体育活动与死亡率:久坐的潜在影响

P. Katzmarzyk, R. Pate
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引用次数: 7

摘要

在过去的几年中,大量关于久坐行为(久坐)的研究已经证明了久坐行为与慢性疾病和死亡率结果的显著关联(6)。这些结果对工作场所健康和相关政策具有重要意义,因为职业数据的长期趋势表明,在1960年至2008年期间,美国久坐的职业显著增加(1)。美国人自我报告的久坐水平平均约为4.7小时·天(3);然而,这一估计可能是保守的,因为人们倾向于低估他们的坐着行为。例如,一项针对澳大利亚成年人的研究使用客观评估(倾斜仪)报告平均每天坐着8.8小时(4)。此外,美国国家健康和营养检查调查中通过加速度计收集的客观数据表明,儿童和成人每天坐着的时间约为7.7小时(5)。很大一部分美国人暴露在久坐不动的行为中,并因此面临更大的健康风险。在这一领域,人们关注的一个话题是,观察到的久坐行为与慢性疾病和死亡风险增加之间的关联是否会因体育活动(轻度、中度、剧烈或完全)而改变或缓和。研究通常通过将身体活动作为协变量纳入统计模型或通过按身体活动水平(即活跃与不活跃)对分析进行分层来统计“调整”身体活动的测量。使用这种方法,Ekelund等人(2)最近报告了一项荟萃分析的结果,该数据来自13项研究的1,005,791名参与者,他们在2至18岁之间进行了全因死亡率随访。总共有8.4%的参与者在随访期间死亡,这是危险的
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Physical Activity and Mortality: The Potential Impact of Sitting
Over the past few years, numerous studies of sedentary behavior (sitting) have documented significant associations with chronic disease and mortality outcomes (6). These results have significant implications for workplace health and associated policies, because long-term trends in occupational data suggest that sedentary occupations have increased significantly in the United States between 1960 and 2008 (1). Self-reported levels of sitting in the United States average approximately 4.7 h·d (3); however, this estimate is likely conservative because individuals tend to underreport their sitting behavior. For example, a study among Australian adults using an objective assessment (inclinometer) reported an average of 8.8 h of sitting per day (4). Furthermore, objective data collected by accelerometry in the U.S. National Health and Nutrition Examination Survey indicate that children and adults spend approximately 7.7 h·d being sedentary (5). Thus, a large proportion of the U.S. population is exposed to excessive levels of sedentary behavior and is at increased health risk because of this exposure. A topic of interest that has been addressed in this arena is whether the observed associations of sedentary behavior and increased chronic disease and mortality risk are modified or moderated by physical activity (light, moderate, vigorous, or total). Studies typically statistically “adjust” for a measure of physical activity by including it in a statistical model as a covariate or by stratifying the analysis by level of physical activity (i.e., active vs inactive). Using this approach, Ekelund et al. (2) recently reported the results of a meta-analysis of data from 1,005,791 participants from 13 studies who were followed for all-cause mortality between 2 and 18 yr. A total of 8.4% of the participants died during follow-up, and the hazardous
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