Cost-effectiveness of reducing children's sedentary time and increasing physical activity at school: the Transform-Us! intervention.
Cost-effectiveness
Economic evaluation
Physical activity
Sedentary behavior
Journal
The international journal of behavioral nutrition and physical activity
ISSN: 1479-5868
Titre abrégé: Int J Behav Nutr Phys Act
Pays: England
ID NLM: 101217089
Informations de publication
Date de publication:
12 Feb 2024
12 Feb 2024
Historique:
received:
13
08
2023
accepted:
08
01
2024
medline:
13
2
2024
pubmed:
13
2
2024
entrez:
12
2
2024
Statut:
epublish
Résumé
Improving physical activity and reducing sedentary behavior represent important areas for intervention in childhood in order to reduce the burden of chronic disease related to obesity and physical inactivity in later life. This paper aims to determine the cost-effectiveness of a multi-arm primary school-based intervention to increase physical activity and/or reduce sedentary time in 8-9 year old children (Transform-Us!). Modelled cost-utility analysis, using costs and effects from a cluster randomized controlled trial of a 30-month intervention that used pedagogical and environmental strategies to reduce and break up sedentary behaviour (SB-I), promote physical activity (PA-I), or a combined approach (PA + SB-I), compared to current practice. A validated multiple-cohort lifetable model (ACE-Obesity Policy model) estimated the obesity and physical activity-related health outcomes (measured as change in body mass index and change in metabolic equivalent task minutes respectively) and healthcare cost-savings over the cohort's lifetime from the public-payer perspective, assuming the intervention was delivered to all 8-9 year old children attending Australian Government primary schools. Sensitivity analyses tested the impact on cost-effectiveness of varying key input parameters, including maintenance of intervention effect assumptions. Cost-effectiveness results demonstrated that, when compared to control schools, the PA-I and SB-I intervention arms were "dominant", meaning that they resulted in net health benefits and healthcare cost-savings if the intervention effects were maintained. When the costs and effects of these intervention arms were extrapolated to the Australian population, results suggested significant potential as obesity prevention measures (PA-I: 60,780 HALYs saved (95% UI 15,007-109,413), healthcare cost-savings AUD641M (95% UI AUD165M-$1.1B); SB-I: 61,126 HALYs saved (95% UI 11,770 - 111,249), healthcare cost-savings AUD654M (95% UI AUD126M-1.2B)). The PA-I and SB-I interventions remained cost-effective in sensitivity analysis, assuming the full decay of intervention effect after 10 years. The PA-I and SB-I Transform-Us! intervention arms represent good value for money and could lead to health benefits and healthcare cost-savings arising from the prevention of chronic disease in later life if intervention effects are sustained. International Standard Randomized Controlled Trial Number (ISRCTN83725066). Australia and New Zealand Clinical Trials Registry Number (ACTRN12609000715279).
Sections du résumé
BACKGROUND
BACKGROUND
Improving physical activity and reducing sedentary behavior represent important areas for intervention in childhood in order to reduce the burden of chronic disease related to obesity and physical inactivity in later life. This paper aims to determine the cost-effectiveness of a multi-arm primary school-based intervention to increase physical activity and/or reduce sedentary time in 8-9 year old children (Transform-Us!).
METHODS
METHODS
Modelled cost-utility analysis, using costs and effects from a cluster randomized controlled trial of a 30-month intervention that used pedagogical and environmental strategies to reduce and break up sedentary behaviour (SB-I), promote physical activity (PA-I), or a combined approach (PA + SB-I), compared to current practice. A validated multiple-cohort lifetable model (ACE-Obesity Policy model) estimated the obesity and physical activity-related health outcomes (measured as change in body mass index and change in metabolic equivalent task minutes respectively) and healthcare cost-savings over the cohort's lifetime from the public-payer perspective, assuming the intervention was delivered to all 8-9 year old children attending Australian Government primary schools. Sensitivity analyses tested the impact on cost-effectiveness of varying key input parameters, including maintenance of intervention effect assumptions.
