The prevalence of obesity and overweight is increasing in child populations throughout the world, affecting short- and long-term health (33). At the same time, it has been shown that physical activity (PA) and cardiorespiratory fitness (V˙O2peak) have decreased particularly in the low-fit pediatric population (25,36). Results from the European Youth Heart Study shows that CVD risk factors tend to cluster in overweight and inactive children and in children with low V˙O2peak as young as the age of 9 yr (2). Although clinical manifestations of CVD do not normally appear before middle age, studies have shown that atherosclerosis in some individuals originates during childhood and adolescence (4). Taken together, the health consequences of these trends will be an upcoming adult population with a high prevalence of obesity and metabolic diseases, which will cause an enormous burden both at the individual and at the societal level.
PA has been suggested as an important area in prevention of both obesity and lifestyle diseases (10,15). Schools provide an advantageous setting for encouraging a healthy lifestyle among children and enhancing PA (13,16). The compulsory physical education (PE) in schools is the only setting that ensures PA for all children, including overweight, inactive, and unfit children, who are difficult to target by other means (16). Several school-based intervention studies addressing different health-related outcomes have been conducted with a large diversity of results on fatness, fitness, glucose metabolism, and lipids (5,7,12–14,18–21,28,30,32,37–39). The challenge is to find an intervention that will provide effective means to improve the health of children and that will be possible to implement on large-scale populations.
The overall objective of the Copenhagen School Child Intervention Study (CoSCIS) was to evaluate the effect of a school-based PA intervention providing a doubling of time for PE, new didactic tools to the PE teachers, and an upgrading of sports and playing facilities in intervention schools on CVD risk factors. CoSCIS was the first large school-based PA intervention in Denmark and assessed health using both single risk factors and a composite risk score, which have been suggested as a good method to assess CVD risk level in apparently healthy children (2).
CoSCIS is a controlled longitudinal intervention study that took place in 18 public schools (10 interventions and 8 controls) in two suburbs of Copenhagen. The local Authority of Ballerup had decided to upgrade the PA opportunities for their youngest schoolchildren and contacted the research group to quantify and measure the effect of such an intervention. The intervention was hereafter planned in cooperation between the intervention local authority and the researchers. Baseline measurements were carried out in 2001/2002, postintervention measurements were carried out in 2004/2005, and follow-up measurements were carried out in 2008. All tests were performed at the participating schools in a gym or a classroom except for the fitness test, which was performed using permanently installed equipment in a camper trailer outside the schools.
All children from 46 preschool classes (age 6–7 yr) in the schools in the two local authorities were invited to participate in the study. A total of 706 children (69%) volunteered to participate and 696 children actually participated at baseline. Written informed consent was obtained from the child’s parent or legal guardian after being given a detailed written explanation of the aims of the study, any possible hazards, discomfort, and inconvenience, and the option to withdraw at any time. The study was approved by the ethics committee of the University of Copenhagen. There were no differences between participants and nonparticipants with respect to age, height, weight, and body mass index (BMI) for either sex measured 1 yr after the baseline measurements (9).
The intervention and control schools were not randomly selected. In 2000, the intervention group (IG) was started in the local authority of Ballerup and involved all first- to third-grade classes. The program consisted of four constituent parts. First, an increase in the amount of PE lessons from 90 to 180 min·wk−1, given as two double sessions each week. The extra PE session was administered by the normal PE teachers, and the content was not controlled or supervised by the researchers. Approximately one-third of the extra PE lessons were swim lessons. The goal of the PE sessions was to make fun activities with a high level of intensity and incorporating both strength and cardiovascular training. The final planning and execution of the lessons were done by the PE teachers; thus, the situation resembles “a real-world scenario.” The teachers were asked to keep a monthly record of the content of the lessons, but the dropout was too big for the data to be used. Second, the children were given lessons in health education, focusing on the importance of PA and healthy eating. Third, the PE teachers received three to four full days a year of supplementary training focused on didactic tools to enhance the children’s motivation for and enjoyment of PA and, at the same time, keeping the intensity in PE lessons moderate to vigorous. All PE teachers were obliged to participate in the teacher training program, and a record was kept to ensure participation. Fourth, indoor and outdoor PE and playing facilities were upgraded in all intervention schools.
