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Vanesa España-Romero, Jonathan A. Mitchell, Marsha Dowda, Jennifer R. O’Neill and Russell R. Pate

The purpose of this study was to examine the associations between sedentary behavior and moderate to vigorous physical activity (MVPA), measured by accelerometry, with body mass index (BMI) and waist circumference in 357 preschool children. Linear mixed models were used adjusting for race/ethnicity, parental education, and preschool. Follow-up analyses were performed using quantile regression. Among boys, MVPA was positively associated with BMI z-score (b = 0.080, p = .04) but not with waist circumference; quantile regression showed that MVPA was positively associated with BMI z-score at the 50th percentile (b = 0.097, p < .05). Among girls, no associations were observed between sedentary behavior and MVPA in relation to mean BMI z-score and mean waist circumference. Quantile regression indicated that, among girls at the 90th waist circumference percentile, a positive association was found with sedentary behavior (b = 0.441, p < .05), and a negative association was observed with MVPA (b = −0.599, p < .05); no associations were found with BMI z-score. In conclusion, MVPA was positively associated with BMI z-score among boys, and MVPA was negatively associated and sedentary behavior was positively associated with waist circumference among girls at the 90th percentile.

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Sofiya Alhassan, John R. Sirard, Laura B. F. Kurdziel, Samantha Merrigan, Cory Greever and Rebecca M. C. Spencer

Purpose:

The purpose of this study was to cross-validate previously developed Actiwatch (AW; Ekblom et al. 2012) and AcitGraph (AG; Sirard et al. 2005; AG-P, Pate et al. 2006) cut-point equations to categorize free-living physical activity (PA) of preschoolers using direct observation (DO) as the criterion measure. A secondary aim was to compare output from the AW and the AG from previously developed equations.

Methods:

Participants’ (n = 33; age = 4.4 ± 0.8 yrs; females, n=12) PA was directly observed for three 10-min periods during the preschool-day while wearing the AW (nondominant wrist) and AG (waist). Device specific cut-points were used to reduce the AW-E (Ekblom et al. 2012) and AG (AG-S, Sirard et al. 2005; AG-P, Pate et al. 2006) data into intensity categories. Spearman correlations (rsp) and agreement statistics were used to assess associations between the DO intensity categories and device data. Mixed model regression was used to identify differences in times spent in activity intensity categories.

Results:

There was a significant correlation between AW and AG output across all data (rsp = 0.41, p < .0001) and both were associated with the DO intensity categories (AW: rsp = 0.47, AG: rsp = 0.47; p < .001). At the individual level, all devices demonstrated relatively low sensitivity but higher specificity. At the group level, AW-E and AG-P provided similar estimates of time spent in moderate-to-vigorous PA (MVPA, AW-E: 4.7 ± 4.1, AG-P: 4.4 ± 3.3), compared with DO (5.1 ± 3.5). Conclusion: The AW-E and AG-P estimated times spent in MVPA were similar to DO, but the weak agreement statistics indicate that neither device cut-point equations provided accurate estimates at the individual level.

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Justin B. Moore, Michael W. Beets, Sara F. Morris and Mary Bea Kolbe

Background:

Most youth fail to achieve 60 minutes of moderate-to-vigorous physical activity (MVPA) daily while engaging in excessive amounts of sedentary behaviors. The objective of this investigation was to identify modifiable factors associated with meeting MVPA recommendations or engaging in greater than 55% of observed time sedentary.

Methods:

Youth (N = 1005, 10.5 yrs, 52% girls) wore accelerometers with daily minutes of MVPA (≥ 2296 counts·min−1) classified as ≥ 60mins/d vs. < 60min/d of MVPA. Sedentary behavior (< 100 counts·min−1) was classified as < 55% or ≥ 55% of total wear-time. Two-level random effects logit survival models for repeated events (days of monitoring) examined the association of psychosocial self-report measures and demographic characteristics to meeting the MVPA recommendation and spending ≥ 55% of time sedentary.

