjsports-2012-091958

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    Introduction

    Increased carotid intima media thickness (cIMT) and arterial stiffness in adults are associated to future cardiovascular disease (CVD) events independent of conventional risk factors.1 ,2 Lack of regular engagement in physical activity (PA) in adulthood is a major risk factor for CVDs and premature death due to CVD.3 Thus, early adoption of PA habits already in childhood may be important for primary prevention. The PA level declines across childhood into adolescence.4 Little is known about how PA across childhood affects arterial health later in life as no studies, to the best of our knowledge, have investigated the associations between PA from childhood to adolescence and adolescent carotid arterial stiffening and cIMT. Several cross-sectional studies between arterial health and PA have been conducted in children, but the observations have been inconsistent.5–9 The vast majority of these studies have assessed PA using self-report. Self-reported PA is susceptible to non-differential misclassification and is particularly vulnerable to recall bias in childhood.10 This could thus introduce a regression and dilution bias, and PA should therefore be assessed objectively.

    The purpose of the study was to investigate the associations between PA intensity across childhood and cIMT or carotid arterial stiffness in adolescence. More specifically, the primary aim of the study was to investigate the association between mean exposure of and changes in objectively measured moderate-and-vigorous and vigorous PA across childhood into adolescence and cIMT or carotid arterial stiffening in adolescence. Second, we investigated the association between the change in and mean exposure to objectively measured moderate-and-vigorous and vigorous PA from childhood to adolescence and a composite metabolic CVD risk score in adolescence in a sample of Danish children from the European Youth Heart Study (EYHS).

    Methods

    Participants and design

    This is a prospective study using data from the Danish site of the EYHS. EYHS is an international population-based mixed longitudinal study that addresses biological, environmental demographic and lifestyle correlates and the determinants of CVD risk factors in children and adolescents. Detailed description of the EYHS and the sampling procedures have been described in detail elsewhere.11 In 2003–2004, 709 9-year-old children were randomly sampled and invited to take part in the study. A total of 458 adolescents participated (65% participation). A 6-year follow-up was conducted in 2009–2010, where all invitees were reinvited to participate. At follow-up, ultrasonography was added to the protocol. At follow-up, a total of 399 participants agreed to participate. The present study reports on 254 participants (55% of baseline participation) with complete data on cIMT, arterial stiffness and PA. For the secondary analyses, fasting blood samples were only available in 205 participants. The study was approved by the Regional Scientific Ethical Committee for Southern Denmark and data were collected according the Helsinki declaration. All participants gave a written informed consent.

    Carotid arterial properties

    The carotid arterial properties were measured using ultrasonography (Model Logic e, 12L-RS probe (5–13 MHz, 12 MHz used) GE Medical) according to the guidelines.12 Before the measurements, participants rested for 10 min in a quiet temperature-controlled room. The arterial properties were conducted at the lateral and posterior position of the common carotid artery, 10 and 20 mm (for arterial stiffness measures) proximal to the beginning of the carotid bulb on both the right and the left common carotid artery. Carotid IMT was obtained at the far wall of the artery. All examinations were performed by a single trained operator. Intrareader coefficients of variation were 5.7%, 4.5% and 4.5% for IMT, systolic and diastolic diameter, respectively.

    Images from seven to eight cardiac cycles were stored offline for the quantification of carotid artery diameters and the cIMT. The analyses were performed by a blinded trained reader, using commercially available analysis software (Vascular Research Tools 5, Medical Imaging Applications, LLC). Peak-systolic (DS), end-diastolic (DD) arterial diameter and cIMT were obtained from both positions. The mean of both positions and both sides was used for the subsequent analysis.

    Brachial systolic and diastolic blood pressures were obtained from the right arm at the end of the examination in a supine position (Welch Allyn Vital Signs monitor 300 series, Kivex, Hoersholm, Denmark) by a trained operator using an appropriate cuff size. Brachial pulse pressure (PP) was calculated as systolic minus diastolic blood pressure. The compliance coefficient (CC), the distensibility coefficient (DC), Young's elastic modules (YEM) and the β stiffness index (SI) were calculated as follows2 ,13:

    1. CC=π×(DS2−DD2)/(4×PP) in mm2/kPa

    2. DC=(2×(DS-DD)×DD+(DS-DD)2)/(PP×DD2) in 10−3/kPa

    3. YEM=DD/(cIMT×DC) in 103×kpa

    4. SI=In(systolic BP/diastolic BP)/((DS−DD)/DD)

    For YEM and SI, higher values mean stiffer carotid arteries; for CC and DC, higher value means lower stiffness of the carotid arteries.

