Effect of Novel, School-Based High-Intensity Interval Training (HIT) on Cardiometabolic Health in Adolescents: Project FFAB (Fun Fast Activity Blasts) - An Exploratory Controlled Before-And-After Trial

Kathryn L Weston, Liane B Azevedo, Susan Bock, Matthew Weston, Keith P George, Alan M Batterham, Kathryn L Weston, Liane B Azevedo, Susan Bock, Matthew Weston, Keith P George, Alan M Batterham

Abstract

Background: Low-volume high-intensity interval training holds promise for cardiometabolic health promotion in adolescents, but sustainable interventions must be practical and engaging. We examined the effect of a school-based multi-activity low-volume high-intensity interval training intervention on adolescents' cardiometabolic health.

Methods: In an exploratory controlled before-and-after design, 101 adolescents (mean age ± standard deviation [SD] 14.0 ± 0.3 years) were recruited from four schools; two were designated as intervention sites (n = 41), and two as control (n = 60). The intervention comprised 4 to 7 repetitions of 45 s maximal effort exercise (basketball, boxing, dance and soccer drills) interspersed with 90-s rest, thrice weekly for 10 weeks. Outcomes were non-fasting blood lipids and glucose, waist circumference, high sensitivity C-reactive protein, resting blood pressure, physical activity, twenty-metre shuttle-run test performance and carotid artery intima-media thickness. The difference in the change from baseline (intervention minus control) was estimated for each outcome. Using magnitude-based inferences, we calculated the probability that the true population effect was beneficial, trivial, and harmful against a threshold for the minimum clinically important difference of 0.2 between-subject SDs.

Results and discussion: Mean (± SD) attendance for the intervention (expressed as percentage of available intervention sessions [n = 30]) was 77 ± 13%. Post-intervention, there were likely beneficial effects for triglycerides (-26%; 90% confidence interval -46% to 0%), waist circumference (-3.9 cm; -6.1 cm to -1.6 cm) and moderate-to-vigorous physical activity (+16 min; -5 to 38 min), and a possibly beneficial effect for twenty-metre shuttle-run test performance (+5 shuttles; -1 to 11 shuttles) in intervention participants (vs controls). The role of elevated triglycerides and waist circumference in cardiovascular disease and metabolic syndrome development underlines the importance of our findings. We also demonstrated that school-based low-volume high-intensity interval training can be delivered as intended, thus representing a novel and scalable means of improving aspects of adolescents' cardiometabolic health.

Trial registration: ClinicalTrials.gov NCT02626767.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exists.

Figures

Fig 1. Participant flow-chart.
Fig 1. Participant flow-chart.

