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Anders Raustorp, Peter Pagels, Cecilia Boldemann, Nilda Cosco, Margareta Söderström and Fredrika Mårtensson

Background:

It is important to understand the correlates of physical activity (PA) to influence policy and create environments that promote PA among preschool children. We compared preschoolers’ PA in Swedish and in US settings and objectively examined differences boys’ and girls’ indoor and outdoor PA regarding different intensity levels and sedentary behavior.

Methods:

Accelerometer determined PA in 50 children with mean age 52 months, (range 40–67) was recorded during preschool time for 5 consecutive weekdays at 4 sites. The children wore an Actigraph GTIM Monitor.

Results:

Raleigh preschool children, opposite to Malmö preschoolers spent significantly more time indoors than outdoors (P < .001). Significantly more moderate-to-vigorous intensity physical activity (MVPA) was observed outdoors (P < .001) in both settings. Malmö children accumulated significantly more counts/min indoors (P < .001). The percent of MVPA during outdoor time did not differ between children at Raleigh and Malmö.

Conclusion:

Physical activity counts/minutes was significantly higher outdoors vs. indoors in both Malmö and Raleigh. Malmö preschoolers spent 47% of attendance time outdoors compared with 18% for Raleigh preschoolers which could have influenced the difference in preschool activity between the 2 countries. Time spent in MVPA at preschool was very limited and predominantly adopted outdoors.

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E. Andrew Pitchford, Leah R. Ketcheson, Hyun-Jin Kwon and Dale A. Ulrich

Background:

Research measuring physical activity behaviors during infancy is critical for evaluation of early intervention efforts to reduce rapid weight gain. There is little known about the physical activity patterns of infants, due in part to limited evidence for measurement procedures. This study sought to determine the minimal number of days and hours of accelerometry needed to reliably measure daily physical activity in infants using Generalizability (G) theory.

Methods:

A total of 23 infants (14 female, 9 male) wore an accelerometer on the right ankle and right wrist for 7 days. Data were manually cleaned to remove activity counts not produced by the infant. G theory analyses were conducted on the average counts per epoch.

Results:

Reliable estimates were observed with at least 2 days (G & Φ = .910) and 12 hours (G = .806, Φ = .803) at the ankle, and with at least 3 days (G & Φ = .906) and 15 hours (G = .802, Φ = .800) at the wrist.

Conclusions:

These results provide some of the first guidelines for objective physical activity measurement during infancy. Accelerometer monitoring periods of at least 3 days including all daytime hours appear to be sufficient for reliable measurement.

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Melissa Raymond, Adele Winter and Anne E. Holland

Background:

Older adults undergoing rehabilitation may have limited mobility, slow gait speeds and low levels of physical activity. Devices used to quantify activity levels in older adults must be able to detect these characteristics.

Objective:

To investigate the validity of the Positional Activity Logger (PAL2) for monitoring position and measuring physical activity in older inpatients (slow stream rehabilitation).

Methods:

Twelve older inpatients (≥65 years) underwent a 1-hour protocol (set times in supine, sitting, standing; stationary and moving). Participants were video-recorded while wearing the PAL2. Time spent in positions and walking (comfortable and fast speeds) were ascertained through video-recording analysis and compared with PAL2 data.

Results:

There was no difference between the PAL2 and video recording for time spent in any position (P-values 0.055 to 0.646). Walking speed and PAL2 count were strongly correlated (Pearson’s r = .913, P < .01). The PAL2 was responsive to within-person changes in gait speed: activity count increased by an average of 52.47 units (95% CI 3.31, 101.63). There was 100% agreement for transitions between lying to sitting and < 1 transition difference between siting to standing.

Conclusion:

The PAL2 is a valid tool for quantifying activity levels, position transitions, and within-person changes in gait speed in older inpatients.

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Alessandra de Carvalho Bastone, Eduardo Ferriolli, Claudine Patricia Teixeira, João Marcos Domingues Dias and Rosângela Corrêa Dias

Background:

Self-reported measures of decreased aerobic fitness and low physical activity are criteria of frailty. However, research assessing aerobic fitness and physical activity levels associated with frailty is limited. Therefore, the aims of this study were to objectively assess the aerobic fitness and the physical activity level of frail and nonfrail elderly, and to examine the association between frailty, aerobic fitness and habitual physical activity.

Methods:

This study included 26 elderly (66 to 86 years), randomly selected. The groups (frail/nonfrail) were age and sex paired. Peak oxygen consumption, maximal walking distance and speed were assessed during the incremental shuttle walk test (ISWT). Average daily time spent in sedentary, light, moderate and hard activity, counts, number of steps and energy expenditure were measured by accelerometry.

Results:

All variables measured by the ISWT and accelerometer differed significantly between the groups (P < .02). All aerobic fitness and physical activity variables were significantly associated with frailty, independent of the number of chronic health conditions (P < .05).

