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BMC Public Health. 2012 Dec 15;12:1079. doi: 10.1186/1471-2458-12-1079.
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Socioeconomic inequalities in occupational, leisure-time, and transport related physical activity among European adults: a systematic review.欧洲成年人职业、休闲时间和交通相关体力活动中的社会经济不平等:系统评价。
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Employment status and health: understanding the health of the economically inactive population in Scotland.就业状况与健康:了解苏格兰非经济活动人口的健康状况。
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Prevalence and predictors of physical inactivity in a slum in Brazil.巴西贫民窟体力活动不足的流行率及预测因素。
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Worldwide variability in physical inactivity a 51-country survey.全球身体活动不足的差异:一项51个国家的调查
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47个低收入和中等收入国家的人类发展、职业结构与身体活动不足情况

Human development, occupational structure and physical inactivity among 47 low and middle income countries.

作者信息

Atkinson Kaitlin, Lowe Samantha, Moore Spencer

机构信息

Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada; School of Kinesiology & Health Studies, Queen's University, Kingston, ON K7L 3N6, Canada.

School of Kinesiology & Health Studies, Queen's University, Kingston, ON K7L 3N6, Canada.

出版信息

Prev Med Rep. 2015 Dec 4;3:40-5. doi: 10.1016/j.pmedr.2015.11.009. eCollection 2016 Jun.

DOI:10.1016/j.pmedr.2015.11.009
PMID:26844185
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4733059/
Abstract

This study aimed to (a) assess the relationship between a person's occupational category and their physical inactivity, and (b) analyze the association among country-level variables and physical inactivity. The World Health Survey (WHS) was administered in 2002-2003 among 47 low- and middle-income countries (n = 196,742). The International Physical Activity Questionnaire (IPAQ) was used to collect verbal reports of physical activity and convert responses into measures of physical inactivity. Economic development (GDP/c), degree of urbanization, and the Human Development Index (HDI) were used to measure country-level variables and physical inactivity. Multilevel logistic regression analysis was used to examine the association among country-level factors, individual occupational status, and physical inactivity. Overall, the worldwide prevalence of physical inactivity in 2002-2003 was 23.7%. Individuals working in the white-collar industry compared to agriculture were 84% more likely to be physically inactive (OR: 1.84, CI: 1.73-1.95). Among low- and middle-income countries increased HDI values were associated with decreased levels of physical inactivity (OR: 0.98, CI: 0.97-0.99). This study is one of the first to adjust for within-country differences, specifically occupation while analyzing physical inactivity. As countries experience economic development, changes are also seen in their occupational structure, which result in increased countrywide physical inactivity levels.

摘要

本研究旨在

(a)评估一个人的职业类别与其身体活动不足之间的关系;(b)分析国家层面变量与身体活动不足之间的关联。2002 - 2003年,在47个低收入和中等收入国家(n = 196,742)开展了世界卫生调查(WHS)。国际体力活动问卷(IPAQ)用于收集体力活动的口头报告,并将回答转换为身体活动不足的衡量指标。经济发展(人均国内生产总值)、城市化程度和人类发展指数(HDI)用于衡量国家层面变量和身体活动不足情况。采用多水平逻辑回归分析来检验国家层面因素、个体职业状况与身体活动不足之间的关联。总体而言,2002 - 2003年全球身体活动不足的患病率为23.7%。与从事农业工作的个体相比,从事白领行业的个体身体活动不足的可能性要高84%(比值比:1.84,置信区间:1.73 - 1.95)。在低收入和中等收入国家中,人类发展指数值的增加与身体活动不足水平的降低相关(比值比:0.98,置信区间:0.97 - 0.99)。本研究是首批在分析身体活动不足时对国内差异(特别是职业差异)进行校正的研究之一。随着各国经历经济发展,其职业结构也会发生变化,这导致全国范围内身体活动不足水平上升。