Tackling childhood obesity with big data and dynamic simulation modelling
Project title: Harnessing big data and dynamic simulation modelling to tackle child and adolescent overweight and obesity and unsustainable healthcare expenditure in Australia
Start date: March 2018
Estimated end date: December 2020
What is the issue?
Overweight and obesity in Australian children and adolescents is a significant public health challenge. When continued to adulthood, it contributes significantly to Australia’s burden of chronic disease. Conditions such as cardiovascular disease, type 2 diabetes, musculoskeletal conditions/back pain and some cancers have been estimated to cost the Australian health system more than $21 billion annually.
Some effective public policy and program interventions to address overweight and obesity in children and adolescents do exist, but they may only show effective weight reduction in individuals at a point in time. Australia needs interventions that create sustained change at population level over the longer term.
Also, the impact of implementing such interventions simultaneously is unknown. With limited public resources to achieve government priorities, it is important to determine the most efficient, effective, and cost-effective combination of child and adolescent overweight and obesity interventions, where they should be targeted, with what intensity, their likely effect over the life-course, and potential savings in healthcare expenditure in the future.
How is the project addressing the issue?
This project will build on work by the Prevention Centre that explored influences on child and adolescent overweight and obesity and chronic disease.
Dynamic simulation modelling brings together a variety of evidence sources, such as research, expert knowledge, practice experience and data, to capture the complexity of a problem. That model is then used to simulate various policy scenarios to see which is likely to deliver optimal outcomes.
The project team will:
- Engage with leading experts and draw on best available evidence and datasets to provide a more detailed representation of the dynamics of early childhood exposures and their impact on overweight and obesity across the individual’s life span
- Study adolescent diet and physical activity behaviours using app-based data collection technology. Adolescents are a notoriously hard to reach and understudied ‘at risk’ group, but an important target of overweight and obesity prevention programs. Use of wearable technologies paired with mobile phones for data collection will provide an enormously rich source of real-time data that will give important insights into influences on adolescent food choices and physical activity behaviours
- Build a national decision support tool to inform best buys for tackling child and adolescent overweight and obesity and reducing the impacts of resulting chronic diseases
- Integrate existing data assets with the national decision support tool for child and adolescent overweight and obesity in partnership with relevant national and state digital health and big data agencies to automate the updating of the tool and secure its value as a long-term decision support asset.
What are the expected outcomes?
The work will expand on the existing, local applications of dynamic simulation modelling in the ACT and NSW, and build capacity and infrastructure for embedding a data driven, interactive, national decision support tool within the Australian Government Department of Health. This tool will inform investment decisions to reduce child and adolescent overweight and obesity, overall healthcare expenditure, and health system burden.
By extending the existing dynamic simulation modelling work, this project will deliver:
- A systems approach to developing new knowledge regarding the complex interplay of in-utero, early childhood and adolescent exposures, their impact on overweight and obesity, and chronic disease impacts over the life-course
- An interactive national decision support tool developed in partnership with expert stakeholders. This tool will be capable of informing best investments across multiple portfolios to reduce child and adolescent overweight and obesity and healthcare expenditure over the short and longer term
- Vital infrastructure, capacity and sustainability of the tool within the Australian Government Department of Health.
Relevance for practice
This project will deliver a national decision support asset to inform investment decisions to reduce child and adolescent overweight and obesity, overall healthcare expenditure, and health system burden.
The project provides an opportunity for public-private partnership in the development of next generation decision support infrastructure, as well as stakeholder engagement, consensus building, and policy coherence around prevention efforts to reduce the significant financial, individual and social burden of the complex problem of child and adolescent overweight and obesity.