References

    1. Andersen LB, Hasselstrøm H, Grønfeldt V, Hansen SE, Froberg K. The relationship between physical fitness and clustered risk, and tracking of clustered risk from adolescence to young adulthood: eight years follow-up in the Danish Youth and Sport Study. Int J of Behav Nut Phys Act. 2004; 1:6 10.1186/1479-5868-1-6
    1. Zimmet P, Alberti KGM, Kaufman F, Tajima N, Silink M, Arslanian S, et al. The metabolic syndrome in children and adolescents–an IDF consensus report. Pediatr Diabetes. 2007; 8:299–306.
    1. McMurray RG, Andersen LB. The influence of exercise on metabolic syndrome in youth: A review. Am J Lifestyle Med. 2010; 4:176–186.
    1. Boddy LM, Thomas NE, Fairclough SJ, Tolfrey K, Brophy S, Rees A, et al. ROC generated thresholds for field-assessed aerobic fitness related to body size and cardiometabolic risk in schoolchildren. PLoS One. 2012; 7:e45755 10.1371/journal.pone.0045755
    1. Scholes S, Mindell J. Health Survey for England 2012. Volume 1: Chapter 3: Physical Activity in Children. The Health and Social Care Information Centre. 2013. Available:
    1. Ryley A. Health Survey for England 2012: Volume 1: Chapter 11: Children's BMI, overweight and obesity. The Health and Social Care Information Centre. 2013. Available:
    1. Griffiths C, Gately P, Marchant P, Cooke C. A five year longitudinal study investigating the prevalence of childhood obesity: comparison of BMI and waist circumference. Public Health, 2013; 127:1090–1096. 10.1016/j.puhe.2013.09.020
    1. Buchan DS, Ollis S, Thomas NE, Buchanan N, Cooper SM, Malina RM, et al. Physical activity interventions: effects of duration and intensity. Scand J Med Sci Sports. 2011; 21: e341–e350. 10.1111/j.1600-0838.2011.01303.x
    1. Hay J, Maximova K, Durksen A, Carson V, Rinaldi RL, Torrance B, et al. Physical activity intensity and cardiometabolic risk in youth. Arch Pediatr Adolesc Med. 2012; 166: 1022–1029. 10.1001/archpediatrics.2012.1028
    1. Carson V, Rinaldi RL, Torrance B, Maximova K, Ball GDC, Majumdar SR, et al. Vigorous physical activity and longitudinal associations with cardiometabolic risk factors in youth. Int J of Obes. 2014; 38: 16–21.
    1. Gibala MJ, Little JP, MacDonald MJ, Hawley JA. Physiological adaptations to low‐volume, high‐intensity interval training in health and disease. J Physiol. 2012; 590:1077–1084. 10.1113/jphysiol.2011.224725
    1. Little JP, Gillen JB, Percival ME, Safdar A, Tarnopolsky MA, Punthakee Z, et al. Low-volume high-intensity interval training reduces hyperglycemia and increases muscle mitochondrial capacity in patients with type 2 diabetes. J Appl Physiol. 2011; 111:1554–1560. 10.1152/japplphysiol.00921.2011
    1. Weston M, Taylor KL, Batterham AM, Hopkins WG. Effects of Low-Volume High-Intensity Interval Training (HIT) on Fitness in Adults: A Meta-Analysis of Controlled and Non-Controlled Trials. Sports Med. 2014; 44:1005–1017. 10.1007/s40279-014-0180-z
    1. Milanović Z, Sporiš G, Weston M. Effectiveness of high-intensity interval training (HIT) and continuous endurance training for VO 2max improvements: a systematic review and meta-analysis of controlled trials. Sports Med, 2015; 45: 1469–1481. 10.1007/s40279-015-0365-0
    1. Babraj JA, Vollaard NB, Keast C, Guppy FM, Cottrell G, Timmons JA. Extremely short duration high intensity interval training substantially improves insulin action in young healthy males. BMC Endocr Disord. 2009; 9: 1–8.
    1. Whyte LJ, Gill JM, Cathcart AJ. Effect of 2 weeks of sprint interval training on health-related outcomes in sedentary overweight/obese men. Metabolism. 2010; 59: 1421–1428. 10.1016/j.metabol.2010.01.002
    1. Hood MS, Little JP, Tarnopolsky MA, Myslik F, Gibala MJ. Low-volume interval training improves muscle oxidative capacity in sedentary adults. Med Sci Sports Exerc 2011; 43: 1849–1856. 10.1249/MSS.0b013e3182199834
    1. Costigan SA, Eather N, Plotnikoff RC, Taaffe DR, Lubans DR. High-intensity interval training for improving health-related fitness in adolescents: a systematic review and meta-analysis. Br J Sports Med. 2015; 49:1253–1261. 10.1136/bjsports-2014-094490
