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北京大学学报（医学版） ›› 2020, Vol. 52 ›› Issue (3): 486-491. doi: 10.19723/j.issn.1671-167X.2020.03.014

• 论著 • 上一篇    下一篇

身体活动、静坐行为的时间分布与肥胖的关系

那晓娜1,朱珠1,陈阳阳1,王东平2,王浩杰2,宋阳2,马晓川1,王培玉1,刘爱萍1,△()   

  1. 1. 北京大学公共卫生学院社会医学与健康教育系,北京 100191
    2. 乌海市疾病预防控制中心,内蒙古自治区乌海 016000
  • 收稿日期:2020-02-06 出版日期:2020-06-18 发布日期:2020-06-30
  • 通讯作者: 刘爱萍 E-mail:apingliu@163.com
  • 基金资助:
    乌海市成人慢性病及危险因素调查项目

Associations of distribution of time spent in physical activity and sedentary behavior with obesity

Xiao-na NA1,Zhu ZHU1,Yang-yang CHEN1,Dong-ping WANG2,Hao-jie WANG2,Yang SONG2,Xiao-chuan MA1,Pei-yu WANG1,Ai-ping LIU1,△()   

  1. 1. Department of Social Medicine and Health Education, Peking University School of Public Health, Beijing 100191, China
    2. Center for Disease Control and Prevention of Wuhai City, Wuhai 016000, Inner Mongolia, China
  • Received:2020-02-06 Online:2020-06-18 Published:2020-06-30
  • Contact: Ai-ping LIU E-mail:apingliu@163.com
  • Supported by:
    Program for the Investigation on the Health Status of Adult Residents in Wuhai City

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摘要：

目的 综合探究乌海市成年居民身体活动(physical activity, PA)、静坐行为(sedentary behavior, SB)的时间分布与肥胖的关系。方法 采用多阶段整群随机抽样,以乌海市18~79岁常住居民为研究对象进行横断面调查。通过问卷调查、体格检查收集研究对象的社会人口学信息、PA和SB时间、饮食摄入、慢性病控制情况、身高、体质量、腰围及其他协变量。成分线性回归分析PA、SB的时间分布与肥胖的关系,以及时间重新分配后对肥胖的影响。结果 成分线性回归结果显示,控制混杂因素后,职业与非职业人群PA、SB的时间占比与体重指数(body mass index, BMI)、腰围身高比(waist to height ratio, WHtR)的负自然对数(-lnWHtR)的关系均有统计学意义(P均<0.001)。职业人群中,中高强度PA的时间占比与-lnWHtR呈负相关(β=-0.008, P=0.022),而SB时间占比与BMI、-lnWHtR呈正相关(β=0.117, P=0.003; β=0.007, P=0.005)。非职业人群中,中高强度PA的时间占比与BMI呈负相关(β=-0.079, P=0.041)。职业与非职业人群中,低强度PA的时间占比与BMI、-lnWHtR 关系无统计学意义。时间重新分配结果显示,10 min的中高强度PA代替低强度PA和SB对肥胖的影响更大。结论 在运动指南的制定以及健康管理的实践中,综合考虑不同人群PA、SB的时间分布对健康的影响,而非简单地增减PA或SB的绝对时间,将取得更长远的健康效果。

关键词: 成分数据分析, 肥胖, 身体活动, 静坐行为

Abstract:

