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      Changes in sedentary behaviour in European Union adults between 2002 and 2017

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          Abstract

          Background

          Sedentary behaviour (SB) has been identified as an important mortality risk factor. Health organizations have recognised SB as a public health challenge with major health, social, and economic consequences. Researchers have alerted the need to develop specific strategies, to monitor, prevent, and reduce SB. However, there is no systematic analysis of the SB changes in European Union adults. We aimed to examine SB changes between 2002 and 2017 in the European Union (EU) adult population.

          Methods

          SB prevalence (>4h30mins of sitting time/day) of 96,004 adults as a whole sample and country-by-country was analysed in 2002, 2005, 2013, and 2017 of the Sport and Physical Activity EU Special Eurobarometers’ data. The SB question of a modified version of the International Physical Activity Questionnaire was considered. SB prevalence between countries and within years was analysed with a χ2 test, and SB between genders was analysed with the Z-Score test for two population proportions.

          Results

          An association between the SB prevalence and the years was found ( p <  0.001), with increases for the whole sample (2002: 49.3%, 48.5–50.0 95% confidence interval (CI); 2017: 54.5%, 53.9–55.0 95% CI) and men (2002: 51.2%, 50.0–52.4 95% CI; 2017: 55.8%, 55.0–56.7 95% CI) and women (2002: 47.6%, 46.6–48.7 95% CI; 2017: 53.4%, 52.6–54.1 95% CI) separately. The adjusted standardised residuals showed an increase in the observed prevalence versus the expected during 2013 and 2017 for the whole sample and women and during 2017 for men. For all years, differences were observed in the SB prevalence between countries for the whole sample, and men and women separately ( p <  0.001). Besides, the SB prevalence was always higher in men versus women in the overall EU sample ( p <  0.001).

          Conclusions

          SB prevalence increased between 2002 and 2017 for the EU as a whole and for both sexes separately. Additionally, differences in SB prevalence were observed for all years between EU countries in the whole sample and both sexes separately. Lastly, SB was consistently higher in men than women. These findings reveal a limited impact of current policies and interventions to tackle SB at the EU population level.

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          Most cited references24

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          Time use and physical activity: a shift away from movement across the globe.

          Technology linked with reduced physical activity (PA) in occupational work, home/domestic work, and travel and increased sedentary activities, especially television viewing, dominates the globe. Using detailed historical data on time allocation, occupational distributions, energy expenditures data by activity, and time-varying measures of metabolic equivalents of task (MET) for activities when available, we measure historical and current MET by four major PA domains (occupation, home production, travel and active leisure) and sedentary time among adults (>18 years). Trends by domain for the United States (1965-2009), the United Kingdom (1961-2005), Brazil (2002-2007), China (1991-2009) and India (2000-2005) are presented. We also project changes in energy expenditure by domain and sedentary time (excluding sleep and personal care) to 2020 and 2030 for each of these countries. The use of previously unexplored detailed time allocation and energy expenditures and other datasets represents a useful addition to our ability to document activity and inactivity globally, but highlights the need for concerted efforts to monitor PA in a consistent manner globally, increase global PA and decrease sedentary behavior. Given the potential impact on weight gain and other cardiometabolic health risks, the differential declines in MET of activity and increases in sedentary time across the globe represent a major threat to global health. © 2012 The Authors. obesity reviews © 2012 International Association for the Study of Obesity.
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            Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).

            Television viewing time, the predominant leisure-time sedentary behavior, is associated with biomarkers of cardiometabolic risk, but its relationship with mortality has not been studied. We examined the associations of prolonged television viewing time with all-cause, cardiovascular disease (CVD), cancer, and non-CVD/noncancer mortality in Australian adults. Television viewing time in relation to subsequent all-cause, CVD, and cancer mortality (median follow-up, 6.6 years) was examined among 8800 adults > or =25 years of age in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). During 58 087 person-years of follow-up, there were 284 deaths (87 CVD deaths, 125 cancer deaths). After adjustment for age, sex, waist circumference, and exercise, the hazard ratios for each 1-hour increment in television viewing time per day were 1.11 (95% confidence interval [CI], 1.03 to 1.20) for all-cause mortality, 1.18 (95% CI, 1.03 to 1.35) for CVD mortality, and 1.09 (95% CI, 0.96 to 1.23) for cancer mortality. Compared with a television viewing time of or =2 to or =4 h/d. For CVD mortality, corresponding hazard ratios were 1.19 (95% CI, 0.72 to 1.99) and 1.80 (95% CI, 1.00 to 3.25). The associations with both cancer mortality and non-CVD/noncancer mortality were not significant. Television viewing time was associated with increased risk of all-cause and CVD mortality. In addition to the promotion of exercise, chronic disease prevention strategies could focus on reducing sitting time, particularly prolonged television viewing.
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              A systematic review of correlates of sedentary behaviour in adults aged 18–65 years: a socio-ecological approach

