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Buck C, Loyen A, Foraita R, Van Cauwenberg J, De Craemer M, Mac Donncha C, Oppert JM, Brug J, Lien N, Cardon G, Pigeot I, Chastin S. Factors influencing sedentary behaviour: A system based analysis using Bayesian networks within DEDIPAC. PLoS One 2019; 14:e0211546. [PMID: 30699199 PMCID: PMC6353197 DOI: 10.1371/journal.pone.0211546] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 01/16/2019] [Indexed: 12/19/2022] Open
Abstract
Background Decreasing sedentary behaviour (SB) has emerged as a public health priority since prolonged sitting increases the risk of non-communicable diseases. Mostly, the independent association of factors with SB has been investigated, although lifestyle behaviours are conditioned by interdependent factors. Within the DEDIPAC Knowledge Hub, a system of sedentary behaviours (SOS)-framework was created to take interdependency among multiple factors into account. The SOS framework is based on a system approach and was developed by combining evidence synthesis and expert consensus. The present study conducted a Bayesian network analysis to investigate and map the interdependencies between factors associated with SB through the life-course from large scale empirical data. Methods Data from the Eurobarometer survey (80.2, 2013) that included the International physical activity questionnaire (IPAQ) short as well as socio-demographic information and questions on perceived environment, health, and psychosocial information were enriched with macro-level data from the Eurostat database. Overall, 33 factors were identified aligned to the SOS-framework to represent six clusters on the individual or regional level: 1) physical health and wellbeing, 2) social and cultural context, 3) built and natural environment, 4) psychology and behaviour, 5) institutional and home settings, 6) policy and economics. A Bayesian network analysis was conducted to investigate conditional associations among all factors and to determine their importance within these networks. Bayesian networks were estimated for the complete (23,865 EU-citizens with complete data) sample and for sex- and four age-specific subgroups. Distance and centrality were calculated to determine importance of factors within each network around SB. Results In the young (15–25), adult (26–44), and middle-aged (45–64) groups occupational level was directly associated with SB for both, men and women. Consistently, social class and educational level were indirectly associated within male adult groups, while in women factors of the family context were indirectly associated with SB. Only in older adults, factors of the built environment were relevant with regard to SB, while factors of the home and institutional settings were less important compared to younger age groups. Conclusion Factors of the home and institutional settings as well as the social and cultural context were found to be important in the network of associations around SB supporting the priority for future research in these clusters. Particularly, occupational status was found to be the main driver of SB through the life-course. Investigating conditional associations by Bayesian networks gave a better understanding of the complex interplay of factors being associated with SB. This may provide detailed insights in the mechanisms behind the burden of SB to effectively inform policy makers for detailed intervention planning. However, considering the complexity of the issue, there is need for a more comprehensive system of data collection including objective measures of sedentary time.
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Affiliation(s)
- Christoph Buck
- Leibniz Institute for Prevention Research and Epidemiology–BIPS, Bremen, Germany
- * E-mail:
| | - Anne Loyen
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, Netherlands
| | - Ronja Foraita
- Leibniz Institute for Prevention Research and Epidemiology–BIPS, Bremen, Germany
| | - Jelle Van Cauwenberg
- Research Foundation Flanders (FWO), Brussels, Belgium
- Department of Public Health, Ghent University, Ghent, Belgium
| | - Marieke De Craemer
- Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
| | - Ciaran Mac Donncha
- Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
| | - Jean-Michel Oppert
- Department of Nutrition, University Pierre et Marie Curie, Institute of Cardiometabolism And Nutrition (ICAN), Pitie-Salpêtrière Hospital (AP-HP), Paris, France
| | - Johannes Brug
- Amsterdam School for Communication Research, University of Amsterdam, Amsterdam, The Netherlands
| | - Nanna Lien
- Department of Nutrition, University of Oslo, Oslo, Norway
| | - Greet Cardon
- Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
| | - Iris Pigeot
- Leibniz Institute for Prevention Research and Epidemiology–BIPS, Bremen, Germany
- University of Bremen, Faculty of Mathematics and Computer Science, Bremen, Germany
| | - Sebastien Chastin
- Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
- Institute for Applied Health Research, School of Health and Life Science, Glasgow Caledonian University, Glasgow, United Kingdom
