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M. Renée Umstattd Meyer, Stephanie L. Baller, Shawn M. Mitchell and Stewart G. Trost

Background:

Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples.

Objective:

To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter’s 2-regression model, Crouter’s refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003–2004 and 2005–2006 cycles), steps, IPAQ, and 7-day PA recall.

Methods:

A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared.

Results:

Crouter’s 2-regression (161.8 ± 52.3 minutes/day) and refined 2-regression (137.6 ± 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 ± 20.2 minutes/day, 18%). Differences between other measures were also significant.

Conclusions:

When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.

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Dale W. Esliger, Jennifer L. Copeland, Joel D. Barnes and Mark S. Tremblay

The unequivocal link between physical activity and health has prompted researchers and public health officials to search for valid, reliable, and logistically feasible tools to measure and quantify free-living physical activity. Accelerometers hold promise in this regard. Recent technological advances have led to decreases in both the size and cost of accelerometers while increasing functionality (e.g., greater memory, waterproofing). A lack of common data reduction and standardized reporting procedures dramatically limit their potential, however. The purpose of this article is to expand on the utility of accelerometers for measuring free-living physical activity. A detailed example profile of physical activity is presented to highlight the potential richness of accelerometer data. Specific recommendations for optimizing and standardizing the use of accelerometer data are provided with support from specific examples. This descriptive article is intended to advance and ignite scholarly dialogue and debate regarding accelerometer data capture, reduction, analysis, and reporting.

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Sofiya Alhassan, John R. Sirard, Tirzah R. Spencer, Ann Varady and Thomas N. Robinson

Background:

The purpose of this study was to develop a data-driven approach for analyzing incomplete accelerometer data from field-base studies.

Methods:

Multiple days of accelerometer data from the Stanford Girls health Enrichment Multi-site Studies (N = 294 African American girls) were summed across each minute of each day to produce a composite weekday and weekend day. Composite method estimates of physical activity were compared with those derived from methods typically described in the literature (comparison methods).

Results:

The composite method retained 99.7% and 100% of participants in weekday and weekend-day analysis, respectively, versus 84.7% to 94.2% and 28.6% to 99.0% for the comparison methods. Average wearing times for the composite method for weekday and weekend day were 99.6% and 98.6%, respectively, 91.7% to 93.9% and 82.3% to 95.4% for the comparison methods. Composite-method physical activity estimates were similar to comparison-methods estimates.

Conclusion:

The composite method used more available accelerometer data than standard approaches, reducing the need to exclude periods within a day, entire days, and participants from analysis.

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Emily L. Mailey, Neha P. Gothe, Thomas R. Wójcicki, Amanda N. Szabo, Erin A. Olson, Sean P. Mullen, Jason T. Fanning, Robert W. Motl and Edward McAuley

The criteria one uses to reduce accelerometer data can profoundly influence the interpretation of research outcomes. The purpose of this study was to examine the influence of 3 different interruption periods (i.e., 20, 30, and 60 min) on the amount of data retained for analyses and estimates of sedentary time among older adults. Older adults (N = 311, M age = 71.1) wore an accelerometer for 7 d and reported wear time on an accelerometer log. Accelerometer data were downloaded and scored using 20-, 30-, and 60-min interruption periods. Estimates of wear time, derived using each interruption period, were compared with self-reported wear time, and descriptive statistics were used to compare estimates of sedentary time. Results showed a longer interruption period (i.e., 60 min) yields the largest sample size and the closest approximation of self-reported wear time. A short interruption period (i.e., 20 min) is likely to underestimate sedentary time among older adults.

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Dan Weaving, Nicholas E. Dalton, Christopher Black, Joshua Darrall-Jones, Padraic J. Phibbs, Michael Gray, Ben Jones and Gregory A.B. Roe

Purpose: To identify which combination metrics of external and internal training load (TL) capture similar or unique information for individual professional players during skills training in rugby union using principal-component (PC) analysis. Methods: TL data were collected from 21 male professional rugby union players across a competitive season. This included PlayerLoad™, total distance, and individualized high-speed distance (>61% maximal velocity; all external TL) obtained from a microtechnology device (OptimEye X4; Catapult Innovations, Melbourne, Australia) that was worn by each player and the session rating of perceived exertion (RPE) (internal TL). PC analysis was conducted on each individual to extract the underlying combinations of the 4 TL measures that best describe the total information (variance) provided by the measures. TL measures with PC loadings (PCL) above 0.7 were deemed to possess well-defined relationships with the extracted PC. Results: The findings show that from the 4 TL measures, the majority of an individual’s TL information (first PC: 55–70%) during skills training can be explained by session RPE (PCL: 0.72–0.95), total distance (PCL: 0.86–0.98), or PlayerLoad (PCL: 0.71–0.98). High-speed distance was the only variable to relate to the second PC (PCL: 0.72–1.00), which captured additional TL information (+19–28%). Conclusions: Findings suggest that practitioners could quantify the TL of rugby union skills training with one of PlayerLoad, total distance, or session RPE plus high-speed distance while limiting omitted information of the TL imposed during professional rugby union skills training.

