There were 83 (40 control school, 43 intervention) who had the Met-S in the sixth grade, which tracked into the eighth grade. There were no significant differences in Met-S prevalence at the follow-up assessment between the intervention and control groups when all participants were included or when any of the subgroups were compared. Inspection of Table 3 indicates that, of those participants who had the Met-S at sixth grade, 69.5% had high TG and 81.9% had low HDL-C with similar proportions evident at the eighth-grade assessment. It is, however, noticeable that the proportion of participants with the Met-S who had high fasting glucose levels increased from 44.3% at sixth grade to 64.1% at eighth grade.
The number of shuttle run laps recorded at baseline (sixth grade) and follow-up (eighth grade) is presented in Table 4. For both the intervention and control groups, the mean number of laps increased from 21 at baseline to 27 at follow-up, but there were no statistically significant differences between the two groups at the follow-up assessment. Moreover, when the models were rerun by ethnic and gender subgroups, there were no statistically significant differences. When the FITNESSGRAM criteria were applied to the baseline data, a larger proportion of males had "below-average" aerobic fitness levels (64.4% control group, 60.5% intervention group) compared with females (38.9% control group, 37.9% intervention group). In contrast, after assessment, the percent of males with "below-average" aerobic fitness (64.8% control and 64.5% intervention) was largely unchanged; however, there was a clear deterioration in the relative fitness levels of the girls with 65.9% of the control and 65.5% of the intervention girls being classified as having below-average fitness levels. Further stratification by baseline gender, ethnicity, and baseline obesity status (normal weight or overweight/obese) did not yield differences between the two intervention groups.
Mean minutes of MVPA per day at baseline (sixth grade) and follow-up (eighth grade) are presented by intervention arm in Table 5. There was a 7.4-min decline in the control group's minutes of MVPA per day from baseline to follow-up, with a comparable 7.9-min decline among the intervention group. There were no statistically significant differences between the two groups at follow-up or for any of the gender, ethnic, or obesity status subgroup.
The data presented in this study have shown that 5% of an ethnically diverse sample of early adolescents had Met-S, but a 3-yr multicomponent intervention had no effect on Met-S prevalence when compared with a control group. Further examination indicated that the baseline Met-S prevalence differed by ethnicity, with the highest prevalence among the Hispanic participants (6.5% vs 2.1% for black and 5.5% for white). The baseline Met-S prevalence was higher when the sample was limited to just overweight males (9.6%) and females (12.2%). There was no intervention effect on Met-S prevalence within these subgroups or within the ethnic and obesity status subgroups. Met-S has been shown to track from adolescence to adulthood (23), and adult Met-S is associated with an increased risk of developing CVD and T2DM (17). Because there are serious health implications for youth who possess Met-S, the failure to affect Met-S prevalence in this study indicates a need to identify more effective intervention approaches.
There was no difference in the number of laps completed by the intervention and control groups at the end of the study. Because the 20-MST has been shown to be sensitive to change in youth interventions (16), the lack of an effect on fitness is unlikely to be a function of measurement. The absence of an effect could, however, be a function of variation in the dose of the PE (min·wk−1) offered across the seven field centers. Because exposure to the PE classes at intervention and control schools was broadly comparable with mean PE class lengths of 57 and 55 min in control and intervention schools at baseline and 54 and 55 min at the eighth grade, there does not seem to be an evidence of difference between intervention and control schools. It is therefore reasonable to conclude that the intervention had no effect on the participant's fitness.
There was no difference in the mean minutes of daily (in and out of school) MVPA between the intervention and control groups at the end of the intervention. Although a large proportion of the physical activity intervention efforts were targeted toward the PE provision during curriculum time, the PE lessons, the behavioral lessons, and the social marketing campaign were also designed to encourage additional habitual physical activity. The SAPAC instrument was therefore chosen as the physical activity measure to capture the intended change in habitual physical activity. Thus, although it might be the case that the SAPAC was not sufficiently sensitive to capture change during PE lessons, the primary focus was on the change in overall physical activity of which physical education was an important component. We may have been able to detect a change in physical activity if we had used an objective measure such as using accelerometers. For example, accelerometers would have facilitated a segmented analysis (12) in which it would have been possible to examine if a change in physical activity occurred during school hours. Equally, it may have been the case that activity levels in the intervention group changed during the early phases of the intervention, but these changes were not maintained. As such, it is possible to argue that the lack of objective, sensitive assessments during the intervention period may also have hindered our ability to capture key changes. However, because the primary aim of the study was reduction in modifiable risk factors for T2DM at the end of eighth grade, we directed our limited resources toward assessing physical activity at the end of the study.