    CVD risk factors and metabolic CVD risk score

    Anthropometric procedures, measurements of blood pressure and assessment of cardio respiratory fitness have been described in detail elsewhere.11 ,14 Mean arterial pressure was calculated as diastolic BP × ((systolic BP – diastolic BP)/3). Blood samples were drawn after an overnight fast. The analysis of the blood samples has been described in details elsewhere.15 Insulin resistance was estimated according to the homoeostasis model assessment (HOMA) and calculated as the product of fasting glucose (mmol/l) and insulin (μU/ml) divided by 22.5.16 A continuous metabolic CVD risk z-score was calculated based on a previously published definition, thus included HOMA, triglyceride, total cholesterol to high-density lipoprotein ratio, the sum of four skinfolds, cardiorespiratory fitness (inverted) and systolic blood pressure.14 Standardisation in adolescence was done according to the baseline distribution (mean and SD) of each risk factor.

    Physical activity

    PA intensity was assessed using the Actigraph PA monitor (Pensacola, Florida, USA). The model AM7164 was used in 2003–2004, whereas the models GT3X or model GT1M were used in 2009–2010. Data were extracted using 20 sec epochs for the subsequent intensity analyses. The participants were instructed to wear the monitor for at least five consecutive days and only remove it during showering, bathing and swimming or during night time sleep. The PA variables were adjusted for within-week variation as described previously.17 All activity files were screened using open-source software (Propero V.1.0.18). Consecutive strings of zero >60 min were defined as ‘activity monitor not worn’ and were removed. Subsequently, activity files not meeting the inclusion criteria of three valid days were excluded. A valid day should include at least 9 h 36 min (60% of daily awake time).

    PA intensity was expressed as minutes per day spent in different intensity intervals. The minutes were adjusted proportionally to a full day of 13.5 h (the mean wear time for this population), as described elsewhere.18 The cut-point for time spent in moderate-and-vigorous PA was >1000 counts×20/s and for vigorous PA was >1733 counts×20/s. The cut-points are equivalent to ∼4> METs for moderate-and-vigorous PA for and ∼>6 METs for vigorous PA.19

    Mean exposure to PA was calculated as (VPAfollow-up+VPAbaseline)/2 and (MVPAfollow-up+MVPAbaseline)/2. The changes in PA from baseline to follow-up were calculated as VPAfollow-up – VPAbaseline and MVPAfollow-up – MVPAbaseline, respectively.

    Other covariates

    Soft drink, fruit and vegetable intake (servings/week) and smoking status (yes/no) were obtained using a computerised questionnaire.11 Family history of CVD (parental and maternal; yes/no), parental and maternal educational level and TV viewing-time were obtained using self-report by the parents as described elsewhere.15 Biological maturity was subjectively assessed according to Tanner's classification.20

    Statistics

    Baseline descriptive statistics were calculated for participants with valid data on exposure and outcome and for excluded participants. Exclusion criteria were (1) drop-out, (2) drop-in and (3) incomplete or invalid data on relevant exposures or outcomes. Drop-outs were defined as participants only participating at baseline and drop-ins were defined as only participating at follow-up.

    The associations between the outcomes and mean exposures were analysed using multiple linear regression analyses. Analysing the mean exposure across childhood, we performed an analysis adjusted for gender, biological maturation and body height at follow-up (model 1). Using changes in exposure level, we further adjusted for baseline exposure level. We did not observed any gender interaction (p>0.1), thus the associations are presented for both genders combined. As none of the potential confounders—parental educational status, frequency of vegetable, fruit and familial history of CVD—were related to either exposure or outcome (data not shown), they were not included in the models in order to preserve power. Therefore, we additionally adjusted the models for soft drink consumption and TV-viewing time as they were associated to PA and carotid properties (p<0.05). Finally, as mean arterial pressure has shown to either mediate or confound the association,13 it was included as a covariate.

