Measurement Effects of Seasonal and Monthly Variability on Pedometer-Determined Data
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Background:
The seasonal and monthly variability of pedometer-determined physical activity and its effects on accurate measurement have not been examined. The purpose of the study was to reduce measurement error in step-count data by controlling a) the length of the measurement period and b) the season or month of the year in which sampling was conducted.
Methods:
Twenty-three middle-aged adults were instructed to wear a Yamax SW-200 pedometer over 365 consecutive days. The step-count measurement periods of various lengths (eg, 2, 3, 4, 5, 6, 7 days, etc.) were randomly selected 10 times for each season and month. To determine accurate estimates of yearly step-count measurement, mean absolute percentage error (MAPE) and bias were calculated. The year-round average was considered as a criterion measure. A smaller MAPE and bias represent a better estimate.
Results:
Differences in MAPE and bias among seasons were trivial; however, they varied among different months. The months in which seasonal changes occur presented the highest MAPE and bias.
Conclusions:
Targeting the data collection during certain months (eg, May) may reduce pedometer measurement error and provide more accurate estimates of year-round averages.
Kang is with the Dept of Health and Human Performance, Middle Tennessee State University, Murfreesboro, TN. Bassett is with the Dept of Exercise, Sport, and Leisure Studies, University of Tennessee, Knoxville, TN. Barreira is with the Physical Activity and Obesity Epidemiology Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA. Tudor-Locke is with the Walking Behavior Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA. Ainsworth with the School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ.
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