A closer examination of the physical activity, fitness, and Met-S data reveals an interesting trend. Overall, minutes of MVPA declined by approximately 8% during the 2.5-yr period, whereas the number of laps completed in the 20-MST increased by approximately 30% overall, with the majority of the increase occurring in the boys and little or no change in the girls. In comparison, the proportion of the overall sample exhibiting Met-S was stable during the 2-yr period. However, the Met-S data (Table 2) show that the proportion of boys with Met-S increased by ∼51%, whereas the proportion of girls decreased by ∼42%. Intriguingly, physical activity and fitness levels of the boys are basically unchanged and the proportion of boys with Met-S is increasing, whereas the physical activity and fitness of the girls are declining and the proportion of girls exhibiting Met-S is declining. Because both physical activity and fitness have been associated with Met-S, these findings suggest that the amount of change in both variables may not have been sufficient to significantly affect Met-S. Potentially, greater changes in physical activity could have influenced changes in body fat or fitness, which would have a direct effect on the Met-S.
The lack of success in achieving change in fitness, physical activity, and Met-S is consistent with the broader literature in which the majority of school-based interventions designed to increase physical activity or prevent weight gain have either reported no effect or very small effects in subgroups (35). Several studies have reported that short-term physical education interventions (≤6 months) (26,29) have yielded positive effects on fitness levels, whereas longer-term studies have yielded no effect (2). It is also important to note that a 3-yr intensive activity program that was delivered after school in US elementary schools yielded a positive change in fitness at the end of each year, but the positive change was lost over the summer vacation (8). It therefore seems plausible that intervention effects could have been ameliorated over the summer months, but the absence of interim measures precluded the detection on such effects on fitness, physical activity, and Met-S. It is, however, important to remember that the primary aim of this study was to assess the longer-term effect of the intervention on fitness, physical activity, and Met-S. As such, although it may have been scientifically interesting to know if the effect had shorter-tem effects on these variables, the more important public health question is whether the intervention had a longer-term effect on these outcomes and it was the key public health question that was the focus of our research.
The failure to affect physical activity, fitness, or Met-S suggests that alternative intervention approaches are needed. Participation in PE and structured group-based PA programs declines throughout adolescence (15), suggesting that future interventions may need to address individual differences in lifestyle activity habits outside of school. We may therefore need to consider alternative approaches to changing youth physical activity, fitness, and ultimately Met-S. Social ecological models (19) suggest that there are multiple levels of influence on youth behavior, and although we made changes to the in-school PA environment, we did not address familial, peer, or wider environmental approaches to increasing physical activity such as active travel to school, which are likely to be important influences on youth physical activity and fitness. Future interventions should consider these wider social and environmental factors on youth physical activity and fitness.
Strengths and limitations.
The data presented here are from a large cluster-designed randomized controlled trial with the majority of the participants (>70%) coming from ethnic minority groups that are at an increased risk of T2DM. The study also included participants from across the United States, and the geographical diversity in sites mimics the US school system. Moreover, this was a multicomponent intervention that was based on the best available evidence with further development during 4 yr of formative work in which the intervention elements were refined (10). As such, the intervention represents a well-thought-out, well-delivered intervention in a high-risk group. There are, however, many limitations that need to be recognized. First, we used the 2-d version of the SAPAC to estimate physical activity levels and sedentary behaviors. Although this is a valid instrument, the wide variance in student response may have affected our ability to detect change. Second, the 20-MST is a field test that has been widely used and validated, but we do not have any information about the consistency in student effort, i.e., did all students work as hard in the test. Third, we used the IDF criteria to define Met-S, and although these criteria were developed to provide a universally accepted criteria, it is plausible that other findings may have resulted if other Met-S definitions had been used. Finally, because the focus of this study was to evaluate a difference between the intervention and control groups at the end of eighth grade, we directed our resources toward assessments at the baseline (sixth grade) and postassessment (eighth grade) periods, which prevented interim assessments of change in outcomes.
The HEALTHY intervention, a complex school-based intervention, had no effect on the Met-S, fitness, or physical activity levels of youth at risk of developing T2DM. The study suggests that school-based behavioral interventions may not be sufficiently intense to facilitate change in these variables. Alternative approaches that focus on how to change physical activity, fitness, and ultimately Met-S in all relevant childhood environments need to be developed. It is unlikely that school-based programming alone can increase activity sufficiently to produce the desired changes.
This work was completed with funding from the National Institute of Diabetes and Digestive and Kidney Diseases/National Institutes of Health grants U01-DK61230, U01 DK61249, U01-DK61231, and U01-DK61223 to the STOPP-T2D collaborative group.
This report is also research arising from a Career Development Fellowship (to Dr. Jago) supported by the National Institute for Health Research. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research, or the Department of Health.
The authors thank the administration, faculty, staff, students, and their families at the middle schools and school districts who participated in the HEALTHY study.
