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MeLisa Creamer, Heather R. Bowles, Belinda von Hofe, Kelley Pettee Gabriel, Harold W. Kohl III and Adrian Bauman

Background:

Computer-assisted techniques may be a useful way to enhance physical activity surveillance and increase accuracy of reported behaviors.

Purpose:

Evaluate the reliability and validity of a physical activity (PA) self-report instrument administered by telephone and internet.

Methods:

The telephone-administered Active Australia Survey was adapted into 2 forms for internet self-administration: survey questions only (internet-text) and with videos demonstrating intensity (internet-video). Data were collected from 158 adults (20–69 years, 61% female) assigned to telephone (telephone-interview) (n = 56), internet-text (n = 51), or internet-video (n = 51). Participants wore an accelerometer and completed a logbook for 7 days. Test-retest reliability was assessed using intraclass correlation coefficients (ICC). Convergent validity was assessed using Spearman correlations.

Results:

Strong test-retest reliability was observed for PA variables in the internet-text (ICC = 0.69 to 0.88), internet-video (ICC = 0.66 to 0.79), and telephone-interview (ICC = 0.69 to 0.92) groups (P-values < 0.001). For total PA, correlations (ρ) between the survey and Actigraph+logbook were ρ = 0.47 for the internet-text group, ρ = 0.57 for the internet-video group, and ρ = 0.65 for the telephone-interview group. For vigorous-intensity activity, the correlations between the survey and Actigraph+logbook were 0.52 for internet-text, 0.57 for internet-video, and 0.65 for telephone-interview (P < .05).

Conclusions:

Internet-video of the survey had similar test-retest reliability and convergent validity when compared with the telephone-interview, and should continue to be developed.

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Leon Straker, Amity Campbell, Svend Erik Mathiassen, Rebecca Anne Abbott, Sharon Parry and Paul Davey

Background:

Capturing the complex time pattern of physical activity (PA) and sedentary behavior (SB) using accelerometry remains a challenge. Research from occupational health suggests exposure variation analysis (EVA) could provide a meaningful tool. This paper (1) explains the application of EVA to accelerometer data, (2) demonstrates how EVA thresholds and derivatives could be chosen and used to examine adherence to PA and SB guidelines, and (3) explores the validity of EVA outputs.

Methods:

EVA outputs are compared with accelerometer data from 4 individuals (Study 1a and1b) and 3 occupational groups (Study 2): seated workstation office workers (n = 8), standing workstation office workers (n = 8), and teachers (n = 8).

Results:

Line graphs and related EVA graphs highlight the use of EVA derivatives for examining compliance with guidelines. EVA derivatives of occupational groups confirm no difference in bouts of activity but clear differences as expected in extended bouts of SB and brief bursts of activity, thus providing evidence of construct validity.

Conclusions:

EVA offers a unique and comprehensive generic method that is able, for the first time, to capture the time pattern (both frequency and intensity) of PA and SB, which can be tailored for both occupational and public health research.

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Jeanne F. Nichols, Hilary Aralis, Sonia Garcia Merino, Michelle T. Barrack, Lindsay Stalker-Fader and Mitchell J. Rauh

There is a growing need to accurately assess exercise energy expenditure (EEE) in athletic populations that may be at risk for health disorders because of an imbalance between energy intake and energy expenditure. The Actiheart combines heart rate and uniaxial accelerometry to estimate energy expenditure above rest. The authors’ purpose was to determine the utility of the Actiheart for predicting EEE in female adolescent runners (N = 39, age 15.7 ± 1.1 yr). EEE was measured by indirect calorimetry and predicted by the Actiheart during three 8-min stages of treadmill running at individualized velocities corresponding to each runner’s training, including recovery, tempo, and 5-km-race pace. Repeated-measures ANOVA with Bonferroni post hoc comparisons across the 3 running stages indicated that the Actiheart was sensitive to changes in intensity (p < .01), but accelerometer output tended to plateau at race pace. Pairwise comparisons of the mean difference between Actiheart- and criterion-measured EEE yielded values of 0.0436, 0.0539, and 0.0753 kcal · kg−1 · min−1 during recovery, tempo, and race pace, respectively (p < .0001). Bland–Altman plots indicated that the Actiheart consistently underestimated EEE except in 1 runner’s recovery bout. A linear mixed-model regression analysis with height as a covariate provided an improved EEE prediction model, with the overall standard error of the estimate for the 3 speeds reduced to 0.0101 kcal · kg−1 · min−1. Using the manufacturer’s equation that combines heart rate and uniaxial motion, the Actiheart may have limited use in accurately assessing EEE, and therefore energy availability, in young, female competitive runners.

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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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Deirdre Dlugonski, Katrina Drowatzky DuBose and Patrick Rider

Background:

Many mothers and young children are not meeting physical activity guidelines. Parent–child coparticipation in physical activity (ie, shared physical activity) provides opportunities for social modeling and might be associated with child physical activity. There is very little information about shared physical activity using objective measures.

Methods:

Participants (N = 17 mother–young child dyads) completed a demographic survey and height/weight measurements, and wore a Bluetooth® accelerometer for 1 week. Accelerometers were initialized using the proximity function to yield both individual and proximity [a minute-by-minute log of whether the 2 accelerometers were in- or out-of-range (∼50 m or less)] data. Shared physical activity was calculated in MATLAB by overlaying individual and proximity accelerometer data.

Results:

Mother–child dyads spent approximately 2 hours per day in shared time that was mostly shared sedentary activities. Less than 1% of shared minutes per day were spent in shared moderate to vigorous physical activity.

