Sarah Kozey Keadle1, Eric J Shiroma2, Masamitsu Kamada3, Charles E Matthews4, Tamara B Harris2, I-Min Lee5. 1. Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland; Cancer Prevention Fellowship Program, Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland. Electronic address: skeadle@calpoly.edu. 2. Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute of Aging, Bethesda, Maryland. 3. Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts; National Institute of Health and Nutrition, Tokyo, Japan. 4. Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland. 5. Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Abstract
INTRODUCTION: Accelerometers are used increasingly in large epidemiologic studies, but, given logistic and cost constraints, most studies are restricted to a single, 7-day accelerometer monitoring period. It is unknown how well a 7-day accelerometer monitoring period estimates longer-term patterns of behavior, which is critical for interpreting, and potentially improving, disease risk estimates in etiologic studies. METHODS: A subset of participants from the Women's Health Study (N=209; mean age, 70.6 [SD=5.7] years) completed at least two 7-day accelerometer administrations (ActiGraph GT3X+) within a period of 2-3 years. Monitor output was translated into total counts, steps, and time spent in sedentary, light-intensity, and moderate to vigorous-intensity activity (MVPA) and bouted-MVPA (i.e., 10-minute bouts). For each metric, intraclass correlations (ICCs) and 95% CIs were calculated using linear-mixed models and adjusted for wear time, age, BMI, and season. The data were collected in 2011-2015 and analyzed in 2015-2016. RESULTS: The ICCs ranged from 0.67 (95% CI=0.60, 0.73) for bouted-MVPA to 0.82 (95% CI=0.77, 0.85) for total daily counts and were similar across age, BMI, and for less and more active women. For all metrics, classification accuracy within 1 quartile was >90%. CONCLUSIONS: These data provide reassurance that a 7-day accelerometer-assessment protocol provides a reproducible (and practical) measure of physical activity and sedentary time. However, ICCs varied by metric; therefore, future prospective studies of chronic diseases might benefit from existing methods to adjust risk estimates for within-person variability in activity to get a better estimate of the true strength of association.
INTRODUCTION: Accelerometers are used increasingly in large epidemiologic studies, but, given logistic and cost constraints, most studies are restricted to a single, 7-day accelerometer monitoring period. It is unknown how well a 7-day accelerometer monitoring period estimates longer-term patterns of behavior, which is critical for interpreting, and potentially improving, disease risk estimates in etiologic studies. METHODS: A subset of participants from the Women's Health Study (N=209; mean age, 70.6 [SD=5.7] years) completed at least two 7-day accelerometer administrations (ActiGraph GT3X+) within a period of 2-3 years. Monitor output was translated into total counts, steps, and time spent in sedentary, light-intensity, and moderate to vigorous-intensity activity (MVPA) and bouted-MVPA (i.e., 10-minute bouts). For each metric, intraclass correlations (ICCs) and 95% CIs were calculated using linear-mixed models and adjusted for wear time, age, BMI, and season. The data were collected in 2011-2015 and analyzed in 2015-2016. RESULTS: The ICCs ranged from 0.67 (95% CI=0.60, 0.73) for bouted-MVPA to 0.82 (95% CI=0.77, 0.85) for total daily counts and were similar across age, BMI, and for less and more active women. For all metrics, classification accuracy within 1 quartile was >90%. CONCLUSIONS: These data provide reassurance that a 7-day accelerometer-assessment protocol provides a reproducible (and practical) measure of physical activity and sedentary time. However, ICCs varied by metric; therefore, future prospective studies of chronic diseases might benefit from existing methods to adjust risk estimates for within-person variability in activity to get a better estimate of the true strength of association.
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