Moore Justin B, Beets Michael W, Brazendale Keith, Blair Steven N, Pate Russell R, Andersen Lars B, Anderssen Sigmund A, Grøntved Anders, Hallal Pedro C, Kordas Katarzyna, Kriemler Susi, Reilly John J, Sardinha Luis B
1Department of Family and Community Medicine, Wake Forest School of Medicine, Winston-Salem, NC; 2Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC; 3Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC; 4Department of Sport Science and Clinical Biomechanics, University of Southern Denmark, Odense, DENMARK; 5Department of Sport Medicine, Norwegian School of Sport Science, Oslo, NORWAY; 6Federal University of Pelotas, Pelotas, BRAZIL; 7School of Social and Community Medicine, University of Bristol, Bristol, UNITED KINGDOM; 8Epidemiology, Biostatistics and Public Health Institute, University of Zürich, Zürich, SWITZERLAND; 9Physical Activity for Health Group, School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UNITED KINGDOM; and 10Exercise and Health Laboratory, CIPER, Faculty of Human Kinetics, University of Lisbon, Cruz-Quebrada, PORTUGAL.
Med Sci Sports Exerc. 2017 Jul;49(7):1366-1374. doi: 10.1249/MSS.0000000000001249.
Physical activity (PA) conveys known cardiometabolic benefits to youth, but the contribution of vigorous-intensity PA (VPA) to these benefits is unknown. Therefore, we sought to determine (a) the associations between VPA and cardiometabolic biomarkers independent of moderate-intensity PA (MPA) and time sedentary and (b) the accelerometer cut point that best represents the threshold for health-promoting VPA in youth.
Data from the International Children's Accelerometry Database (ICAD) were analyzed in 2015. The relationship between cardiometabolic biomarkers and four categories of VPA estimated via three sets of cut points were examined using isotemporal substitution quantile regression modeling at the 10th, 25th, 50th, 75th, and 90th percentile of the distribution of each biomarker, separately. Age, sex, accelerometer wear time, sedentary time, and MPA were controlled for while allowing substitution for light-intensity PA. Data from 11,588 youth (4-18 yr) from 11 ICAD studies (collected 1998-2009) were analyzed.
Only 32 of 360 significant associations were observed. Significant, negative relationships were observed for VPA with waist circumference and insulin. Replacing light-intensity PA with VPA (corresponding to at the 25th to 90th percentiles of VPA) was associated with 0.67 (-1.33 to -0.01; P = 0.048) to 7.30 cm (-11.01 to -3.58; P < 0.001) lower waist circumference using Evenson and ICAD cut points (i.e., higher counts per minute). VPA levels were associated with 12.60 (-21.28 to -3.92; P = 0.004) to 27.03 pmol·L (-45.03 to -9.03; P = 0.003) lower insulin levels at the 75th to 90th percentiles using Evenson and ICAD cut points when substituted for light PA.
Substituting light PA with VPA was inversely associated with waist circumference and insulin. However, VPA was inconsistently related to the remaining biomarkers after controlling for time sedentary and MPA.
体育活动（PA）对青少年具有已知的心脏代谢益处，但高强度体育活动（VPA）对这些益处的贡献尚不清楚。因此，我们试图确定（a）VPA与心脏代谢生物标志物之间的关联，独立于中等强度体育活动（MPA）和久坐时间；（b）最能代表青少年促进健康的VPA阈值的加速度计切点。
2015年对国际儿童加速度计数据库（ICAD）的数据进行了分析。使用等时替代分位数回归模型，分别在每个生物标志物分布的第10、25、50、75和90百分位数处，研究心脏代谢生物标志物与通过三组切点估计的四类VPA之间的关系。在允许替代低强度体育活动的同时，对年龄、性别、加速度计佩戴时间、久坐时间和MPA进行了控制。分析了来自11项ICAD研究（1998 - 2009年收集）的11588名青少年（4 - 18岁）的数据。
在360个显著关联中仅观察到32个。观察到VPA与腰围和胰岛素之间存在显著的负相关关系。使用埃文森和ICAD切点（即每分钟更高的计数），用VPA替代低强度体育活动（对应于VPA的第25至90百分位数）与腰围降低0.67（-1.33至-0.01；P = 0.048）至7.30厘米（-11.01至-3.58；P < 0.001）相关。当用VPA替代低强度体育活动时，在第75至90百分位数处，使用埃文森和ICAD切点，VPA水平与胰岛素水平降低12.60（-21.28至-3.92；P = 0.004）至27.03 pmol·L（-45.03至-9.03；P = 0.003）相关。
用VPA替代低强度体育活动与腰围和胰岛素呈负相关。然而，在控制久坐时间和MPA后，VPA与其余生物标志物的关系并不一致。