    All statistical analyses were performed in STATA V.11.2 (STATA Corp. Fort Valton, Texas, USA) with α=0.05 (two-sided).

    Results

    Baseline characteristics for included and excluded participants are shown in table 1. The excluded participants (N=222) did not differ from the included participants, except for the excluded boys who displayed a slightly lower systolic blood pressure (p<0.05) and the excluded girls who displayed slightly less accepted PA wear time (p<0.05) compared with the included participants. Adolescence outcome measures, mean PA exposure and change, herein, are described in table 2. Boys had larger cIMT, carotid compliance, mean PA intensity (moderate-and-vigorous and vigorous) and a steeper decrease of PA intensity (moderate-and-vigorous and vigorous) at follow-up compared with girls (p<0.05). Drop-ins did not differ from the included participants in any of the outcomes or PA intensity at follow-up (p>0.1; data not shown). Age at follow-up was 15.6 (0.4) years.

    View this table:
    Table 1

    Population characteristics

    View this table:
    Table 2

    Arterial properties, metabolic CVD risk at follow-up and PA intensity across from childhood to adolescence

    Table 3 shows the association between baseline, mean exposure to and change in PA intensity from childhood to adolescence and cIMT or carotid arterial stiffness in adolescence adjusted for gender, biological maturity and body height at follow-up. No associations were observed between moderate-and-vigorous or vigorous PA and cIMT or any measures of carotid stiffness. Further adjustment for soda consumption and TV-viewing or mean arterial pressure did not change this. We repeated the analyses using the PP, the diastolic diameter or distension as outcomes. Neither moderate-and-vigorous nor vigorous PA was associated with these arterial properties (std. β coefficients ranged from –0.05 to 0.05 SD, p>0.3).

    View this table:
    Table 3

    Associations between physical activity intensity in and across childhood and subclinical cardiovascular disease risk in adolescence

    Second, we observed that a one-SD (8.3 min) increment in the mean exposure to vigorous PA across childhood was associated with a 0.19 SD lower clustered risk z-score in adolescence (table 3). Further adjustment for baseline soda consumption and TV-viewing time attenuated the association slightly (standard β=−0.16, p=0.03). Analysing this association across quintiles of the mean exposure to vigorous PA revealed that only the most active participants displayed lower metabolic risk z-score in adolescence compared with the least active adjusted for gender, pubertal development, childhood soda consumption and TV-viewing time (figure 1). No associations were observed between the mean exposure to or the change in moderate-and-vigorous PA and adolescence metabolic CVD risk z-score.

    Figure 1
    Figure 1

    Differences in the sum of metabolic cardiovascular disease risk z-scores between the least active (1) and the more active (2–5) quintiles of the cumulative exposure to vigorous intensity (minutes) physical activity in childhood and adolescence. *p<0.05 for differences to the least active quintile (#1).

    Discussion

    In this population-based prospective study, we did not observe any associations between cIMT or arterial stiffness and PA intensity, but we observed that a high mean exposure to vigorous PA across childhood was independently associated with a decreased metabolic CVD risk z-score in adolescence. As structural arterial remodelling and stiffening later in life are thought to be products of the cumulative load of CVD risk factors21 and as CVD factors track from adolescence to adulthood,22 ,23 our observations suggest that PA at higher intensities (of at least 6 METs, which are equivalent to activities such as jogging, staircase walking, hopscotch or basketball24) across childhood could be associated to improved health later in life through decreasing metabolic CVD risk in adolescence.

    Our observations confirm the observations from earlier cross-sectional studies with arterial stiffness.8 ,25 Sakuragi et al observed an association between number of daily steps and carotid-femoral pulse-wave velocity in a population-based sample of 573 children (10.1 years), but the association was attenuated after adjustment for gender, age and systolic blood pressure. Reed et al25 observed an association between the self-reported PA and pulse-wave velocity. Associations between PA and peripheral endothelial function in children have generally been more consistent.5–7 The earliest indication of atherosclerotic progression includes endothelial dysfunction26 and there are some indications that the association between PA and arterial health differentiates across the arterial tree.25 It is possible that the inconsistencies between studies could be ascribed differences in the measures of arterial health, artery segment (central or peripheral). This needs further attention in future studies.

