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      Systematic literature review of determinants of sedentary behaviour in older adults: a DEDIPAC study

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          Abstract

          Background

          Older adults are the most sedentary segment of society and high sedentary time is associated with poor health and wellbeing outcomes in this population. Identifying determinants of sedentary behaviour is a necessary step to develop interventions to reduce sedentary time.

          Methods

          A systematic literature review was conducted to identify factors associated with sedentary behaviour in older adults. Pubmed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between 2000 and May 2014. The search strategy was based on four key elements: (a) sedentary behaviour and its synonyms; (b) determinants and its synonyms (e.g. correlates, factors); (c) types of sedentary behaviour (e.g. TV viewing, sitting, gaming) and (d) types of determinants (e.g. environmental, behavioural). Articles were included in the review if specific information about sedentary behaviour in older adults was reported. Studies on samples identified by disease were excluded. Study quality was rated by means of QUALSYST. The full review protocol is available from PROSPERO (PROSPERO 2014: CRD42014009823). The analysis was guided by the socio-ecological model framework.

          Results

          Twenty-two original studies were identified out of 4472 returned by the systematic search. These included 19 cross-sectional, 2 longitudinal and 1 qualitative studies, all published after 2011. Half of the studies were European. The study quality was generally high with a median of 82 % (IQR 69–96 %) using Qualsyst tool. Personal factors were the most frequently investigated with consistent positive association for age, negative for retirement, obesity and health status. Only four studies considered environmental determinants suggesting possible association with mode of transport, type of housing, cultural opportunities and neighbourhood safety and availability of places to rest. Only two studies investigated mediating factors. Very limited information was available on contexts and sub-domains of sedentary behaviours.

          Conclusion

          Few studies have investigated determinants of sedentary behaviour in older adults and these have to date mostly focussed on personal factors, and qualitative studies were mostly lacking. More longitudinal studies are needed as well as inclusion of a broader range of personal and contextual potential determinants towards a systems-based approach, and future studies should be more informed by qualitative work.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12966-015-0292-3) contains supplementary material, which is available to authorized users.

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          Most cited references50

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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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            Validation of wearable monitors for assessing sedentary behavior.

            A primary barrier to elucidating the association between sedentary behavior (SB) and health outcomes is the lack of valid monitors to assess SB in a free-living environment. The purpose of this study was to examine the validity of commercially available monitors to assess SB. Twenty overweight (mean ± SD: body mass index = 33.7 ± 5.7 kg·m(-2)) inactive, office workers age 46.5 ± 10.7 yr were directly observed for two 6-h periods while wearing an activPAL (AP) and an ActiGraph GT3X (AG). During the second observation, participants were instructed to reduce sitting time. We assessed the validity of the commonly used cut point of 100 counts per minute (AG100) and several additional AG cut points for defining SB. We used direct observation (DO) using focal sampling with duration coding to record either sedentary (sitting/lying) or nonsedentary behavior. The accuracy and precision of the monitors and the sensitivity of the monitors to detect reductions in sitting time were assessed using mixed-model repeated-measures analyses. On average, the AP and the AG100 underestimated sitting time by 2.8% and 4.9%, respectively. The correlation between the AP and DO was R2 = 0.94, and the AG100 and DO sedentary minutes was R2 = 0.39. Only the AP was able to detect reductions in sitting time. The AG 150-counts-per-minute threshold demonstrated the lowest bias (1.8%) of the AG cut points. The AP was more precise and more sensitive to reductions in sitting time than the AG, and thus, studies designed to assess SB should consider using the AP. When the AG monitor is used, 150 counts per minute may be the most appropriate cut point to define SB.
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              Measurement of adults' sedentary time in population-based studies.

              Sedentary time (too much sitting) increasingly is being recognized as a distinct health risk behavior. This paper reviews the reliability and validity of self-reported and device-based sedentary time measures and provides recommendations for their use in population-based studies. The focus is on instruments that have been used in free-living, population-based research in adults. Data from the 2003-2006 National Health and Nutrition Examination Survey are utilized to compare the descriptive epidemiology of sedentary time that arises from the use of different sedentary time measures. A key recommendation from this review is that, wherever possible, population-based monitoring of sedentary time should incorporate both self-reported measures (to capture important domain- and behavior-specific sedentary time information) and device-based measures (to measure both total sedentary time and patterns of sedentary time accumulation). Copyright © 2011 American Journal of Preventive Medicine. All rights reserved.
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                Author and article information

                Contributors
                Sebastien.Chastin@gcu.ac.uk
                buck@bips.uni-bremen.de
                ellen.freiberger@fau.de
                mh.murphy@ulster.ac.uk
                j.brug@vumc.nl
                Greet.Cardon@ugent.be
                grainne.odonoghue@dcu.ie
                pigeot@bips.uni-bremen.de
                jean-michel.oppert@psl.aphp.fr
                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central (London )
                1479-5868
                6 October 2015
                6 October 2015
                2015
                : 12
                : 127
                Affiliations
                [ ]Institute of Applied Health Research, School of Health and Life Science, Glasgow Caledonian University, Glasgow, UK
                [ ]Leibniz Institute for Prevention Research and Epidemiology- BIPS, Bremen, Germany
                [ ]Institute for Biomedicine of Aging Friedrich-Alexander-Universität, Erlangen, Nürnberg Germany
                [ ]Centre for Physical Activity and Health Research, University of Ulster, Newtownabbey, Co. Antrim, Northern Ireland UK
                [ ]Department of Epidemiology and Biostatistics and the EMGO Institute for Health & Care Research, VU Medical Centre, Amsterdam, The Netherlands
                [ ]Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
                [ ]Centre for Preventive Medicine, School of Health & Human Performance, Dublin City University, Dublin, Ireland
                [ ]Institute of Cardiometabolism and Nutrition (ICAN), Centre for Research on Human Nutrition Ile-de-France (CRNH), University Pierre et Marie Curie, Paris, France
                Article
                292
                10.1186/s12966-015-0292-3
                4595239
                26437960
                27ab03d0-159f-42be-ba64-3f98d0600ff1
                © Chastin 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
                : 14 April 2015
                : 25 September 2015
                Categories
                Review
                Custom metadata
                © The Author(s) 2015

                Nutrition & Dietetics
                sitting,sedentary behaviour,determinants,older adults,ageing,life-course,obesity,system-based approach,physical activity,environment

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