National youth sedentary behavior and physical activity daily patterns using latent class analysis applied to accelerometry

被引:14
|
作者
Evenson, Kelly R. [1 ]
Wen, Fang [2 ]
Hales, Derek [3 ]
Herring, Amy H. [4 ]
机构
[1] Univ N Carolina, Dept Epidemiol, Ctr Hlth Promot & Dis Prevent, Gillings Sch Global Publ Hlth, 137 East Franklin St,Suite 306, Chapel Hill, NC 27514 USA
[2] Univ N Carolina, Dept Epidemiol, Gillings Sch Global Publ Hlth, Chapel Hill, NC USA
[3] Univ N Carolina, Dept Nutr, Gillings Sch Global Publ Hlth, Chapel Hill, NC USA
[4] Univ N Carolina, Carolina Populat Ctr, Gillings Sch Global Publ Hlth, Dept Biostat, Chapel Hill, NC USA
关键词
Accelerometry; Children; Cluster analysis; Latent class analysis; Surveillance; ADOLESCENTS; CHILDREN;
D O I
10.1186/s12966-016-0382-x
中图分类号
R15 [营养卫生、食品卫生]; TS201 [基础科学];
学科分类号
100403 ;
摘要
Background: Applying latent class analysis (LCA) to accelerometry can help elucidated underlying patterns. This study described the patterns of accelerometer-determined sedentary behavior and physical activity among youth by applying LCA to a nationally representative United States (US) sample. Methods: Using 2003-2006 National Health and Nutrition Examination Survey data, 3998 youths 6-17 years wore an ActiGraph 7164 accelerometer for one week, providing > =3 days of wear for > =8 h/day from 6: 00 am-midnight. Cutpoints defined sedentary behavior (<100 counts/minute), light activity (100-2295 counts/minute), moderate to vigorous physical activity (MVPA; > = 2296 counts/minute), and vigorous activity (> = 4012 counts/minute). To account for wear time differences, outcomes were expressed as percent of day in a given intensity. LCA was used to classify daily (Monday through Sunday) patterns of average counts/minute, sedentary behavior, light activity, MVPA, and vigorous activity separately. The latent classes were explored overall and by age (6-11, 12-14, 15-17 years), gender, and whether or not youth attended school during measurement. Estimates were weighted to account for the sampling frame. Results: For average counts/minute/day, four classes emerged from least to most active: 40.9 % of population (mean 323.5 counts/minute/day), 40.3 % (559.6 counts/minute/day), 16.5 % (810.0 counts/minute/day), and 2.3 % (1132.9 counts/minute/day). For percent of sedentary behavior, four classes emerged: 13.5 % of population (mean 544.6 min/day), 30.1 % (455.1 min/day), 38.5 % (357.7 min/day), and 18.0 % (259.2 min/day). For percent of light activity, four classes emerged: 12.3 % of population (mean 222.6 min/day), 29.3 % (301.7 min/day), 41.8 % (384.0 min/day), and 16.6 % (455.5 min/day). For percent of MVPA, four classes emerged: 59.9 % of population (mean 25.0 min/day), 33.3 % (60.9 min/day), 3.1 % (89.0 min/day), and 3.6 % (109.3 min/day). For percent of vigorous activity, three classes emerged: 76.8 % of population (mean 7.1 min/day), 18.5 % (23.9 min/day), and 4.7 % (47.4 min/day). Classes were developed by age, gender, and school attendance since some patterns differed when stratifying by these factors. Conclusion: The models supported patterns for average intensity, sedentary behavior, light activity, MVPA, and vigorous activity. These latent class derived patterns can be used in other youth studies to explore correlates or outcomes and to target sedentary behavior or physical activity interventions.
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页数:14
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