AIM: To compare Actigraph-defined moderate-to-vigorous physical activity (MVPA) cutpoints among children, combining statistical and biobehavioural analyses. METHODS: One hundred and thirteen children aged 10.0 +/- 0.8 years wore accelerometer for three days. The time they spent in MVPA was estimated using 10 thresholds ranged from 3000 to 3900 cpm. A statistical construct including 45 Bland and Altman pairwise analyses was used to compare the 10 estimates of MVPA. A regression was performed to develop an equation relating mean differences to the between-cutpoint gaps. RESULTS: Mean differences in the MVPA estimates ranged from 1.6 to 12.8 min as a function of increment. Raw estimates of MVPA decreased according to an arithmetic sequence with a common difference of 200 cpm. This difference translates into a drop of 12% in MVPA and a misclassification of up to 5% of children. Mean differences (Y) could be predicted from increments (X) using: Y= 0.02 X (R(2)= 0.99, SEE = 0.72, p < 0.0001). CONCLUSION: When a lack of agreement should be assumed as the between-cutpoint gap exceeds 200 cpm, statistical differences may occur earlier at 90 cpm. Yet, the current equation makes it possible to compare and adjust results from studies/interventions using diverse cutpoints for MVPA among children.
AIM: To compare Actigraph-defined moderate-to-vigorous physical activity (MVPA) cutpoints among children, combining statistical and biobehavioural analyses. METHODS: One hundred and thirteen children aged 10.0 +/- 0.8 years wore accelerometer for three days. The time they spent in MVPA was estimated using 10 thresholds ranged from 3000 to 3900 cpm. A statistical construct including 45 Bland and Altman pairwise analyses was used to compare the 10 estimates of MVPA. A regression was performed to develop an equation relating mean differences to the between-cutpoint gaps. RESULTS: Mean differences in the MVPA estimates ranged from 1.6 to 12.8 min as a function of increment. Raw estimates of MVPA decreased according to an arithmetic sequence with a common difference of 200 cpm. This difference translates into a drop of 12% in MVPA and a misclassification of up to 5% of children. Mean differences (Y) could be predicted from increments (X) using: Y= 0.02 X (R(2)= 0.99, SEE = 0.72, p < 0.0001). CONCLUSION: When a lack of agreement should be assumed as the between-cutpoint gap exceeds 200 cpm, statistical differences may occur earlier at 90 cpm. Yet, the current equation makes it possible to compare and adjust results from studies/interventions using diverse cutpoints for MVPA among children.
Authors: Daniel B Bornstein; Michael W Beets; Wonwoo Byun; Greg Welk; Matteo Bottai; Marsha Dowda; Russell Pate Journal: J Sci Med Sport Date: 2011-04-27 Impact factor: 4.319
Authors: Justin B Moore; Michael W Beets; Keith Brazendale; Steven N Blair; Russell R Pate; Lars B Andersen; Sigmund A Anderssen; Anders Grøntved; Pedro C Hallal; Katarzyna Kordas; Susi Kriemler; John J Reilly; Luis B Sardinha Journal: Med Sci Sports Exerc Date: 2017-07 Impact factor: 5.411
Authors: Richard M Pulsford; Mario Cortina-Borja; Carly Rich; Florence-Emilie Kinnafick; Carol Dezateux; Lucy J Griffiths Journal: PLoS One Date: 2011-08-11 Impact factor: 3.240