Results:

Wednesdays, Thursdays, and Sundays were associated with a decreased likelihood of meeting MVPA recommendations relative to Mondays. Wednesday thru Sunday were associated with a decreased likelihood of spending ≥ 55% of time sedentary. Being a boy, receiving transportation, and fewer reported barriers to physical activity were associated with meeting MVPA recommendations.

Conclusions:

Relatively few youth are engaging in recommended levels of physical activity. Provision of transportation and reduction of barriers to physical activity are relevant targets for physical activity promotion.

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Katya M. Herman, Gilles Paradis, Marie-Eve Mathieu, Jennifer O’Loughlin, Angelo Tremblay and Marie Lambert

This study examines the association between objectively-measured physical activity (PA) intensities and sedentary behavior (SED) in a cohort of 532 children aged 8–10 y. PA and SED were assessed by accelerometer over 7-days. Television and computer/video-game use were self-reported. Associations between PA intensities and SED variables were assessed by Spearman correlations and adjusted multiple linear regression. Higher mean daily moderate-to-vigorous and vigorous PA (MVPA, VPA) were negatively associated with mean daily SED (r = −0.47 and −0.37; p < .001), and positively associated with mean daily total PA (r = .58 and 0.46; p < .001). MVPA was also positively associated with light PA (LPA; r = .26, p < .00l). MVPA and VPA were not significantly associated with TV, computer/video or total screen time; accelerometer SED was only weakly associated with specific SED behaviors. On average, for each additional 10 min daily MVPA, children accumulated >14 min less SED, and for each additional 5 min VPA, 11 min less SED. Thus, over the course of a week, higher mean daily MVPA may displace SED time and is associated with higher total PA over and above the additional MVPA, due to concomitant higher levels of LPA. Public health strategies should target both MVPA and SED to improve overall PA and health in children.

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Ing-Mari Dohrn, Maria Hagströmer, Mai-Lis Hellénius and Agneta Ståhle

Aim:

To describe objectively-measured physical activity levels and patterns among community-dwelling older adults with osteoporosis, impaired balance, and fear of falling, and to explore the associations with gait, balance performance, falls self-efficacy, and health-related quality of life (HRQoL).

Methods:

Ninety-four individuals (75.6 ± 5.4 years) were included. Physical activity was assessed with pedometers and accelerometers. Mean steps/day, dichotomized into < 5,000 or = 5,000 steps/day, and time spent in different physical activity intensities were analyzed. Gait was assessed with a GAITRite walkway, balance performance was assessed with the modified figure-eight test and oneleg stance, falls self-efficacy was assessed with the Falls Efficacy Scale International, and HRQoL was assessed with Short Form-36.

Results:

Mean steps/day were 6,201 (991–17,156) and 40% reported < 5,000 steps/day. Participants with < 5,000 steps/day spent more time sedentary, had slower gait speed, poorer balance performance, and lower HRQoL than participants with ≥ 5,000 steps/day. No participants with < 5,000 met the recommended level of physical activity.

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Sarah Kozey Keadle, Shirley Bluethmann, Charles E. Matthews, Barry I. Graubard and Frank M. Perna

Background:

This paper tested whether a physical activity index (PAI) that integrates PA-related behaviors (ie, moderate-to-vigorous physical activity [MVPA] and TV viewing) and performance measures (ie, cardiorespiratory fitness and muscle strength) improves prediction of health status.

Methods:

Participants were a nationally representative sample of US adults from 2011 to 2012 NHANES. Dependent variables (self-reported health status, multimorbidity, functional limitations, and metabolic syndrome) were dichotomized. Wald-F tests tested whether the model with all PAI components had statistically significantly higher area under the curve (AUC) values than the models with behavior or performance scores alone, adjusting for covariates and complex survey design.

Results:

The AUC (95% CI) for PAI in relation to health status was 0.72 (0.68, 0.76), and PAI-AUC for multimorbidity was 0.72 (0.69, 0.75), which were significantly higher than the behavior or performance scores alone. For functional limitations, the PAI AUC was 0.71 (0.67, 0.74), significantly higher than performance, but not behavior scores, while the PAI AUC for metabolic syndrome was 0.69 (0.66, 0.73), higher than behavior but not performance scores.

