Stephen D. Herrmann and Karin A. Pfeiffer
Christiana M.T. van Loo, Anthony D. Okely, Marijka Batterham, Tina Hinkley, Ulf Ekelund, Soren Brage, John J. Reilly, Gregory E. Peoples, Rachel Jones, Xanne Janssen and Dylan P. Cliff
To validate the activPAL3 algorithm for predicting metabolic equivalents (TAMETs) and classifying MVPA in 5- to 12-year-old children.
Fifty-seven children (9.2 ± 2.3y, 49.1% boys) completed 14 activities including sedentary behaviors (SB), light (LPA) and moderate-to-vigorous physical activities (MVPA). Indirect calorimetry (IC) was used as the criterion measure. Analyses included equivalence testing, Bland-Altman procedures and area under the receiver operating curve (ROC-AUC).
At the group level, TAMETs were significantly equivalent to IC for handheld e-game, writing/coloring, and standing class activity (P < .05). Overall, TAMETs were overestimated for SB (7.9 ± 6.7%) and LPA (1.9 ± 20.2%) and underestimated for MVPA (27.7 ± 26.6%); however, classification accuracy of MVPA was good (ROC-AUC = 0.86). Limits of agreement were wide for all activities, indicating large individual error (SB: −27.6% to 44.7%; LPA: −47.1% to 51.0%; MVPA: −88.8% to 33.9%).
TAMETs were accurate for some SB and standing, but were overestimated for overall SB and LPA, and underestimated for MVPA. Accuracy for classifying MVPA was, however, acceptable.
John M. Schuna Jr., Tiago V. Barreira, Daniel S. Hsia, William D. Johnson and Catrine Tudor-Locke
Energy expenditure (EE) estimates for a broad age range of youth performing a variety of activities are needed.
106 participants (6–18 years) completed 6 free-living activities (seated rest, movie watching, coloring, stair climbing, basketball dribbling, jumping jacks) and up to 9 treadmill walking bouts (13.4 to 120.7 m/min; 13.4 m/min increments). Breath-by-breath oxygen uptake (VO2) was measured using the COSMED K4b2 and EE was quantified as youth metabolic equivalents (METy1:VO2/measured resting VO2, METy2:VO2/estimated resting VO2). Age trends were evaluated with ANOVA.
Seated movie watching produced the lowest mean METy1 (6- to 9-year-olds: 0.94 ± 0.13) and METy2 values (13- to 15-year-olds: 1.10 ± 0.19), and jumping jacks produced the highest mean METy1 (13- to 15-year-olds: 6.89 ± 1.47) and METy2 values (16- to 18-year-olds: 8.61 ± 2.03). Significant age-related variability in METy1 and METy2 were noted for 8 and 2 of the 15 evaluated activities, respectively.
Descriptive EE data presented herein will augment the Youth Compendium of Physical Activities.
Kimberly Hannam, Kevin Deere, Sue Worrall, April Hartley and Jon H. Tobias
The purpose of this study was to establish the feasibility of using an aerobics class to produce potentially bone protective vertical impacts of ≥ 4g in older adults and to determine whether impacts can be predicted by physical function. Participants recruited from older adult exercise classes completed an SF-12 questionnaire, short physical performance battery, and an aerobics class with seven different components, performed at low and high intensity. Maximum g and jerk values were identified for each activity. Forty-one participants (mean 69 years) were included. Mean maximal values approached or exceeded the 4g threshold for four of the seven exercises. In multivariate analyses, age (−0.53; −0.77, −0.28) (standardized beta coefficient; 95% CI) and 4-m walk time (−0.39; −0.63, −0.16) were inversely related to maximum g. Aerobics classes can be used to produce relatively high vertical accelerations in older individuals, although the outcome is strongly dependent on age and physical function.
Kevin C. Deere, Kimberly Hannam, Jessica Coulson, Alex Ireland, Jamie S. McPhee, Charlotte Moss, Mark H. Edwards, Elaine Dennison, Cyrus Cooper, Adrian Sayers, Matthijs Lipperts, Bernd Grimm and Jon H. Tobias
Physical activity (PA) may need to produce high impacts to be osteogenic. The aim of this study was to identify threshold(s) for defining high impact PA for future analyses in the VIBE (Vertical Impact and Bone in the Elderly) study, based on home recordings with triaxial accelerometers. Recordings were obtained from 19 Master Athlete Cohort (MAC; mean 67.6 years) and 15 Hertfordshire Cohort Study (HCS; mean 77.7 years) participants. Data cleaning protocols were developed to exclude artifacts. Accelerations expressed in g units were categorized into three bands selected from the distribution of positive Y-axis peak accelerations. Data were available for 6.6 and 4.4 days from MAC and HCS participants respectively, with approximately 14 hr recording daily. Three-fold more 0.5−1.0g impacts were observed in MAC versus HCS, 20-fold more 1.0−1.5g impacts, and 140-fold more impacts ≥ 1.5g. Our analysis protocol successfully distinguishes PA levels in active and sedentary older individuals.