    Our observations are in contrast to observations from the Amsterdam Growth and Health Longitudinal study where vigorous PA across adolescence was associated to decreased carotid arterial stiffness in adulthood13 and an observation from the Cardiovascular Risk in Young Finns Study, where childhood and youth PA was inversely associated with cIMT progression in adulthood.27 As advanced age is associated to arterial stiffening,28 thus atherosclerotic progression, the discrepancies across studies could be ascribed to differences in age at follow-up. As cIMT is a consistently independent predictor of future CVD event in adults, it was surprising to observe a positive association between cIMT and the change in vigorous PA (although insignificant). It is possible that other exposures, such as increased exercise or an increased volume of high intensity PA, might affect cIMT through non-atherosclerotic compensatory enlargement of the Tunica media.12 During high-intensity PA, shear stress and cyclic strain are increased acutely and long-term exercise has shown to increase arterial calipre size.29 ,30 This could potentially induce smooth muscle hypertrophy in highly trained individuals.31 According to the law of Laplace, the tension relates positively with arterial calipre size and negatively with wall thickness in healthy individuals.32 In order for the artery to maintain ‘tensional homeostasis’, compensatory mechanisms must counteract the increased tension. An exercise-induced increase in cIMT might therefore not be related to higher CVD risk per se. Therefore, we conducted a post hoc analysis where the cIMT and PA association was additionally adjusted for arterial cross-sectional area. This attenuated the association (data not shown). Thus, it is possible that the association between cIMT and PA could be negatively confounded by arterial cross-sectional area. In contrast to our findings, Meyer et al33 observed a significant reduction of cIMT following a 6-month exercise intervention in a sample of overweight and obese children. Taken together, this suggests that exercise or PA might only have an effect on the carotid properties in high risk paediatric populations.

    As we did not observe an association between the change in PA across childhood and adolescence metabolic CVD risk, our observations generally confirm previous longitudinal studies.34–36 However, the present study is the first study to observe a significant association between the mean exposure to vigorous PA in childhood and later metabolic CVD risk. This contradicts previous longitudinal observations in children,34 ,37 ,38 but is supported by randomised controlled trials reporting on the beneficial effect of exercise metabolic risk factors in high risk children.39 ,40 As the mean exposure to moderate-and-vigorous PA was not associated with later metabolic CVD risk, this suggests that in order to obtained beneficial effects from habitual PA it has to include vigorous PA (our data suggests ∼10 min/day). Further, as changes in vigorous PA were not associated with later CVD risk, the observations suggest that a continuously high volume of vigorous PA across childhood should be reinforced from an early age to obtain beneficial effects in regard to metabolic CVD risk. This is supported in a recent review by Andersen et al.41

    Strengths of this study include the objective measure of PA, the inclusion of multiple markers of the atherosclerotic progression, the prospective study design and the heterogeneous sample. There are some limitations to the study. First, the insignificant findings between the carotid arterial properties and PA could be explained by a lack of power. We are not aware of any studies in the paediatric population on the association between PA and carotid properties. Furthermore, it is not clear to what extent a change in arterial properties is needed to prevent an adverse health outcome. Thus, clinically meaningful power calculations are not possible to perform. However, the absolute effect size would not change with increasing number of participants unless our observations are explained by selection bias. From childhood to adolescence, excluded participants did not differ from the participants in their baseline levels of PA variables 6 years earlier. The drop-ins did not differ from the included participants at follow-up on the exposure or outcome variables (data not shown). We further performed a post hoc sensitivity analysis, where the estimates were weighed according to the probability of participating at follow-up given they participated at baseline according to overweight, parental educational status and smoking status at baseline (using the pweight option in Stata). This did not affect the effect estimates. Therefore, we do not suspect that selection bias explain our observations. Second, we used brachial blood pressure for calculation of blood pressure which may overestimate pulse-pressure in the central arteries, especially in young people.42 This may therefore overestimate our measure of arterial stiffness. This bias would be random as the cohort was homogeneous according to age. However, since pulse-pressure amplifications may differ across gender and CVD risk,43 ,44 this would potentially introduce a differential bias if the size of the amplification is related to PA level and confounding factors in this population of healthy young adults.