Conclusions:

Frailty is associated with low peak oxygen consumption and low physical activity level. These findings could guide future clinical trials designed to evaluate the efficacy of aerobic exercises in the prevention and treatment of frailty.

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Daniel P. Hatfield, Virginia R. Chomitz, Kenneth Chui, Jennifer M. Sacheck and Christina D. Economo

Background:

Associations between physical activity (PA) intensity and volume and adolescents’ cardiometabolic health have research, policy, and practice implications. This study compares associations between cardiometabolic risk factors and 1) moderate-to-vigorous PA (MVPA) minutes versus total PA volume (accelerometer-derived total activity counts, TAC) and 2) light PA volume (counts at light intensity, L-TAC) versus moderate-to-vigorous PA volume (counts at moderate-to-vigorous intensity, MV-TAC).

Methods:

2105 adolescents from 2003– 2006 NHANES were included. Independent variables were MVPA minutes, TAC, L-TAC, and MV-TAC. Regression models tested associations between PA variables and continuous metabolic risk index (CMRI), waist circumference, systolic and diastolic blood pressure, HDL, insulin, and triglycerides.

Results:

TAC demonstrated a slightly stronger inverse association with CMRI (P = .004) than did MVPA (P = .013). TAC and MVPA were both associated with systolic and diastolic pressure, HDL, and insulin; associations were similar or slightly stronger for TAC. L-TAC and MV-TAC were both associated with CMRI and HDL. Only L-TAC was associated with diastolic pressure. Only MV-TAC was associated with waist circumference, systolic pressure, and insulin.

Conclusions:

Compared with MVPA minutes, TAC demonstrates similar or slightly stronger associations with cardiometabolic risk factors. L-TAC and MV-TAC appear similarly associated with adolescents’ clustered risk but differently associated with individual risk factors.

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Alex V. Rowlands

Background:

The total activity volume performed is an overall measure that takes into account the frequency, intensity, and duration of activities performed. The importance of considering total activity volume is shown by recent studies indicating that light physical activity (LPA) and intermittent moderate-to-vigorous physical activity (MVPA) have health benefits. Accelerometer-derived total activity counts (TAC) per day from a waist-worn accelerometer can serve as a proxy for an individual’s total activity volume. The purpose of this study was to develop age- and gender-specific percentiles for daily TAC, minutes of MVPA, and minutes of LPA in U.S. youth ages 6-19 y.

Methods:

Data from the 2003-2006 NHANES waist-worn accelerometer component were used in this analysis. The sample was composed of youth aged 6-19 years with at least 4 d of ≥10 hr of accelerometer wear time (N = 3698). MVPA was defined using age specific cutpoints as the total number of minutes at ≥4 metabolic equivalents (METs) for youth 6-17 y or minutes with ≥2020 counts for youth 18-19 y. LPA was defined as the total number of minutes between 100 counts and the MVPA threshold. TAC/d, MVPA, and LPA were averaged across all valid days.

Results:

For males in the 50th percentile, the median activity level was 441,431 TAC/d, with 53 min/d of MVPA and 368 min/d of LPA. The median level of activity for females was 234,322 TAC/d, with 32 min/d of MVPA and 355 min/d of LPA.

Conclusion:

Population referenced TAC/d percentiles for U.S. youth ages 6-19 y provide a novel means of characterizing the total activity volume performed by children and adolescents.

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Erik A. Willis, Amanda N. Szabo-Reed, Lauren T. Ptomey, Jeffery J. Honas, Felicia L. Steger, Richard A. Washburn and Joseph E. Donnelly

assessed in the participant using the calorimeter was representative of the group, we compared percent HR max and physical activity (counts/min) in the participants wearing the calorimeter to the study and to not wearing the calorimeter. Each participant completed one session wearing an indirect

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Charity B. Breneman, Christopher E. Kline, Delia West, Xuemei Sui and Xuewen Wang

exercise in postmenopausal women—specifically, wake after sleep onset (WASO), number of awakenings, and activity counts ( Wang & Youngstedt, 2014 ). Therefore, we hypothesized that these sleep outcomes were most likely to be impacted by an acute bout of exercise among postmenopausal women in an exercise

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Katja Krustrup Pedersen, Esben Lykke Skovgaard, Ryan Larsen, Mikkel Stengaard, Søren Sørensen and Kristian Overgaard

, & Holtermann, 2014 ). Accelerometers record accelerations as a person moves, and the output measure extracted from accelerometers (e.g., ActiGraph GT3X+) is typically “activity counts” derived from the collected raw acceleration data. In order to translate activity counts into a meaningful outcome variable

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Kosuke Tamura, Jeffrey S. Wilson, Robin C. Puett, David B. Klenosky, William A. Harper and Philip J. Troped

points) and (2) using a combination of accelerometer counts and GPS speed. For the second approach, intensity of activity was classified based on average speed from the GPS device for a given minute, the metabolic equivalent (MET) value for bicycling at that speed, 31 and activity counts from