    1. Logan GR, Harris N, Duncan S, Schofield G. A review of adolescent high-intensity interval training. Sports Med. 2014; 44:1071–1085. 10.1007/s40279-014-0187-5
    1. Martin R, Buchan DS, Baker JS, Young J, Sculthorpe N, Grace FM. Sprint interval training (SIT) is an effective method to maintain cardiorespiratory fitness (CRF) and glucose homeostasis in Scottish adolescents. Biol Sport. 2015; 32: 307–313. 10.5604/20831862.1173644
    1. Buchan DS, Ollis S, Young JD, Cooper SM, Shield JP, Baker JS. High intensity interval running enhances measures of physical fitness but not metabolic measures of cardiovascular disease risk in healthy adolescents. BMC Public Health. 2013; 13:498 10.1186/1471-2458-13-498
    1. Bond B, Cockcroft EJ, Williams CA, Harris S, Gates PE, Jackman SR, et al. Two weeks of high-intensity interval training improves novel but not traditional cardiovascular disease risk factors in adolescents. Am J Physiol Heart Circ Physiol. 2015; 309:H1039–1047. 10.1152/ajpheart.00360.2015
    1. Murphy A, Kist C, Gier AJ, Edwards NM, Gao Z, Siegel RM. The feasibility of high-intensity interval exercise in obese adolescents. Clin Pediatr. 2015; 54:87–90.
    1. Young DR, Johnson CC, Steckler A, Gittelsohn J, Saunders RP, Saksvig BI, et al. Data to action: Using formative research to develop intervention programs to increase physical activity in adolescent girls. Health Educ Behav. 2006; 33:97–111.
    1. Logan GR, Harris N, Duncan S, Plank LD, Merien F, Schofield G. Low-Active Male Adolescents: A Dose Response to High-Intensity Interval Training. Med Sci Sports Exerc. 2016; 48: 481–490 10.1249/MSS.0000000000000799
    1. Costigan SA, Eather N, Plotnikoff RC, Taaffe DR, Pollock E, Kennedy SG, et al. Preliminary efficacy and feasibility of embedding high intensity interval training into the school day: A pilot randomized controlled trial. Prev Med Rep. 2015; 2:973–979. 10.1016/j.pmedr.2015.11.001
    1. Department for Communities and Local Government. The English Indices of Deprivation 2010. Department for Communities and Local Government. 2011. Available:
    1. Des Jarlais DC, Lyles C, Crepaz N. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement. Am J Public Health 2004; 94: 361–366.
    1. Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ 2008; 337:a1655 10.1136/bmj.a1655
    1. Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014; 348:g1687 10.1136/bmj.g1687
    1. Taylor KL. Project FFAB (Fun Fast Activity Blasts): Effect of a novel school-based high-intensity interval training intervention on cardiometabolic risk markers and physical activity levels in adolescents. PhD thesis, Teesside University. 2014. Available: .
    1. Taylor KL, Weston M, Batterham AM. Evaluating Intervention Fidelity: An Example from a High-Intensity Interval Training Study. PLoS One. 2014; 10: e0125166 10.1371/journal.pone.0125166
    1. Mirwald RL, Baxter-Jones AD, Bailey DA, Beunen GP. An assessment of maturity from anthropometric measurements. Med Sci Sports Exerc 2002; 34:689–694.
    1. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000; 320:1240–1243.
    1. Lim JS, Hwang JS, Lee JA, Kim DH, Park KD, Jeong JS, et al. Cross‐calibration of multi‐frequency bioelectrical impedance analysis with eight‐point tactile electrodes and dual‐energy X‐ray absorptiometry for assessment of body composition in healthy children aged 6–18 years. Pediatr Int. 2009; 51:263–268. 10.1111/j.1442-200X.2008.02698.x
    1. Parikh P, Mochari H, Mosca L. Clinical utility of a fingerstick technology to identify individuals with abnormal blood lipids and high-sensitivity C-reactive protein levels. Am J of Health Promot. 2009; 23:279–82.
    1. Shemesh T, Rowley KG, Shephard M, Piers LS, O'Dea K. Agreement between laboratory results and on-site pathology testing using Bayer DCA2000 and Cholestech LDX point-of-care methods in remote Australian Aboriginal communities. Clinica Chimica Acta. 2006; 367: 69–76.
    1. Langsted A, Freiberg JJ, Nordestgaard BG. Fasting and nonfasting lipid levels influence of normal food intake on lipids, lipoproteins, apolipoproteins, and cardiovascular risk prediction. Circulation. 2008; 118:2047–2056. 10.1161/CIRCULATIONAHA.108.804146
