The aim of this study was to investigate the relationship between habitual physical activity and body fatness in Hong Kong Chinese children. Fifty children aged 8–11 yrs wore a uniaxial accelerometer for 7 days to determine physical activity levels. The sum of seven skinfolds was used to estimate body fatness. Activity counts summed over 1 day (299384 – 140427, mean – SD) were similar to activity counts recorded in previous studies. Activity correlated significantly negatively with sum of skinfolds in boys (r = –.50, N = 24, P < .05) but not girls. In conclusion this study supports a negative relationship between physical activity and body fatness in Hong Kong Chinese boys.
Ann V. Rowlands, Roger G. Eston, Lobo Louie, David K. Ingledew, Kwok K. Tong and Frank H. Fu
Catrine Tudor-Locke, William D. Johnson and Peter T. Katzmarzyk
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.
Linear regression models were used to characterize the relationship between steps/day, activity counts/day, estimates of wear time, and intensity categories.
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.
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.
Binh Ba Chu, David Lawson and Geraldine Naughton
This study considered the validation of the Computer Science Applications (CSA) activity monitor (model 7164) for predicting activity energy expenditure (EE). A group of 34 Vietnamese adolescents (aged 11 to 15) performed three 5-minute treadmill trials at 4.5, 6.6, and 8.8 km · h−1. Mean activity counts and heart rate (HR) were significantly changed with the three-speed trials (p > 0.05). An equation to predict EE (kcal · min−1) was developed from activity counts and body mass (BM) from the 24 random subjects in Vietnam and was validated on the remaining 10 subjects. This equation explained 72% of the variability in kcal · min−1 (adjusted R2 = 0.72, SEE = 0.91 kcal · min−1). Consistent with previous studies, the relatively high SEE indicates that the equation is more suited for groups of Vietnamese adolescents rather than individuals.
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.
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.
Ann F. Maliszewski, Patty S. Freedson, Chris J. Ebbeling, Jill Crussemeyer and Kari B. Kastango
The Caltrac accelerometer functions as either an activity monitor that provides activity counts based on vertical acceleration as the individual moves about, or as a calorie counter in which the acceleration units are used in conjunction with body size, age, and sex to estimate energy expenditure. This study compared VO2 based energy expenditure with Caltrac estimated energy expenditure during three speeds of treadmill walking in children and adults. It also tested the validity of the Caltrac to differentiate between high and low levels of walking activity (activity counts). Ten boys and 10 men completed three randomly assigned walks while oxygen consumption was monitored and Caltrac estimates were obtained. The results indicate that the Caltrac does not accurately predict energy expenditure for boys and men across the three speeds of walking. Although there were no significant differences between actual and predicted energy expenditure values, the standard errors of estimate were high (17-25%) and the only significant correlation was found for men at the fastest walking speed (r=.81). However, the 95% confidence intervals of the activity counts and energy expenditure estimates from the Caltrac support its use as an activity monitor during walking.
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.
Susan L. Murphy, Dylan M. Smith and Angela K. Lyden
In a previous pilot study, the effect of 2 types of activity pacing instruction, general versus tailored, on osteoarthritis symptoms was examined and fatigue improved in the tailored group. Because activity pacing involves instruction on physical activity engagement, we undertook this secondary analysis to examine how pacing instruction affected physical activity patterns.
Thirty-two adults with knee or hip osteoarthritis, stratified by age and gender, received either tailored or general activity pacing instruction. All participants wore an accelerometer for 5 days that measured physical activity and allowed for repeated symptom assessment at baseline and 10-week follow-up. Activity patterns were assessed by examining physical activity variability (standard deviation of 5-day average activity counts per minute), and average activity level (5-day average activity counts per minute).
Physical activity variability decreased in the tailored group and increased in the general group. No significant group changes in average activity from baseline to 10-week follow-up were found.
In this pilot study, type of activity pacing instruction affected objective physical activity patterns in adults with OA. Tailored activity pacing was more effective at reducing high and low activity bouts corresponding to the message of keeping a steady pace to reduce symptoms.
Corneel Vandelanotte, Ilse De Bourdeaudhuij, Renaat Philippaerts, Michael Sjöström and James Sallis
The purpose of this study was to examine the reliability and validity of a newly developed computerized Dutch version of the International Physical Activity Questionnaire (IPAQ).
Subjects (N = 53) completed the computerized IPAQ at three specified times. Subjects wore a CSA activity monitor during seven full days and simultaneously completed a 7-d physical activity diary. Finally, respondents filled out a paper and pencil IPAQ.
Intraclass correlation coefficient ranged from 0.60 to 0.83. Correlations for “total physical activity” between the computerized IPAQ and the CSA activity counts were moderate (min: r = 0.38; kcal: r = 0.43). Correlations with the physical activity diary were also moderate (min: r = 0.39; kcal: r = 0.46). Correlations between the computerized and the paper and pencil IPAQ were high (min: r = 0.80; kcal: r = 0.84).
The computerized Dutch IPAQ is a reliable and reasonably valid physical activity measurement tool for the general adult population.
Ralph Maddison, Cliona Ni Mhurchu, Andrew Jull, Yannan Jiang, Harry Prapavessis and Anthony Rodgers
This study sought to quantify the energy expenditure and physical activity associated with playing the “new generation” active and nonactive console-based video games in 21 children ages 10–14 years. Energy expenditure (kcal) derived from oxygen consumption (VO2) was continuously assessed while children played nonactive and active console video games. Physical activity was assessed continuously using the Actigraph accelerometer. Significant (p < .001) increases from baseline were found for energy expenditure (129–400%), heart rate (43–84%), and activity counts (122–1,288 versus 0–23) when playing the active console video games. Playing active console video games over short periods of time is similar in intensity to light to moderate traditional physical activities such as walking, skipping, and jogging.