title: Predicting energy expenditure from accelerometry counts in adolescent girls.
abstract: OBJECTIVE
  Calibration of accelerometer counts against oxygen consumption to predict energy expenditure has not been conducted in middle school girls. We concurrently assessed energy expenditure and accelerometer counts during physical activities on adolescent girls to develop an equation to predict energy expenditure.
  
  
  METHODS
  Seventy-four girls aged 13-14 yr performed 10 activities while wearing an Actigraph accelerometer and a portable metabolic measurement unit (Cosmed K4b2). The activities were resting, watching television, playing a computer game, sweeping, walking 2.5 and 3.5 mph, performing step aerobics, shooting a basketball, climbing stairs, and running 5 mph. Height and weight were also assessed. Mixed-model regression was used to develop an equation to predict energy expenditure (EE) (kJ.min(-1)) from accelerometer counts.
  
  
  RESULTS
  Age (mean [SD] = 14 yr [0.34]) and body-weight-adjusted correlations of accelerometer counts with EE (kJ.min(-1)) for individual activities ranged from -0.14 to 0.59. Higher intensity activities with vertical motion were best correlated. A regression model that explained 85% of the variance of EE was developed: [EE (kJ.min(-1)) = 7.6628 + 0.1462 [(Actigraph counts per minute - 3000)/100] + 0.2371 (body weight in kilograms) - 0.00216 [(Actigraph counts per minute - 3000)/100](2) + 0.004077 [((Actigraph counts per minute - 3000)/100) x (body weight in kilograms)]. The MCCC = 0.85, with a standard error of estimate = 5.61 kJ.min(-1).
  
  
  CONCLUSIONS
  We developed a prediction equation for kilojoules per minute of energy expenditure from Actigraph accelerometer counts. This equation may be most useful for predicting energy expenditure in groups of adolescent girls over a period of time that will include activities of broad-ranging intensity, and may be useful to intervention researchers interested in objective measures of physical activity.
authors.affiliation: Division of Epidemiology, University of Minnesota, 1300 South Second Street #300, Minneapolis, MN 55454, USA. schmitz@epi.umn.edu
authors.forename: Kathryn H
authors.initials: KH
authors.lastname: Schmitz
authors.forename: Margarita
authors.initials: M
authors.lastname: Treuth
authors.forename: Peter
authors.initials: P
authors.lastname: Hannan
authors.forename: Robert
authors.initials: R
authors.lastname: McMurray
authors.forename: Kimberly B
authors.initials: KB
authors.lastname: Ring
authors.forename: Diane
authors.initials: D
authors.lastname: Catellier
authors.forename: Russ
authors.initials: R
authors.lastname: Pate
mesh_terms: D000293:Adolescent; D002138:Calibration; D002245:Carbon Dioxide / Q000032:analysis; D004734:Energy Metabolism / Q000502:physiology*; D015444:Exercise / Q000502:physiology*; D005260:Female; D006339:Heart Rate; D006801:Humans; D010101:Oxygen Consumption; D011237:Predictive Value of Tests
chemical_list: D002245:Carbon Dioxide