MRC Epidemiology Unit & UKCRC Centre for Diet and Activity Research (CEDAR), University of Cambridge, School of Clinical Medicine, Box 285, Cambridge Biomedical Campus, Cambridge, Cambridgeshire CB2 0QQ, UK.
Prev Med. 2019 Jan;118:150-158. doi: 10.1016/j.ypmed.2018.10.024. Epub 2018 Oct 25.
Characteristics of the environment influence health and may promote physical activity. We explored the associations between neighborhood environmental characteristics grouped within five facets (spaces for physical activity, walkability, disturbance, natural environment, and the sociodemographic environment) and objective ('recorded') and self-reported ('reported') physical activity in adults from UK Biobank. Recorded activity was assessed using wrist-worn accelerometers (2013-2015, n = 65,967) and time spent in moderate-to-vigorous physical activity (MVPA), walking, and walking for pleasure was self-reported (2006-2010, n = 337,822). Associations were assessed using linear and multinomial logistic regression models and data were analyzed in 2017. We found participants living in areas with higher concentrations of air pollution recorded and reported lower levels of physical activity and those in rural areas and more walkable areas had higher levels of both recorded and reported activity. Some associations varied according to the specificity of the outcome, for example, those living in the most deprived areas were less likely to record higher levels of MVPA (upper tertile: RRR: 0.80 95% CI: 0.74, 0.86) but were more likely to report higher levels of walking (upper tertile: RRR: 1.09, 95% CI: 1.06, 1.13). Environmental characteristics have the potential to contribute to different physical activities but interventions which focus on a single environmental attribute or physical activity outcome may not have the greatest benefits.
环境特征会影响健康，并可能促进身体活动。我们探索了环境特征在五个方面（身体活动空间、步行性、干扰、自然环境和社会人口环境）分组与成年人客观（“记录”）和自我报告（“报告”）身体活动之间的关联，这些成年人来自英国生物银行。记录的活动使用佩戴在手腕上的加速度计进行评估（2013-2015 年，n=65967），中等至剧烈体力活动（MVPA）、步行和散步的时间是自我报告的（2006-2010 年，n=337822）。使用线性和多项逻辑回归模型评估关联，数据于 2017 年进行分析。我们发现，生活在空气污染浓度较高地区的参与者记录和报告的身体活动水平较低，而生活在农村地区和步行更方便的地区的参与者记录和报告的身体活动水平较高。一些关联因结果的特异性而异，例如，生活在最贫困地区的人记录的高水平 MVPA（上三分位数：RRR：0.80 95%CI：0.74, 0.86）的可能性较小，但报告高水平步行（上三分位数：RRR：1.09，95%CI：1.06，1.13）的可能性较大。环境特征有可能促进不同的身体活动，但关注单一环境属性或身体活动结果的干预措施可能不会带来最大的益处。