Schools within Tårnby local authority were chosen as control group (CG) because this local area resembles the sociodemographic characteristics of the intervention authority. Control schools followed the normal curriculum of one double PE session per week (90 min·wk−1) and had no teacher training or facility upgrading.
All measurements were performed between 8:00 a.m. and 2:00 p.m. Blood draws were completed before 9:30 a.m. followed by breakfast. Accelerometer data were collected the week after the other measurements. Because the data collection took several months, testing was done in alternating weeks in intervention schools and control schools to account for growth, maturation, and seasonality in PA. Age was computed from date of birth, which was obtained from the national registry and verified by the parents. Height was measured without shoes to the nearest 1 mm using Harpenden stadiometer (West Sussex, UK). Body mass was measured in light clothing to the nearest 0.1 kg using an electronic scale (Seca 882, Brooklyn, NY). BMI was calculated (kg·m−2), and BMI z-scores were computed based on World Health Organization recommendations (40). Biceps, triceps, subscapular, and suprailiac skinfolds were measured to the nearest millimeter, in triplicate, with Harpenden calipers (Baty International, West Sussex, UK). The mean of three measurements was used for the analysis. All skinfold measurements were taken on the self-reported nondominant side of the body by the same two skilled researchers. The sum of four skinfolds (S4SF) was calculated according to the method presented by Durnin and Rahaman (8) and used as an estimate of body fatness. Waist circumference was measured to the nearest millimeter with an anthropometric tape, midway between the lower rib margin and the iliac of the trunk. Sexual maturation was assessed postintervention and at follow-up by self-report using a scale of pictures of breast and genital development for girls and boys, respectively (35). Blood pressure was measured after 15 min of rest with a Dinamap XL vital signs blood pressure monitor (Critikron, Inc., Tampa, FL) using appropriately sized cuffs. Five measurements were taken during 10 min, and the mean of the last three measurements was recorded.
Cardiorespiratory fitness (V˙O2peak) was assessed using a protocol of continuous running on a treadmill. V˙O2peak was measured directly on an AMIS 2001 Cardiopulmonary Function Test System (DK 5260; Innovision, Odense, Denmark) at baseline and postintervention and using the COSMED K4b2 portable metabolic system (COSMED, Rome, Italy) at follow-up. Both systems were calibrated immediately before each trial. We were unable to cross-validate the two systems, but both have been validated against the Douglas bag method and were found to obtain valid measures of V˙O2 (17,23). The children were instructed to run until exhaustion. To determine whether a test was performed satisfactorily, at least one of three objective physiological criteria should be fulfilled; HR > 200 bpm, RER ≥ 0.99, or a defined plateau of V˙O2 (an increase of <2.1 mL·min−1·kg−1) together with a subjective criteria for exercise intolerance (31). For children who ran to exhaustion but did not attain a valid measurement because of equipment failure, V˙O2peak was estimated from a regression equation calculated from all the valid tests using running time to exhaustion and sex (∼10% of participants). This method has been reported earlier (9).
