Defining accelerometer thresholds for activity intensities in adolescent girls
Treuth, M.S.; Schmitz, K.; Catellier, D.J.; McMurray, R.G.; Murray, D.M.; Almeida, M.Joao.; Going, S.; Norman, J.E.; Pate, R.
Medicine and Science in Sports and Exercise 36(7): 1259-1266
2004
ISSN/ISBN: 0195-9131 PMID: 15235335 Document Number: 574891
Purpose: To derive a regression equation that estimates metabolic equivalent (MET) from accelerometer counts, and to define thresholds of accelerometer counts that can be used to delineate sedentary, light, moderate, and vigorous activity in adolescent girls. Methods: Seventy-four healthy 8th grade girls, age 13-14 yr, were recruited from urban areas of Baltimore, MD, Minneapolis/St. Paul, MN, and Columbia, SC, to participate in the study. Accelerometer and oxygen consumption (VO2) data for 10 activities that varied in intensity from sedentary (e.g., TV watching) to vigorous (e.g., running) were collected. While performing these activities, the girls wore two accelerometers, a heart rate monitor and a Cosmed K4b2 portable metabolic unit for measurement of VO2. A random-coefficients model was used to estimate the relationship between accelerometer counts and VO2. Activity thresholds were defined by minimizing the false positive and false negative classifications. Results: The activities provided a wide range in VO2 (3-36 mLcntdotkg-1cntdotmin-1) with a correspondingly wide range in accelerometer counts (1-3928 countscntdot30 s-1). The regression line for MET score versus counts was MET = 2.01 + 0.00171 (countscntdot30 s-1) (mixed model R2 = 0.84, SEE = 1.36). A threshold of 1500 countscntdot30 s-1 defined the lower end of the moderate intensity (apprx4.6 METs) range of physical activity. That cutpoint distinguished between slow and brisk walking, and gave the lowest number of false positive and false negative classifications. The threshold ranges for sedentary, light, moderate, and vigorous physical activity were found to be 0-50, 51-1499, 1500-2600, and >2600 countscntdot30 s-1, respectively. Conclusion: The developed equation and these activity thresholds can be used for prediction of MET score from accelerometer counts and participation in various intensities of physical activity in adolescent girls.