Research Article: Factors influencing sedentary behaviour: A system based analysis using Bayesian networks within DEDIPAC

Date Published: January 30, 2019

Publisher: Public Library of Science

Author(s): Christoph Buck, Anne Loyen, Ronja Foraita, Jelle Van Cauwenberg, Marieke De Craemer, Ciaran Mac Donncha, Jean-Michel Oppert, Johannes Brug, Nanna Lien, Greet Cardon, Iris Pigeot, Sebastien Chastin, Maciej S. Buchowski.

http://doi.org/10.1371/journal.pone.0211546

Abstract

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.

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.

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.

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.

Partial Text

Sitting has become the dominant posture in most domains of human activity; including work, education, transport, and leisure time, gradually displacing most forms of physical activity over the last fifty years in developed and developing countries [1]. Nowadays people tend to spend a major part of their waking day sitting with 50% of the European population sitting more than 6 hours per day and particularly older adults being sedentary in excess of 60% of their waking day [2, 3]. Activities of daily life that are performed while in a sitting, reclining, or lying posture and that require little energy expenditure are referred to as sedentary behaviour (SB) [4, 5]. High levels of SB are associated with an increased risk of major chronic diseases, loss of independence in later life and premature mortality [6–8].

Table 1 presents sample sizes and network statistics for all resulting networks of the whole sample and of all sex- and age-specific strata. The sample was almost sex-balanced with more participants in the age groups from 26 to 44 and 45 to 64 years. Network denseness for the whole study sample was 16.9% between the 32 nodes including age and sex. Network denseness of sex- and age-specific strata considering 30 variables were lower and varied between 6.7% and 12.4% with more associations found in the two middle-age groups than in the youngest and oldest age groups. Study characteristics of the study sample and each stratum, with regard to all 33 variables, are presented as supplementary material in S1 Table. Mean distance of factors within clusters of the SOS-framework is also presented in Table 1, while distance of each factor to SB is presented in detail in S2 Table as supplementary material.

This was the first study which explored and depicted the clustering and interplay between factors that might be associated with SB using BNs. The results showed that, as theoretically expected [20], factors associated with SB build a very complex interacting web with differences between sexes and over the life-course. The network of the overall sample showed a macroscopic structure with two main groups of factors; one group related to individual’s immediate surroundings including factors related to their home and institutional settings and the proximal built environment and the other group related to the broader economic and political context they live in. Interestingly, psychological and behavioural factors that are most often targeted by interventions [38] appeared not to be the factors most closely related to SB. However, only two factors of this cluster were collected by the Eurobarometer survey and could be included in the present analysis.

The BN approach provides important insights into the complex interplay of factors related to SB. Aligned to the SOS-framework, this study presents consistent findings of factors related to the home and institutional settings as well as to the social and cultural context clustering around SB and supports the research priorities for these factors. Considering the complexity of the issue, there is need for a more comprehensive system of data collection including objective measures of sedentary time and a multilevel assessment of lifestyle-related factors in these clusters.

 

Source:

http://doi.org/10.1371/journal.pone.0211546

 

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