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Lam HY, Jayasinghe S, Ahuja KDK, Hills AP. Active School Commuting in School Children: A Narrative Review of Current Evidence and Future Research Implications. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6929. [PMID: 37887667 PMCID: PMC10606062 DOI: 10.3390/ijerph20206929] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/06/2023] [Accepted: 10/11/2023] [Indexed: 10/28/2023]
Abstract
Active school commuting (ASC) has been proposed as a practical way to inculcate positive physical activity habits in children. This paper reviews the current evidence regarding ASC among children, highlights advances in research techniques and existing limitations in the field, and outlines future implications for research and promotion. A comprehensive literature search was conducted to identify English language studies on ASC among children aged 6-12 years, followed by a narrative review. ASC has witnessed a global decline, despite evidence of its contribution to physical activity levels. Context-dependent factors such as commuting distance and parental safety concerns are consistently identified as key determinants of ASC. Several promising interventions have been identified. Despite the limitations in intervention scope and quality, notable advancements in research techniques, such as multilevel regression and agent-based modelling, have been identified. Effective promotion of ASC to tackle childhood physical inactivity requires collaborative efforts among schools, parents, and the government, and should be tailored to address multilevel determinants within the local context. Future research should leverage recent advancements in research techniques to develop effective promotion strategies, while considering the context-dependent nature of ASC behaviours and addressing existing limitations, including the lack of standardised definitions and limited geographical and age coverage.
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Affiliation(s)
- Ho Yeung Lam
- School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, TAS 7250, Australia; (S.J.); (K.D.K.A.); (A.P.H.)
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Baugh Littlejohns L, Near E, McKee G, Rasali D, Naiman D, Faulkner G. A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach? Health Res Policy Syst 2023; 21:18. [PMID: 36864409 PMCID: PMC9979563 DOI: 10.1186/s12961-023-00961-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 02/11/2023] [Indexed: 03/04/2023] Open
Abstract
BACKGROUND Complex systems approaches are increasingly used in health promotion and noncommunicable disease prevention research, policy and practice. Questions emerge as to the best ways to take a complex systems approach, specifically with respect to population physical activity (PA). Using an Attributes Model is one way to understand complex systems. We aimed to examine the types of complex systems methods used in current PA research and identify what methods align with a whole system approach as reflected by an Attributes Model. METHODS A scoping review was conducted and two databases were searched. Twenty-five articles were selected and data analysis was based upon the following: the complex systems research methods used, research aims, if participatory methods were used and evidence of discussion regarding attributes of systems. RESULTS There were three groups of methods used: system mapping, simulation modelling and network analysis. System mapping methods appeared to align best with a whole system approach to PA promotion because they largely aimed to understand complex systems, examined interactions and feedback among variables, and used participatory methods. Most of these articles focused on PA (as opposed to integrated studies). Simulation modelling methods were largely focused on examining complex problems and identifying interventions. These methods did not generally focus on PA or use participatory methods. While network analysis articles focused on examining complex systems and identifying interventions, they did not focus on PA nor use participatory methods. All attributes were discussed in some way in the articles. Attributes were explicitly reported on in terms of findings or were part of discussion and conclusion sections. System mapping methods appear to be well aligned with a whole system approach because these methods addressed all attributes in some way. We did not find this pattern with other methods. CONCLUSIONS Future research using complex systems methods may benefit from applying the Attributes Model in conjunction with system mapping methods. Simulation modelling and network analysis methods are seen as complementary and could be used when system mapping methods identify priorities for further investigation (e.g. what interventions to implement or how densely connected relationships are in systems).
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Affiliation(s)
- Lori Baugh Littlejohns
- BC Centre for Disease Control, 655 W 12th Ave, Vancouver, BC, V5Z 4R4, Canada. .,School of Kinesiology, University of British Columbia, 210-6081 University Boulevard, Vancouver, BC, V6T 1Z1, Canada.