Conclusions:

These results provide empirical support that an integrated PAI may improve prediction of health and disease. Future research should examine the clinical utility of a PAI and verify these findings in prospective studies.

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Nirjhar Dutta and Mark A. Pereira

Background:

The objective of this study was to estimate the mean difference in energy expenditure (EE) in healthy adults between playing active video games (AVGs) compared with traditional video games (TVGs) or rest.

Methods:

A systematic search was conducted on Ovid MEDLINE, Web of Knowledge, and Academic Search Premier between 1998 and April 2012 for relevant keywords, yielding 15 studies. EE and heart rate (HR) data were extracted, and random effects meta-analysis was performed.

Results:

EE during AVG play was 1.81 (95% CI, 1.29–2.34; I 2 = 94.2%) kcal/kg/hr higher, or about 108 kcal higher per hour for a 60-kg person, compared with TVG play. Mean HR was 21 (95% CI, 13.7–28.3; I 2 = 93.4%) beats higher per minute during AVG play compared with TVG play. There was wide variation in the EE and HR estimates across studies because different games were evaluated. Overall metabolic equivalent associated with AVG play was 2.62 (95% CI, 2.25–3.00; I 2 = 99.2%), equivalent to a light activity level. Most studies had low risk of bias due to proper study design and use of indirect calorimetry to measure EE.

Conclusion:

AVGs may be used to replace sedentary screen time (eg, television watching or TVG play) with light activity in healthy adults.

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Jennifer L. Copeland and Dale W. Esliger

Despite widespread use of accelerometers to objectively monitor physical activity among adults and youth, little attention has been given to older populations. The purpose of this study was to define an accelerometer-count cut point for a group of older adults and to then assess the group’s physical activity for 7 days. Participants (N = 38, age 69.7 ± 3.5 yr) completed a laboratory-based calibration with an Actigraph 7164 accelerometer. The cut point defining moderate to vigorous physical activity (MVPA) was 1,041 counts/min. On average, participants obtained 68 min of MVPA per day, although more than 65% of this occurred as sporadic activity. Longer bouts of activity occurred in the morning (6 a.m. to 12 p.m.) more frequently than other times of the day. Almost 14 hr/day were spent in light-intensity activity. This study demonstrates the rich information that accelerometers provide about older adult activity patterns—information that might further our understanding of the relationship between physical activity and healthy aging.

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Molly P. O’Sullivan, Matthew R. Nagy, Shannon S. Block, Trevor R. Tooley, Leah E. Robinson, Natalie Colabianchi and Rebecca E. Hasson

Purpose: The purpose of this study was to compare the effects of intermittent activity performed at varying intensities and of prolonged sitting on physical activity compensation. Methods: A total of 33 children (14 boys and 19 girls; age 7–11 y; 24% overweight/obese; 61% nonwhite) completed 4 experimental conditions in random order: 8 hours of sitting interrupted with 20 two-minute low-, moderate-, or high-intensity activity breaks or 20 two-minute sedentary computer game breaks. Physical activity energy expenditure (PAEE) was assessed via accelerometry to establish baseline PAEE and throughout each condition day (8-h in-lab PAEE, out-of-lab PAEE, and 3-d postcondition). Results: Compared with baseline PAEE, total daily PAEE was significantly higher during the high-intensity condition day (153 ± 43 kcal, P = .03), unchanged during the low-intensity (−40 ± 23 kcal, P > .05) and moderate-intensity condition days (−11 ± 18 kcal, P > .05), and decreased in response to prolonged sitting (−79 ± 22 kcal, P = .03). There were no significant differences in PAEE 3-day postcondition across conditions (P > .05). Conclusion: Despite the varying levels of PAEE accumulated during the 8-hour laboratory conditions, out-of-lab PAEE during each condition day and 3-day postcondition did not change from the baseline. These findings provide preliminary evidence that spontaneous physical activity in children does not change in response to intermittent activity or prolonged sitting.