Felipe Fossati Reichert, Jonathan Charles Kingdom Wells, Ulf Ekelund, Ana Maria Baptista Menezes, Cesar Gomes Victora and Pedro C. Hallal
Physical activity may influence both fat and lean body mass. This study investigated the association between physical activity in children between the ages of 11 and 13 years and both fat and lean mass.
A subsample of the 1993 Pelotas (Brazil) Birth Cohort was visited in 2004–2005 and 2006–2007. Physical activity was estimated through standardized questionnaires. Body composition (ie, fat and lean mass) was measured using deuterium dilution. Those with moderate-to-vigorous activity greater than 420 min/wk were classified as active, and physical activity trajectory was defined as being above or below the cutoff at each visit.
Four hundred eighty-eight adolescents (51.8% boys) were evaluated. The mean difference in fat mass in boys and girls who reported ≥ 420 min/wk of physical activity in both visits compared with those who were consistently inactive was –4.8 kg (P ≤ .001). There was an inverse association between physical activity and fat mass among boys in both crude and confounder-adjusted analyses, whereas for girls, the association was evident only in the crude analysis. There was no significant association between physical activity and lean mass.
Physical activity may contribute to tackling the growing epidemic of adolescent obesity in low- and middle-income countries.
Maureen R. Weiss
Jitka Jancova-Vseteckova, Martin Bobak, Ruzena Kubinova, Nada Capkova, Anne Peasey, Michael G. Marmot and Hynek Pikhart
The aim was to examine the association of objective measures of physical functioning (PF) with education and material circumstances and the decline in PF with age by socioeconomic position (SEP).
In 3,205 subjects (60–75 years) from the Czech Republic, we assessed relationship between PF, SEP, and age. Linear regression was used to assess PF measures and SEP measures.
Cross-sectional decline in PF by age was similar in all individuals. Differences between SEP groups were similar across age groups, except for the difference in walk speed by material circumstances in men—bigger at older ages (p = .004). Men and women with the highest education were about 2 s faster at the chair rise test than those with the lowest education.
Findings suggest strong educational gradient in PF, an inconsistent role of self-assessed material circumstances, and virtually no interaction of SEP with the cross-sectional decline in PF by age.
Patricia A. Collins and Daphne Mayer
Individuals that engage in active transportation (AT) have healthier weights and fitness levels. Most AT research has focused on work- or school-based destinations. Meanwhile, little is known about the differences between individuals that engage in the most common forms of AT—walking and cycling—and how these AT patterns vary by destination, duration, and season.
We recruited 1400 randomly sampled adults (350 per season) in Kingston, Ontario, Canada to complete a cross-sectional telephone survey. The survey captured the prevalence, destinations, and duration of AT, and we examined the observed differences by mode.
The majority (72%) of respondents were AT-users; walking constituted 93% of overall mode share. Cyclists were more likely to be male, younger, and employed than walkers. Walkers tended to access neighborhood-based destinations, while cyclists were more likely to use AT to get to work. AT duration was comparable by mode, ranging from approximately 8 to 20 minutes. Overall rates of AT were lowest in the winter, but walking rates were reasonably high year-round.
Beyond commuting to work and school, policy-makers and planners should consider the breadth of destinations accessed by different modes when aiming to increase physical activity through AT in their communities.
Sara Wilcox, Melinda Forthofer, Patricia A. Sharpe and Brent Hutto
Walking interventions delivered by lay leaders have been shown to be effective. Knowing the characteristics of individuals who volunteer to be group leaders in walking programs could facilitate more efficient and effective recruitment and training.
Walking group leaders were recruited into a community-based program and formed walking groups from existing social networks. Leaders and members completed a survey, participated in physical measurements, and wore an accelerometer. Regression models (adjusting for group clustering and covariates) tested psychosocial and behavioral differences between leaders and members.
The sample included 296 adults (86% women, 66% African American). Leaders (n = 60) were similar to members (n = 236) with respect to most sociodemographic and health characteristics, but were significantly older and more likely to report arthritis and high cholesterol (P-values < .05). Although leaders and members were similar in sedentary behavior and physical activity, leaders reported higher levels of exercise self-regulation, self-efficacy, and social support (P-values < .01). Leaders also reported greater use of outdoor trails (P = .005) and other outdoor recreation areas (P = .003) for physical activity than members.
Although walking group leaders were no more active than members, leaders did display psychosocial characteristics and behaviors consistent with a greater readiness for change.