A closer look at the relationship among accelerometer-based physical activity metrics: ICAD pooled data.
Andersen, Lars Bo
Page, Angie S
Puder, Jardena J
Reilly, John J
Janz, Kathleen F
The international journal of behavioral nutrition and physical activity
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Kwon, S., Andersen, L. B., Grøntved, A., Kolle, E., Cardon, G., Davey, R., Kriemler, S., et al. (2019). A closer look at the relationship among accelerometer-based physical activity metrics: ICAD pooled data.. The international journal of behavioral nutrition and physical activity, 16 (1), 40. https://doi.org/10.1186/s12966-019-0801-x
ABSTRACT Background: Accelerometers are widely used to assess child physical activity (PA) levels. Using the accelerometer data, several PA metrics can be estimated. Knowledge about the relationships between these different metrics can improve our understanding of children’s PA behavioral patterns. It also has significant implications for comparing PA metrics across studies and fitting a statistical model to examine their health effects. The aim of this study was to examine the relationships among the metrics derived from accelerometers in children. Methods: Accelerometer data from 24,316 children aged 5 to 18 years were extracted from the International Children’s Accelerometer Database (ICAD) 2.0. Correlation coefficients between wear time, sedentary behavior (SB), light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA), moderate- and vigorous-intensity PA (MVPA), and total activity counts (TAC) were calculated. Results: TAC was approximately 22X103 counts higher (p<0.01) with longer wear time (13 to 18 hours/day) as compared to shorter wear time (8 to <13 hours/day), while MVPA was similar across the wear time categories. MVPA was very highly correlated with TAC (r=.91; 99% CI=.91 to .91). Wear time-adjusted correlation between SB and LPA was also very high (r=-.96; 99% CI=-.96, -95). VPA was moderately correlated with MPA (r=.58; 99% CI=.57, .59). Conclusions: TAC is mostly explained by MVPA, while it could be more dependent on wear time, compared to MVPA. MVPA appears to be comparable across different wear durations and studies when wear time is ≥8 hours/day. Due to the moderate to high correlation between some PA metrics, potential collinearity should be addressed when including multiple PA metrics together in statistical modeling. Keywords. ICAD, Children, adolescents, ActiGraph, total activity counts, sedentary, physical activity measurement.
ICAD Collaborators, Humans, Exercise, Models, Statistical, Human Activities, Databases, Factual, Adolescent, Child, Child, Preschool, Accelerometry, Fitness Trackers, Sedentary Behavior
The pooling of the data was funded through a grant from the National Prevention Research Initiative (Grant Number: G0701877) (http://www.mrc.ac.uk/research/initiatives/national-prevention-research-initiative-npri/). The funding partners relevant to this award are: British Heart Foundation; Cancer Research UK; Department of Health; Diabetes UK; Economic and Social Research Council; Medical Research Council; Research and Development Office for the Northern Ireland Health and Social Services; Chief Scientist Office; Scottish Executive Health Department; The Stroke Association; Welsh Assembly Government and World Cancer Research Fund. This work was additionally supported by the Medical Research Council [MC_UU_12015/3; MC_UU_12015/7], The Research Council of Norway (249932/F20), Bristol University, Loughborough University and Norwegian School of Sport Sciences.
Medical Research Council (G0701877)
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External DOI: https://doi.org/10.1186/s12966-019-0801-x
This record's URL: https://www.repository.cam.ac.uk/handle/1810/292335
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Licence URL: https://creativecommons.org/licenses/by/4.0/