Assessing Volume of Accelerometry Data for Reliability in Preschool Children

HINKLEY, TRINA1,2; O’CONNELL, EOIN2; OKELY, ANTHONY D.1; CRAWFORD, DAVID2; HESKETH, KYLIE2; SALMON, JO2

Medicine & Science in Sports & Exercise:
doi: 10.1249/MSS.0b013e3182661478
Applied Sciences
Abstract

Purpose: This study examines what volume of accelerometry data (h·d−1) is required to reliably estimate preschool children’s physical activity and whether it is necessary to include weekday and weekend data.

Methods: Accelerometry data from 493 to 799 (depending on wear time) preschool children from the Melbourne-based Healthy Active Preschool Years study were used. The percentage of wear time each child spent in total (light–vigorous) physical activity was the main outcome. Hourly increments of daily data were analyzed. t-tests, controlling for age and clustering by center of recruitment, assessed the differences between weekday and weekend physical activity. Intraclass correlation coefficients estimated reliability for an individual day. Spearman–Brown prophecy formula estimated the number of days required to reach reliability estimates of 0.7, 0.8, and 0.9.

Results: The children spent a significantly greater percentage of time being physically active on weekend compared with weekdays regardless of the minimum number of hours included (t = 12.49–16.76, P < 0.001 for all). The number of days required to reach each of the predetermined reliability estimates increased as the number of hours of data per day decreased. For instance, 2.7–2.8 d of data were required to reach a reliability estimate of 0.7 with 10 or more hours of data per day; 3.3–3.4 d were required to meet the same reliability estimate for days with 7 h of data.

Conclusions: Future studies should ensure they include the minimum amount of data (hours per day and number of days) as identified in this study to meet at least a 0.7 reliability level and should report the level of reliability for their study. In addition to weekdays, at least one weekend day should be included in analyses to reliably estimate physical activity levels for preschool children.

Author Information

1Interdisciplinary Educational Research Institute, University of Wollongong, Wollongong, New South Wales, AUSTRALIA; and 2Center for Physical Activity and Nutrition Research, Deakin University, Burwood, Victoria, AUSTRALIA

Address for correspondence: Trina Hinkley, Ph.D., Center for Physical Activity and Nutrition Research, Deakin University, 221 Burwood Hwy, Burwood, Victoria 3125, Australia; E-mail: trina.hinkley@deakin.edu.au.

Submitted for publication February 2012.

Accepted for publication June 2012.

©2012The American College of Sports Medicine