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Trever J. Ball, Elizabeth A. Joy, Lisa H. Gren, Ruthann Cunningham and Janet M. Shaw


Few have examined predictive relationships between physical activity (PA) and health using electronic health records (EHRs) of patient-reported PA.


Assess initial predictive validity of the Physical Activity “Vital Sign” (PAVS) recorded in EHRs with BMI and disease burden.


EHRs were from November 2011 to November 2013 (n = 34,712). Differences in not meeting Physical Activity Guidelines (PAG) were tested using chi-square analysis between being normal weight versus overweight/obese, and scoring below versus above the 50th percentile of the Charlson Comorbidity Index (CCI). Repeated measures logistic regression was used to determine odds of BMI and CCI classifications according to responses to the PAVS as not meeting PAG.


Patients who did not meet PAG according to the PAVS were more likely than normal weight patients to have a higher BMI (BMI 25.0–29.9, OR = 1.19, P = .001; BMI 30.0–34.9, OR = 1.39, P < .0001; BMI 35.0–39.9, OR = 2.42, P < .0001; BMI ≥ 40, OR = 3.7, P < .0001) and also higher disease burden (above 50th percentile for CCI, OR = 1.8, P < .0001).


The strong association of the PAVS found with patient BMI and moderately-strong association with disease burden supports initial predictive validity of the PAVS recorded in EHRs. PA recorded in EHRs may be vastly useful for assessing patient disease and cost burdens attributed independently to PA behavior.

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Janice O’Connor, Elizabeth J. Ball, Kate S. Steinbeck, Peter S.W. Davies, Connie Wishart, Kevin J. Gaskin and Louise A. Baur

The aim of this study of 56 children aged 6-9 years was to identify measures of physical activity that could be used in either clinical or population studies. Comparisons were made between four measures of physical activity: a three day parent-reported activity diary, a parent-reported physical activity questionnaire, the Tritrac-R3D™ accelerometer (worn three days) and physical activity energy expenditure calculated over 10 days by the doubly labeled water (DLW) technique. The strongest correlation between methods was for the diary and Tritrac-R3D™ during the two hour after-school period (1530-1730 hours) (r = 0.75, P < 0.0001). Activity level in this after-school period was positively correlated with average activity level over three days for both Tritrac-R3D™ (r = 0.53, P < 0.01) and diary (r = 0.54, P < 0.0001). No associations were found between measures of activity from DLW and activity measures from the Tritrac-R3D™, diary or questionnaire. These results suggest that the two hour after-school period is of high interest for future population studies of physical activity in school-age children.