Effectiveness and cost-effectiveness of The Daily Mile on childhood weight outcomes and wellbeing: a cluster randomised controlled trial

Katie Breheny, Sandra Passmore, Peymane Adab, James Martin, Karla Hemming, Emma R Lancashire, Emma Frew, Katie Breheny, Sandra Passmore, Peymane Adab, James Martin, Karla Hemming, Emma R Lancashire, Emma Frew

Abstract

Background: The Daily Mile is designed to increase physical activity levels with children running or walking around school grounds for 15-min daily. It has been adopted by schools worldwide and endorsed as a solution to tackle obesity, despite no robust evidence of its benefits. We conducted a cluster randomised controlled trial to determine its clinical and cost-effectiveness.

Methods: Forty schools were randomly assigned (1:1) to either the Daily Mile intervention or control group in which only the usual school health and wellbeing activities were implemented. The primary outcome was BMI z-score (BMIz) at 12 months follow-up from baseline, with planned subgroup analysis to examine differential effects. Primary economic analysis outcome was incremental cost per Quality-Adjusted-Life-Year (QALY) gained.

Results: Using a constrained randomisation approach, balanced on school size, baseline BMIz and proportion of pupils eligible for free school meals, 20 schools were allocated to intervention (n = 1,153 participants) and 20 to control (n = 1,127); 3 schools withdrew (2 intervention, 1 control). At 12 months, BMIz data were available for 18 intervention schools (n = 850) and 19 control schools (n = 820 participants). Using intention-to-treat analysis the adjusted mean difference (MD) in BMIz (intervention - control) was -0.036 (95% CI: -0.085 to 0.013, p = 0.146). Pre-specified subgroup analysis showed a significant interaction with sex (p = 0.001) suggesting a moderate size benefit of The Daily Mile in girls (MD -0.097, 95% CI -0.156 to -0.037). This was consistent with the exploratory economic results that showed The Daily Mile to be highly cost-effective in girls (£2,492 per QALY), but not in boys, and overall to have a 76% chance of cost-effectiveness for the whole sample, at the commonly applied UK threshold of £20,000 per QALY.

Conclusions: Overall the Daily Mile had a small but non-significant effect on BMIz, however, it had a greater effect in girls suggesting that it might be considered as a cost-effective component of a system-wide approach to childhood obesity prevention.

Conflict of interest statement

This study was funded by Birmingham City Council and was facilitated by a collaboration between Birmingham City Council, SportBirmingham, Services for Education and the University of Birmingham. The National Institute for Health Research in England under its Career Development Fellowship fund (CDF-2015-08-013) supported KB and EF. The views expressed in this publication are those of the authors and do not necessarily reflect those of the UK NHS, the National Institute for Health Research, or the Department of Health for England. EF, PA, KH, SP and EL have previously received research grants from the National Institute of Health Research; there are no other relationships or activities that could appear to have influenced the submitted work.

Figures

Fig. 1. Participant flow.
Fig. 1. Participant flow.
*Reason for individual children lost to follow-up is unknown because loss might be due to absence (illness) on the day of measurements or being out of the school classroom for an unknown reason at the time of measurements.

