Radim Jurca, Michael J. LaMonte and J. Larry Durstine
Steven P. Hooker, Anna Feeney, Brent Hutto, Karin A. Pfeiffer, Kerry McIver, Daniel P. Heil, John E. Vena, Michael J. LaMonte and Steven N. Blair
This study was designed to validate the Actical activity monitor in middle-aged and older adults of varying body composition to develop accelerometer thresholds to distinguish between light and moderate intensity physical activity (PA).
Nonobese 45 to 64 yr (N = 29), obese 45 to 64 yr (N = 21), and ≥65 yr (N = 23; varying body composition) participants completed laboratory-based sitting, household, and locomotive activities while wearing an Actical monitor and a portable metabolic measurement system. Nonlinear regression analysis was used to identify activity count (AC) cut-points to differentiate between light intensity (<3 METs) and moderate intensity (≥3METs) PA.
Using group-specific algorithms, AC cut points for 3 METs were 1634, 1107, and 431 for the obese 45 to 64 yr group, nonobese 45 to 64 yr group, and ≥65 yr group, respectively. However, sensitivity and specificity analysis revealed that an AC cut-point of 1065 yielded similar accuracy for detecting an activity as less than or greater than 3 METs, regardless of age and body composition.
For the Actical activity monitor, an AC cut-point of 1065 can be used to determine light and moderate intensity PA in people ≥45 years of age.
Michael J. LaMonte, I-Min Lee, Eileen Rillamas-Sun, John Bellettiere, Kelly R. Evenson, David M. Buchner, Chongzhi Di, Cora E. Lewis, Dori E. Rosenberg, Marcia L. Stefanick and Andrea Z. LaCroix
Background: Limited data are available regarding the correlation between questionnaire and device-measured physical activity (PA) and sedentary behavior (SB) in older women. Methods: We evaluated these correlations in 5,992 women, aged 63 and older, who completed the Women’s Health Initiative (WHI) and Community Healthy Activities Model Program for Seniors (CHAMPS) PA questionnaires and the CARDIA SB questionnaire prior to wearing a hip-worn accelerometer for 7 consecutive days. Accelerometer-measured total, light, and moderate-to-vigorous PA (MVPA), and total SB time were defined according to cutpoints established in a calibration study. Spearman coefficients were used to evaluate correlations between questionnaire and device measures. Results: Mean time spent in PA and SB was lower for questionnaire than accelerometer measures, with variation in means according to age, race/ethnicity, body mass index, and functional status. Overall, correlations between questionnaires and accelerometer measures were moderate for total PA, MVPA, and SB (r ≈ 0.20–0.40). Light intensity PA correlated weakly for WHI (r ≈ 0.01–0.06) and was variable for CHAMPS (r ≈ 0.07–0.22). Conclusion: Questionnaire and accelerometer estimates of total PA, MVPA, and SB have at best moderate correlations in older women and should not be assumed to be measuring the same behaviors or quantity of behavior. Light intensity PA is poorly measured by questionnaire. Because light intensity activities account for the largest proportion of daily activity time in older adults, and likely contribute to its health benefits, further research should investigate how to improve measurement of light intensity PA by questionnaires.