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The purpose of this study was to explore the current levels of physical activity among youth with disabilities using meta-analysis. The search identified 11 publications including 729 participants (age 4–20 yr). The overall effect size for 11 studies was Hedges g = 0.60 (SE = 0.18, 95% confidence interval [CI] [0.24, 0.96], p < .05, k = 11) using a random-effects model. The findings suggest that differences in physical activity levels between youth with and without disabilities are complex. Results indicated that youth without disabilities engaged in higher levels of physical activity of moderate to vigorous intensity (g = 0.66, SE = 0.18, p < .05). However, no differences were found in light-intensity physical activity (g = −0.03, SE = 0.16, p > .85). Results also suggested that the differences in physical activity between youth with and without disabilities were affected by age (<12 yr, g = 0.83, SE = 0.24, 95% CI [0.37, 1.29], p < .05, and >13 yr, g = 0.37, SE = 0.10, 95% CI [0.18, 0.57], p < .05; Q value = 3.20, df = 1, p < .05), with children with disabilities engaging in less physical activity than children without disabilities in younger ages. Differences in physical activity level between youth with and without disabilities are functions of intensity of physical activity and age but may not be of type of disability (Q value = 0.22, df = 1, p > .6).

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Background Using uniaxial accelerometry approach in measuring physical activity levels of individuals with Down syndrome (DS) might underestimate their energy expenditure due to the unique mediolateral walking pattern. Therefore, the purpose of this study was to examine and compare the relationship between two types of accelerometer outputs, uniaxial and triaxial, and energy expenditure in individuals with and without DS. Methods Eighteen participants with DS and 19 participants without DS wore a GT3X+ accelerometer and a portable metabolic system in three different walking conditions. Results Correlations between _ VO 2 and each of the two accelerometer outputs (uniaxial: r = 0.75, triaxial: r = 0.75) were not significantly different among individuals without DS (z = 0.14, P = 0.89); however, significant differences in the relationship between _ VO 2 and accelerometer outputs (uniaxial: r = 0.53, triaxial: r = 0.64) were observed among individuals with DS (z = À1.72, P < 0.046). Conclusions The findings suggest that when using accelerometers to measure physical activity levels for individuals with DS, triaxial outputs may better predict physical activity levels.

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