The results of the current study do not constitute endorsement by the American College of Sports Medicine.
The following individuals and institutions constitute the HEALTHY Study Group (* indicates principal investigator or director):
Children's Hospital Los Angeles: F.R. Kaufman
Baylor College of Medicine: T. Baranowski,* L. Adams, J. Baranowski, A. Canada, K.T. Carter, K.W. Cullen, M.H. Dobbins, R. Jago, A. Oceguera, A.X. Rodriguez, C. Speich, L.T. Tatum, D. Thompson, M.A. White, C.G. Williams
Oregon Health & Science University: L. Goldberg,* D. Cusimano, L. DeBar, D. Elliot, H.M. Grund, S. McCormick, E. Moe, J.B. Roullet, D. Stadler
Temple University: G. Foster* (Steering Committee Chair), J. Brown, B. Creighton, M. Faith, E.G. Ford, H. Glick, S. Kumanyika, J. Nachmani, L. Rosen, S. Sherman, S. Solomon, A. Virus, S. Volpe, S. Willi
University of California at Irvine: D. Cooper,* S. Bassin, S. Bruecker, D. Ford, P. Galassetti, S. Greenfield, J. Hartstein, M. Krause, N. Opgrand, Y. Rodriguez, M. Schneider
University of North Carolina at Chapel Hill: J. Harrell,* A. Anderson, T. Blackshear, J. Buse, J. Caveness, A. Gerstel, C. Giles, A. Jessup, P. Kennel, R. McMurray, A.-M. Siega-Riz, M. Smith, A. Steckler, A. Zeveloff
University of Pittsburgh: M.D. Marcus,* M. Carter, S. Clayton, B. Gillis, K. Hindes, J. Jakicic, R. Meehan, R. Noll, J. Vanucci, E. Venditti
University of Texas Health Science Center at San Antonio: R. Treviño,* A. Garcia, D. Hale, A. Hernandez, I. Hernandez, C. Mobley, T. Murray, J. Stavinoha, K. Surapiboonchai, Z. Yin
George Washington University: K. Hirst,* K. Drews, S. Edelstein, L. El ghormli, S. Firrell, M. Huang, P. Kolinjivadi, S. Mazzuto, T. Pham, A. Wheeler
National Institute of Diabetes and Digestive and Kidney Diseases: B. Linder,* C. Hunter, M. Staten
Central Biochemistry Laboratory
University of Washington Northwest Lipid Metabolism and Diabetes Research Laboratories: S.M. Marcovina*
HEALTHY intervention materials are available for download at http://www.healthystudy.org/
Clinical trial registration information: NCT00458029
1. Blair SN, Kohl HW 3rd, Barlow CE, Paffenbarger RS Jr, Gibbons LW, Macera CA. Changes in physical fitness and all-cause mortality: a prospective study of healthy and unhealthy men. JAMA
2. Boyle-Holmes T, Grost L, Russell L, et al. Promoting elementary physical education: results of a school-based evaluation study. Health Educ Behav
3. Centers for Disease Control National Center for Health Statistics. 2000 CDC Growth Charts for the United States
. Atlanta (GA): Centers for Disease Control. 2009 [cited 2009 Jun 1]. Available from: http://www.cdc.gov/growthcharts
4. de Ferranti SD, Gauvreau K, Ludwig DS, Newburger JW, Rifai N. Inflammation and changes in metabolic syndrome abnormalities in US adolescents
: findings from the 1988-1994 and 1999-2000 National Health and Nutrition Examination Surveys. Clin Chem
5. Fernandez JR, Redden DT, Pietrobelli A, Allison DB. Waist circumference percentiles in nationally representative samples of African-American, European-American and Mexican-American children and adolescents
. J Pediatr
6. Finley CE, LaMonte MJ, Waslien CI, Barlow CE, Blair SN, Nichaman MZ. Cardiorespiratory fitness, macronutrient intake, and the metabolic syndrome: the Aerobics Center Longitudinal Study. J Am Diet Assoc
7. Fridewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem
8. Gutin B, Yin Z, Johnson M, Barbeau P. Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia FitKid Project. Int J Pediatr Obes
. 2008;3(1 suppl):3-9.
9. Harrell JS, McMurray RG, Bangdiwala SI, Baggett C, Pearce PF, Pennel M. Determining MET values in children and adolescents
. Med Sci Sports Exerc
. 2003;35(suppl 5):S342.
10. Hirst K, Baranowski T, DeBar L, et al. HEALTHY study rationale, design and methods: moderating risk of type 2 diabetes in multi-ethnic middle school students. Int J Obes (Lond)
. 2009;33(suppl 4):S4-20.