    Third, the activity monitor does not capture activities such as bicycling, weight-bearing activities and swimming very well. Furthermore, a measurement period of ∼4 days might not represent the participant's true PA activity level. This would introduce a random error and thus attenuate the association between intensity and outcome. Fourth, we have shown that the Actigraph models AM7164 and the GT models applied in this study are not fully compatible.45 However, this problem is primarily evident at lower intensities. As we focused on higher intensities and the different models were not mixed within waves of follow-up, we do not suspect this to affect the associations. However, it might have underestimated the absolute change of PA. Finally, we cannot exclude the possibility of unknown and residual confounding due to the observational nature of the study. As the assessment of the dietary intake was measured crudely, this could potentially confound our observations.

    In conclusion, we did not observe any associations between PA across childhood and cIMT or carotid stiffness in adolescence. However, we observed that a high mean exposure to vigorous PA was associated with lower metabolic CVD risk in adolescence.

    What are new the findings?

    • This is the first study to investigate the associations between objectively measured physical activity (PA) across childhood and carotid intima media thickness (IMT) and arterial stiffness in adolescence.

    • The changes in or the mean exposure to PA from childhood to adolescence were not associated with carotid IMT or arterial stiffness in adolescence.

    • A high mean exposure to vigorous PA was associated with lower metabolic cardiovascular disease risk in adolescence.

    How might it impact on clinical practice in the near future?

    • Currently, no recommendations have been made on vigorous PA in childhood. Our observations suggest that it could be recommended that healthy children should engage in vigorous PA in order to decrease cardio vascular disease risk later in life.

    • Clinicians should promote vigorous PA level alongside promoting a reduction of TV-viewing and unhealthy foods in the young healthy population continuously throughout childhood and youth.

    Acknowledgments

    We thank the participants and their families who gave their time to the study.