RESULTS
RESULTS
Cost-effectiveness results demonstrated that, when compared to control schools, the PA-I and SB-I intervention arms were "dominant", meaning that they resulted in net health benefits and healthcare cost-savings if the intervention effects were maintained. When the costs and effects of these intervention arms were extrapolated to the Australian population, results suggested significant potential as obesity prevention measures (PA-I: 60,780 HALYs saved (95% UI 15,007-109,413), healthcare cost-savings AUD641M (95% UI AUD165M-$1.1B); SB-I: 61,126 HALYs saved (95% UI 11,770 - 111,249), healthcare cost-savings AUD654M (95% UI AUD126M-1.2B)). The PA-I and SB-I interventions remained cost-effective in sensitivity analysis, assuming the full decay of intervention effect after 10 years.
CONCLUSIONS
CONCLUSIONS
The PA-I and SB-I Transform-Us! intervention arms represent good value for money and could lead to health benefits and healthcare cost-savings arising from the prevention of chronic disease in later life if intervention effects are sustained.
TRIAL REGISTRATION
BACKGROUND
International Standard Randomized Controlled Trial Number (ISRCTN83725066). Australia and New Zealand Clinical Trials Registry Number (ACTRN12609000715279).
Identifiants
pubmed: 38347579
doi: 10.1186/s12966-024-01560-3
pii: 10.1186/s12966-024-01560-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
15Subventions
Organisme : National Health and Medical Research Council
ID : 533815
Organisme : National Health and Medical Research Council
ID : 1041020
Organisme : National Health and Medical Research Council
ID : 1041020
Organisme : National Health and Medical Research Council
ID : 1101675
Organisme : National Health and Medical Research Council
ID : 1101675
Organisme : National Health and Medical Research Council
ID : 1176885
Organisme : National Health and Medical Research Council
ID : 1078630
Organisme : Australian Research Council
ID : 130100637
Organisme : Australian Research Council
ID : 140100085
Organisme : National Heart Foundation of Australia
ID : 101895
Informations de copyright
© 2024. The Author(s).
Références
Aubert S, Barnes JD, Abdeta C, Abi Nader P, Adeniyi AF, Aguilar-Farias N, et al. Global matrix 3.0 physical activity report card grades for children and youth: results and analysis from 49 countries. J Phys Act Health. 2018;15(S2):251–s73.
doi: 10.1123/jpah.2018-0472
Centers for Disease Control and Prevention. Childhood Overweight and Obesity 2021 [12 January]. Available from: https://www.cdc.gov/obesity/childhood/ .
Kohl HW, Craig CL, Lambert EV, Inoue S, Alkandari JR, Leetongin G, et al. The pandemic of physical inactivity: global action for public health. The Lancet. 2012;380(9838):294–305.
doi: 10.1016/S0140-6736(12)60898-8
Verswijveren SJJM, Lamb KE, Bell LA, Timperio A, Salmon J, Ridgers ND. Associations between activity patterns and cardio-metabolic risk factors in children and adolescents: a systematic review. PLoS ONE. 2018;13(8):e0201947.
pubmed: 30114269
pmcid: 6095515
doi: 10.1371/journal.pone.0201947
Hamilton D, Dee A, Perry IJ. The lifetime costs of overweight and obesity in childhood and adolescence: a systematic review. Obes Rev. 2018;19:452–63.
pubmed: 29271111
doi: 10.1111/obr.12649
Love R, Adams J, van Sluijs EMF. Are school-based physical activity interventions effective and equitable? A meta-analysis of cluster randomized controlled trials with accelerometer-assessed activity. Obes Rev. 2019;20(6):859–70.
pubmed: 30628172
pmcid: 6563481
doi: 10.1111/obr.12823
Schaap R, Bessems K, Otten R, Kremers S, van Nassau F. Measuring implementation fidelity of school-based obesity prevention programmes: a systematic review. Int J Behav Nutr Phys Activity. 2018;15(1):75.
doi: 10.1186/s12966-018-0709-x
Brown T, Moore THM, Hooper L, Gao Y, Zayegh A, Ijaz S et al. Interventions for preventing obesity in children. Cochrane Database of Systematic Reviews. 2019(7).
