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Calibration of the global physical activity questionnaire to Accelerometry measured physical activity and sedentary behavior
Journal article   Open access   Peer reviewed

Calibration of the global physical activity questionnaire to Accelerometry measured physical activity and sedentary behavior

Kristen M. Metcalf, Barbara I. Baquero, Mayra L. Coronado Garcia, Shelby L. Francis, Kathleen F. Janz, Helena H. Laroche and Daniel K. Sewell
BMC Public Health, Vol.18(1), 412
03/27/2018
DOI: 10.1186/s12889-018-5310-3
PMCID: PMC5870179
PMID: 29587694
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BMC-PublicHealth-2018.412745.97 kBDownloadView
Published (Version of record)CC BY V4.0 Open Access
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https://doi.org/10.1186/s12889-018-5310-3View
Published (Version of record)Metcalf et al. BMC Public Health (2018) 18:412

Abstract

Background Self-report questionnaires are a valuable method of physical activity measurement in public health research; however, accuracy is often lacking. The purpose of this study is to improve the validity of the Global Physical Activity Questionnaire by calibrating it to 7 days of accelerometer measured physical activity and sedentary behavior. Methods Participants (n = 108) wore an ActiGraph GT9X Link on their non-dominant wrist for 7 days. Following the accelerometer wear period, participants completed a telephone Global Physical Activity Questionnaire with a research assistant. Data were split into training and testing samples, and multivariable linear regression models built using functions of the GPAQ self-report data to predict ActiGraph measured physical activity and sedentary behavior. Models were evaluated with the testing sample and an independent validation sample (n = 120) using Mean Squared Prediction Errors. Results The prediction models utilized sedentary behavior, and moderate- and vigorous-intensity physical activity self-reported scores from the questionnaire, and participant age. Transformations of each variable, as well as break point analysis were considered. Prediction errors were reduced by 77.7–80.6% for sedentary behavior and 61.3–98.6% for physical activity by using the multivariable linear regression models over raw questionnaire scores. Conclusions This research demonstrates the utility of calibrating self-report questionnaire data to objective measures to improve estimates of physical activity and sedentary behavior. It provides an understanding of the divide between objective and subjective measures, and provides a means to utilize the two methods as a unified measure.
Measurement Sedentary behavior Calibration Physical activity Accelerometry Self-report OAfund

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