No abstract

Modeling measurement error in recall data can be used to provide more accurate estimates of long-term activity behavior.

BackgroundThe utility of self-report measures of physical activity (PA) in youth can be greatly enhanced by calibrating self-report output against objectively measured PA data.This study demonstrates the potential of calibrating self-report output against objectively measured physical activity (PA) in youth by using a commonly used self-report tool called the Physical Activity Questionnaire (PAQ).MethodsA total of 148 participants (grades 4 through 12) from 9 schools (during the 2009–2010 school year) wore an Actigraph accelerometer for 7 days and then completed the PAQ. Multiple linear regression modeling was used on 70% of the available sample to develop a calibration equation and this was cross validated on an independent sample of participants (30% of sample).ResultsA calibration model with age, gender, and PAQ scores explained 40% of the variance in values for the percentage of time in moderate-to-vigorous PA (%MVPA) measured from the accelerometers (%MVPA = 14.56 - (sex*0.98) - (0.84*age) + (1.01*PAQ)). When tested on an independent, hold-out sample, the model estimated %MVPA values that were highly correlated with the recorded accelerometer values (r = .63) and there was no significant difference between the estimated and recorded activity values (mean diff. = 25.3 ± 18.1 min; p = .17).ConclusionsThese results suggest that the calibrated PAQ may be a valid alternative tool to activity monitoring instruments for estimating %MVPA in groups of youth.

Individuals who do not meet the PA guidelines exhibited greater odds of having metabolic syndrome. This relationship tended to be stronger for objective PA measures than for self-report.

The results of this study support the overall utility of the 24PAR for group-level estimates of daily EE and MVPA.