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Lakerveld J, Loyen A, Ling FCM, De Craemer M, van der Ploeg HP, O’Gorman DJ, Carlin A, Caprinica L, Kalter J, Oppert JM, Chastin S, Cardon G, Brug J, MacDonncha C. Identifying and sharing data for secondary data analysis of physical activity, sedentary behaviour and their determinants across the life course in Europe: general principles and an example from DEDIPAC. BMJ Open 2017; 7:e017489. [PMID: 29061620 PMCID: PMC5665252 DOI: 10.1136/bmjopen-2017-017489] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND The utilisation of available cross-European data for secondary data analyses on physical activity, sedentary behaviours and their underlying determinants may benefit from the wide variation that exists across Europe in terms of these behaviours and their determinants. Such reuse of existing data for further research requires Findable; Accessible; Interoperable; Reusable (FAIR) data management and stewardship. We here describe the inventory and development of a comprehensive European dataset compendium and the process towards cross-European secondary data analyses of pooled data on physical activity, sedentary behaviour and their correlates across the life course. METHODS A five-step methodology was followed by the European Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub, covering the (1) identification of relevant datasets across Europe, (2) development of a compendium including details on the design, study population, measures and level of accessibility of data from each study, (3) definition of key topics and approaches for secondary analyses, (4) process of gaining access to datasets and (5) pooling and harmonisation of the data and the development of a data harmonisation platform. RESULTS A total of 114 unique datasets were found for inclusion within the DEDIPAC compendium. Of these datasets, 14 were eventually obtained and reused to address 10 exemplar research questions. The DEDIPAC data harmonisation platform proved to be useful for pooling, but in general, harmonisation was often restricted to just a few core (crude) outcome variables and some individual-level sociodemographic correlates of these behaviours. CONCLUSIONS Obtaining, pooling and harmonising data for secondary data analyses proved to be difficult and sometimes even impossible. Compliance to FAIR data management and stewardship principles currently appears to be limited for research in the field of physical activity and sedentary behaviour. We discuss some of the reasons why this might be the case and present recommendations based on our experience.
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Affiliation(s)
- Jeroen Lakerveld
- Department of Epidemiology and Biostatistics, AmsterdamPublic Health research institute, VU University Medical Center, Amsterdam, Netherlands
| | - Anne Loyen
- Department of Epidemiology and Biostatistics, AmsterdamPublic Health research institute, VU University Medical Center, Amsterdam, Netherlands
| | - Fiona Chun Man Ling
- Department of Physical Education and Sport Sciences, Centre for Physical Activity and Health Research, University of Limerick, Limerick, Ireland
- Institute of Sport, Exercise and Active Living, Victoria University, Melbourne, Victoria, Australia
- Department of Psychology, Bournemouth University, Bournemouth, UK
| | - Marieke De Craemer
- Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
| | - Hidde P van der Ploeg
- Department of Public and Occupational Health, AmsterdamPublic Health research institute, VU University Medical Center, Amsterdam, Netherlands
| | - Donal J O’Gorman
- Centre for Preventive Medicine, School of Health and Human Performance, Dublin City University, Dublin, Ireland
| | - Angela Carlin
- Department of Physical Education and Sport Sciences, Centre for Physical Activity and Health Research, University of Limerick, Limerick, Ireland
| | - Laura Caprinica
- Department of Movement, Human and Health Sciences, University of Rome Foro Italico, Rome, Italy
| | - Joeri Kalter
- Department of Epidemiology and Biostatistics, AmsterdamPublic Health research institute, VU University Medical Center, Amsterdam, Netherlands
| | - Jean-Michel Oppert
- Department of Nutrition, Pitie-Salpetriere hospital (AP-HP), Institute of Cardiometabolism and Nutrition (ICAN), University Pierre et Marie Curie-Paris6, Paris, France
| | - Sebastian Chastin
- Institute of Applied Health Research, School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK
| | - Greet Cardon
- Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
| | - Johannes Brug
- Department of Epidemiology and Biostatistics, AmsterdamPublic Health research institute, VU University Medical Center, Amsterdam, Netherlands
- Amsterdam School for Communication Research, University of Amsterdam, Amsterdam, Netherlands
| | - Ciaran MacDonncha
- Department of Physical Education and Sport Sciences, Centre for Physical Activity and Health Research, University of Limerick, Limerick, Ireland
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