PA was assessed using a combination of a questionnaire and the ActiGraph 7164 activity monitor at baseline and postintervention and the GTIM activity monitor at follow-up (ActiGraph, Inc., Pensacola, FL). The accelerometer was secured directly to the skin at the lower back using an elastic belt. The children were instructed to use the accelerometer for four consecutive days, two weekdays, and two weekend days. They wore the accelerometer during the entire day and only removed it, e.g., during water activities. A recording epoch of 10 s was selected for this study. All continuous sequences of 60 consecutive epochs (i.e., 10 min) or more with zero counts were considered as nonwearing and were subsequently deleted (29). Only children providing a minimum of 3 d with 8 h of valid recording, after removal of missing data, were included in this analysis. The PA questionnaire was distributed and returned with the accelerometers. Children and parents were, among other things, asked to note time and reason for any period of “nonwear.” Accelerometer data were subsequently adjusted for water activities information obtained by the questionnaires. This was done by inserting blocks of activity corresponding to the mean counts per minute in normal PE lessons in all nonwear periods that could be identified as water activity. This was done because part of the intervention was delivered as swim lessons and would not be captured by accelerometers alone. For this article, we report the overall amount of PA (mean counts per minute) and minutes per day spent on moderate-to-vigorous PA (MVPA) (min·d−1≥1500 counts per minute) (27).
Blood samples were collected from the antecubital vein after a verified overnight fast. The children were asked what they had been eating and drinking from the night before, and only water and sugar-free chewing gum were allowed for a child to be accepted as fasting. Glucose was analyzed immediately after sampling (Hemocue). The remainder of the samples was centrifuged; plasma aliquoted within 30 min, kept at −20°C, and later stored at −80°C. Insulin was analyzed spectrophotometrically using an enzyme-linked immunosorbent assay (code no. K6219; DAKO Insulin). Total cholesterol (TC), HDL cholesterol, and triglyceride (TG) were analyzed on a COBAS FARA (Roche, Switzerland) using a spectrophotometer (ABX Diagnostics, Montpellier, France). Insulin resistance was estimated according to homeostasis model assessment (HOMA-IR) as glucose (mmol·L−1) multiplied by insulin (mU·L−1) divided by 22.5 (22).
SPSS version 15 was used for all analyses. Dropout analyses and analyses of missing data were done using independent-samples t-tests adjusting for sex comparing baseline BMI z-scores, waist circumference and V˙O2peak between participants, and dropouts between children who gave blood versus those who did not.
Means and SD for physical characteristics and CVD risk factors at baseline, postintervention and at follow-up were calculated by sex and group. BMI, waist circumference, S4SF, HOMA-IR, TG, TC-to-HDL ratio, and sum of z-scores were positively skewed and therefore transformed (natural log) for the analyses. Because single risk factors tend to fluctuate on a day-to-day basis, we included a composite CVD risk score, which may provide a more valid overall risk assessment (1,2). We constructed the composite score from the sex-specific sum of z-scores for systolic blood pressure (SBP), TG, TC-to-HDL ratio, HOMA-IR, S4SF, and the negative value of V˙O2peak z-score.
Differences between groups at baseline were analyzed using a general linear model adjusted for sex. Change scores were calculated by subtracting baseline values from postintervention and follow-up values, respectively. Differences between IG and CG in change scores from baseline to postintervention and from baseline to follow-up were analyzed using a general linear model adjusted for sex, maturation, and baseline level, if this differed between groups. The child’s school at baseline was included in the analyses as a cluster option to account for any between-school variation. Group-by-sex interaction was tested, but where no interaction was found, the interaction term was removed from the final model. In case of significance on sex × group interaction, only the interaction P value was presented in the table. Then, follow-up analyses were done with split for sex and presented in the figures. A significance level of P < 0.05 was chosen. Because of multiple testing, P values were subsequently Bonferroni adjusted.
Characteristics of participants in IG and CG are presented by sex in Table 1. At baseline, children in IG were significantly older and had a significantly higher SBP compared with children in CG (P = 0.022 and 0.016, respectively). There were no other significant group differences at baseline.
Table 2 presents the immediate and long-term effect of the intervention. The immediate effect is the difference between IG and CG change scores from baseline to postintervention. IG had a borderline smaller increase in SBP compared with CG (P = 0.092). There was a significant sex × group interaction for change scores of HOMA-IR (Table 2). IG boys had a significantly smaller increase in HOMA-IR compared to CG boys (P = 0.004), whereas no difference between groups was found for girls (Fig. 1). There were no other significant group differences in change scores from baseline to postintervention. Long-term effects of the intervention were measured comparing IG and CG change scores from baseline to follow-up. There was a significant sex × group interaction for SBP (Table 2). The change scores of SBP were significantly lower for IG boys compared to CG boys (P = 0.010), but this was not found for girls (Fig. 2). There were no other significant differences in change scores from baseline to follow-up. After Bonferroni correction, no differences were found between groups.
