Suchergebnisse

PURPOSE: Assess the agreement between commonly used self-report methods compared with objectively measured physical activity (PA) in defining the prevalence of individuals compliant with PA recommendations. METHODS: Time spent in moderate and vigorous PA (MVPA) was measured at two time points in 1713 healthy individuals from nine European countries using individually calibrated combined heart rate and movement sensing. Participants also completed the Recent Physical Activity Questionnaire (RPAQ), short form of the International Physical Activity Questionnaire (IPAQ), and short European Prospective Investigation into Cancer and Nutrition Physical Activity Questionnaire (EPIC-PAQ). Individuals were categorized as active (e.g., reporting ≥150 min of MVPA per week) or inactive, based on the information derived from the different measures. Sensitivity and specificity analyses and Kappa statistics were performed to evaluate the ability of the three PA questionnaires to correctly categorize individuals as active or inactive. RESULTS: Prevalence estimates of being sufficiently active varied significantly (P for all <0.001) between self-report measures (IPAQ 84.2% [95% confidence interval {CI}, 82.5-85.9], RPAQ 87.6% [95% CI, 85.9-89.1], EPIC-PAQ 39.9% [95% CI, 37.5-42.1] and objective measure 48.5% [95% CI, 41.6-50.9]. All self-report methods showed low or moderate sensitivity (IPAQ 20.0%, RPAQ 18.7%, and EPIC-PAQ 69.8%) to correctly classify inactive people and the agreement between objective and self-reported PA was low (ĸ = 0.07 [95% CI, 0.02-0.12], 0.12 [95% CI, 0.06-0.18], and 0.19 [95% CI, 0.13-0.24] for IPAQ, RPAQ, and EPIC-PAQ, respectively). CONCLUSIONS: The modest agreement between self-reported and objectively measured PA suggests that population levels of PA derived from self-report should be interpreted cautiously. Implementation of objective measures in large-scale cohort studies and surveillance systems is recommended. ; The preparation of this paper was supported by the DEterminants of DIet and Physical ACtivity (DEDIPAC) knowledge hub. This work is supported by the Joint Programming Initiative 'Healthy Diet for a Healthy Life'. The funding agencies supporting this work are Ireland: The Health Research Board (HRB); The Netherlands: The Netherlands Organisation for Health Research and Development (ZonMw); Norway: The Research Council of Norway, Division for Society and Health The data collection was supported by funding from the European Union (Integrated Project LSHM-CT-2006-037197 in the Framework Programme 6 of the European Community) and the MRC Epidemiology Unit Programmes (MC_UU_12015/3). We would like to thank the Interact validation group* and MRC Epidemiology Unit physical activity technical team and data management team, in particular Mark Betts, Laura Lamming, Stefanie Mayle, Kate Westgate and Nicola Kerrison who assisted with data reduction, cleaning and processing. The InterAct validation working group* are Anne M May, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; Wanda Wendel-Vos, National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, Bilthoven, The Netherlands; Kristin Benjaminsen Borch, Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway; Kim Overvad, Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark and Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark; Marie-Aline Charles, Inserm, Centre for research in Epidemiology and Population Health, U1018, Lifelong epidemiology of obesity, diabe`tes and chronic renal disease Team, F-94807, Villejuif, France; Univ Paris-Sud, UMRS 1018, F-94807, Villejuif, France; Maria Jose Tormo Diaz, Department of Epidemiology, Murcia Regional Health Authority, Murcia, Spain, CIBER Epidemiologıa y Salud Publica (CIBERESP), Spain and Department Sociosanitary Sciences, Murcia School of Medicine, Murcia, Spain; Pilar Amiano, Public Health Division of Gipuzkoa, BioDonostia Research Isntitute, Basque Region, San Sebastian ; CIBER Epidemiologıa y Salud Publica (CIBERESP), Madrid, Spain; Domenico Palli ,Molecular and Nutritional Epidemiology Unit, ISPO, Cancer Prevention and Research Institute, Florence, Italy; Eliavet Valanou, Hellenic Health Foundation (HHF), Athens, Greece;, Department of Epidemiology; Mattheaus Vigl, German Institute of Human Nutrition (DIfE) Potsdam-Rehbruecke, Germany and Paul W Franks, Department of Clinical Sciences, Genetic & Molecular Epidemiology Unit, Skåne University Hospital, Lund University, Malmö, Sweden, Genetic Epidemiology & Clinical Research Group, Department of Public Health & Clinical Medicine, Section for medicine, Umeå University, Sweden. The results of the current study do not constitute an endorsement by the American College of Sports Medicine. The authors have no conflict of interest to report. ; This is the author accepted manuscript. The final version is available from Lippincott Williams & Wilkins via http://dx.doi.org/10.1249/MSS.0000000000000760