| | - Erin Near
- grid.34429.380000 0004 1936 8198Department of Population Medicine, University of Guelph, Stewart Building, Building #45, Rm 2509, Guelph, ON N1G 2W1 Canada
| | - Geoff McKee
- grid.418246.d0000 0001 0352 641XBC Centre for Disease Control, 655 W 12th Ave, Vancouver, BC V5Z 4R4 Canada ,grid.17091.3e0000 0001 2288 9830School of Population and Public Health, University of British Columbia, 2206 E Mall, Vancouver, BC V6T 1Z3 Canada
| | - Drona Rasali
- grid.418246.d0000 0001 0352 641XBC Centre for Disease Control, 655 W 12th Ave, Vancouver, BC V5Z 4R4 Canada ,grid.17091.3e0000 0001 2288 9830School of Population and Public Health, University of British Columbia, 2206 E Mall, Vancouver, BC V6T 1Z3 Canada
| | - Daniel Naiman
- grid.453059.e0000000107220098BC Ministry of Health, Stn Prov Govt, PO Box 9646, Victoria, BC V8W 9P1 Canada
| | - Guy Faulkner
- grid.17091.3e0000 0001 2288 9830School of Kinesiology, University of British Columbia, 210-6081 University Boulevard, Vancouver, BC V6T 1Z1 Canada
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Boyd J, Wilson R, Elsenbroich C, Heppenstall A, Meier P. Agent-Based Modelling of Health Inequalities following the Complexity Turn in Public Health: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:16807. [PMID: 36554687 PMCID: PMC9779847 DOI: 10.3390/ijerph192416807] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/11/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
There is an increasing focus on the role of complexity in public health and public policy fields which has brought about a methodological shift towards computational approaches. This includes agent-based modelling (ABM), a method used to simulate individuals, their behaviour and interactions with each other, and their social and physical environment. This paper aims to systematically review the use of ABM to simulate the generation or persistence of health inequalities. PubMed, Scopus, and Web of Science (1 January 2013-15 November 2022) were searched, supplemented with manual reference list searching. Twenty studies were included; fourteen of them described models of health behaviours, most commonly relating to diet (n = 7). Six models explored health outcomes, e.g., morbidity, mortality, and depression. All of the included models involved heterogeneous agents and were dynamic, with agents making decisions, growing older, and/or becoming exposed to different health risks. Eighteen models represented physical space and in eleven models, agents interacted with other agents through social networks. ABM is increasingly contributing to our understanding of the socioeconomic inequalities in health. However, to date, the majority of these models focus on the differences in health behaviours. Future research should attempt to investigate the social and economic drivers of health inequalities using ABM.
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Affiliation(s)
- Jennifer Boyd
- MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow G3 7HR, UK
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - Rebekah Wilson
- College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G61 1QH, UK
| | - Corinna Elsenbroich
- MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow G3 7HR, UK
| | - Alison Heppenstall
- MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow G3 7HR, UK
- School of Social and Political Sciences, University of Glasgow, Glasgow G12 8RT, UK
| | - Petra Meier
- MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow G3 7HR, UK
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Sonnenschein T, Scheider S, de Wit GA, Tonne CC, Vermeulen R. Agent-based modeling of urban exposome interventions: prospects, model architectures, and methodological challenges. EXPOSOME 2022; 2:osac009. [PMID: 37811475 PMCID: PMC7615180 DOI: 10.1093/exposome/osac009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
With ever more people living in cities worldwide, it becomes increasingly important to understand and improve the impact of the urban habitat on livability, health behaviors, and health outcomes. However, implementing interventions that tackle the exposome in complex urban systems can be costly and have long-term, sometimes unforeseen, impacts. Hence, it is crucial to assess the health impact, cost-effectiveness, and social distributional impacts of possible urban exposome interventions (UEIs) before implementing them. Spatial agent-based modeling (ABM) can capture complex behavior-environment interactions, exposure dynamics, and social outcomes in a spatial context. This article discusses model architectures and methodological challenges for successfully modeling UEIs using spatial ABM. We review the potential and limitations of the method; model components required to capture active and passive exposure and intervention effects; human-environment interactions and their integration into the macro-level health impact assessment and social costs benefit analysis; and strategies for model calibration. Major challenges for a successful application of ABM to UEI assessment are (1) the design of realistic behavioral models that can capture different types of exposure and that respond to urban interventions, (2) the mismatch between the possible granularity of exposure estimates and the evidence for corresponding exposure-response functions, (3) the scalability issues that emerge when aiming to estimate long-term effects such as health and social impacts based on high-resolution models of human-environment interactions, (4) as well as the data- and computational complexity of calibrating the resulting agent-based model. Although challenges exist, strategies are proposed to improve the implementation of ABM in exposome research.
