1 Bureau of Epidemiology Services, New York City Department of Health and Mental Hygiene, Queens, NY, USA.
2 Division of Preventive Medicine, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.
Public Health Rep. 2019 May/Jun;134(3):293-299. doi: 10.1177/0033354919841855. Epub 2019 Apr 5.
Inactive lifestyles contribute to health problems and premature death and are influenced by the physical environment. The primary objective of this study was to quantify patterns of physical inactivity in New York City and the United States by combining data from surveys and accelerometers.
We used Poisson regression models and self-reported survey data on physical activity and other demographic characteristics to predict accelerometer-measured inactivity in New York City and the United States among adults aged ≥18. National data came from the 2003-2004 and 2005-2006 National Health and Nutrition Examination Surveys. New York City data came from the 2010-2011 New York City Physical Activity and Transit survey.
Self-reported survey data indicated no significant differences in inactivity between New York City and the United States, but accelerometer data showed that 53.1% of persons nationally, compared with 23.4% in New York City, were inactive ( P < .001). New Yorkers reported a median of 139 weekly minutes of transportation activity, compared with 0 minutes nationally. Nationally, 50.0% of self-reported activity minutes came from recreation activity, compared with 17.5% in New York City. Regression models indicated differences in the association between self-reported minutes of transportation and recreation and accelerometer-measured inactivity in the 2 settings.
The prevalence of physical inactivity was higher nationally than in New York City. The largest difference was in walking behavior indicated by self-reported transportation activity. The study demonstrated the feasibility of combining accelerometer and survey measurement and that walkable environments promote an active lifestyle.
缺乏运动的生活方式会导致健康问题和早逝，而且还会受到物理环境的影响。本研究的主要目的是通过结合调查和加速度计数据，量化纽约市和美国的身体活动不足模式。
我们使用泊松回归模型和关于身体活动和其他人口统计学特征的自我报告调查数据，来预测在 18 岁及以上成年人中，加速度计测量的纽约市和美国的不活跃状态。国家数据来自 2003-2004 年和 2005-2006 年国家健康和营养调查。纽约市数据来自 2010-2011 年纽约市体育活动和交通调查。
自我报告的调查数据表明，纽约市和美国之间的不活跃状态没有显著差异，但加速度计数据显示，全国有 53.1%的人不活跃，而纽约市只有 23.4%（P<0.001）。纽约人报告每周有 139 分钟的交通活动，而全国则为 0 分钟。全国有 50.0%的自我报告活动分钟数来自娱乐活动，而纽约市则为 17.5%。回归模型表明，在这两个环境中，自我报告的交通和娱乐活动分钟数与加速度计测量的不活跃状态之间的关联存在差异。
身体活动不足的流行率在全国范围内高于纽约市。最大的差异在于自我报告的交通活动所表示的步行行为。该研究证明了结合加速度计和调查测量的可行性，并且可步行的环境可以促进积极的生活方式。