Associate Professor Jo-An Atkinson, University of Sydney
Professor Louise Baur AM, University of Sydney
Dr Louise Freebairn, ACT Health
Professor Andrew Page, Western Sydney University
Professor Nate Osgood, University of Saskatchewan
Dr Geoff McDonnell, The Australian Prevention Partnership Centre
Simon Chiu, The Australian Prevention Partnership Centre and the Sax Institute
Yang Qin, The Australian Prevention Partnership Centre
Former project team members
Associate Professor Alison Hayes, University of Sydney
Dr Ante Prodan, The Australian Prevention Partnership Centre
Mark Heffernan, The Australian Prevention Partnership Centre
Adam Skinner, The Australian Prevention Partnership Centre and the Sax Institute
Funding for this research has been provided from the Australian Government’s Medical Research Future Fund (MRFF). The MRFF provides funding to support health and medical research and innovation, with the objective of improving the health and wellbeing of Australians. MRFF funding has been provided to The Australian Prevention Partnership Centre under the MRFF Boosting Preventive Health Research Program. Further information on the MRFF is available at www.health.gov.au/mrff.
An interim fact sheet for the Diabetes in Pregnancy modelling work has been developed.
- Expansion of the Diabetes in Pregnancy model to include a more detailed representation of the dynamics of weight gain in early childhood has commenced.
- A proof-of-concept dynamic dashboard for visualising Ethica data has been finalised.
- A youth advisory group is being established to help us design social media recruitment materials for our study into health behaviours of adolescents.
- A new pilot study that is capturing the diet and physical activity behaviours of adolescents went live in the first week of November 2019. The project team developed a social media campaign for Facebook and Instagram using app-based data collection technology to recruit participants.
- We have recruited more than 660 young people, aged 13–19 years, to participate in the pilot study. Survey participants are asked to fill in multiple surveys over three months, responding to questions about their health, daily activities and screen use.
- Between September and November 2109, we held held two workshops on dynamic simulation methods to develop understanding with policy agencies. At our September 2019 workshop, childhood overweight and obesity experts mapped the causal factors around childhood overweight and obesity. The conceptual map will be used to develop a simulation model that will help us explore the potential impact of interventions over time.
- Freebairn L, Atkinson JA, Qin Y, Nolan C, Kent A L, et al. ‘Turning the tide’ on hyperglycemia in pregnancy: Insights from multi-scale dynamic simulation modelling. BMJ Open Diabetes Research & Care.
- Freebairn L, Atkinson J, Osgood N, Kelly P M, McDonnell G, and Rychetnik L. Turning conceptual systems maps into dynamic simulation models: revealing the analytical deliberations and decisions of participatory dynamic simulation modelling – an Australian health sector case study. PLOS ONE, 2019.
- Freebairn L, Atkinson JA, Kelly P, McDonnell G, Rychetnik L. Decision makers’ experience of participatory dynamic simulation modelling: methods for public health policy. BMC Med Inform Decis. 2018; doi.org/10.1186/s12911-018-0707-6
- Roberts N, Atkinson J, McDonnell G, Osgood N, Wutzke S. Systems modeling and big data for non-communicable disease prevention. Oxford Bibliographies. doi:10.1093/OBO/9780199756797
- Mihrshahi S, Gow ML, Baur LA. Contemporary approaches to the prevention and management of paediatric obesity: an Australian focus. Med J Australia. 2018;209 (6): 267-274. doi: 10.5694/mja18.00140
- Mihrshahi S, Baur LA. What exposures in early life are risk factors for childhood obesity? J Paediatr Child Health. 2018; doi: 10.1111/jpc.14195. [Epub ahead of print]
- Page A, Currie D, Peng C, Prodan A, Freebairn L. Systems science for public health. Preconference workshop. Australian Epidemiological Association annual Scientific Meeting. 23-25 October 2019. Brisbane, Australia.
- Atkinson J-A, Kruger K. Dynamic simulation modelling for health. ACT Health workshop. 16 October 2019. Canberra.
- Freebairn, L. Co-producing knowledge using participatory modelling for complex, health policy questions. Invited speaker at: Environmental Prediction Symposium. Symposium hosted by CSIRO. 4-5 June 2019. Canberra.
- Freebairn, L. Harnessing advances in simulation modelling to explore the complex issue of diabetes in pregnancy. Presentation at Diabetes in Pregnancy Forum hosted by ACT Health and University of Canberra. 17 August 2018. Canberra
- Freebairn L, Atkinson JA, Kelly PM and Rychetnik L. Participatory dynamic simulation modelling for knowledge mobilisation in public health policy. Abstract accepted for Sax Institute Knowledge Mobilisation Conference. 4-5 July 2018. Sydney