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John R. Sirard and Megan E. Slater

Background:

Accelerometer use in physical activity research has become increasingly popular but is prone to problems with missing data, which complicate the data reduction and analysis process. The purpose of this study was to determine the effect of hypothesized compliance strategies on improving compliance with wearing a physical activity accelerometer in high school students.

Methods:

Each of four local high schools was assigned to one of four compliance strategies: (1) receiving three phone calls, (2) completing a daily journal, (3) compensation contingent on number of complete (≥ 10 hours) days of data, and (4) control condition. Participants wore ActiGraph accelerometers for seven days to determine compliance and physical activity.

Results:

The contingent group had the highest level of compliance with 96% of the participants acquiring at least four of seven complete days of data. After controlling for grade level, school level percent minority students, and school level socioeconomic status (SES), the contingent group’s compliance remained significantly higher (P = .04) than the journal (85%), phone (72%), and control (70%) participants.

Conclusions:

The contingent compliance strategy improved the amount of time the students wore the monitor each day and, thus, the total number of days with ≥ 10 hours of data.

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Albert R. Mendoza, Kate Lyden, John Sirard, John Staudenmayer, Catrine Tudor-Locke and Patty S. Freedson

We evaluated the accuracy and precision of wearable activity trackers and a pedometer (ATPs) in estimating steps and sedentary time (ST) in free-living settings. Thirty-two healthy men and women (M ± SD: age = 32.3 ± 13.3 years; BMI = 24.4 ± 3.3 kg·m−2) were directly observed during three, 2-hour sessions on different days while wearing 10 devices and a biometric shirt. A validated direct observation (DO) system provided criterion measures for steps and ST. For steps, bias ranged from −753 steps/2-hrs (Fitbit Flex) to −57 steps/2-hrs (Polar Loop) and CIs ranged from [−1,144, −365] (Fitbit Flex) to [−291,175] (Polar Loop) steps/2-hrs. For all devices, step estimates were strongly correlated (r = 0.90 [Fitbit Flex] to r = 0.97 [New Lifestyles pedometer model 1000]) with DO counted steps. Estimates of ST were not accurate and were weakly correlated (r = −0.06 and r = 0.06 for Fitbit Flex and Fitbit One, respectively) with DO ST. Most ATPs were not accurate and varied in precision in estimating steps and ST in free-living settings. Implications from this study are that although point estimates of steps from ATPs are not accurate, ATPs’ ranking of step counts among individuals was high. However, the Fitbit Flex and Fitbit One are not recommended for estimating ST. This study advances our understanding of the performance of ATPs in estimating steps and ST in free-living settings, and significantly advances activity tracker and pedometer validation studies.

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John R. Sirard, Stewart G. Trost, Karin A. Pfeiffer, Marsha Dowda and Russell R. Pate

Background:

The purposes of this study were 1) to establish accelerometer count cutoffs to categorize activity intensity of 3 to 5-y old-children and 2) to evaluate the accelerometer as a measure of children’s physical activity in preschool settings.

Methods:

While wearing an ActiGraph accelerometer, 16 preschool children performed five, 3-min structured activities. Receiver Operating Characteristic (ROC) curve analyses identified count cutoffs for four physical activity intensities. In 9 preschools, 281 children wore an ActiGraph during observations performed by three trained observers (interobserver reliability = 0.91 to 0.98).

Results:

Separate count cutoffs for 3, 4, and 5-y olds were established. Sensitivity and specificity for the count cutoffs ranged from 86.7% to 100.0% and 66.7% to 100.0%, respectively. ActiGraph counts/15 s were different among all activities (P < 0.05) except the two sitting activities. Correlations between observed and ActiGraph intensity categorizations at the preschools ranged from 0.46 to 0.70 (P < 0.001).

Conclusions:

The ActiGraph count cutoffs established and validated in this study can be used to objectively categorize the time that preschool-age children spend in different physical activity intensity levels.

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Russell R. Pate, Rebecca Ross, Marsha Dowda, Stewart G. Trost and John R. Sirard

The purpose of this study was to examine the validity of the 3-Day Physical Activity Recall (3DPAR) self-report instrument in a sample of eighth and ninth grade girls (n = 70, 54.3% white, 37.1% African American). Criterion measures of physical activity were derived using the CSA 7164 accelerometer. Participants wore a CSA monitor for 7 consecutive days and completed the self-report physical activity recall for the last 3 of those days. Self-reported total METs, 30-min blocks of MVPA, and 30-min blocks of VPA were all significantly correlated with analogous CSA variables for 7 days (r = 0.35–0.51; P < 0.01) and 3 days (r = 0.27–0.46; P < 0.05) of monitoring. The results indicate that the 3DPAR is a valid instrument for assessing overall, vigorous, and moderate to vigorous physical activity in adolescent girls.

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John R. Sirard, Karin A. Pfeiffer, Marsha Dowda and Russell R. Pate

The purpose of this study was to identify racial differences in physical activity (PA), fitness, and BMI in female 8th-grade sports participants and nonparticipants. Girls from 31 South Carolina middle schools (N = 1,903, 48% White; mean age = 13.6 ± 0.63) reported PA and previous year sports-team participation, completed a submaximal fitness test, and had height and weight measured. Sports team participation was positively associated with PA and negatively associated with television viewing and BMI, in a dose-response manner. Compared with Whites, African-Americans reported less PA and more television viewing, and had greater BMI scores. Whereas PA intervention programs that incorporate a sports-team component could benefit all girls, African-American girls could be specifically targeted because of their lower physical activity.