Dropout and missing data.
At baseline, 696 children participated, 613 participated postintervention (≈88%) and 441 participated at follow-up (≈63%). Most dropouts were caused by families moving away from the school districts. There were no significant differences at baseline between children who participated postintervention and children who dropped out. Children who participated at follow-up had significantly lower baseline BMI z-scores (−0.2) and waist circumference (−2.9 cm) and a higher baseline V˙O2peak (1.7 mL·kg−1) compared to children who dropped out (P > 0.006) in both groups.
Blood was obtained from ≈69% of the children participating at baseline, 74.4% of the children participating postintervention and 87.8% of the children participating at follow-up. At baseline, children without blood samples had higher waist circumference (∼1 cm) compared to children who gave blood (P = 0.025). postintervention and at follow-up, children without blood samples had lower V˙O2peak compared to children who gave blood (−2.6 and −2.7 mL·kg−1, respectively; both P > 0.04). There were no other significant differences between children who gave versus those who did not.
CoSCIS was proposed as a way to enhance and improve PA and thereby health in Danish children in public schools. The plan was to test the largest possible change in PA in schools, which we considered politically realistic to implement nationwide. Also, the magnitude and costs of the intervention elements in CoSCIS were realistic and did not exceed what could be implemented on large-scale populations. Positive results could therefore provide politicians with an idea of a relatively simple way to improve health in school-age children. Thus, results from the CoSCIS are potentially important in planning and implementing public health strategies.
Surprisingly, doubling the amount of PE had no significant effect on overall PA levels in IG. One possible explanation is that IG children compensated for the increased school-time PA during the remainder of the day. It is also notable that the amount of MVPA at baseline was quite high in this population (both in the IG and CG). The increase in PA in an already-active population may not induce sufficiently large, measurable metabolic changes. Conjecture suggests that, if the children were less active, there may have been a greater effect of the intervention.
However, although not statistically significant, the IG did decrease their MVPA less compared to CG from baseline to postintervention the difference amounted to ∼12 min·d−1. Because MVPA is related to CVD risk factors (1,10), this modest, 12-min difference could explain some of the small positive metabolic changes we found in this study. The lack of statistically significant difference could have at least two contributory causes. First, although the use of accelerometers and questionnaires to assess PA is the best available method at this time, these kinds of data have a large variation because of measurement error, noncompliance with wearing, and the device’s inability to measure some activities, such as swimming, which was part of the PE intervention. Second, dropout rate on this variable was also considerably larger than many of the other variables because of the strict inclusion criteria.
We did not find any positive intervention effect on V˙O2peak. Researchers have suggested that, to improve the V˙O2peak of children, the focus has to be on high-intensity exercise with three to five training sessions per week (31,34). Most population-based long-term intervention studies with PE intervention comparable to CoSCIS fail to achieve improvements in V˙O2peak (7,20), which emphasizes the difficulty in implementing sufficiently intense large-scale interventions to meet these criteria. Others do, however, find an effect on fitness (19,28,37). The intervention in the study by Kriemler et al. (19) consisted of two extra PE lessons of 45 min, giving a total number of five weekly PE lessons (225 min·wk−1), several short PA breaks during the day, plus 10 min of exercise homework for 9 months. They found a significantly greater improvement in fitness in the IG compared to the CG. In addition, Resaland et al. (28) found a significant intervention effect on V˙O2peak after a 2-yr school-based PA intervention. Their intervention consisted of 60-min daily PA lessons (300 min·wk−1), with focus on keeping the intensity moderate to vigorous. This was compared to a CG receiving normal curriculum of 45 min of PE twice a week (90 min·wk−1). These studies suggest that it is possible to improve fitness in normal pediatric populations but that intensity, frequency, and duration must be considered. The intervention in the present study was focused on increasing the overall PA levels in PE classes and on enhancing the motivation for and enjoyment of PA. Obvious differences between the interventions in CoSCIS and the studies of Kriemler et al. and Resaland et al. are the number of minutes of PE/PA lessons (180 vs 225 and 300 min) and the distribution throughout the week (two times per week vs five times per week). In addition, if the 90 min of extra PA we provided is divided by seven weekdays, the number of extra minutes expected is ∼12 min·d−1, whereas the other studies mentioned above would have proven >25 min·d−1 of activity. These results suggest that, in an already-fit group, 12 min·d−1 may not be sufficient to cause a change.
