Relationship between 24-hour movement behavior and obesity indicators in children and adolescents
-
摘要:
目的 采用成分数据分析法探讨儿童青少年24 h活动行为与肥胖指标间的关联并探究活动行为间等时替代后指标产生的定量变化,为儿童青少年预防肥胖提供具体的活动行为建议。 方法 2021年6月在山西省太原市1所小学和1所中学按照随机整群抽样方法,从8个班级中选取231名学生。采用ActiGraph GT3X+加速度计测试学生24 h活动行为,采用Inbody J20身体成分分析仪,通过生物电阻抗法(BIA)测试身体成分。使用成分多元线性回归分析探讨各成分与肥胖指标间的关系,采用某一行为的30 min替代另一行为,预测替代后对结局变量产生的变化。 结果 调整身高、体重、年龄、性别等协变量后,相对于久坐行为(SB)、睡眠(SLP)、低强度身体活动(LPA)所花费时间,学生中高强度身体活动(MVPA)所花费时间与去脂体重指数(FFMI)呈正相关(β=0.40)、与腰围(WC)(β=-2.50)和腰臀比(WHR)(β=-0.04)呈负相关;相对于SB、SLP、MVPA所花费时间,LPA所花费时间与WHR(β=0.06)呈正相关(P值均 < 0.05)。30 min/d的MVPA分别替代SLP、SB、LPA,WC和WHR分别降低1.10,1.10,1.34 cm和0.02,0.02,0.02,而FFMI分别增加0.19,0.19,0.15 kg/m2。 结论 在24 h活动行为中,久坐行为、睡眠或低强度身体活动时间在现有基础上不再增加,或维持每天的MVPA时间,对儿童青少年控制体重、预防肥胖至关重要,额外增加MVPA时间才会获得额外的健康效益。 Abstract:Objective The method of compositional data analysis was used to explore the relationship between 24-hour movement behavior and obesity indicators, and to examine the difference of quantitative effect on obesity indicators when one behavior replaced another behavior, so as to provide specific movement behavior advice for weight control in children and adolescents. Methods In June 2021, 231 students from eight classes in a primary school and a middle school in Taiyuan City, Shanxi Province were voluntarily recruited by using random cluster sampling. ActiGraph GT3X+ accelerometer was used to measure 24-hour movement behavior and Inbody J20 body composition analyzer was used to measure body composition. The relationship between each component and obesity indicators was analyzed by compositional multivariate linear regression model. In addition, 30 minutes of one behavior was used to replace another behavior to predict the effect difference of the outcomes. Results After adjusting for covariates such as height, weight, age, and sex, compared with time spent in sedentary behavior(SB), sleep (SLP) and light physical activity (LPA), time spent on moderate to vigorous physical activity (MVPA) was positively correlated with fat-free mass index (FFMI) (β=0.40, P < 0.05), negatively correlated with waist circumference (WC) (β=-2.50, P < 0.05) and waist-hip ratio (WHR) (β=-0.04, P < 0.05). Compared with SB, SLP and MVPA, time spent on LPA was positively correlated with WHR (β=0.06, P < 0.05). If MVPA of 30 min/d replaces SLP, SB, and LPA respectively, WC and WHR decrease 1.10, 1.10, 1.34 cm and 0.02, 0.02, 0.02 respectively, and FFMI increases 0.19, 0.19, 0.15 kg/m2 respectively. Conclusion In 24 h movement behavior, with consistent level of sedentary behavior, sleep or low-intensity movement behavior, maintaining a high level of MVPA and replacing sedentary with active activities are crucial for optimal abdominal fat and fat free mass in children and adolescents. -
Key words:
- Motor activity /
- Obesity /
- Compositional data analysis /
- Isotemporal substitution /