              Background Recent research shows that sedentary behaviour is associated with adverse cardio-metabolic consequences even among those considered sufficiently physically active. In order to successfully develop interventions to address this unhealthy behaviour, factors that influence sedentariness need to be identified and fully understood. The aim of this review is to identify individual, social, environmental, and policy-related determinants or correlates of sedentary behaviours among adults aged 18–65 years. Methods PubMed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between January 2000 and September 2015. The search strategy was based on four key elements and their synonyms: (a) sedentary behaviour (b) correlates (c) types of sedentary behaviours (d) types of correlates. Articles were included if information relating to sedentary behaviour in adults (18–65 years) was reported. Studies on samples selected by disease were excluded. The full protocol is available from PROSPERO (PROSPERO 2014:CRD42014009823). Results 74 original studies were identified out of 4041: 71 observational, two qualitative and one experimental study. Sedentary behaviour was primarily measured as self-reported screen leisure time and total sitting time. In 15 studies, objectively measured total sedentary time was reported: accelerometry (n = 14) and heart rate (n = 1). Individual level factors such as age, physical activity levels, body mass index, socio-economic status and mood were all significantly correlated with sedentariness. A trend towards increased amounts of leisure screen time was identified in those married or cohabiting while having children resulted in less total sitting time. Several environmental correlates were identified including proximity of green space, neighbourhood walkability and safety and weather. Conclusions Results provide further evidence relating to several already recognised individual level factors and preliminary evidence relating to social and environmental factors that should be further investigated. Most studies relied upon cross-sectional design limiting causal inference and the heterogeneity of the sedentary measures prevented direct comparison of findings. Future research necessitates longitudinal study designs, exploration of policy-related factors, further exploration of environmental factors, analysis of inter-relationships between identified factors and better classification of sedentary behaviour domains. Electronic supplementary material The online version of this article (doi:10.1186/s12889-016-2841-3) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                alejandro.valenciano@urjc.es
                xian.mayo@urjc.es
                gliguori@uri.edu
                R.J.Copeland@shu.ac.uk
                m.lamb@shu.ac.uk
                alfonso.jimenez@ingesport.es
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                26 August 2020
                26 August 2020
                2020
                : 20
                : 1206
                Affiliations
                [1 ]GRID grid.28479.30, ISNI 0000 0001 2206 5938, Observatory of Healthy & Active Living of Spain Active Foundation, Centre for Sport Studies, , King Juan Carlos University, ; Madrid, Spain
                [2 ]GO fit LAB, Ingesport, Madrid, Spain
                [3 ]GRID grid.20431.34, ISNI 0000 0004 0416 2242, University of Rhode Island, ; Kingston, RI USA
                [4 ]GRID grid.5884.1, ISNI 0000 0001 0303 540X, Advanced Wellbeing Research Centre, College of Health, Wellbeing, and Life Sciences, , Sheffield Hallam University, ; Sheffield, UK
                [5 ]The National Centre for Sport and Exercise Medicine, Sheffield, UK
                [6 ]GRID grid.5884.1, ISNI 0000 0001 0303 540X, Centre for Behavioural Science and Applied Psychology, , Sheffield Hallam University, ; Sheffield, UK
                Author information
                http://orcid.org/0000-0002-4143-701X
                Article
                9293
                10.1186/s12889-020-09293-1
                7448983
                32843022
                036ad6f9-c2b3-4618-8d0a-23a9b2b371ec
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 27 March 2020
                : 23 July 2020
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Public health
                sitting,sedentarism,national policies,eurobarometer
                Public health
                sitting, sedentarism, national policies, eurobarometer

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