( Grant et al., 2006 ). Therefore, current best practice ( Grant et al., 2006 ; Matthews et al., 2012 ) for the objective measurement of free-living MVPA is measured using the ActiGraph GT3X, and SED is measured using the activPAL. This requirement of two devices for best practice measurement, increases
Melissa A. Jones, Sara J. Diesel, Bethany Barone Gibbs, and Kara M. Whitaker
Gerald Barber and Charles T. Heise
Although not well validated, physicians frequently use subjective estimates of exercise ability to assess clinical status and therapeutic results. This study employed a standardized questionnaire and cardiopulmonary exercise test to compare the results of subjective estimates by 211 patients (mean age 13.9 yrs) with objective measurements of exercise ability. Questionnaire data correlated with measured maximal oxygen consumption. Individuals thought to be below average had a maximal oxygen consumption of 21±6 ml/kg/min. Those thought to have average fitness had a maximal oxygen consumption of 26±8 ml/kg/min, and those thought to be above average had a maximal oxygen consumption of 30±7 ml/kg/min. There was a great degree of overlap and scatter of these data, however, such that questionnaire data significantly overestimated exercise ability in 67% and underestimated it in 3% of the subjects. In only 30% of the subjects did the subjective estimate of exercise ability correspond with objectively measured exercise ability. It was concluded that subjective estimates are unreliable and should not be used in assessing the functional status of an individual patient, but subjective estimates may give some idea of objective capabilities in large population studies.
Ja’mese V. Booth, Sarah E. Messiah, Eric Hansen, Maria I. Nardi, Emily Hawver, Hersila H. Patel, Hannah Kling, Deidre Okeke, and Emily M. D’Agostino
with limited objective measurement (eg, accelerometer, fitness trackers) of daily physical activity to confirm the added benefit of such programs. 47 , 48 , 50 – 52 Therefore, this study objectively assessed physical activity levels directly attributable to participation (vs nonparticipation) days in
William L. Haskell
This symposium addressed the ongoing development of new technologies for the objective measurement of physical activity and diet and efforts to provide best practice guidelines for scientists developing, evaluating and using existing and new technologies for the objective measurement of physical activity. The research projects discussed and the workshop overview presented are components of the Genes, Environment, and Health Initiative (GEI) of the National Institutes of Health. The rationale, plans and progress of the GEI physical activity and diet initiative were presented. Detailed presentations described 2 projects focused on the use of mobile phone based systems designed to collect, process and store data; 1 uses multiple wireless accelerometers to detect body movement and the other uses a camera built into a mobile phone and advanced software to quantify dietary intake. Given the rapid development of new accelerometer-based physical activity measurement devices and analytical approaches, it is important that best practices be used by scientists and practitioners using theses devices. An overview of a “best practices” workshop held in July 2009 was presented. The presentations and discussions during this symposium made evident the progress, potential and challenges of implementing advanced technologies to enhance the measurement of physical activity and diet.
