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      Exploring the context of sedentary behaviour in older adults (what, where, why, when and with whom)

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          Abstract

          Background

          Older adults are the most sedentary segment of the population. Little information is available about the context of sedentary behaviour to inform guidelines and intervention. There is a dearth of information about when, where to intervene and which specific behaviours intervention should target. The aim of this exploratory study was to obtain objective information about what older adults do when sedentary, where and when they are sedentary and in what social context.

          Methods

          The study was a cross-sectional data collection. Older adults (Mean age = 73.25, SD ± 5.48, median = 72, IQR = 11) volunteers wore activPAL monitors and a Vicon Revue timelapse camera between 1 and 7 days. Periods of sedentary behaviour were identified using the activPAL and the context extracted from the pictures taken during these periods. Analysis of context was conducted using the Sedentary Behaviour International Taxonomy classification system.

          Results

          In total, 52 days from 36 participants were available for analysis. Participants spent 70.1 % of sedentary time at home, 56.9 % of sedentary time on their own and 46.8 % occurred in the afternoon. Seated social activities were infrequent (6.9 % of sedentary bouts) but prolonged (18 % of sedentary time). Participants appeared to frequently have vacant sitting time (41 % of non-screen sedentary time) and screen sitting was prevalent (36 % of total sedentary time).

          Conclusions

          This study provides valuable information to inform future interventions to reduce sedentary behaviour. Interventions should consider targeting the home environment and focus on the afternoon sitting time, though this needs confirmation in a larger study. Tackling social isolation may also be a target to reduce sedentary time.

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          Most cited references39

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          Global physical activity levels: surveillance progress, pitfalls, and prospects

          The Lancet, 380(9838), 247-257
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            Correlates of physical activity: why are some people physically active and others not?

            Physical inactivity is an important contributor to non-communicable diseases in countries of high income, and increasingly so in those of low and middle income. Understanding why people are physically active or inactive contributes to evidence-based planning of public health interventions, because effective programmes will target factors known to cause inactivity. Research into correlates (factors associated with activity) or determinants (those with a causal relationship) has burgeoned in the past two decades, but has mostly focused on individual-level factors in high-income countries. It has shown that age, sex, health status, self-efficacy, and motivation are associated with physical activity. Ecological models take a broad view of health behaviour causation, with the social and physical environment included as contributors to physical inactivity, particularly those outside the health sector, such as urban planning, transportation systems, and parks and trails. New areas of determinants research have identified genetic factors contributing to the propensity to be physically active, and evolutionary factors and obesity that might predispose to inactivity, and have explored the longitudinal tracking of physical activity throughout life. An understanding of correlates and determinants, especially in countries of low and middle income, could reduce the eff ect of future epidemics of inactivity and contribute to effective global prevention of non-communicable diseases.
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              Objectively measured sedentary time, physical activity, and metabolic risk: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).

              We examined the associations of objectively measured sedentary time and physical activity with continuous indexes of metabolic risk in Australian adults without known diabetes. An accelerometer was used to derive the percentage of monitoring time spent sedentary and in light-intensity and moderate-to-vigorous-intensity activity, as well as mean activity intensity, in 169 Australian Diabetes, Obesity and Lifestyle Study (AusDiab) participants (mean age 53.4 years). Associations with waist circumference, triglycerides, HDL cholesterol, resting blood pressure, fasting plasma glucose, and a clustered metabolic risk score were examined. Independent of time spent in moderate-to-vigorous-intensity activity, there were significant associations of sedentary time, light-intensity time, and mean activity intensity with waist circumference and clustered metabolic risk. Independent of waist circumference, moderate-to-vigorous-intensity activity time was significantly beneficially associated with triglycerides. These findings highlight the importance of decreasing sedentary time, as well as increasing time spent in physical activity, for metabolic health.
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                Author and article information

                Contributors
                calum.leask@gcu.ac.uk
                juliet.harvey@gcu.ac.uk
                dawn.skelton@gcu.ac.uk
                sebastien.chastin@gcu.ac.uk
                Journal
                Eur Rev Aging Phys Act
                Eur Rev Aging Phys Act
                European Review of Aging and Physical Activity
                BioMed Central (London )
                1813-7253
                1861-6909
                7 October 2015
                7 October 2015
                2015
                : 12
                : 4
                Affiliations
                Institute of Applied Health Research, School of Health & Life Sciences, Glasgow Caledonian University, Glasgow, G4 0BA UK
                Article
                146
                10.1186/s11556-015-0146-7
                4745148
                26865868
                8bac28fb-0be1-4825-a6bb-78cdcf261e86
                © Leask et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

                History
                : 15 May 2015
                : 6 August 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Medicine
                camera,seniors,accelerometer,inclinometer,lifelogging,sitting,sitonaumy
                Medicine
                camera, seniors, accelerometer, inclinometer, lifelogging, sitting, sitonaumy

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