There were no positive intervention effects on any measure of body composition. CoSCIS was not specifically focused on overweight and obesity prevention. Some school-based interventions have had an effect on overweight and obesity outcomes (12–14), whereas most large-scale studies do not find any effects (5,18,20,32). An extensive review on studies addressing obesity prevention programs in children concluded that most studies show limited success in preventing childhood obesity (11). This emphasizes the difficulty in preventing overweight and obesity even in interventions with this specific aim.
Although we did not find any significant group differences in measurements of fatness, PA, or V˙O2peak, we did find indicators for positive intervention effects on some CVD risk factors, especially for boys. We found a borderline smaller increase in SBP from baseline to postintervention compared to controls. This difference was significant at the 4-yr follow-up but only for boys. Strong et al. (34) reviewed more than 850 studies on exercise in youth and found four studies showing an effect on blood pressure in children with elevated blood pressure but no effect on children with normal blood pressure. However, some studies have found short-term improvements in blood pressure after exercise interventions in children (24). These results, together with our results, suggest that it is possible to generate positive alterations on blood pressure in both normotensive and hypertensive children.
A smaller increase in HOMA-IR from baseline to postintervention was observed for the boys in the IG compared to CG, but this difference did not persist to follow-up. Previous studies have reported positive intervention effects on glucose and/or insulin levels (12,30,37), whereas others have not found an effect on these variables (7). The newer large-scale intervention study, The HEALTHY Study, found that the improvement in insulin levels in intervention schools compared to control schools was accompanied by improvements in measures of fatness (12). However, other studies on overweight and obese children have found improvements in indices of insulin sensitivity, independent of changes in body composition (3,26). These results, together with our results, suggest that it is possible to make favorable changes in insulin sensitivity by targeting PA, even without changes in fatness or fitness. It is possible that the better maintenance of mean PA and MVPA in IG compared to CG, although not statistically significant, could have mediated these changes. We can only speculate about why we are finding better results forthe boys compared to the girls. One possible explanation for the sex differences in the intervention effect could be the slightly greater increase in all body fatness measures in girls in IG compared to CG girls, which was not found for the boys. A larger fat mass is associated with insulin resistance and maybe any effect of the PA intervention on this variable is superseded by the gain in fat mass seen in the girls.
We did not find any intervention effects on blood lipids, similar to the results from most (20,39) but not all other intervention studies in children (21). The review by Strong et al. (34) found evidence for a weak relationship between PA and blood lipids, especially for HDL-C and TG. They concluded that there seems to be a minimum threshold of 40 min·d−1 of activity 5 d·wk−1 (total 200 min·wk−1) to achieve an improvement in blood lipid profile. The PE intervention of CoSCIS (180 min·wk−1 given in two sessions) did not meet this threshold, and this may be one reason why we did not find any effect on blood lipids.
