Laura K Callender1, Michael M Borghese1, Ian Janssen2. 1. School of Kinesiology and Health Studies, Queen's University, Kingston, ON K7L 3N6, Canada. 2. School of Kinesiology and Health Studies, Queen's University, Kingston, ON K7L 3N6, Canada; Department of Public Health Sciences, Queen's University, Kingston, ON K7L 3N6, Canada. Electronic address: ian.janssen@queensu.ca.
Abstract
PURPOSE: The purpose of this study was to determine which intensities, patterns, and types of 24-h movement behaviors are most strongly associated with cardiometabolic risk factors among children. METHODS: A total of 369 children aged 10-13 years were studied. Participants wore an Actical accelerometer and a Garmin Forerunner 220 Global Positioning System logger and completed an activity and sleep log for 7 days. Data from these instruments were combined to estimate average minute per day spent in 14 intensities, 11 types, and 14 patterns of movement. Body mass index, resting heart rate, and systolic blood pressure values were combined to create a cardiometabolic risk factor score. Partial least squares regression analysis was used to examine associations between the 39 movement behavior characteristics and the cardiometabolic risk factor score. The variable importance in projection (VIP) values were used to determine and rank important movement behavior characteristics. There was evidence of interaction by biological maturity, and the analyses were conducted separately in the 50% least mature and 50% most mature participants. RESULTS: For the least biologically mature participants, fifteen of the 39 movement behavior characteristics had important VIP value scores; eight of these reflected movement intensities (particularly moderate and vigorous intensities), six reflected movement patterns, and one reflected a movement type. For the most mature participants, thirteen of the 39 movement behavior characteristics had important VIP value scores, with five reflecting intensities (particularly moderate and vigorous intensities), five reflecting patterns, and three reflecting types of movement. CONCLUSION: More than 12 movement behavior characteristics were associated with cardiometabolic risk factors within both the most and least mature participants. Movement intensities within the moderate and vigorous intensity ranges were the most consistent correlates of these risk factors.
PURPOSE: The purpose of this study was to determine which intensities, patterns, and types of 24-h movement behaviors are most strongly associated with cardiometabolic risk factors among children. METHODS: A total of 369 children aged 10-13 years were studied. Participants wore an Actical accelerometer and a Garmin Forerunner 220 Global Positioning System logger and completed an activity and sleep log for 7 days. Data from these instruments were combined to estimate average minute per day spent in 14 intensities, 11 types, and 14 patterns of movement. Body mass index, resting heart rate, and systolic blood pressure values were combined to create a cardiometabolic risk factor score. Partial least squares regression analysis was used to examine associations between the 39 movement behavior characteristics and the cardiometabolic risk factor score. The variable importance in projection (VIP) values were used to determine and rank important movement behavior characteristics. There was evidence of interaction by biological maturity, and the analyses were conducted separately in the 50% least mature and 50% most mature participants. RESULTS: For the least biologically mature participants, fifteen of the 39 movement behavior characteristics had important VIP value scores; eight of these reflected movement intensities (particularly moderate and vigorous intensities), six reflected movement patterns, and one reflected a movement type. For the most mature participants, thirteen of the 39 movement behavior characteristics had important VIP value scores, with five reflecting intensities (particularly moderate and vigorous intensities), five reflecting patterns, and three reflecting types of movement. CONCLUSION: More than 12 movement behavior characteristics were associated with cardiometabolic risk factors within both the most and least mature participants. Movement intensities within the moderate and vigorous intensity ranges were the most consistent correlates of these risk factors.
Authors: Tianyou Guo; Zhihao Zhang; Alyx Taylor; Daniel L Hall; Albert S Yeung; Arthur F Kramer; Liye Zou Journal: Front Psychiatry Date: 2022-08-15 Impact factor: 5.435