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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.

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

Purpose:

To contrast associations of accelerometer-measured moderate-to-vigorous physical activity (MVPA) accumulated in bouts and total activity counts (TAC) with cardiometabolic biomarkers in U.S. adults.

Methods:

Using 2003–2006 National Health and Nutrition Examination Survey (NHANES) data, the sample was comprised of adults ≥ 20 years, not pregnant or lactating, with self-reported PA and at least 4 days of ≥ 10 hours accelerometer wear time (N = 5668). Bouted MVPA represented the minutes/day with ≥ 2020 counts/minute in bouts of 10 minutes or longer and TAC represented the total activity counts per day. Biomarkers included: cholesterol, triglyceride, glycohemoglobin, plasma glucose, C-peptide, insulin, C-reactive protein, homocysteine, blood pressure, body mass index (BMI), waist circumference, and skinfolds. Nested regression models were conducted which regressed each biomarker on bouted MVPA and TAC simultaneously, while adjusting for relevant covariates.

Results:

Results indicated TAC was more strongly associated with 11 biomarkers: HDL-C, triglyceride, plasma glucose, C-peptide, insulin, C-reactive protein, homocysteine, systolic blood pressure, waist circumference, triceps skinfold, and subscapular skinfold. Bouted MVPA, however, only displayed stronger associations with BMI.

Conclusions:

The total volume of physical activity, represented by TAC, appears to have stronger associations with cardiometabolic biomarkers than MVPA accumulated in bouts.

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Sze Yen Tan, Marijka Batterham and Linda Tapsell

Background:

Knowing the total energy expenditure (TEE) of overweight adults is important for prescribing weight loss interventions. However, objective measurements of TEE may not always be readily available and can be expensive. This study aimed to investigate the validity of RT3 accelerometers in predicting the TEE of sedentary overweight adults, and to identify any sensitivity to anthropometric changes.

Methods:

The analysis used data from a 12-week weight loss study. At baseline and 12-week, TEE was predicted using RT3 accelerometers during whole room calorimeter stays. Bias between 2 methods was compared at and between the baseline and 12-week measurement points. Multiple regression analyses of TEE data were conducted.

Results:

Predicted and measured values for TEE were not different at baseline (P = .677) but were significantly different after weight loss (P = .007). However, the mean bias between methods was small (<100 kcal/d) and was not significantly different between 2 time-points. RT3 activity counts explained an additional 2% of the variation in TEE at 12-week but not at baseline.

Conclusion:

RT3 accelerometers are not sensitive to body composition changes and do not explain variation in TEE of overweight and obese individuals in a sedentary environment.

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Scott E. Crouter, Paul R. Hibbing and Samuel R. LaMunion

The purpose of this study was to conduct a comprehensive evaluation of the ActiGraph GT3X+ (AG) and activPAL (AP) for assessing time spent in sedentary behaviors (SB) in youth using structured and free-living activities. Forty-four participants (M age, 12.7±0.8 yrs) completed up to eight structured activities and approximately 2 hrs of free-living activity while wearing an AG (right hip) and AP (right thigh). A Cosmed K4b2 was used for measured energy expenditure (METy; activity VO2 ÷ resting VO2). Direct observation was used during the structured activities. SB time was estimated using the inclinometer function of the AP and AG, and count thresholds with AG (<75 vector magnitude [VM] counts/10-s; <25 vertical axis [VA] counts/10-s; and <50, 100, 150, and 200 VA counts/min). For the structured activities, the AG inclinometer and AP correctly classified supine rest about 45% of the time, seated activities 54.6% and 65.1% of the time, respectively, and walking and running >96% of the time. For the free-living measurement, the VA <25 counts/10-s had the lowest RMSE (20.6 min), while the VM <75 counts/10-s had the lowest MAPE (69.2%). The AG inclinometer was within 0.2 minutes of measured time, but had the highest MAPE (107.1%). The AP was within 1.6 minutes of measured time, but had the highest RMSE (28.5 minutes). Compared to measured SB time, the VA <25 counts/10-s and VM <75 counts/10-s provided the most precise estimates of SB during free-living activity. Further refinement is needed to improve the AP and AG posture estimates.

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Jeremy A. Steeves, Catrine Tudor-Locke, Rachel A. Murphy, George A. King, Eugene C. Fitzhugh, David R. Bassett, Dane Van Domelen, John M. Schuna Jr and Tamara B. Harris

-derived daily PA variables closely linked to health outcomes (total activity counts [TAC] per day, MVPA minutes per week in modified 10-minute bouts (MVPA 10), and proportion of wear time spent in sedentary intensity activity). 1 – 3 , 5 , 18 , 19 Methods This analysis used data from the occupational

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Catrine Tudor-Locke, William D. Johnson and Peter T. Katzmarzyk

Background:

We examined the effects of wear time on a population profile of time-stamped accelerometer outputs using the 2005−2006 National Health and Nutrition Examination Survey (NHANES) data representing 3744 adults ≥ 20 years of age.