    References

    1. ↵
      1. Lorenz MW,
      2. Markus HS,
      3. Bots ML,
      4. et al
      . Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic review and meta-analysis. Circulation 2007;115:459–67.
      OpenUrlAbstract/FREE Full Text
    2. ↵
      1. Yang EY,
      2. Chambless L,
      3. Sharrett AR,
      4. et al
      . Carotid arterial wall characteristics are associated with incident ischemic stroke but not coronary heart disease in the Atherosclerosis Risk in Communities (ARIC) study. Stroke 2012;43:103–8.
      OpenUrlAbstract/FREE Full Text
    3. ↵
      1. Lee IM,
      2. Shiroma EJ,
      3. Lobelo F,
      4. et al
      . Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012;380:219–29.
      OpenUrlCrossRefPubMedWeb of Science
    4. ↵
      1. Dumith SC,
      2. Gigante DP,
      3. Domingues MR,
      4. et al
      . Physical activity change during adolescence: a systematic review and a pooled analysis. Int J Epidemiol 2011;40:685–98.
      OpenUrlAbstract/FREE Full Text
    5. ↵
      1. Abbott RA,
      2. Harkness MA,
      3. Davies PS
      . Correlation of habitual physical activity levels with flow-mediated dilation of the brachial artery in 5–10 year old children. Atherosclerosis 2002;160:233–9.
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Hopkins ND,
      2. Stratton G,
      3. Tinken TM,
      4. et al
      . Relationships between measures of fitness, physical activity, body composition and vascular function in children. Atherosclerosis 2009;204:244–9.
      OpenUrlCrossRefPubMedWeb of Science
    7. ↵
      1. Pahkala K,
      2. Heinonen OJ,
      3. Lagstrom H,
      4. et al
      . Vascular endothelial function and leisure-time physical activity in adolescents. Circulation 2008;118:2353–9.
      OpenUrlAbstract/FREE Full Text
    8. ↵
      1. Sakuragi S,
      2. Abhayaratna WP
      . Arterial stiffness: methods of measurement, physiologic determinants and prediction of cardiovascular outcomes. Int J Cardiol 2010;138:112–18.
      OpenUrlCrossRefPubMed
    9. ↵
      1. Schmidt-Trucksass AS,
      2. Grathwohl D,
      3. Frey I,
      4. et al
      . Relation of leisure-time physical activity to structural and functional arterial properties of the common carotid artery in male subjects. Atherosclerosis 1999;145:107–14.
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      1. Corder K,
      2. Ekelund U,
      3. Steele RM,
      4. et al
      . Assessment of physical activity in youth. J Appl Physiol 2008;105:977–87.
      OpenUrlAbstract/FREE Full Text
    11. ↵
      1. Riddoch C,
      2. Edwards D,
      3. Page A,
      4. et al
      . The European Youth Heart Study—cardiovascular disease risk factors in children: rationale, aims, design and validation of methods. J Phys Activ Health 2005;:115–29.
    12. ↵
      1. Touboul PJ,
      2. Hennerici MG,
      3. Meairs S,
      4. et al
      . Mannheim carotid intima-media thickness consensus (2004–2006). An update on behalf of the Advisory Board of the 3rd and 4th Watching the Risk Symposium, 13th and 15th European Stroke Conferences, Mannheim, Germany, 2004, and Brussels, Belgium, 2006. Cerebrovasc Dis 2007;23:75–80.
      OpenUrlCrossRefPubMedWeb of Science
    13. ↵
      1. Van de Laar RJ,
      2. Ferreira I,
      3. Van MW,
      4. et al
      . Lifetime vigorous but not light-to-moderate habitual physical activity impacts favorably on carotid stiffness in young adults: the Amsterdam growth and health longitudinal study. Hypertension 2010;55:33–9.
      OpenUrlCrossRef
    14. ↵
      1. Andersen LB,
      2. Harro M,
      3. Sardinha LB,
      4. et al
      . Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study). Lancet 2006;368:299–304.
      OpenUrlCrossRefPubMedWeb of Science
    15. ↵
      1. Grontved A,
      2. Ried-Larsen M,
      3. Moller NC,
      4. et al
      . Youth screen-time behaviour is associated with cardiovascular risk in young adulthood: the European Youth Heart Study. Eur J Prev Cardiol 2013 (in press).
    16. ↵
      1. Matthews DR,
      2. Hosker JP,
      3. Rudenski AS,
      4. et al
      . Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412–19.
      OpenUrlCrossRefPubMedWeb of Science
    17. ↵
      1. Kristensen PL,
      2. Moller NC,
      3. Korsholm L,
      4. et al
      . Tracking of objectively measured physical activity from childhood to adolescence: the European youth heart study. Scand J Med Sci Sports 2008;18:171–8.
      OpenUrlPubMedWeb of Science
    18. ↵
      1. Andersen LB,
      2. Harro M,
      3. Sardinha LB,
      4. et al
      . Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study). Lancet 2006;368:299–304.
      OpenUrlCrossRefPubMedWeb of Science
    19. ↵
      1. Freedson P,
      2. Pober D,
      3. Janz KF
      . Calibration of accelerometer output for children. Med Sci Sports Exerc 2005;37(Suppl 11):S523–30.
      OpenUrlCrossRefPubMedWeb of Science
    20. ↵
      1. Duke PM,
      2. Litt IF,
      3. Gross RT
      . Adolescents’ self-assessment of sexual maturation. Pediatrics 1980;66:918–20.
      OpenUrlAbstract/FREE Full Text
    21. ↵
      1. Laurent S,
      2. Cockcroft J,
      3. Van Bortel L,
      4. et al
      . Expert consensus document on arterial stiffness: methodological issues and clinical applications. Eur Heart J 2006;27:2588–605.
      OpenUrlAbstract/FREE Full Text
    22. ↵
      1. Andersen LB,
      2. Haraldsdottir J
      . Tracking of cardiovascular disease risk factors including maximal oxygen uptake and physical activity from late teenage to adulthood. An 8-year follow-up study. J Intern Med 1993;234:309–15.
      OpenUrlCrossRefPubMedWeb of Science
    23. ↵
      1. Chen W,
      2. Srinivasan SR,
      3. Li S,
      4. et al
      . Clustering of long-term trends in metabolic syndrome variables from childhood to adulthood in Blacks and Whites: the Bogalusa Heart Study. Am J Epidemiol 2007;166:527–33.