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Affiliation(s)
- Tabea Sonnenschein
- Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Institute of Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | | | - G. Ardine de Wit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Centre for Nutrition, Prevention and Healthcare, National Institute of Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Health Economics and Health Technology Assessment, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Cathryn C. Tonne
- Barcelona Institute for Global Health, CIBER Epidemiologia y Salud Publica (CIBERESP), Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Roel Vermeulen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Institute of Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
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Nau T, Bauman A, Smith BJ, Bellew W. A scoping review of systems approaches for increasing physical activity in populations. Health Res Policy Syst 2022; 20:104. [PMID: 36175916 PMCID: PMC9524093 DOI: 10.1186/s12961-022-00906-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 09/02/2022] [Indexed: 11/27/2022] Open
Abstract
Introduction The past decade has increasingly seen systems approaches as a featured theme in public health studies and policy documents. This trend is evident in the area of physical activity, which is a significant global health risk factor that is addressed in WHO’s Global Action Plan on Physical Activity. We undertook a comprehensive scoping review to characterize the application of systems approaches to physical activity, to develop a typology of the objectives, themes and methods of research papers that purported to apply systems thinking to this issue. Methods We searched electronic databases (PubMed, Web of Science, Scopus and PsycINFO) for studies published during the period 2010–2021 that explicitly applied systems approaches or methods to investigate and/or address population physical activity. A framework using systems-based methodological approaches was adapted to classify physical activity studies according to their predominant approach, covering basic descriptive, complex analytical and advanced forms of practice. We selected case studies from retained studies to depict the current “state of the art”. Results We included 155 articles in our narrative account. Literature reporting the application of systems approaches to physical activity is skewed towards basic methods and frameworks, with most attention devoted to conceptual framing and predictive modelling. There are few well-described examples of physical activity interventions which have been planned, implemented and evaluated using a systems perspective. There is some evidence of “retrofitted” complex system framing to describe programmes and interventions which were not designed as such. Discussion We propose a classification of systems-based approaches to physical activity promotion together with an explanation of the strategies encompassed. The classification is designed to stimulate debate amongst policy-makers, practitioners and researchers to inform the further implementation and evaluation of systems approaches to physical activity. Conclusion The use of systems approaches within the field of physical activity is at an early stage of development, with a preponderance of descriptive approaches and a dearth of more complex analyses. We need to see movement towards a more sophisticated research agenda spanning the development, implementation and evaluation of systems-level interventions. Supplementary Information The online version contains supplementary material available at 10.1186/s12961-022-00906-2.
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Affiliation(s)
- Tracy Nau
- Prevention Research Collaboration, Charles Perkins Centre, School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia. .,The Australian Prevention Partnership Centre, Sydney, NSW, Australia.
| | - Adrian Bauman
- Prevention Research Collaboration, Charles Perkins Centre, School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,The Australian Prevention Partnership Centre, Sydney, NSW, Australia
| | - Ben J Smith
- Prevention Research Collaboration, Charles Perkins Centre, School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,The Australian Prevention Partnership Centre, Sydney, NSW, Australia
| | - William Bellew
- Prevention Research Collaboration, Charles Perkins Centre, School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,The Australian Prevention Partnership Centre, Sydney, NSW, Australia
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Network Analysis for a Community-Based School- and Family-Based Obesity Prevention Program. Healthcare (Basel) 2022; 10:healthcare10081501. [PMID: 36011157 PMCID: PMC9408267 DOI: 10.3390/healthcare10081501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/05/2022] [Accepted: 08/06/2022] [Indexed: 11/17/2022] Open
Abstract
Rising childhood obesity with its detrimental health consequences poses a challenge to the health care system. Community-based, multi-setting interventions with the participatory involvement of relevant stakeholders are emerging as promising. To gain insights into the structural and processual characteristics of stakeholder networks, conducting a network analysis (NA) is advisable. Within the program “Family+—Healthy Living Together in Families and Schools”, a network analysis was conducted in two rural model regions and one urban model region. Relevant stakeholders were identified in 2020–2021 through expert interviews and interviewed by telephone to elicit key variables such as frequency of contact and intensity of collaboration. Throughout the NA, characteristics such as density, centrality, and connectedness were analyzed and are presented graphically. Due to the differences in the number of inhabitants and the rural or urban structure of the model regions, the three networks (network#1, network#2, and network#3) included 20, 14, and 12 stakeholders, respectively. All networks had similar densities (network#1, 48%; network#2, 52%; network#3, 42%), whereas the degree centrality of network#1 (0.57) and network#3 (0.58) was one-third higher compared with network#2 (0.39). All three networks differed in the distribution of stakeholders in terms of field of expertise and structural orientation. On average, stakeholders exchanged information quarterly and were connected on an informal level. Based on the results of the NA, it appears to be useful to initialize a community health facilitator to involve relevant stakeholders from the education, sports, and health systems in projects and to strive for the goal of sustainable health promotion, regardless of the rural or urban structure of the region. Participatory involvement of relevant stakeholders can have a positive influence on the effective dissemination of information and networking with other stakeholders.
