PURPOSE: To compare the validity of various physical activity measures with doubly labeled water (DLW)-measured physical activity energy expenditure (PAEE) in free-living older adults. METHODS: Fifty-six adults aged ≥65 yr wore three activity monitors (New Lifestyles pedometer, ActiGraph accelerometer, and a SenseWear (SW) armband) during a 10-d free-living period and completed three different surveys (Yale Physical Activity Survey (YPAS), Community Health Activities Model Program for Seniors (CHAMPS), and a modified Physical Activity Scale for the Elderly (modPASE)). Total energy expenditure was measured using DLW, resting metabolic rate was measured with indirect calorimetry, the thermic effect of food was estimated, and from these, estimates of PAEE were calculated. The degree of linear association between the various measures and PAEE was assessed, as were differences in group PAEE, when estimable by a given measure. RESULTS: All three monitors were significantly correlated with PAEE (r=0.48-0.60, P<0.001). Of the questionnaires, only CHAMPS was significantly correlated with PAEE (r=0.28, P=0.04). Statistical comparison of the correlations suggested that the monitors were superior to YPAS and modPASE. Mean squared errors for all correlations were high, and the median PAEE from the different tools was significantly different from DLW for all but the YPAS and regression-estimated PAEE from the ActiGraph. CONCLUSIONS: Objective devices more appropriately rank PAEE than self-reported instruments in older adults, but absolute estimates of PAEE are not accurate. Given the cost differential and ease of use, pedometers seem most useful in this population when ranking by physical activity level is adequate.
PURPOSE: To compare the validity of various physical activity measures with doubly labeled water (DLW)-measured physical activity energy expenditure (PAEE) in free-living older adults. METHODS: Fifty-six adults aged ≥65 yr wore three activity monitors (New Lifestyles pedometer, ActiGraph accelerometer, and a SenseWear (SW) armband) during a 10-d free-living period and completed three different surveys (Yale Physical Activity Survey (YPAS), Community Health Activities Model Program for Seniors (CHAMPS), and a modified Physical Activity Scale for the Elderly (modPASE)). Total energy expenditure was measured using DLW, resting metabolic rate was measured with indirect calorimetry, the thermic effect of food was estimated, and from these, estimates of PAEE were calculated. The degree of linear association between the various measures and PAEE was assessed, as were differences in group PAEE, when estimable by a given measure. RESULTS: All three monitors were significantly correlated with PAEE (r=0.48-0.60, P<0.001). Of the questionnaires, only CHAMPS was significantly correlated with PAEE (r=0.28, P=0.04). Statistical comparison of the correlations suggested that the monitors were superior to YPAS and modPASE. Mean squared errors for all correlations were high, and the median PAEE from the different tools was significantly different from DLW for all but the YPAS and regression-estimated PAEE from the ActiGraph. CONCLUSIONS: Objective devices more appropriately rank PAEE than self-reported instruments in older adults, but absolute estimates of PAEE are not accurate. Given the cost differential and ease of use, pedometers seem most useful in this population when ranking by physical activity level is adequate.
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