Predicting objective physical activity from self-report surveys: a model validation study using estimated generalized least-squares regression

Nicholas Beyler, Wayne Fuller, Sarah Nusser and Gregory Welk

Journal of Applied Statistics, 2015, vol. 42, issue 3, 555-565

Abstract: Physical activity measurements derived from self-report surveys are prone to measurement errors. Monitoring devices like accelerometers offer more objective measurements of physical activity, but are impractical for use in large-scale surveys. A model capable of predicting objective measurements of physical activity from self-reports would offer a practical alternative to obtaining measurements directly from monitoring devices. Using data from National Health and Nutrition Examination Survey 2003-2006, we developed and validated models for predicting objective physical activity from self-report variables and other demographic characteristics. The prediction intervals produced by the models were large, suggesting that the ability to predict objective physical activity for individuals from self-reports is limited.

Date: 2015
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DOI: 10.1080/02664763.2014.978271

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