To the best of our knowledge, only one other school-based intervention study has analyzed the effect on a clustered risk score consisting of z-scores of waist circumference, mean blood pressure, glucose, TG, and inverted HDL cholesterol (19). They found a significantly larger decrease in the cardiovascular risk score in the IG compared to the CG, which is in contrast to our findings. Results from the European Youth Heart Study shows that both low cardiorespiratory fitness and high levels of body fat are strong predictors for clustering of CVD risk factors in children (2). The fact that we did not find an effect of the intervention on the sum of z-scores may be caused by the lack of intervention results on these variables. In support of this, the study by Kriemler et al. (19) also found positive intervention results in measures of fatness and V˙O2peak.
The main strengths of our study were the length of the intervention, the inclusion of a 4-yr follow-up postintervention and the use of accurate methods of measuring PA, V˙O2peak, and CVD risk factors. One of the limitations of the study was the quasi-experimental study design. A randomized controlled design would have been stronger but was not practically a possibility at the time the study was started. However, we did attempt to match IG and CG on sociodemographic characteristics, which could be considered a strength. In addition, we did not have a stringent control with the content of the extra PE sessions. For example, we did not examine the amount of time actually spent on PA in the sessions or the individual student participation rate. We do, however, know that the students received the extra PE sessions because PE is mandatory in Denmark. Furthermore, in the youngest classes, the children are not allowed to leave the school during the day, and all children present at a given day are attending PE. The observed (but nonsignificant) difference in MVPA (∼12 min·d−1) between IG and CG could also indirectly shows that the intervention was delivered as intended. Although the lack of stringent control over intervention components is a limitation of our study, it could be stated that our results reflect the real-life school system. The results are therefore more generalizable and easy to apply on a population basis.
Another factor influencing our results was the dropout rate. We found that the children who dropped out were heavier and had poorer V˙O2peak than those who remained. This observation was found in both IG and CG. Because the fattest and most unfit children are the ones most expected to gain from an intervention like CoSCIS, this could theoretically cause an underestimation of the true intervention effect. Also, a dropout rate similar to this study is very common and difficult to avoid in large-scale school-based interventions. The amount of missing data was larger for some variables, namely, blood variables, cardiorespiratory fitness, and PA owing to the unpleasant and comprehensive nature of these measurements. This could have limited our power to detect differences between groups in these variables. Finally, a general problem with school-based interventions is that they are not sustained during vacation. A study on overweight American children showed that all improvements in V˙O2peak, percentage body fat, and insulin concentration gained in a 9-month intervention were lost during summer vacation (6).
This is the first Danish large-scale school-based PA intervention using the best-available methods in measuring PA, V˙O2peak, and CVD risk factors. Other school-based intervention studies providing more substantial effects on CVD risk factors and V˙O2peak have conducted an intervention more focused on high intensity and had a greater overall amount of PA (e.g., Foster et al.  and Katz et al. ). However, these interventions could be difficult to implement on a population basis because of the large time and resource expenditure, and further research is needed to investigate how interventions should be conducted to obtain positive intervention results in rather healthy youth populations. Future PA intervention studies should specifically focus on the influence of duration, frequency, and intensity of the programs on the development in health in children. For this purpose, studies with a stronger design and more comprehensive interventions compared to CoSCIS have now been started in Scandinavia.
This study found that a 3-yr school-based exercise intervention resulted in positive changes in SBP and HOMA score in the IG compared with the CG, especially for the boys. We did not find any effects on PA, V˙O2peak, and fatness, and no differences were statistically significant after Bonferroni corrections. Therefore, our results indicate that a doubling of PE exposure and providing training and equipment may not be sufficient to induce major changes in CVD risk factors in healthy populations, at least not when administered as two double lessons per week. Furthermore, if positive changes should be sustained, the increased amount of PE exposure should probably continue throughout the children’s school-life.
This study was supported by The Danish Heart Foundation and TrygFonden.
The authors are thankful to all participating children and their families, school principals and teachers, and politicians and employees in the local authorities of Ballerup and Tårnby.
The authors declare that they have no competing interests.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
1. Andersen LB, Harro M, Sardinha LB, et al.. Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study). Lancet. 2006; 368 (9532): 299–304.