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Koorts H, Salmon PM, Swain CTV, Cassar S, Strickland D, Salmon J. A systems thinking approach to understanding youth active recreation. Int J Behav Nutr Phys Act 2022; 19:53. [PMID: 35549726 PMCID: PMC9097093 DOI: 10.1186/s12966-022-01292-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 04/05/2022] [Indexed: 11/30/2022] Open
Abstract
Background Active recreation contributes to child and adolescent physical activity, however, factors affecting uptake are poorly understood at the systems level. The aims of this study were: (1) to use systems analysis methods to understand youth active recreation in Victoria, Australia, (ii) identify potential system leverage points to enhance active recreation, and (iii) explore stakeholder views of systems analysis methods for informing practice and policy decision-making. Methods Phase 1: Umbrella review of systematic reviews (2013–2018), synthesising evidence for correlates, determinants and intervention evidence for promoting active recreation. Phase 2: Development of three systems models (ActorMap and two ActivMaps), depicting active recreation actors/organisations, correlates, determinants and intervention evidence. Phase 3: Development of causal loop diagrams (CLDs) and identification of leverage points based on the Action Scales Model. Phase 4: Model feedback via stakeholder interviews (n = 23; 16 organisations). Results From the literature, 93 correlates and determinants, and 49 intervention strategies were associated with child and adolescent active recreation; the majority located at a social or individual level. Ten potential system leverage points were identified in the CLDs, which differed for pre-schoolers versus children and adolescents. Only time outdoors (an event leverage point) emerged for all age groups. Changes to the built and natural environment (i.e., land use planning, urban design) as a complete domain was a key structural leverage point for influencing active recreation in children and adolescents. Subject matter experts and stakeholder interviews identified 125 actors operating across seven hierarchical active recreation system levels in Victoria. Stakeholder interviews identified 12 areas for future consideration and recommendations for practice/policy influence. Conclusions Our findings underscore the need for dynamic models of system behaviour in active recreation, and to capture stakeholder influence as more than a transactional role in evidence generation and use. Effective responses to youth inactivity require a network of interventions that target specific leverage points across the system. Our models illustrate areas that may have the greatest system-level impact, such as changes to the built and natural environment, and they provide a tool for policy, appraisal, advocacy, and decision-making within and outside of government. Supplementary Information The online version contains supplementary material available at 10.1186/s12966-022-01292-2.
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Affiliation(s)
- Harriet Koorts
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition (IPAN), Deakin University, 221 Burwood Highway, Burwood, Geelong, VIC, 3125, Australia.
| | - Paul M Salmon
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia
| | - Christopher T V Swain
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition (IPAN), Deakin University, 221 Burwood Highway, Burwood, Geelong, VIC, 3125, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Samuel Cassar
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition (IPAN), Deakin University, 221 Burwood Highway, Burwood, Geelong, VIC, 3125, Australia
| | - David Strickland
- Sport and Recreation Victoria, Department of Jobs Precincts and Regions, Melbourne, Victoria, Australia
| | - Jo Salmon
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition (IPAN), Deakin University, 221 Burwood Highway, Burwood, Geelong, VIC, 3125, Australia
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