Objective: To explore associations of distribution of time spent in physical activity (PA) and sedentary behavior (SB) with obesity with taking account that time is finite during the day of adult residents in Wuhai City.Methods: A cross-sectional study was undertaken in Wuhai City, and we carried out a sampling of local residents aged 18-79 by using multiple stratified cluster sampling method. Data about social demographic characteristics, time spent in PA and SB, diet intake, controlling situation of chronic disease and other covariates were obtained by qualified investigators for face-to-face questionnaire survey. Data about height, weight, and waist circumstance, were obtained by doctors in a secondary hospital or above for body measurements. The statistical method used in our study was known as compositional data analysis, which had been used to process compositional data in many fields. Liner regression analysis with compositional data was used to synthetically analyze the associations of distribution of time spent in PA and SB with obesity,and to investigate the effect of re-allocating time from one behavior to another one whilst the remaining one was kept stable.Results: The investigation revealed the special advantage of compositional data analysis in processing time-use data. The result of liner regression analysis with the compositional data showed that after controlling the potential confounding factors, the associations of distribution of time spent in PA and SB was significantly associated with body mass index (BMI, P<0.001) and the negative natural logarithm of waist to height ratio (-lnWHtR, P<0.001). Among them, in professional population, the proportion of time spent in moderate-to-vigorous physical activity (MVPA) was negatively correlated with -lnWHtR (β=-0.008, P=0.022), while the proportion of time spent in SB was positively correlated with BMI and -lnWHtR (β=0.117, P=0.003; β=0.007, P=0.005). However, in nonprofessional population, the proportion of time spent in MVPA was only negatively correlated with BMI (β=-0.079, P=0.041). Nevertheless, the proportion of time spent in low-intensity physical activity (LIPA) was not significantly associated with BMI and -lnWHtR in both professional and nonprofessional population. In addition, the effects of MVPA replacing another behavior and of MVPA being displaced by another behavior were not symmetrical, and 10 minutes of MVPA replacing LIPA or SB had a greater influence on intervention and prevention of obesity than 10 minutes MVPA being replaced by LIPA or SB.Conclusion: The research has resulted in a solution of the associations of the distribution of time spent in PA, SB with health risk. Our results suggest that public health messages should target the health effects of the distribution of time of PA and SB synergistically in developing PA guidelines and health management practice, rather than simply increasing or decreasing the absolute time of PA or SB, so that we can provide scientific suggestions to make people get a profounder healthy effect.

Key words: Compositional data analysis, Obesity, Physical activity, Sedentary behavior

中图分类号: 

  • R163

表1

身体活动、静坐时间的算术均数与成分均数比较"

Items MVPA/min LIPA/min SB/min
Professional population
Arithmetic mean 114.35 (11.76%) 459.40 (47.26%) 398.41 (40.98%)
Compositional mean 94.16 (9.81%) 468.40 (48.79%) 397.44 (41.40%)
Nonprofessional population
Arithmetic mean 125.86 (12.54%) 603.45 (60.11%) 274.67 (27.36%)
Compositional mean 110.01 (11.46%) 600.00 (62.50%) 249.99 (26.04%)

表2

身体活动、静坐时间的成分方差矩阵"

Items Professional population Nonprofessional population
MVPA LIPA SB MVPA LIPA SB
MVPA 0 1.204 1.437 0 0.801 0.941
LIPA 1.204 0 1.043 0.801 0 0.828
SB 1.437 1.043 0 0.941 0.828 0

表3

肥胖与身体活动、静坐的时间分布的成分线性回归分析"

Items Professional population Nonprofessional population
BMI -lnWHtR BMI -lnWHtR
β P β P β P β P
MVPA -0.084 0.255 -0.008 0.022 -0.079 0.041 -0.002 0.630
LIPA -0.033 0.685 0.004 0.201 -0.096 0.515 -0.004 0.934
SB 0.117 0.003 0.007 0.005 -0.017 0.904 0.003 0.473

表4

身体活动、静坐时间重新分配的BMI、WHtR预测值变化"

Items BMI -lnWHtR
MVPA LIPA SB MVPA LIPA SB
Professional population
MVPA 0.446 0.445 0.017 0.017
LIPA -0.464 0.455 -0.019 0.017
SB -0.462 -0.456 -0.018 -0.015
Nonprofessional population
MVPA 0.483 0.484 0.019 0.020
LIPA -0.487 0.486 -0.020 0.019
SB -0.485 -0.483 -0.021 -0.018
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