Methods:

Outputs included activity counts, steps, and time variables: nonwear (macro-determined), sedentary behavior (<100 activity counts/minute), and time in low (100−499 activity counts/minute), light (500−2019 activity counts/minute), and moderate-to-vigorous physical activity (MVPA; ≥2020 activity counts/minute) intensities. We describe mean values according to a 24-hour clock. Analysis was repeated in a reduced data set with only those who wore the accelerometer for 60 minutes within each considered hour of the day.

Results:

Between 12:00 and 17:00, U.S. adults spend approximately 31 minutes each hour in sedentary behaviors, and approximately 14 minutes, 10 minutes, and 2 minutes in low, light, and MVPA intensity activity, respectively. Removing the effect of nonwear time, sedentary behaviors are reduced in the morning hours and increase in the evening hours.

Conclusion:

At either end of the day, nonwear time appears to distort population estimates of all accelerometer time and physical activity volume indicators, but its effects are particularly clear on population estimates of time spent in sedentary behavior.

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Catrine Tudor-Locke, William D. Johnson and Peter T. Katzmarzyk

Background:

The purpose of this study was to examine the relationship between 2005−2006 National Health and Nutrition Examination Survey (NHANES) accelerometer-determined steps/day and activity counts/day, and between steps/day and estimates of nonwear time (as an indicator of the unmonitored day) and time spent in sedentary behaviors as well as a range of physical activity intensities.

Methods:

Linear regression models were used to characterize the relationship between steps/day, activity counts/day, estimates of wear time, and intensity categories.

Results:

1781 males (mean age = 46.5 years) and 1963 females (mean age = 47.7 years) wore accelerometers 14.0 ± SEM0.06 hours/day. The relationship between steps/day and activity counts/day was positive and strong (R 2 = .87). The relationship between steps/day and time spent in sedentary behaviors was inverse and moderate (R 2 = .25). Stronger and positive relationships were apparent between steps/day and time in light (R 2 = .69) and moderate (R 2 = .63) intensity activities. There was no discernable relationship between steps/day and time spent in low or vigorous intensity activities or with wear time.

Conclusions:

Assessed by accelerometer, steps/day explains 87% of the variation in activity counts/day, 25% of the variation in time in sedentary behaviors, 69% of time in light intensity, and 63% of time in moderate intensity.

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Brian C. Focht, Wendy M. Sanders, Peter H. Brubaker and W. Jack Rejeski

The authors examined the validity of the Computer Science and Application (CSA) activity monitor during a bout of rehabilitative exercise among older adults with chronic disease. In order to determine convergent validity, 50 participants were monitored during a 30-min walk in Study 1. In order to assess concurrent validity, 10 volunteers wore both a CSA accelerometer and a Cosmed K4 b2 portable gas-analysis unit during 30 min of rehabilitative exercise in Study 2. Study 1 results revealed significant (p < .01) positive relationships between mean CSA activity counts and estimated METs (r = .60), pedometer readings (r = .47), 6-min walk (r = .62), and self-efficacy (r = .45). Study 2 results demonstrated a significant (p < .01) positive correlation between CSA activity counts and oxygen uptake (r = .72). The findings suggest that the CSA activity monitor is an effective objective measure of physical activity during a structured, moderate-intensity bout of exercise among older adults with chronic disease.

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Leslie A. Pruitt, Nancy W. Glynn, Abby C. King, Jack M. Guralnik, Erin K. Aiken, Gary Miller and William L. Haskell

The authors explored using the ActiGraph accelerometer to differentiate activity levels between participants in a physical activity (PA, n = 54) or “successful aging” (SA) program (n = 52). The relationship between a PA questionnaire for older adults (CHAMPS) and accelerometry variables was also determined. Individualized accelerometry-count thresholds (ThreshIND) measured during a 400-m walk were used to identify “meaningful activity.” Participants then wore the ActiGraph for 7 days. Results indicated more activity bouts/day ≥10 min above ThreshIND in the PA group than in the SA group (1.1 ± 2.0 vs 0.5 ± 0.8, p = .05) and more activity counts/day above ThreshIND for the PA group (28,101 ± 27,521) than for the SA group (17,234 ± 15,620, p = .02). Correlations between activity counts/hr and CHAMPS ranged from .27 to .42, p < .01. The ActiGraph and ThreshIND might be useful for differentiating PA levels in older adults at risk for mobility disability.

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Joaquin U. Gonzales, Dustin M. Grinnell, Martha J. Kalasky and David N. Proctor

The authors examined interindividual and sex-specific variation in systolic (SBP) and diastolic (DBP) blood pressure responses to graded leg-extension exercise in healthy older (60–78 yr) women (n = 21) and men (n = 19). Maximal oxygen uptake (VO2max), body composition, physical activity (accelerometry), and vascular function were measured to identify predictors of exercise BP. Neither VO2max nor activity counts were associated with the rise in SBP or DBP during exercise in men. The strongest predictors of these responses in men were age (SBP: r 2 = .19, p = .05) and peak exercise leg vasodilation (DBP: r 2 = –.21, p < .05). In women, the modest relationship observed between VO2max and exercise BP was abolished after adjusting for central adiposity and activity counts (best predictors, cumulative r 2 = .53, p < .05, for both SBP and DBP). These results suggest that determinants of variation in submaximal exercise BP responses among older adults are sex specific, with daily physical activity influencing these responses in women but not men.