      OpenUrlAbstract/FREE Full Text
    24. ↵
      1. Ridley K,
      2. Ainsworth BE,
      3. Olds TS
      . Development of a compendium of energy expenditures for youth. Int J Behav Nutr Phys Act 2008;5:45.
      OpenUrlCrossRefPubMed
    25. ↵
      1. Reed KE,
      2. Warburton DE,
      3. Lewanczuk RZ,
      4. et al
      . Arterial compliance in young children: the role of aerobic fitness. Eur J Cardiovasc Prev Rehabil 2005;12:492–7.
      OpenUrlCrossRefPubMedWeb of Science
    26. ↵
      1. Ross R
      . Mechanisms of disease—atherosclerosis—an inflammatory disease. N Engl J Med 1999;340:115–26.
      OpenUrlCrossRefPubMedWeb of Science
    27. ↵
      1. Juonala M,
      2. Viikari JS,
      3. Kahonen M,
      4. et al
      . Life-time risk factors and progression of carotid atherosclerosis in young adults: the Cardiovascular Risk in Young Finns study. Eur Heart J 2010;31:1745–51.
      OpenUrlAbstract/FREE Full Text
    28. ↵
      1. Lakatta EG,
      2. Levy D
      . Arterial and cardiac aging: major shareholders in cardiovascular disease enterprises: Part I: aging arteries: a “set up” for vascular disease. Circulation 2003;107:139–46.
      OpenUrlFREE Full Text
    29. ↵
      1. Green DJ
      . Exercise training as vascular medicine: direct impacts on the vasculature in humans. Exerc Sport Sci Rev 2009;37:196–202.
      OpenUrlPubMedWeb of Science
    30. ↵
      1. Green DJ,
      2. Spence A,
      3. Halliwill JR,
      4. et al
      . Exercise and vascular adaptation in asymptomatic humans. Exp Physiol 2011;96:57–70.
      OpenUrlCrossRefPubMedWeb of Science
    31. ↵
      1. Humphrey JD
      . Mechanisms of arterial remodeling in hypertension: coupled roles of wall shear and intramural stress. Hypertension 2008;52:195–200.
      OpenUrlCrossRef
    32. ↵
      1. Korshunov VA,
      2. Schwartz SM,
      3. Berk BC
      . Vascular remodeling: hemodynamic and biochemical mechanisms underlying Glagov's phenomenon. Arterioscler Thromb Vasc Biol 2007;27:1722–8.
      OpenUrlAbstract/FREE Full Text
    33. ↵
      1. Meyer AA,
      2. Kundt G,
      3. Lenschow U,
      4. et al
      . Improvement of early vascular changes and cardiovascular risk factors in obese children after a six-month exercise program. J Am Coll Cardiol 2006;48:1865–70.
      OpenUrlCrossRefPubMedWeb of Science
    34. ↵
      1. Boreham C,
      2. Twisk J,
      3. Neville C,
      4. et al
      . Associations between physical fitness and activity patterns during adolescence and cardiovascular risk factors in young adulthood: the Northern Ireland Young Hearts Project. Int J Sports Med 2002;23(Suppl 1):S22–6.
      OpenUrlPubMedWeb of Science
    35. ↵
      1. Hasselstrom H,
      2. Hansen SE,
      3. Froberg K,
      4. et al
      . Physical fitness and physical activity during adolescence as predictors of cardiovascular disease risk in young adulthood. Danish Youth and Sports Study. An eight-year follow-up study. Int J Sports Med 2002;23(Suppl 1):S27–31.
      OpenUrlCrossRefPubMedWeb of Science
    36. ↵
      1. Janz KF,
      2. Dawson JD,
      3. Mahoney LT
      . Increases in physical fitness during childhood improve cardiovascular health during adolescence: the Muscatine Study. Int J Sports Med 2002;23(Suppl 1):S15–21.
      OpenUrlCrossRefPubMedWeb of Science
    37. ↵
      1. Lefevre J,
      2. Philippaerts R,
      3. Delvaux K,
      4. et al
      . Relation between cardiovascular risk factors at adult age, and physical activity during youth and adulthood: the Leuven Longitudinal Study on Lifestyle, Fitness and Health. Int J Sports Med 2002;23(Suppl 1):S32–8.
      OpenUrlCrossRefPubMedWeb of Science
    38. ↵
      1. Twisk JW,
      2. Kemper HC,
      3. Van MW
      . The relationship between physical fitness and physical activity during adolescence and cardiovascular disease risk factors at adult age. The Amsterdam growth and health longitudinal study. Int J Sports Med 2002;23(Suppl 1):S8–14.
      OpenUrlCrossRefPubMedWeb of Science
    39. ↵
      1. Ferguson MA,
      2. Gutin B,
      3. Le NA,
      4. et al
      . Effects of exercise training and its cessation on components of the insulin resistance syndrome in obese children. Int J Obes Relat Metab Disord 1999;23:889–95.
      OpenUrlCrossRefPubMedWeb of Science
    40. ↵
      1. Kang HS,
      2. Gutin B,
      3. Barbeau P,
      4. et al
      . Physical training improves insulin resistance syndrome markers in obese adolescents. Med Sci Sports Exerc 2002;34:1920–7.
      OpenUrlCrossRefPubMedWeb of Science
    41. ↵
      1. Andersen LB,
      2. Riddoch C,
      3. Kriemler S,
      4. et al
      . Physical activity and cardiovascular risk factors in children. Br J Sports Med 2011;45:871–6.
      OpenUrlAbstract/FREE Full Text
    42. ↵
      1. Boutouyrie P,
      2. Bussy C,
      3. Lacolley P,
      4. et al
      . Association between local pulse pressure, mean blood pressure, and large-artery remodeling. Circulation 1999;100:1387–93.
      OpenUrlAbstract/FREE Full Text
    43. ↵
      1. Agnoletti D,
      2. Zhang Y,
      3. Salvi P,
      4. et al
      . Pulse pressure amplification, pressure waveform calibration and clinical applications. Atherosclerosis 2012;224:108–12.
      OpenUrlCrossRefPubMedWeb of Science
    44. ↵
      1. Regnault V,
      2. Thomas F,
      3. Safar ME,
      4. et al
      . Sex difference in cardiovascular risk: role of pulse pressure amplification. J Am Coll Cardiol 2012;59:1771–7.
      OpenUrlCrossRefPubMedWeb of Science
    45. ↵
      1. Ried-Larsen M,
      2. Brond JC,
      3. Brage S,
      4. et al
      . Mechanical and free living comparisons of four generations of the Actigraph activity monitor. Int J Behav Nutr Phys Act 2012;9:113.
      OpenUrlCrossRefPubMed