References

    1. World Health Organisation. Prevalence of obesity among children and adolescents. 2018. .
    1. World Health Organisation. Facts and figures on childhood obesity. 2018. .
    1. Simmonds M, Llewellyn A, Owen CG, Woolacott N. Predicting adult obesity from childhood obesity: a systematic review and meta-analysis. Obes Rev. 2016;17:95–107. doi: 10.1111/obr.12334.
    1. The GBD 2015 Obesity Collaborators. Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med. 2017;377:13–27. doi: 10.1056/NEJMoa1614362.
    1. Dobbs R, Sawyers C, Thompson F, Manyika J, Woetzel J, Child P, et al. Overcoming obesity: an initial economic analysis. Jakarta, Indonesia: McKinsey Global Institute; 2014.
    1. Sahoo K, Sahoo B, Choudhury A, Sofi N, Kumar R, Bhadoria A. Childhood obesity: causes and consequences. J Fam Med Primary Care. 2015;4:187–92. doi: 10.4103/2249-4863.154628.
    1. Wang Y, Cai L, Wu Y, Wilson RF, Weston C, Fawole O, et al. What childhood obesity prevention programmes work? A systematic review and meta-analysis. Obes Rev. 2015;16:547–65.. doi: 10.1111/obr.12277.
    1. Waters E, de Silva-Sanigorski A, Burford BJ, Brown T, Campbell KJ, Gao Y, et al. Interventions for preventing obesity in children. Cochrane Datab Syst Rev. 2011;12:1645–858.
    1. The Daily Mile Foundation. The Daily Mile—about. 2018. .
    1. The Daily Mile Foundation. The Daily Mile 2018. .
    1. HM Government. Childhood obesity: a plan for action. Chapter 2. UK:HM Government; 2018.
    1. Chesham RA, Booth JN, Sweeney EL, Ryde GC, Gorely T, Brooks NE, et al. The Daily Mile makes primary school children more active, less sedentary and improves their fitness and body composition: a quasi-experimental pilot study. BMC Med. 2018;16:64. doi: 10.1186/s12916-018-1049-z.
    1. Birmingham City Council. Local area health profiles. 2018. .
    1. Conrad D, Capewell S. Associations between deprivation and rates of childhood overweight and obesity in England, 2007–2010: an ecological study. BMJ Open. 2012;2:e000463. doi: 10.1136/bmjopen-2011-000463.
    1. Breheny K, Adab P, Passmore S, Martin J, Lancashire E, Hemming K, et al. A cluster randomised controlled trial evaluating the effectiveness and cost-effectiveness of the daily mile on childhood obesity and wellbeing; the Birmingham daily mile protocol. BMC Public Health. 2018;18:126. doi: 10.1186/s12889-017-5019-8.
    1. Carter BR, Hood K. Balance algorithm for cluster randomized trials. BMC Med Res Methodol. 2008;8:65. doi: 10.1186/1471-2288-8-65.
    1. OFSTED. Beyond 2012—Outstanding physical activity for all. UK:OFSTED; 2013.
    1. Cole T, Pan H. LMS growth computer program. UK:Medical Research Council; 2002.
    1. Cole TJ, Freeman JV, Preece MA. Body mass index reference curves for the UK, 1990. Arch Dis Childhood. 1995;73:25–9. doi: 10.1136/adc.73.1.25.
    1. British Athletics. British Athletics Primary Endurance Awards 2018. .
    1. Stevens KJ. Working with children to develop dimensions for a preference-based, generic, pediatric, health-related quality-of-life measure. Qual Health Res. 2010;20:340–51. doi: 10.1177/1049732309358328.
    1. Schonert-Reichl KA, Guhn M, Gadermann AM, Hymel S, Sweiss L, Hertzman C. Development and validation of the middle years development instrument (MDI): assessing children’s well-being and assets across multiple contexts. Soc Indic Res. 2012;114:345–69.. doi: 10.1007/s11205-012-0149-y.
    1. HM Government. National curriculum assessments Key Stage 2. UK:Standards and Testing Agency; 2017.
    1. Kolsgaard MLP, Joner G, Brunborg C, Anderssen SA, Tonstad S, Andersen LF. Reduction in BMI z-score and improvement in cardiometabolic risk factors in obese children and adolescents. The Oslo Adiposity Intervention Study—a hospital/public health nurse combined treatment. BMC Ped. 2011;11:47. doi: 10.1186/1471-2431-11-47.
    1. Hemming K, Marsh J. A menu-driven facility for sample-size calculations in cluster randomized controlled trials. Stata J. 2013;13:114–35. doi: 10.1177/1536867X1301300109.
