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      Comparison of the EPIC Physical Activity Questionnaire with Combined Heart Rate and Movement Sensing in a Nationally Representative Sample of Older British Adults

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          Abstract

          Objectives

          To compare physical activity (PA) subcomponents from EPIC Physical Activity Questionnaire (EPAQ2) and combined heart rate and movement sensing in older adults.

          Methods

          Participants aged 60–64y from the MRC National Survey of Health and Development in Great Britain completed EPAQ2, which assesses self-report PA in 4 domains (leisure time, occupation, transportation and domestic life) during the past year and wore a combined sensor for 5 consecutive days. Estimates of PA energy expenditure (PAEE), sedentary behaviour, light (LPA) and moderate-to-vigorous PA (MVPA) were obtained from EPAQ2 and combined sensing and compared. Complete data were available in 1689 participants (52% women).

          Results

          EPAQ2 estimates of PAEE and MVPA were higher than objective estimates and sedentary time and LPA estimates were lower [bias (95% limits of agreement) in men and women were 32.3 (−61.5 to 122.6) and 29.0 (−39.2 to 94.6) kJ/kg/day for PAEE; −4.6 (−10.6 to 1.3) and −6.0 (−10.9 to −1.0) h/day for sedentary time; −171.8 (−454.5 to 110.8) and −60.4 (−367.5 to 246.6) min/day for LPA; 91.1 (−159.5 to 341.8) and 55.4 (−117.2 to 228.0) min/day for MVPA]. There were significant positive correlations between all self-reported and objectively assessed PA subcomponents (rho  = 0.12 to 0.36); the strongest were observed for MVPA (rho = 0.30 men; rho = 0.36 women) and PAEE (rho = 0.26 men; rho = 0.25 women).

          Conclusion

          EPAQ2 produces higher estimates of PAEE and MVPA and lower estimates of sedentary and LPA than objective assessment. However, both methodologies rank individuals similarly, suggesting that EPAQ2 may be used in etiological studies in this population.

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          Most cited references59

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT

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              Compendium of physical activities: an update of activity codes and MET intensities.

              We provide an updated version of the Compendium of Physical Activities, a coding scheme that classifies specific physical activity (PA) by rate of energy expenditure. It was developed to enhance the comparability of results across studies using self-reports of PA. The Compendium coding scheme links a five-digit code that describes physical activities by major headings (e.g., occupation, transportation, etc.) and specific activities within each major heading with its intensity, defined as the ratio of work metabolic rate to a standard resting metabolic rate (MET). Energy expenditure in MET-minutes, MET-hours, kcal, or kcal per kilogram body weight can be estimated for specific activities by type or MET intensity. Additions to the Compendium were obtained from studies describing daily PA patterns of adults and studies measuring the energy cost of specific physical activities in field settings. The updated version includes two new major headings of volunteer and religious activities, extends the number of specific activities from 477 to 605, and provides updated MET intensity levels for selected activities.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                6 February 2014
                : 9
                : 2
                : e87085
                Affiliations
                [1 ]Medical Research Council Epidemiology Unit, University of Cambridge, School of Clinical Medicine, Institute of Metabolic Science, Cambridge, United Kingdom
                [2 ]Medical Research Council Unit for Lifelong Health and Ageing at University College London, London, United Kingdom
                [3 ]Epidemiology Group, Institute of Applied Health Sciences, University of Aberdeen, School of Medicine and Dentistry, Aberdeen, United Kingdom
                [4 ]Norwegian School of Sport Sciences, Norges Idrettshøgskole, Oslo, Norway
                Delft University of Technology (TUDelft), Netherlands
                Author notes

                ¶ Membership of the NSHD scientific and data collection teams is provided in the Acknowledgments.

                Competing Interests: The authors have declared that no competing interests exist.

                Analyzed the data: VER RG SB. Wrote the paper: VER RG SB. Conceived the study question: VER RG SB. Contributed to the interpretation of results: VER RG KRM RH UE DK NJW RC SB.

                Article
                PONE-D-13-27134
                10.1371/journal.pone.0087085
                3916297
                24516543
                02e8ab1e-81b2-40a7-bb82-13d60a4c2576
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 2 July 2013
                : 19 December 2013
                Page count
                Pages: 10
                Funding
                This work was supported by the MRC grant numbers U1200632239, U123092720 and U106179473. Rajna Golubic is financially supported by a scholarship from the Gates Cambridge Trust, Benefactors' Scholarship from St. John's College Cambridge and Raymond and Beverly Sackler Studentship from the School of Clinical Medicine, University of Cambridge. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Population Biology
                Epidemiology
                Epidemiological Methods
                Epidemiology of Aging
                Medicine
                Clinical Research Design
                Epidemiology
                Epidemiology
                Epidemiological Methods
                Epidemiology of Aging
                Non-Clinical Medicine
                Health Care Policy
                Elderly Care
                Science Policy
                Research Assessment
                Research Validity

                Uncategorized
                Uncategorized

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