Miguel Ángel de la Cámara, Sara Higueras-Fresnillo, David Martinez-Gomez, and Óscar L. Veiga
education, or measurement day. In the same way, a previous study that analyzed moderator effects of sex on interday reliability using objective measurement did not find differences ( Tudor-Locke et al., 2005 ). Measurement days constitute an important factor to consider when PA is evaluated by objective
Nicholas D. Gilson, Caitlin Hall, Andreas Holtermann, Allard J. van der Beek, Maaike A. Huysmans, Svend Erik Mathiassen, and Leon Straker
in 2011 36 with the majority published over the last 3 years (ie, 2015–2018). 20 – 35 , 37 , 38 Twelve studies were located in Denmark, 23 – 34 all but one 22 accessing 2 large national data sets (ie, New method for Objective Measurements of physical Activity in Daily living [NOMAD], Danish
Miguel A. de la Cámara, Sara Higueras-Fresnillo, Verónica Cabanas-Sánchez, Kabir P. Sadarangani, David Martinez-Gomez, and Óscar L. Veiga
well as low precision, error, and bias. 17 It has been observed that they generally underestimate sedentary time in comparison with accelerometer data (>2 h/d), 18 – 25 showing weak to moderate correlations when they are compared with objective measurements. 18 – 21 , 25 The Global Physical Activity
Anne Martin, Mhairi McNeill, Victoria Penpraze, Philippa Dall, Malcolm Granat, James Y. Paton, and John J. Reilly
The Actigraph is well established for measurement of both physical activity and sedentary behavior in children. The activPAL is being used increasingly in children, though with no published evidence on its use in free-living children to date. The present study compared the two monitors in preschool children. Children (n 23) wore both monitors simultaneously during waking hours for 5.6d and 10h/d. Daily mean percentage of time sedentary (nontranslocation of the trunk) was 74.6 (SD for the Actigraph and 78.9 (SD 4.3) for activPAL. Daily mean percentage of time physically active (light intensity physical activity plus MVPA) was 25.4 (SD for the Actigraph and 21.1 (SD 4.3) for the activPAL. Bland-Altman tests and paired t tests suggested small but statistically significant differences between the two monitors. Actigraph and activPAL estimates of sedentary behavior and physical activity in young children are similar at a group level.
Abolanle R. Gbadamosi, Alexandra M. Clarke-Cornwell, Paul A. Sindall, and Malcolm H. Granat
Background: Actively commuting to and from work can increase moderate-to-vigorous physical activity (MVPA) and increase adherence to physical activity (PA) guidelines; however, there is a lack of evidence on the contribution of mixed-mode commutes and continuous stepping bouts to PA. Many commuting studies employ the use of self-reported PA measures. This study objectively determined the contribution of MVPA during commuting to total MVPA, using cadence to define MVPA, and explored how the length of stepping bouts affects adherence to PA guidelines. Methods: Twenty-seven university staff wore an activPAL™ activity monitor for seven days and kept an activity diary. The activPAL™quantified MVPA and bouts duration and the activity diary collected information about commute times and the modes of commute. Twenty-three participants with at least four days of data were included in the final analysis. Results: The median total time per day spent in MVPA was 49.6 (IQR: 27.4–75.8) minutes and 31% of the total time was accumulated during commuting (median = 15.2 minutes; IQR: 4.11–26.9). Walking and mixed-mode commuters spent more time in MVPA (37.6 and 26.9 minutes, respectively), compared to car commuters (5.8 minutes). Seventeen out of the 23 participants achieved more than 30 minutes of MVPA per day, with five achieving this in their commute alone. A significant positive association was found between commute time spent in MVPA and total MVPA (p < .001). Conclusion: Commuting can be a major contributor to total MVPA, with the mode of commute having a significant role in the level of this contribution to total MVPA.
Carla Elane Silva dos Santos, Sofia Wolker Manta, Guilherme Pereira Maximiano, Susana Cararo Confortin, Tânia Rosane Bertoldo Benedetti, Eleonora d’Orsi, and Cassiano Ricardo Rech
Background: To examine the level of physical activity and sedentary behavior (SB), measured with accelerometers, in older adults from a city in southern Brazil according to sociodemographic and health characteristics. Methods: The sample consisted of 425 older adults (≥63 y) from the EpiFloripa Aging Study. Light physical activity (LPA), moderate to vigorous physical activity (MVPA), and SB were measured with accelerometers over a period of 7 days. Results: The older adults spent two-thirds of the time of use in SB, one-third in LPA, and only 2.1% (95% confidence interval, 1.8–2.2) in MVPA. In the final adjusted model, lower levels of MVPA were observed for women, as well as higher SB and lower LPA and MVPA for those with higher age. There were also trends toward prolonged SB and lower LPA when participants had a higher educational level and toward lower MVPA with higher body mass index. Conclusions: Constant monitoring of physical activity levels and SB using objective measures is recommended and interventions should be directed at the groups most exposed to excessive SB and low levels of MVPA.