PURPOSE: The present study estimated the long-term reproducibility of accelerometer-based measures over 6 months in adults and the implications for statistical power, and attenuation in regression coefficients for future activity-disease studies. METHODS: We used data from 914 adults in the Interactive Diet and Activity Tracking in AARP study. Participants wore an activPAL 3 (AP) and an ActiGraph GT3X (AG) twice, 6 months apart. AP measures included time spent sitting or lying, standing, and stepping, whereas AG measures included time spent in sedentary, light, and moderate-to-vigorous physical activity (PA). Reproducibility of each metric and implications for epidemiological studies were determined based on intraclass correlation coefficients (ICC; 95% confidence interval). RESULTS: The ICC values for AP estimates were 0.58 (95% confidence interval, 0.53-0.63) for sitting, 0.62 (0.57-0.67) for standing, and 0.57 (0.51-0.62) for stepping. The ICC values for AG were 0.56 (0.50-0.61) for sedentary, 0.54 (0.49-0.60) for light PA, and 0.58 (0.52-0.63) for moderate-to-vigorous PA. Modeling showed that increasing the number of replicate administrations to two or three resulted in the most noticeable increases in ICC values, statistical power, and reductions in attenuation coefficients. For example, administering the AP twice reduced within-subject variability by half and resulted in an increase in the ICC associated with sitting time from 0.58 to 0.74. Similar comparisons for AG and measure of sedentary time resulted in an increase in ICC values from 0.56 to 0.72. Increasing the number of replicate administrations from one to two reduced the attenuation in activity-outcome associations from 40% to 25%. CONCLUSION: Accelerometer-based classifications of activity are moderately stable over time, but there is considerable within-subject variability that needs to be considered when estimating usual activity in future studies.
PURPOSE: The present study estimated the long-term reproducibility of accelerometer-based measures over 6 months in adults and the implications for statistical power, and attenuation in regression coefficients for future activity-disease studies. METHODS: We used data from 914 adults in the Interactive Diet and Activity Tracking in AARP study. Participants wore an activPAL 3 (AP) and an ActiGraph GT3X (AG) twice, 6 months apart. AP measures included time spent sitting or lying, standing, and stepping, whereas AG measures included time spent in sedentary, light, and moderate-to-vigorous physical activity (PA). Reproducibility of each metric and implications for epidemiological studies were determined based on intraclass correlation coefficients (ICC; 95% confidence interval). RESULTS: The ICC values for AP estimates were 0.58 (95% confidence interval, 0.53-0.63) for sitting, 0.62 (0.57-0.67) for standing, and 0.57 (0.51-0.62) for stepping. The ICC values for AG were 0.56 (0.50-0.61) for sedentary, 0.54 (0.49-0.60) for light PA, and 0.58 (0.52-0.63) for moderate-to-vigorous PA. Modeling showed that increasing the number of replicate administrations to two or three resulted in the most noticeable increases in ICC values, statistical power, and reductions in attenuation coefficients. For example, administering the AP twice reduced within-subject variability by half and resulted in an increase in the ICC associated with sitting time from 0.58 to 0.74. Similar comparisons for AG and measure of sedentary time resulted in an increase in ICC values from 0.56 to 0.72. Increasing the number of replicate administrations from one to two reduced the attenuation in activity-outcome associations from 40% to 25%. CONCLUSION: Accelerometer-based classifications of activity are moderately stable over time, but there is considerable within-subject variability that needs to be considered when estimating usual activity in future studies.
Authors: Pamela L Horn-Ross; Valerie S Lee; Christine N Collins; Susan L Stewart; Alison J Canchola; Marion M Lee; Peggy Reynolds; Christina A Clarke; Leslie Bernstein; Daniel O Stram Journal: Cancer Causes Control Date: 2008-02-07 Impact factor: 2.506
Authors: Sarah Kozey Keadle; Eric J Shiroma; Masamitsu Kamada; Charles E Matthews; Tamara B Harris; I-Min Lee Journal: Am J Prev Med Date: 2017-01-03 Impact factor: 5.043
Authors: Benjamin T Schumacher; John Bellettiere; Michael J LaMonte; Kelly R Evenson; Chongzhi Di; I-Min Lee; David A Sleet; Charles B Eaton; Cora E Lewis; Karen L Margolis; Lesley F Tinker; Andrea Z LaCroix Journal: J Aging Phys Act Date: 2021-10-09 Impact factor: 2.109
Authors: Pedro F Saint-Maurice; Richard P Troiano; David R Bassett; Barry I Graubard; Susan A Carlson; Eric J Shiroma; Janet E Fulton; Charles E Matthews Journal: JAMA Date: 2020-03-24 Impact factor: 56.272
Authors: Charles E Matthews; Richard P Troiano; Elizabeth A Salerno; David Berrigan; Shreya B Patel; Eric J Shiroma; Pedro F Saint-Maurice Journal: Med Sci Sports Exerc Date: 2020-12
Authors: David Berrigan; Ailing Liu; Britni R Belcher; Ann Chao; Liwen Fang; Charles E Matthews; Baohua Wang; Linhong Wang; Ning Wang; Yu Wang; Lichen Yang; Martha S Linet; Nancy Potischman Journal: Int J Environ Res Public Health Date: 2020-08-26 Impact factor: 4.614
Authors: Guo-Chong Chen; Qibin Qi; Simin Hua; Jee-Young Moon; Nicole L Spartano; Ramachandran S Vasan; Daniela Sotres-Alvarez; Sheila F Castaneda; Kelly R Evenson; Krista M Perreira; Linda C Gallo; Amber Pirzada; Keith M Diaz; Martha L Daviglus; Marc D Gellman; Robert C Kaplan; Xiaonan Xue; Yasmin Mossavar-Rahmani Journal: Am J Clin Nutr Date: 2020-11-11 Impact factor: 7.045
Authors: Asier Mañas; Borja Del Pozo Cruz; Ulf Ekelund; José Losa Reyna; Irene Rodríguez Gómez; José Antonio Carnicero Carreño; Leocadio Rodríguez Mañas; Francisco J García García; Ignacio Ara Journal: J Sport Health Sci Date: 2021-05-23 Impact factor: 13.077