Liu Z, Xu H-M, Wen L-M, Peng Y-Z, Lin L-Z, Zhou S, et al. A systematic review and meta-analysis of the overall effects of school-based obesity prevention interventions and effect differences by intervention components. Int J Behav Nutr Phys Activity. 2019;16(1):95.
doi: 10.1186/s12966-019-0848-8
Oosterhoff M, Bosma H, van Schayck OCP, Evers SMAA, Dirksen CD, Joore MA. A systematic review on economic evaluations of school-based lifestyle interventions targeting weight-related behaviours among 4–12 year olds: issues and ways forward. Prev Med. 2018;114:115–22.
pubmed: 29959951
doi: 10.1016/j.ypmed.2018.06.015
Salmon J, Arundell L, Hume C, Brown H, Hesketh K, Dunstan DW, et al. A cluster-randomized controlled trial to reduce sedentary behavior and promote physical activity and health of 8–9 year olds: the Transform-Us! Study. BMC Public Health. 2011;11(1):759.
pubmed: 21970511
pmcid: 3213038
doi: 10.1186/1471-2458-11-759
Yıldırım M, Arundell L, Cerin E, Carson V, Brown H, Crawford D, et al. What helps children to move more at school recess and lunchtime? Mid-intervention results from Transform-Us! Cluster-randomised controlled trial. Br J Sports Med. 2014;48(3):271–7.
pubmed: 24124036
doi: 10.1136/bjsports-2013-092466
Carson V, Salmon J, Arundell L, Ridgers ND, Cerin E, Brown H, et al. Examination of mid-intervention mediating effects on objectively assessed sedentary time among children in the Transform-Us! Cluster-randomized controlled trial. Int J Behav Nutr Phys Activity. 2013;10(1):62.
doi: 10.1186/1479-5868-10-62
Salmon J, Arundell L, Cerin E, Ridgers ND, Hesketh KD, Daly RM et al. Transform-Us! Cluster RCT: 18-month and 30-month effects on children’s physical activity, sedentary time and cardiometabolic risk markers. Br J Sports Med. 2022:bjsports–2022.
Sanders GD, Neumann PJ, Basu A, Brock DW, Feeny D, Krahn M, et al. Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA. 2016;316(10):1093–103.
pubmed: 27623463
doi: 10.1001/jama.2016.12195
Husereau D, Drummond M, Augustovski F, de Bekker-Grob E, Briggs AH, Carswell C, et al. Consolidated Health Economic evaluation reporting standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations. BMJ. 2022;376:e067975.
pubmed: 35017145
pmcid: 8749494
doi: 10.1136/bmj-2021-067975
Australian Bureau of Statistics. Schools Australia. Canberra, Australia: ABS; 2019.
Lal A, Mantilla-Herrera AM, Veerman L, Backholer K, Sacks G, Moodie M, et al. Modelled health benefits of a sugar-sweetened beverage tax across different socioeconomic groups in Australia: a cost-effectiveness and equity analysis. PLoS Med. 2017;14(6):e1002326.
pubmed: 28654688
pmcid: 5486958
doi: 10.1371/journal.pmed.1002326
Brown V, Moodie M, Cobiac L, Herrera AM, Carter R. Obesity-related health impacts of fuel excise taxation-an evidence review and cost-effectiveness study. BMC Public Health. 2017;17(1):359.
pubmed: 28468618
pmcid: 5415832
doi: 10.1186/s12889-017-4271-2
Crino M, Herrera AMM, Ananthapavan J, Wu JH, Neal B, Lee YY, et al. Modelled cost-effectiveness of a Package size Cap and a Kilojoule Reduction Intervention to Reduce Energy Intake from Sugar-Sweetened beverages in Australia. Nutrients. 2017;9(9):983.
pubmed: 28878175
pmcid: 5622743
doi: 10.3390/nu9090983
Brown V, Ananthapavan J, Veerman L, Sacks G, Lal A, Peeters A, et al. The potential cost-effectiveness and Equity Impacts of Restricting Television Advertising of Unhealthy Food and Beverages to Australian children. Nutrients. 2018;10(5):622.
pubmed: 29762517
pmcid: 5986502
doi: 10.3390/nu10050622
Ananthapavan J, Sacks G, Brown V, Moodie M, Nguyen P, Barendregt J et al. Priority-setting for Obesity Prevention - the assessing cost-effectiveness of obesity Prevention policies in Australia (ACE-Obesity policy) study. PLoS ONE. 2020;15: e0234804.