2. Andersen LB, Sardinha LB, Froberg K, Riddoch CJ, Page AS, Anderssen SA. Fitness, fatness and clustering of cardiovascular risk factors in children from Denmark, Estonia and Portugal: the European Youth Heart Study. Int J Pediatr Obes. 2008; 3 (Suppl 1): 58–66.
3. Bell LM, Watts K, Siafarikas A, et al.. Exercise alone reduces insulin resistance in obese children independently of changes in body composition. J Clin Endocrinol Metab. 2007; 92 (11): 4230–5.
4. Berenson GS, Srinivasan SR, Bao W, Newman WP III, Tracy RE, Wattigney WA. Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N Engl J Med. 1998; 338 (23): 1650–6.
5. Caballero B, Clay T, Davis SM, et al.. Pathways: a school-based, randomized controlled trial for the prevention of obesity in American Indian schoolchildren. Am J Clin Nutr. 2003; 78 (5): 1030–8.
6. Carrel AL, Clark RR, Peterson S, Eickhoff J, Allen DB. School-based fitness changes are lost during the summer vacation. Arch Pediatr Adolesc Med. 2007; 161 (6): 561–4.
7. Donnelly JE, Jacobsen DJ, Whatley JE, et al.. Nutrition and physical activity program to attenuate obesity and promote physical and metabolic fitness in elementary school children. Obes Res. 1996; 4 (3): 229–43.
8. Durnin JV, Rahaman MM. The assessment of the amount of fat in the human body from measurements of skinfold thickness. Br J Nutr. 1967; 89 (1): 147–55.
9. Eiberg S, Hasselstrom H, Gronfeldt V, Froberg K, Svensson J, Andersen LB. Maximum oxygen uptake and objectively measured physical activity in Danish children 6–7 years of age: the Copenhagen School Child Intervention Study. Br J Sports Med. 2005; 39 (10): 725–30.
10. Ekelund U, Anderssen SA, Froberg K, Sardinha LB, Andersen LB, Brage S. Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European Youth Heart Study. Diabetologia. 2007; 50 (9): 1832–40.
11. Flodmark CE, Marcus C, Britton M. Interventions to prevent obesity in children and adolescents: a systematic literature review. Int J Obes (Lond). 2006; 30 (4): 579–89.
12. Foster GD, Linder B, Baranowski T, et al.. A school-based intervention for diabetes risk reduction. N Engl J Med. 2010; 363 (5): 443–53.
13. Foster GD, Sherman S, Borradaile KE, et al.. A policy-based school intervention to prevent overweight and obesity. Pediatrics. 2008; 121 (4): e794–802.
14. Gortmaker SL, Peterson K, Wiecha J, et al.. Reducing obesity via a school-based interdisciplinary intervention among youth: planet health. Arch Pediatr Adolesc Med. 1999; 153 (4): 409–18.
15. Hill JO, Wyatt HR. Role of physical activity in preventing and treating obesity. J Appl Physiol. 2005; 99 (2): 765–70.
17. Jensen K, Jorgensen S, Johansen L. A metabolic cart for measurement of oxygen uptake during human exercise using inspiratory flow rate. Eur J Appl Physiol. 2002; 87 (3): 202–6.
18. Katz DL, O’Connell M, Njike VY, Yeh MC, Nawaz H. Strategies for the prevention and control of obesity in the school setting: systematic review and meta-analysis. Int J Obes (Lond). 2008; 32 (12): 1780–9.
19. Kriemler S, Zahner L, Schindler C, et al.. Effect of school based physical activity programme (KISS) on fitness and adiposity in primary schoolchildren: cluster randomised controlled trial. BMJ. 2010; 340: c785.
20. Luepker RV, Perry CL, McKinlay SM, et al.. Outcomes of a field trial to improve children’s dietary patterns and physical activity. The Child and Adolescent Trial for Cardiovascular Health. CATCH collaborative group. JAMA. 1996; 275 (10): 768–76.
