Impact of accelerometer wear time on physical activity data: a NHANES semisimulation data approach Stephen D Herrmann, 1 Tiago V Barreira, 2 Minsoo Kang, 3 Barbara E Ainsworth 4 1 Cardiovascular Research Institute, University of Kansas Medical Center, Kansas City, Kansas, USA 2 Division of Population Science, Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA 3 Health and Human Performance, Middle Tennessee State University, Murfreesboro, Tennessee, USA 4 Department of Exercise and Wellness, Arizona State University, Phoenix, Arizona, USA Correspondence to Dr Stephen D Herrmann, Department of Internal Medicine, Cardiovascular Research Institute, Center for Physical Activity and Weight Management, University of Kansas Medical Center, 1301 Sunnyside Ave—Robinson: Room 100, Lawrence, KS 66045, USA; sherrmann@ku.edu Accepted 31 July 2012 ABSTRACT Background Current research practice employs wide-ranging accelerometer wear time criteria to identify a valid day of physical activity (PA) measurement. Objective To evaluate the effects of varying amounts of daily accelerometer wear time on PA data. Methods A total of 1000 days of accelerometer data from 1000 participants (age=38.7±14.3 years; body mass index=28.2±6.7 kg/m 2 ) were selected from the 2005–2006 National Health and Nutrition Examination Study data set. A reference data set was created using 200 random days with 14 h/day of wear time. Four additional samples of 200 days were randomly selected with a wear time of 10, 11, 12 and 13 h/day 1 . These data sets were used in day-to-day comparison to create four semisimulation data sets (10, 11, 12, 13 h/day) from the reference data set. Differences in step count and time spent in inactivity (<100 cts/min), light (100–1951 cts/min), moderate (1952–5724 cts/min) and vigorous (≥5725 cts/min) intensity PA were assessed using repeated-measures analysis of variance and absolute percent error (APE). Results There were significant differences for moderate intensity PA between the reference data set and semisimulation data sets of 10 and 11 h/day. Differences were observed in 10–13 h/day 1 for inactivity and light intensity PA, and 10–12 h/day for steps (all p values <0.05). APE increased with shorter wear time (13 h/day=3.9–14.1%; 12 h/day=9.9–15.2%, 11 h/day=17.1–35.5%; 10 h/day=24.6–40.3%). Discussion These data suggest that using accelerometer wear time criteria of 12 h/day or less may underestimate step count and time spent in various PA levels. INTRODUCTION Low physical activity (PA) and high inactivity and the associated health concerns (eg, cardiovascular disease, metabolic risk, obesity, etc.) have become increasingly important. 12 Researchers and health professional have focused on assessing these behaviours to assess health and as an avenue for interventions. Objectively measuring PA with accel- erometers has become a popular method for PA assessment. Standard measures and methodologies for accelerometer use are paramount to assess PA for appropriately classifying individuals and to accurately monitor changes in PA. 3 For example, significant research has been done to understand PA behaviour reliability, 4–7 replacing missing PA data 89 and accelerometer epoch length. 10 11 Few studies, however, have sought to identify the optimal number of hours per day an accelerometer should be worn to identify a valid day. 12 13 The majority of studies do not require partici- pants to wear accelerometers for 24 h/day, which creates a problem for researchers to determine how many hours of wear time represents a valid day. In current practice, there is a wide range of wear time criteria used to identify a valid day. Reports in the literature range from as few as 2 h 14 15 to limiting the upper range to 16 h. 16 Several studies have identified valid days by using different criteria for weekdays (10 h/day) versus weekend days (8 h/day). 17 Some researchers report valid days based on a percentage of time awake ranging from 60% 13 to 75% 4 of awake time. Still others recom- mend using sample-specific criteria that may change based on the amount of time a specific sample wore the accelerometer. 9 18 For example, Catellier et al 9 proposed the 70/80 rule which requires 70% of the sample to have accelerometer data and 80% of that observed period becomes the valid day threshold. Another method that has been used is to ‘ normalise’ the data to 12 h by inputting data (eg, 10 h/day of wear time was changed to 12 h/day increasing minutes in each intensity level proportionally). 19 20 The criterion of 10 h/day of accelerometer wear time is regularly used to identify a valid day of accelerometer data. 21–23 However, empirical evidence is lacking to support 10 h/day of wear time or that any other criterion is superior to another. Without data to support a consensus for daily wear time criteria, the validity of daily wear time and the comparability of studies using different wear time criteria must be questioned. The purpose of this study was to evaluate the effects of varying amounts of daily accelerometer wear time on PA in a sample of adults participating in the 2005–2006 National Health and Nutrition Examination Study (NHANES). METHODS Study design and participant selection NHANES 2005–2006 employs a complex, multi- stage probability sampling method to obtain a rep- resentative sample of the US population. The purpose of NHANES is to assess the health and nutritional status of adults and children in the USA for use in understanding the prevalence and risk factors for diseases. NHANES participants undergo extensive evaluations that include inter- views and health examinations. In 2003, as part of the evaluation process, all ambulatory participants older than 6 years were asked to wear a PA Br J Sports Med 2012;0:1–5. doi:10.1136/bjsports-2012-091410 1 Original article BJSM Online First, published on August 30, 2012 as 10.1136/bjsports-2012-091410 Copyright Article author (or their employer) 2012. Produced by BMJ Publishing Group Ltd under licence. group.bmj.com on August 31, 2012 - Published by bjsm.bmj.com Downloaded from