- Students
1) 利益冲突声明 所有作者声明无利益冲突。 -
表 1 学生各行为成分与肥胖相关指标关系的成分线性回归模型(n=231)
Table 1. Compositional linear regression models showing the association between time spent on different movement behavior and obesity indicators of students(n=231)
自变量 FAT% FFMI 腰臀比 腰围 β值(β值95%CI) P值 β值(β值95%CI) P值 β值(β值95%CI) P值 β值(β值95%CI) P值 MVPA -1.64(-3.83~0.54) 0.14 0.40(0.00~0.80) 0.05 -0.04(-0.07~-0.01) 0.02 -2.50(-4.97~-0.11) 0.04 LPA -0.80(-3.62~2.02) 0.58 0.21(-0.30~0.73) 0.41 0.06(0.02~0.10) < 0.01 2.08(-1.05~5.21) 0.19 SB 2.71(-0.09~5.52) 0.06 -0.30(0.08~0.21) 0.25 -0.01(-0.05~0.03) 0.74 0.24(-2.88~3.36) 0.88 SLP -0.27(-2.69~2.15) 0.83 -0.31(-0.76~0.13) 0.16 -0.02(-0.05~0.02) 0.37 0.22(-2.47~2.91) 0.87 表 2 学生活动行为间一对一成分等时替代(差值, n=231)
Table 2. One-to-one compositional isotemporal substitutions of movement behavior among students(d, n=231)
肥胖相关指标 活动行为 MVPA(+Δ) LPA(+Δ) SB(+Δ) SLP(+Δ) 腰围 MVPA(-Δ) +2.49* +2.28* +2.28* LPA(-Δ) -1.34* -0.24 -0.24 SB(-Δ) -1.10* +0.21 -0.00 SLP(-Δ) -1.10* +0.21 -0.00 腰臀比 MVPA(-Δ) +0.04* +0.03* +0.03* LPA(-Δ) -0.02* -0.01* -0.01* SB(-Δ) -0.02* +0.01* 0.00 SLP(-Δ) -0.02* +0.01* 0.00 FFMI MVPA(-Δ) -0.34* -0.37* -0.37* LPA(-Δ) +0.15* -0.04 -0.04 SB(-Δ) +0.19* +0.04 -0.00 SLP(-Δ) +0.19* +0.04 +0.00 注: *P < 0.05;-Δ表示被替代变量;+Δ表示替代变量。 -
[1] 马冠生. 中国儿童肥胖报告[M]. 北京: 北京人民出版社, 2017: 1-35.MA G S. Chinese childhood obesity report[M]. Beijing: Beijing People's Publishing House, 2017: 1-35. (in Chinese) [2] JANSSEN I, LEBLANC A G. Systematic review of the health benefits of physical activity and fitness in school-aged children and youth[J]. Int J Behav Nutr Phys Act, 2010, 7: 40-56. doi: 10.1186/1479-5868-7-40 [3] TREMBLAY M S, LEBLANC A G, KHO M E, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth[J]. Int J Behav Nutr Phys Act, 2011, 8: 98-120. doi: 10.1186/1479-5868-8-98 [4] CHEN X, BEYDOUN M A, WANG Y. Is sleep duration associated with childhood obesity? A systematic review and Meta-analysis[J]. Obesity(Silver Spring), 2008, 16(2): 265-274. [5] 关尚一, 朱为模. 身体活动与青少年代谢综合征风险的"剂量-效应"关系[J]. 西安体育学院学报, 2013, 30(2): 211-216. https://www.cnki.com.cn/Article/CJFDTOTAL-XATY201302020.htmGUAN S Y, ZHU W M. Dose-effect relationship between physical activity and metabolic syndrome risk in youth[J]. J Xi'an Phys Educ Univ, 2013, 30(2): 211-216. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XATY201302020.htm [6] DUMUID D, STANFORD T E, MARTIN-FERNANDEZ J A, et al. Compositional data analysis for physical activity, sedentary time and sleep research[J]. Stat Methods Med Res, 2018, 27(12): 3726-3738. doi: 10.1177/0962280217710835 [7] TALARICO R, JANSSEN I. Compositional associations of time spent in sleep, sedentary behavior and physical activity with obesity measures in children[J]. Int J Obes(Lond), 2018, 42(8): 1508-1514. doi: 10.1038/s41366-018-0053-x [8] 李红娟, 宋俊辰, 蒋玖君. 基于等时替代方法的超重肥胖职业人群健步走干预效果分析[J]. 