    1. Sidhu D, Naugler C. Fasting time and lipid levels in a community-based population: a cross-sectional study. Arch Intern Med. 2012; 172:1707–1710.
    1. Krishnaveni P, Gowda VMN. Assessing the validity of Friedewald’s formula and Anandraja’s formula for serum LDL-cholesterol calculation. J Clin Diagn Res. 2015;9:BC01–BC4.
    1. Ramsbottom R, Brewer J, Williams C. A progressive shuttle run test to estimate maximal oxygen uptake. Br J Sports Med. 1988; 22:141–144.
    1. Treuth MS, Sherwood NE, Butte NF, McClanahan BA, Obarzanek EV, Zhou A. Validity and reliability of activity measures in African-American girls for GEMS. Med Sci Sports Exerc. 2003; 35:532–539.
    1. Craig R, Mindell J, Hirani V. Health Survey for England 2008 Volume 1: Physical Activity and Fitness. The Health and Social Care Information Centre; 2009. Available:
    1. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008; 26:1557–1565. 10.1080/02640410802334196
    1. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc. 2011; 43: 1360–1368. 10.1249/MSS.0b013e318206476e
    1. Hopkins W, Marshall S, Batterham A, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009; 41:3–13. 10.1249/MSS.0b013e31818cb278
    1. Senn S. Change from baseline and analysis of covariance revisited. Stat Med. 2006; 25:4334–44.
    1. Hopkins WG, Batterham AM. Error Rates, Decisive Outcomes and Publication Bias with Several Inferential Methods. Sports Med. 2016. 10.1007/s40279-016-0517-x
    1. Batterham A, Hopkins W.Making meaningful inferences about magnitudes. Int J Sports Physiol Perform. 2006; 1(1):50–57.
    1. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale (NJ): Lawrence Erlbaum Associates; 1988.
    1. Allinson P. Missing Data: Sage University Papers Series on Quantitative Applications in the Social Sciences (07–136). London: Sage; 2001.
    1. Uh HW, Hartgers FC, Yazdanbakhsh M, Houwing-Duistermaat JJ. Evaluation of regression methods when immunological measurements are constrained by detection limits. BMC Immunol. 2008; 9 10.1186/1471-2172-9-59
    1. Rubin D. Multiple Imputation for Nonresponse in Surveys. New York: Wiley; 1987.
    1. McCarthy H, Jarrett K, Crawley H. The development of waist circumference percentiles in British children aged 5.0–16.9 y. Eur J Clin Nutr. 2001; 55:902–907.
    1. Racil G, Ounis OB, Hammouda O, Kallel A, Zouhal H, Chamari K, et al. Effects of high vs. moderate exercise intensity during interval training on lipids and adiponectin levels in obese young females. Eur J Appl Physiol. 2013; 113:2531–2540. 10.1007/s00421-013-2689-5
    1. Thackray AE, Barrett LA, Tolfrey K. Acute high-intensity interval running reduces postprandial lipemia in boys. Med Sci Sports Exerc. 2013; 45:1277–1284. 10.1249/MSS.0b013e31828452c1
    1. Freese EC, Levine AS, Chapman DP, Hausman DB, Cureton KJ. Effects of acute sprint interval cycling and energy replacement on postprandial lipemia. J Appl Physiol. 2011; 111: 1584–1589. 10.1152/japplphysiol.00416.2011
    1. Trombold JR, Christmas KM, Machin DR, Kim IY, Coyle EF. Acute high-intensity endurance exercise is more effective than moderate-intensity exercise for attenuation of postprandial triglyceride elevation. J Appl Physiol. 2013; 114: 792–800. 10.1152/japplphysiol.01028.2012
    1. Bond B, Williams CA, Jackman SR, Woodward A, Armstrong N, Barker AR. Accumulating exercise and postprandial health in adolescents. Metabolism. 2015; 64: 1068–1076. 10.1016/j.metabol.2015.05.016
    1. Buchheit M. Should we be recommending repeated sprints to improve repeated-sprint performance? Sports Med. 2102; 42:169–172.
    1. Biddle SJ, Batterham AM. High-intensity interval exercise training for public health: a big HIT or shall we HIT it on the head? Int J Behav Nutr Phys Act 2015. 10.1186/s12966-015-0254-9
    1. Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, et al. A new approach to monitoring exercise training. J Strength Cond Res.2001;15:109–115.

Source: PubMed

3
Subskrybuj