    1. StataCorp. Stata statistical software: Release 13. College Station, TX: StataCorp LP; 2013.
    1. Klar N, Darlington G. Methods for modelling change in cluster randomization trials. Stat Med. 2004;23:2341–57. doi: 10.1002/sim.1858.
    1. Wright N, Ivers N, Eldridge S, Taljaard M, Bremner S. A review of the use of covariates in cluster randomized trials uncovers marked discrepancies between guidance and practice. J Clin Epidemiol. 2015;68:603–9. doi: 10.1016/j.jclinepi.2014.12.006.
    1. Speidel M, Drechsler J, Sakshaug JW. Biases in multilevel analyses caused by cluster-specific fixed-effects imputation. Behav Res Methods. 2018;50:1824–40.. doi: 10.3758/s13428-017-0951-1.
    1. Stevens K. Valuation of the child health utility 9D index. Pharmacoeconomics. 2012;30:729–47. doi: 10.2165/11599120-000000000-00000.
    1. Hoch JS, Dewa CS. Advantages of the net benefit regression framework for economic evaluations of interventions in the workplace: a case study of the cost-effectiveness of a collaborative mental health care program for people receiving short-term disability benefits for psychiatric disorders. J Cccup Environ Med. 2014;56:441–5. doi: 10.1097/JOM.0000000000000130.
    1. Hoch JS, Briggs AH, Willan AR. Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis. Health Econ. 2002;11:415–30. doi: 10.1002/hec.678.
    1. Mei H, Xiong Y, Xie S, Guo S, Li Y, Guo B, et al. The impact of long-term school-based physical activity interventions on body mass index of primary school children—a meta-analysis of randomized controlled trials. BMC Public Health. 2016;16:205. doi: 10.1186/s12889-016-2829-z.
    1. Adab P, Pallan MJ, Lancashire ER, Hemming K, Frew E, Barrett T, et al. Effectiveness of a childhood obesity prevention programme delivered through schools, targeting 6 and 7 year olds: cluster randomised controlled trial (WAVES study). BMJ. 2018;360:k211.
    1. Lloyd J, Creanor S, Logan S, Green C, Dean SG, Hillsdon M, et al. Effectiveness of the Healthy Lifestyles Programme (HeLP) to prevent obesity in UK primary-school children: a cluster randomised controlled trial. Lancet Child Adolesc Health. 2018;2:35–45. doi: 10.1016/S2352-4642(17)30151-7.
    1. Khambalia AZ, Dickinson S, Hardy LL, Gill T, Baur LA. A synthesis of existing systematic reviews and meta-analyses of school-based behavioural interventions for controlling and preventing obesity. Obes Rev. 2011;13:214–33. doi: 10.1111/j.1467-789X.2011.00947.x.
    1. Bleich SN, Vercammen KA, Zatz LY, Frelier JM, Ebbeling CB, Peeters A. Interventions to prevent global childhood overweight and obesity: a systematic review. Lancet Diab Endocrinol. 2018;6:332–46. doi: 10.1016/S2213-8587(17)30358-3.
    1. Grydeland M, Bjelland M, Anderssen SA, Klepp K-I, Bergh IH, Andersen LF, et al. Effects of a 20-month cluster randomised controlled school-based intervention trial on BMI of school-aged boys and girls: the HEIA study. Br J Sports Med. 2014;48:768. doi: 10.1136/bjsports-2013-092284.
    1. Gortmaker SL, Peterson K, Wiecha J, et al. Reducing obesity via a school-based interdisciplinary intervention among youth: planet health. Arch Pediatrics Adolesc Med. 1999;153:409–18. doi: 10.1001/archpedi.153.4.409.
    1. Allender S, Millar L, Hovmand P, Bell C, Moodie M, Carter R, et al. Whole of systems trial of prevention strategies for childhood obesity: WHO STOPS childhood obesity. Int J Environ Res Public Health. 2016;13:1143.
    1. Bagnall A-M, Radley D, Jones R, Gately P, Nobles J, Van Dijk M, et al. Whole systems approaches to obesity and other complex public health challenges: a systematic review. BMC Public Health. 2019;19:8. doi: 10.1186/s12889-018-6274-z.
    1. Swinburn B, Kraak V, Rutter H, Vandevijvere S, Lobstein T, Sacks G, et al. Strengthening of accountability systems to create healthy food environments and reduce global obesity. The Lancet. 2015;385:2534–45. doi: 10.1016/S0140-6736(14)61747-5.

Source: PubMed

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