北京体育大学学报, 2020, 43(11): 111-118. https://www.cnki.com.cn/Article/CJFDTOTAL-BJTD202011012.htmLI H J, SONG J C, JIANG J J. Effect analysis of walking intervention for overweight and obese occupational population based on isotemporal substitution model[J]. J Beijing Sport Univ, 2020, 43(11): 111-118. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-BJTD202011012.htm [9] WARD D S, EVENSON K R, VAUGHN A, et al. Accelerometer use in physical activity: best practices and research recommendations[J]. Med Sci Sports Exerc, 2005, 37(11 Suppl): S582-S588. [10] TUDOR-LOCKE C, BARREIRA T V, SCHUNA J M, et al. Improving wear time compliance with a 24-hour waist-worn accelerometer protocol in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE)[J]. Int J Behav Nutr Phys Act, 2015, 12: 11-20. doi: 10.1186/s12966-015-0172-x [11] EGOZCUE J J, PAWLOWSKY-GLAHN V, MATEU-FIGUERAS G, et al. Isometric logratio transformations for compositional data analysis[J]. Math Geol, 2003, 35(3): 279-300. doi: 10.1023/A:1023818214614 [12] 张婷, 李红娟. 成分数据分析方法在身体活动与健康研究领域的应用展望[J]. 体育科学, 2020, 40(9): 74-82, 97. doi: 10.16469/j.css.202009008ZHANG T, LI H J. Application prospect of compositional data analysis method in physical activity and health[J]. Chin Sport Sci, 2020, 40(9): 74-82, 97. (in Chinese) doi: 10.16469/j.css.202009008 [13] CHASTIN S F M, PALAREA-ALBALADEJO J, DONTJE M L, et al. Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: a novel compositional data analysis approach[J]. PLoS One, 2015, 10(10): e0139984. doi: 10.1371/journal.pone.0139984 [14] MCGREGOR D E, CARSON V, PALAREA-ALBALADEJO J, et al. Compositional analysis of the associations between 24-h movement behaviors and health indicators among adults and older adults from the Canadian Health Measure Survey[J]. Int J Environ Res Public Health, 2018, 15(8): 1779. doi: 10.3390/ijerph15081779 [15] DUMUID D, WAKE M, CLIFFORD S, et al. The association of the body composition of children with 24-hour activity composition[J]. J Pediatr, 2019, 208: 43-49. doi: 10.1016/j.jpeds.2018.12.030 [16] DUMUID D, STANFORD T E, PEDIŠI C Ž, et al. Adiposity and the isotemporal substitution of physical activity, sedentary time and sleep among school-aged children: a compositional data analysis approach[J]. BMC Public Health, 2018, 18(1): 311. doi: 10.1186/s12889-018-5207-1 [17] FAIRCLOUGH S J, DUMUID D, TAYLOR S, et al. Fitness, fatness and the reallocation of time between children's daily movement behaviors: an analysis of compositional data[J]. Int J Behav Nutr Phys Act, 2017, 14(1): 64-76. doi: 10.1186/s12966-017-0521-z [18] LUND R C, JOHANSSON M S, CROWLEY P, et al. Light-intensity physical activity derived from count or activity types is differently associated with adiposity markers[J]. Scand J Med Sci Sports, 2020, 30(10): 1966-1975. doi: 10.1111/sms.13743 -

计量
- 文章访问数: 653
- HTML全文浏览量: 291
- PDF下载量: 105
- 被引次数: 0