Carter R, Moodie M, Markwick A, Magnus A, Vos T, Swinburn B, et al. Assessing cost-effectiveness in obesity (ACE-obesity): an overview of the ACE approach, economic methods and cost results. BMC Public Health. 2009;9:419.
pubmed: 19922625
pmcid: 2785790
doi: 10.1186/1471-2458-9-419
York Health Economics Consortium. Time Horizon The University of York2016 [Available from: https://yhec.co.uk/glossary/time-horizon/ .
George B, Harris A, Mitchell A. Cost-effectiveness analysis and the consistency of decision making. PharmacoEconomics. 2001;19(11):1103–9.
pubmed: 11735677
doi: 10.2165/00019053-200119110-00004
Australian Government Department of Education and Training. School term dates 2018 Canberra, Australia: Australian Government.; 2018 [Available from: https://www.education.gov.au/school-term-dates-2018 .
Australian Bureau of Statistics. 5345.0 - Labour Price Index, Australia, Dec 2011 Canberra, Australia: ABS.; 2012 [Available from: http://www.abs.gov.au/AUSSTATS/abs@.nsf/allprimarymainfeatures/6206728D8CE976E 8CA2579FF0011B52F?opendocument.
Ridley K, Ainsworth BE, Olds TS. Development of a compendium of energy expenditures for youth. Int J Behav Nutr Phys Activity. 2008;5(1):45.
doi: 10.1186/1479-5868-5-45
Ananthapavan J, Sacks G, Brown V, Moodie M, Nguyen P, Barendregt J, et al. Assessing cost-effectiveness of obesity Prevention policies in Australia. Melbourne: Deakin University; 2018.
Briggs A, Sculpher M. An introduction to Markov modelling for economic evaluation. PharmacoEconomics. 1998;13(4):397–409.
pubmed: 10178664
doi: 10.2165/00019053-199813040-00003
Barendregt JJ, Veerman JL. Categorical versus continuous risk factors and the calculation of potential impact fractions. J Epidemiol Community Health. 2010;64(3):209–12.
pubmed: 19692711
doi: 10.1136/jech.2009.090274
Danaei G, Ding EL, Mozaffarian D, Taylor B, Rehm J, Murray CJ, et al. The preventable causes of death in the United States: comparative risk assessment of dietary, lifestyle, and metabolic risk factors. PLoS Med. 2009;6(4):e1000058.
pubmed: 19399161
pmcid: 2667673
doi: 10.1371/journal.pmed.1000058
Cobiac L, Vos T, Veerman L. Cost-effectiveness of Weight watchers and the Lighten up to a healthy lifestyle program. Aust N Z J Public Health. 2010;34(3):240–7.
pubmed: 20618263
doi: 10.1111/j.1753-6405.2010.00520.x
Australian Bureau of Statistics. Australian Health Survey 2011-12, confidentialised unit record files (CURFs). Canberra, Australia: ABS; 2015.
Institute for Health Metrics and Evaluation. Global Burden of Disease Database Seattle: IHME, University of Washington.; 2016 [Available from: http://www.healthdata.org/search-gbd-data?s=Transport%20injuries .
Salomon JA, Vos T, Hogan DR, Gagnon M, Naghavi M, Mokdad A, et al. Common values in assessing health outcomes from disease and injury: disability weights measurement study for the global burden of Disease Study 2010. The Lancet. 2012;380(9859):2129–43.
doi: 10.1016/S0140-6736(12)61680-8
Chen G, Ratcliffe J, Olds T, Magarey A, Jones M, Leslie E, BMI. Health behaviors, and quality of life in children and adolescents: a School-based study. Pediatrics. 2014;133(4):e868–e74.
pubmed: 24590749
doi: 10.1542/peds.2013-0622
George B, Harris A, Mitchell A. Cost-effectiveness analysis and the consistency of decision making: evidence from pharmaceutical reimbursement in Australia (1991 to 1996). PharmacoEconomics. 2001;19(11):1103–9.
pubmed: 11735677
doi: 10.2165/00019053-200119110-00004
Australian Bureau of Statistics. Census 2011 Canberra: ABS.; 2011 [Available from: http://www.abs.gov.au/websitedbs/censushome.nsf/home/data?opendocument&navpos=200 .