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Bareket Falk and Raffy Dotan

pediatric-specific issues and considerations that may affect the measurement and interpretation of the main outcome of these measurements, namely, V ˙ O 2 max or V ˙ O 2 peak . An inappropriate protocol, use of an improper ergometer or metabolic system, or inappropriate data reduction, could all lead to

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Jason Wicke and Genevieve A. Dumas

Body segment inertial parameters are required as input parameters when the kinetics of human motion is to be analyzed. However, owing to interindividual differences in body composition, noninvasive inertial estimates are problematic. Dual-energy x-ray absorptiometry (DXA) is a relatively new imaging approach that can provide cost- and time-effective means for estimating these parameters with minimal exposure to radiation. With the introduction of a new generation of DXA machines, utilizing a fan-beam configuration, this study examined their accuracy as well as a new interpolative data-reduction process for estimating inertial parameters. Specifically, the inertial estimates of two objects (an ultra-high molecular density plastic rod and an animal specimen) and 50 participants were obtained. Results showed that the fan-beam DXA, along with the new interpolative data-reduction process, provided highly accurate estimates (0.10–0.39%). A greater variance was observed in the center of mass location and moment of inertia estimates, likely as a result of the course end-point location (1.31 cm). However, using a midpoint interpolation of the end-point locations, errors in the estimates were greatly reduced for the center of mass location (0.64–0.92%) and moments of inertia (–0.23 to –0.48%).

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Alicia Dixon-Ibarra, Miyoung Lee and Anisia Dugala

The purpose of this study was to examine the physical activity patterns of older adults with intellectual disabilities (ID) in comparison with younger adults with ID and older adults without ID. A sample of 109 participants was included in the study. Sophisticated data reduction, time stamped technology, and multiple objective measures (i.e., pedometers and accelerometers) were used to determine physical activity intensities and walking patterns of participants. Results indicate that older adults with ID are performing less physical activity than comparison groups. A small proportion of older adults with ID (6%) met national physical activity recommendations of 150 min of moderate or 75 min of vigorous physical activity in bouts greater than ten minutes across the week (USDHHS, 2008). Sedentary behavior was also an observable factor in this study. These findings demonstrate the need for health promotion efforts for adults with ID across the lifespan.

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Catrine Tudor-Locke, David R. Bassett, Michael F. Shipe and James J. McClain

Background:

The purpose of this review is to update the methodological aspects of pedometry to encourage the consistent use of pedometers for assessment, to decrease sources of error, and to facilitate comparison and interpretation of results.

Methods:

The specific measurement topics addressed include: instrument choice, metric choice, validity, reliability, data collection and retrieval, time worn, day-to-day variability, monitoring time frame, reactivity, and data treatment.

Results:

A wide variety of valid and reliable instruments are commercially available and we can expect continued evolutions in value-added features as supporting technology improves. Data collection and retrieval has been achieved through various methods, including face-to-face contact, fax, e-mail, website, and conventional mail, and sometimes a combination of these. Day-to-day variation is not random, as would be expected from inconsistent pedometer performance, but rather exposes true behavior instability that can be explained by other factors and described using a coefficient of variation. Data reduction should be conducted cautiously and only after a full discovery (and disclosure) of its impact on aggregated group statistics and their relationship with other parameters.

Conclusions:

We have no doubt that research with pedometers will continue to yield new and important insights in the coming years.

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Dana L. Wolff-Hughes, Eugene C. Fitzhugh, David R. Bassett and James R. Churilla

Background:

Accelerometer-derived total activity count is a measure of total physical activity (PA) volume. The purpose of this study was to develop age- and gender-specific percentiles for daily total activity counts (TAC), minutes of moderate-to-vigorous physical activity (MVPA), and minutes of light physical activity (LPA) in U.S. adults.

Methods:

Waist-worn accelerometer data from the 2003-2006 National Health and Nutrition Examination Survey were used for this analysis. The sample included adults >20 years with >10 hours accelerometer wear time on >4 days (N = 6093). MVPA and LPA were defined as the number of 1-minute epochs with counts >2020 and 100 to 2019, respectively. TAC represented the activity counts acquired daily. TAC, MVPA, and LPA were averaged across valid days to produce a daily mean.

Results:

Males in the 50th percentile accumulated 288 140 TAC/day, with 357 and 22 minutes/day spent in LPA and MVPA, respectively. The median for females was 235 741 TAC/day, with 349 and 12 minutes/day spent in LPA and MVPA, respectively.

Conclusions:

Population-referenced TAC percentiles reflect the total volume of PA, expressed relative to other adults. This is a different approach to accelerometer data reduction that complements the current method of looking at time spent in intensity subcategories.