    Footnotes

    • Contributors MR-L conceptualised the study, collected the data, carried out the initial analyses, drafted the manuscript and approved the final manuscript as submitted. AG conceptualised the study, collected data, reviewed and revised the manuscript and approved the final manuscript as submitted. N CM coordinated, collected the data and supervised the data collection at baseline (2003), interpreted observations, critically reviewed the manuscript for important intellectual content, and approved the final manuscript as submitted. KTL collected the data, reviewed and revised the manuscript important intellectual content and approved the final manuscript as submitted. KF designed the study, coordinated and supervised data collection at baseline (2003), interpreted observations, critically reviewed the manuscript for important intellectual content and approved the final manuscript as submitted. LBA designed the study, interpreted observations, supervised data collection at follow-up (2009), critically reviewed the manuscript for important intellectual content and approved the final manuscript as submitted.

    • Funding The study was funded by The Danish Council for Strategic Research (grant number 2101–08–0058), the Danish Heart Foundation, the Danish Health Fund..

    • Competing interests None.

    • Ethics approval The regional Scientific Ethical Commitee of Southern Denmark.

    • Provenance and peer review Not commissioned; internally peer reviewed.

    • Data sharing statement All researchers can apply for approval to publish on EYHS data. A proposal should be sent to the EYHS scientific committee. The study and data have been described in Riddoch et al 2005.