11. Hu FB, Leitzmann MF, Stampfer MJ, Colditz GA, Willett WC, Rimm E. Physical activity and television watching in relation to risk for type 2 diabetes mellitus in men. Arch Intern Med
12. Jago R, Fox KR, Page AS, Brockman R, Thompson JL. Physical activity and sedentary behaviour typologies of 10-11 year olds. Int J Behav Nutr Phys Act
13. Jago R, Harrell JS, McMurray RG, Edelstein S, El Ghormli L, Bassin S. Prevalence of abnormal lipid and blood pressure values among an ethnically diverse population of eighth-grade adolescents
and screening implications. Pediatrics
14. Jago R, McMurray RG, Bassin S, et al. Modifying middle school physical education: piloting strategies to increase physical activity. Pediatr Exerc Sci
15. Johnston LD, Delva J, O'Malley PM. Sports participation and physical education in American secondary schools: current levels and racial/ethnic and socioeconomic disparities. Am J Prev Med
. 2007;33(suppl 4):S195-208.
16. Kriemler S, Zahner L, Schindler C, et al. Effect of school based physical activity programme (KISS) on fitness and adiposity in primary schoolchildren: cluster randomized controlled trial. BMJ
17. Laaksonen DE, Lakka HM, Niskanen LK, Kaplan GA, Salonen JT, Lakka TA. Metabolic syndrome and development of diabetes mellitus: application and validation of recently suggested definitions of the metabolic syndrome in a prospective cohort study. Am J Epidemiol
18. Leger LA, Lambert J. A maximal multistage 20-m shuttle run test to predict V˙O2max
. Eur J Appl Physiol Occup Physiol
19. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Health Educ Q
20. McMurray RG, Harrell JS, Bangdiwala SI, Hu J. Tracking of physical activity and aerobic power from childhood through adolescence. Med Sci Sports Exerc
21. McMurray RG, Ring KB, Treuth MS, et al. Comparison of two approaches to structured physical activity surveys for adolescents
. Med Sci Sports Exerc
22. Molenberghs G, Verbeke G. Models for Discrete Longitudinal Data
. New York (NY): Springer; 2005. p. 151-86.
23. Morrison JA, Friedman LA, Wang P, Glueck CJ. Metabolic syndrome in childhood predicts adult metabolic syndrome and type 2 diabetes mellitus 25 to 30 years later. J Pediatr
24. Ness AR, Leary SD, Mattocks C, et al. Objectively measured physical activity and fat mass in a large cohort of children. PLoS Med
25. Pate RR, Wang CY, Dowda M, Farrell SW, O'Neill JR. Cardiorespiratory fitness levels among US youth 12 to 19 years of age: findings from the 1999-2002 National Health and Nutrition Examination Survey. Arch Pediatr Adolesc Med
26. Peralta LR, Jones RA, Okely AD. Promoting healthy lifestyles among adolescent boys: the Fitness Improvement and Lifestyle Awareness Program RCT. Prev Med
27. Petersen AC, Crockett L, Richards M, Boxer A. A self-report measure of pubertal status: reliability, validity, and initial norms. Youth Adolesc
28. Sallis JF, Buono MJ, Roby JJ, Micale FG, Nelson JA. Seven-day recall and other physical activity self-reports in children and adolescents
. Med Sci Sports Exerc
29. Shaw-Perry M, Horner C, Trevino RP, Sosa ET, Hernandez I, Bhardwaj A. NEEMA: a school-based diabetes risk prevention
program designed for African-American children. J Natl Med Assoc
30. Studies to Treat or Prevent Pediatric Type 2 Diabetes Prevention
Study Group. Prevalence of the metabolic syndrome among a racially/ethnically diverse group of U.S. eighth-grade adolescents
and associations with fasting insulin and homeostasis model assessment of insulin resistance levels. Diabetes Care
31. Tanasescu M, Leitzmann MF, Rimm EB, Hu FB. Physical activity in relation to cardiovascular disease and total mortality among men with type 2 diabetes. Circulation
32. The Healthy Study Group. A school-based intervention
for diabetes risk reduction. N Engl J Med
33. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc
34. Tukey JW. The future of data analysis. Ann Math Stat
35. van Sluijs EM, McMinn AM, Griffin SJ. Effectiveness of interventions to promote physical activity in children and adolescents
: systematic review of controlled trials. BMJ
36. Welk GJ, Meredith MD. FITNESSGRAM/ACTIVITYGRAM Reference Guide
. Dallas (TX): The Cooper Institute; 2008. p. 96-121.
37. Zimmet P, Alberti G, Kaufman F, et al. The metabolic syndrome in children and adolescents
Keywords:©2011The American College of Sports Medicine
SCHOOL-BASED INTERVENTION; PREVENTION; ADOLESCENTS; MULTICOMPONENT