Conclusions:

Mothers and young children spent a small portion of their day in shared activities. Most mother–child shared time was spent in sedentary or light activities rather than moderate to vigorous physical activity. This method for objectively measuring shared physical activity provides novel information about the context in which physical activity occurs and could be used to understand patterns of physical activity among other dyads.

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Joanna Kostka, Tomasz Kostka and Ewa Borowiak

Background:

The goal of this study was to assess the physical activity (PA) and its determinants of older people living in the 3 different environments.

Methods:

Three equal (n = 693 each) groups of individuals aged ≥65 years living in urban, rural and institutional environments took part in this study. PA was measured by the Seven Day Recall PA Questionnaire (energy expenditure—PA-EE) and the Stanford Usual Activity Questionnaire (health-related behaviors—PA-HRB).

Results:

PA-EE was highest in the rural environment and lowest in nursing homes. PA-HRB were most common in urban area. Older age, lower education level, several concomitant diseases and the number of systematically used medications were consistently related to lower PA-EE and PA-HRB. Smoking habit, presence of hypertension, musculoskeletal and gastrointestinal disorders had different association to PA-EE and PA-HRB in the 3 environments.

Conclusions:

Subpopulations of older people differ from the general population with regard to their level of PA and its association with sociodemographic data and concomitant diseases. Concomitant serious diseases significantly decrease the level of PA of older subjects. The relationship between PA and nondebilitating disorders may vary depending on the living environment or PA assessment methodology.

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Nicolas Aguilar-Farias, Wendy J. Brown, Tina L. Skinner and G.M.E.E. (Geeske) Peeters

Background: The purpose was to assess metabolic equivalent (MET) values of common daily activities in middle-age and older adults in free-living environments and compare these with MET values listed in the compendium of physical activities (CPA). Methods: Sixty participants (mean age = 71.5, SD = 10.8) completed a semistructured protocol of sitting, lying, self-paced walking, and 4 self-selected activities in their residences. Oxygen consumption was measured using portable indirect calorimetry, to assess METs for each activity relative to VO2 at rest (VO2 during activity/VO2 at rest). Measured MET values for 20 different activities were compared with those in the CPA, for the total sample and for participants aged 55–64, 65–74, and 75–99 years. Results: Measured METs for sitting, walking, sweeping, trimming, and laundry were significantly different from the CPA values. Measured MET values for sedentary activities were lower in all age groups, and those for walking and household activities were higher in the youngest age group, than the CPA values. For gardening activities, there was a significant decline in measured METs with age. Conclusions: Some measured MET values in older people differed from those in the CPA. The values reported here may be useful for future research with younger, middle-age, and older-old people.

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Steven P. Singleton, James T. Fitzgerald and Anne Victoria Neale

This study was conducted to determine the exercise habits and fitness status of healthy older black and white adults, ages 50 to 80 years. The 384 subjects were enrolled in a health promotion project conducted by a midwestern medical school. Self-reported exercise levels were higher for men than for women and were higher for whites compared with blacks. Age had the greatest impact on treadmill performance for both sexes. Activity levels declined with age for men but not for women. Self-reported exercise levels were highly predictive of fitness status for men but not for women. The relationship in older adults between activity levels and both measured fitness and health status needs further investigation.

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Ryan McGrath, Chantal A. Vella, Philip W. Scruggs, Mark D. Peterson, Christopher J. Williams and David R. Paul

Background: This investigation sought to determine how accelerometer wear (1) biased estimates of sedentary behavior (SB) and physical activity (PA), (2) affected misclassifications for meeting the Physical Activity Guidelines for Americans, and (3) impacted the results of regression models examining the association between moderate to vigorous physical activity (MVPA) and a clinically relevant health outcome. Methods: A total of 100 participants [age: 20.6 (7.9) y] wore an ActiGraph GT3X+ accelerometer for 15.9 (1.6) hours per day (reference dataset) on the hip. The BOD POD was used to determine body fat percentage. A data removal technique was applied to the reference dataset to create individual datasets with wear time ranging from 15 to 10 hours per day for SB and each intensity of PA. Results: Underestimations of SB and each intensity of PA increased as accelerometer wear time decreased by up to 167.2 minutes per day. These underestimations resulted in Physical Activity Guidelines for Americans misclassification rates of up to 42.9%. The regression models for the association between MVPA and body fat percentage demonstrated changes in the estimates for each wear-time adherence level when compared to the model using the reference MVPA data. Conclusions: Increasing accelerometer wear improves daily estimates of SB and PA, thereby also improving the precision of statistical inferences that are made from accelerometer data.

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Greg Welk, Youngwon Kim, Robin P. Shook, Laura Ellingson and Roberto L. Lobelo

Background:

The study evaluated the concurrent and criterion validity of a new, disposable activity monitor designed to provide objective data on physical activity and energy expenditure in clinical populations.

Methods:

A sample of healthy adults (n = 52) wore the disposable Metria IH1 along with the established Sensewear armband (SWA) monitor for a 1-week period. Concurrent validity was examined by evaluating the statistical equivalence of estimates from the Metria and the SWA. Criterion validity was examined by comparing the relative accuracy of the Metria IH1 and the SWA for assessing walking/running. The absolute validity of the 2 monitors was compared by computing correlations and mean absolute percent error (MAPE) relative to criterion data from a portable metabolic analyzer.

Results:

The output from 2 monitors was highly correlated (correlations > 0.90) and the summary measures yielded nearly identical allocations of time spent in physical activity and energy expenditure. The monitors yielded statistically equivalent estimates and had similar absolute validity relative to the criterion measure (12% to 15% error).

Conclusions:

The disposable nature of the adhesive Metria IH1 monitor offers promise for clinical evaluation of physical activity behavior in patients. Additional research is needed to test utility for counseling and behavior applications.