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Liu Y, Zhou X, Ding N, Song S, Gittelsohn J, Jiang N, Sundermeir SM, Ma Y, Wen D. Obesity contagion among classmates: Children's relation with each other regarding weight status, physical activity, and dietary intake. SSM Popul Health 2024; 26:101636. [PMID: 38516526 PMCID: PMC10955631 DOI: 10.1016/j.ssmph.2024.101636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 02/07/2024] [Accepted: 02/16/2024] [Indexed: 03/23/2024] Open
Abstract
A series of influential articles suggests that obesity may spread between couples, siblings, and close friends via an obesity contagion phenomenon. Classmates, as important structural equivalents in one's social network, may experience obesity contagion. However, this has rarely been examined. Anthropometric measurements, questionnaire surveys, and geographic information were collected from 3670 children from 26 schools in Northeast China. We found that classmates were positively related in terms of body mass index (BMI), body fat, physical activity, and intake of vegetables, fruits, fast food, snacks, and sugar-sweetened beverages. One standard deviation (SD) increase in classmates' mean BMI and percentage body fat was associated with 0.19 SD higher individual BMI (95% confidence interval [CI]: 0.00, 0.39) and 0.31 SD higher percentage body fat (95% CI: 0.13, 0.48). Coefficients ranged from 0.48 to 0.76 in models for physical activity, and the dietary intake of vegetables, fruit, fast food, snacks, and sugar-sweetened beverages. Children's BMI and body fat were more strongly associated with the maximum and minimum body fat levels of their same-sex classmates than with those of their general classmates. Their dietary intake and physical activity were more strongly associated with the mean/median levels of their general classmates than with those of their same-sex classmates. This study suggests that children's BMI, body fat, physical activity, and dietary intake may be related to those of their classmates. Modeling healthy behaviors in the classroom may help children develop habits that support achieving and maintaining a healthy weight. Future interventions should consider the inclusion of classmates as a social network strategy for obesity prevention.
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Affiliation(s)
- Yang Liu
- China Medical University, Health Sciences Institute, Address: No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, PR China
| | - Xiaobei Zhou
- China Medical University, Health Sciences Institute, Address: No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, PR China
| | - Ning Ding
- China Medical University, Institute of International Medical Education, Address: No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, PR China
| | - Shenzhi Song
- China Medical University, Health Sciences Institute, Address: No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, PR China
| | - Joel Gittelsohn
- Johns Hopkins Bloomberg School of Public Health, Department of International Health, Human Nutrition Center, Address: 615 North Wolfe St, Baltimore, MD, 21205-2179, USA
| | - Nan Jiang
- China Medical University, Institute of International Medical Education, Address: No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, PR China
| | - Samantha M. Sundermeir
- Johns Hopkins Bloomberg School of Public Health, Department of International Health, Human Nutrition Center, Address: 615 North Wolfe St, Baltimore, MD, 21205-2179, USA
| | - Yanan Ma
- China Medical University, School of Public Health, Address: No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, PR China
| | - Deliang Wen
- China Medical University, Health Sciences Institute, Address: No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, PR China
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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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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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