Murray CJ, Abraham J, Ali MK, Alvarado M, Atkinson C, Baddour LM, et al. The state of US health, 1990–2010: burden of diseases, injuries, and risk factors. JAMA. 2013;310(6):591–606.
pubmed: 23842577
doi: 10.1001/jama.2013.13805
Zapata-Diomedi B, Herrera AMM, Veerman JL. The effects of built environment attributes on physical activity-related health and health care costs outcomes in Australia. Health Place. 2016;42:19–29.
pubmed: 27614063
doi: 10.1016/j.healthplace.2016.08.010
Australian Institute of Health and Welfare. Health system expenditure on disease and injury in Australia, 2000-01. Canberra, Australia: AIHW; 2004.
Australian Institute of Health and Welfare. Health expenditure Australia 2009-10, Cat no. HWE55. Canberra: AIHW; 2011.
Victorian Department of Education and Training. Victorian School Summary Statistics July 2017: Victorian Government 2017 [Available from: www.education.vic.gov.au/Documents/about/department/classsizes.xlsx .
Department of Education and Early Childhood Development. Teacher salary rates Victoria: Victorian Government.; 2011 [Available from: http://www.eduweb.vic.gov.au/edulibrary/public/hr/empconditions/Teacher_salary_rates.pdf .
Australian Bureau of Statistics. 6348.0- Labour Costs, Australia, 2010-11 Canberra, Australia: ABS.; 2012 [Available from: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6348.02010-11?OpenDocument .
Australian Bureau of Statistics. 6302.0-Average Weekly Earnings, Australia, May 2010 Canberra, Australia: ABS.; 2010 [Available from: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6302.0May%202010?OpenDocument .
EpiGear International. Ersatz Brisbane, Australia: EpiGear International.; 2016 [Available from: http://www.epigear.com/index_files/ersatz.html .
Gortmaker SL, Long MW, Resch SC, Ward ZJ, Cradock AL, Barrett JL, et al. Cost effectiveness of childhood obesity interventions: evidence and methods for CHOICES. Am J Prev Med. 2015;49(1):102–11.
pubmed: 26094231
pmcid: 9508900
doi: 10.1016/j.amepre.2015.03.032
Brown V, Ananthapavan J, Sonntag D, Tan EJ, Hayes A, Moodie M. The potential for long-term cost-effectiveness of obesity prevention interventions in the early years of life. Pediatr Obes. 2019;0(0):e12517.
doi: 10.1111/ijpo.12517
Ananthapavan J, Sacks G, Brown V, Moodie M, Nguyen P, Barendregt J, et al. Assessing cost-effectiveness of obesity Prevention policies in Australia 2018 (ACE-Obesity policy). Melbourne: Deakin University; 2018.
Herman KM, Craig CL, Gauvin L, Katzmarzyk PT. Tracking of obesity and physical activity from childhood to adulthood: the physical activity longitudinal study. Int J Pediatr Obes. 2009;4(4):281–8.
pubmed: 19922043
doi: 10.3109/17477160802596171
Gordon-Larsen P, Nelson MC, Popkin BM. Longitudinal physical activity and sedentary behavior trends: adolescence to adulthood. Am J Prev Med. 2004;27(4):277–83.
pubmed: 15488356
doi: 10.1016/j.amepre.2004.07.006
Batista MB, Romanzini CLP, Barbosa CCL, Blasquez Shigaki G, Romanzini M, Ronque ERV. Participation in sports in childhood and adolescence and physical activity in adulthood: a systematic review. J Sports Sci. 2019;37(19):2253–62.
pubmed: 31179841
doi: 10.1080/02640414.2019.1627696
Döring N, Zethraeus N, Tynelius P, de Munter J, Sonntag D, Rasmussen F. Economic evaluation of PRIMROSE-A trial-based analysis of an early childhood intervention to prevent obesity. Front Endocrinol. 2018;9:104.
doi: 10.3389/fendo.2018.00104
Brown V, Tan E, Hayes A, Petrou S, Moodie M. Utility values for childhood obesity interventions: a systematic review and meta-analysis of the evidence for use in economic evaluation. Obes Rev. 2018;19(7):905–16.
pubmed: 29356315
doi: 10.1111/obr.12672
Centers for Disease Control and Prevention. Childhood Obesity Causes and Consequences Atlanta, USA, CDC.:; 2016 [Available from: https://www.cdc.gov/obesity/childhood/causes.html .