21. Manios Y, Moschandreas J, Hatzis C, Kafatos A. Evaluation of a health and nutrition education program in primary school children of Crete over a three-year period. Prev Med. 1999; 28 (2): 149–59.
22. 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 (7): 412–9.
23. McLaughlin JE, King GA, Howley ET, Bassett DR Jr, Ainsworth BE. Validation of the COSMED K4b2
portable metabolic system. Int J Sports Med. 2001; 22 (4): 280–4.
24. McMurray RG, Harrell JS, Bangdiwala SI, Bradley CB, Deng S, Levine A. A school-based intervention can reduce body fat and blood pressure in young adolescents. J Adolesc Health. 2002; 31 (2): 125–32.
25. Moller NC, Wedderkopp N, Kristensen PL, Andersen LB, Froberg K. Secular trends in cardiorespiratory fitness and body mass index in Danish children: the European Youth Heart study. Scand J Med Sci Sports. 2007; 17 (4): 331–9.
26. Nassis GP, Papantakou K, Skenderi K, et al.. Aerobic exercise training improves insulin sensitivity without changes in body weight, body fat, adiponectin, and inflammatory markers in overweight and obese girls. Metabolism. 2005; 54 (11): 1472–9.
27. Puyau MR, Adolph AL, Vohra FA, Zakeri I, Butte NF. Prediction of activity energy expenditure using accelerometers in children. Med Sci Sports Exerc. 2004; 36 (9): 1625–31.
28. Resaland GK, Andersen LB, Mamen A, Anderssen SA. Effects of a 2-year school-based daily physical activity intervention on cardiorespiratory fitness: the Sogndal school-intervention study. Scand J Med Sci Sports. 2011; 21 (2): 302–9.
29. Riddoch CJ, Bo Andersen L, Wedderkopp N, et al.. Physical activity levels and patterns of 9- and 15-yr-old European children. Med Sci Sports Exerc. 2004; 36 (1): 86–92.
30. Rosenbaum M, Nonas C, Weil R, et al.. School-based intervention acutely improves insulin sensitivity and decreases inflammatory markers and body fatness in junior high school students. J Clin Endocrinol Metab. 2007; 92 (2): 504–8.
31. Rowland TW. Developmental Exercise Physiology. Champaign (IL): Human Kinetics; 1996. pp. 35–6.
32. Sallis JF, McKenzie TL, Alcaraz JE, Kolody B, Hovell MF, Nader PR. Project SPARK. Effects of physical education on adiposity in children. Ann N Y Acad Sci. 1993; 699: 127–36.
33. Silventoinen K, Sans S, Tolonen H, et al.. Trends in obesity and energy supply in the WHO MONICA Project. Int J Obes Relat Metab Disord. 2004; 28 (5): 710–8.
34. Strong WB, Malina RM, Blimkie CJ, et al.. Evidence based physical activity for school-age youth. J Pediatr. 2005; 146 (6): 732–7.
35. Tanner JM. Growth at Adolescence. Oxford (UK): Blackwell; 1962. pp. 28–39.
36. Tomkinson GR, Olds TS. Secular changes in pediatric aerobic fitness test performance: the global picture. Med Sport Sci. 2007; 50: 46–66.
37. Trevino RP, Yin Z, Hernandez A, Hale DE, Garcia OA, Mobley C. Impact of the Bienestar school-based diabetes mellitus prevention program on fasting capillary glucose levels: a randomized controlled trial. Arch Pediatr Adolesc Med. 2004; 158 (9): 911–7.
38. Verstraete SJ, Cardon GM, De Clercq DL, De BI. A comprehensive physical activity promotion programme at elementary school: the effects on physical activity, physical fitness and psychosocial correlates of physical activity. Public Health Nutr. 2007; 10 (5): 477–84.
39. Webber LS, Osganian SK, Feldman HA, et al.. Cardiovascular risk factors among children after a 2 1/2-year intervention—the CATCH study. Prev Med. 1996; 25 (4): 432–41.