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Measurement effects of seasonal and monthly variability on pedometer-determined data
Minsoo Kang1, David R Bassett, Tiago V Barreira
1Dept of Health and Human Performance, Middle Tennessee State University, Murfreesboro, TN, USA.
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.
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