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24 – Seasonal Adjustment at Statistical Agencies
Measurement Error Properties in an Accelerometer Sample of U.S. Elementary School Children
Nicholas Beyler
Mathematica Policy Research
Susanne James-Burdumy
Mathematica Policy Research
Martha Bleeker
Mathematica Policy Research
Jane Fortson
Mathematica Policy Research
Max Benjamin
Mathema
Measurement error modeling approaches have been used extensively in nutrition studies to estimate distributions of usual dietary intakes by accounting for and adjusting for day-to-day variability and measurement errors in observed intakes. Similar procedures have recently been developed for studies of physical activity and energy expenditure, but applications usually focus on study data obtained from adult populations. In this paper, we use measurement error modeling procedures to estimate the distributions of usual physical activity and the sources of variation in physical activity data collected via accelerometers from a sample of 4th- and 5th-grade U. S. students. The students were part of the Randomized Experiment of Playworks study. We found that most of the variability in the physical activity data was due to intra-individual (day-to-day) variations in measured activity. Conversely, in studies of adult populations, the majority of variability in physical activity was inter-individual variability; intra-individual sources of variations in activity were fairly minimal. Adjustments for measurement errors and other sources of intra-individual variations should be made when estimating usual physical activity outcomes, especially in populations of children.