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Mary O. Hearst, John R. Sirard, Leslie Lytle, Donald R. Dengel and David Berrigan

Background:

The association of physical activity (PA), measured 3 ways, and biomarkers were compared in a sample of adolescents.

Methods:

PA data were collected on 2 cohorts of adolescents (N = 700) in the Twin Cities, Minnesota, 2007–2008. PA was measured using 2 survey questions [Modified Activity Questionnaire (MAQ)], the 3-Day Physical Activity Recall (3DPAR), and accelerometers. Biomarkers included systolic (SBP) and diastolic blood pressure (DBP), lipids, percent body fat (%BF), and body mass index (BMI) percentile. Bivariate relationships among PA measures and biomarkers were examined followed by generalized estimating equations for multivariate analysis.

Results:

The 3 measures were significantly correlated with each other (r = .22–.36, P < .001). Controlling for study, puberty, age, and gender, all 3 PA measures were associated with %BF (MAQ = −1.93, P < .001; 3DPAR = −1.64, P < .001; accelerometer = −1.06, P = .001). The MAQ and accelerometers were negatively associated with BMI percentile. None of the 3 PA measures were significantly associated with SBP or lipids. The percentage of adolescents meeting the national PA recommendations varied by instrument.

Conclusions:

All 3 instruments demonstrated consistent findings when estimating associations with %BF, but were different for prevalence estimates. Researchers must carefully consider the intended use of PA data when choosing a measurement instrument.

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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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John R. Sirard, Peter Hannan, Gretchen J. Cutler and Dianne Nuemark-Sztainer

Background:

The purpose of this paper is to evaluate self-reported physical activity of young adults using 1-week and 1-year recall measures with an accelerometer as the criterion measure.

Methods:

Participants were a subsample (N = 121, 24 ± 1.7 yrs) from a large longitudinal cohort study. Participants completed a detailed 1-year physical activity recall, wore an accelerometer for 1 week and then completed a brief 1-week physical activity recall when they returned the accelerometer.

Results:

Mean values for moderate-to-vigorous physical activity (MVPA) from the 3 instruments were 3.2, 2.2, and 13.7 hours/wk for the accelerometer, 1-week recall, and 1-year recall, respectively (all different from each other, P < .001). Spearman correlations for moderate, vigorous, and MVPA between the accelerometer and the 1-week recall (0.30, 0.50, and 0.40, respectively) and the 1-year recall (0.31, 0.42, and 0.44, respectively) demonstrated adequate validity.

Conclusions:

Both recall instruments may be used for ranking physical activity at the group level. At the individual level, the 1-week recall performed much better in terms of absolute value of physical activity. The 1-year recall overestimated total physical activity but additional research is needed to fully test its validity.

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Jeanette M. Garcia, John R. Sirard, Ross Larsen, Meg Bruening, Melanie Wall and Dianne Neumark-Sztainer

Objective:

The purpose of this study was to examine, using structural equation modeling, the associations between nominated friend physical activity (PA), friend social support with individual PA-related psychological factors, and adolescent PA.

Methods:

Data were obtained from EAT 2010 (Eating and Activity Among Teens), a large cross-sectional study conducted in 20 middle and high schools. The sample consisted of 1951 adolescents (mean age: 14.25 ± 1.96, 54% female, 68% ethnic minorities). PA, parent and friend social support (perceived social support for PA from parents and friends), and psychological measures (PA enjoyment, PA self-efficacy, and PA barriers) were assessed by self-report questionnaires. The SEM analysis consisted of 1 observed variable: friend PA, and 2 latent constructs: psychological factors, perceived social support.

Results:

The model was a good fit, indicating that there were significant direct effects of both friend PA (P < .01) and psychological factors (P < .0001) on adolescent PA. In addition, psychological factors mediated the association between friend PA and adolescent PA.

Conclusion:

The results of this model suggest that psychological factors and friend PA are associated with adolescent PA, and that psychological factors may play an important role. Future studies should further examine the association of both friend PA and psychological variables with adolescent PA.

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John R. Sirard, Ann Forsyth, J. Michael Oakes and Kathryn H. Schmitz

Background:

The purpose of this study was to determine 1) the test-retest reliability of adult accelerometer-measured physical activity, and 2) how data processing decisions affect physical activity levels and test-retest reliability.

Methods:

143 people wore the ActiGraph accelerometer for 2 7-day periods, 1 to 4 weeks apart. Five algorithms, varying nonwear criteria (20 vs. 60 min of 0 counts) and minimum wear requirements (6 vs. 10 hrs/day for ≥ 4 days) and a separate algorithm requiring ≥ 3 counts per min and ≥ 2 hours per day, were used to process the accelerometer data.

Results:

Processing the accelerometer data with different algorithms resulted in different levels of counts per day, sedentary, and moderate-to-vigorous physical activity. Reliability correlations were very good to excellent (ICC = 0.70−0.90) for almost all algorithms and there were no significant differences between physical activity measures at Time 1 and Time 2.

Conclusions:

This paper presents the first assessment of test-retest reliability of the Actigraph over separate administrations in free-living subjects. The ActiGraph was highly reliable in measuring activity over a 7-day period in natural settings but data were sensitive to the algorithms used to process them.