Changes in walking, body mass index, and cardiometabolic risk factors following residential relocation: Longitudinal results from the CARDIA study.
Changes in walking, body mass index, and cardiometabolic risk factors following residential relocation: Longitudinal results from the CARDIA study.
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住宅搬迁后步行，体重指数和心脏代谢风险因素的变化：Cardia研究的纵向结果。
DOI：
10.1016/j.jth.2016.08.006
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发表时间：
2016-12
影响因子：
3.6
通讯作者：
Gordon-Larsen P
中科院分区：
文献类型：
--
作者：
Braun LM;Rodriguez DA;Song Y;Meyer KA;Lewis CE;Reis JP;Gordon-Larsen P
虽然许多研究发现建筑环境与步行有关，但大多数研究采用横断面研究设计，很少有研究更远的心脏代谢结果。这项研究提供了纵向证据的基础上的变化，步行，体重指数（BMI），和心脏代谢风险后，住宅搬迁。我们检查了1,079名参与CARDIA研究的参与者，他们在2000年至2006年期间搬迁了居住地点（2000年年龄为32-46岁，49%白色/51%黑人，55%女性）。我们创建了一个步行指数，从人口密度，街道连通性，食物和体育活动资源的措施，在参与者的搬迁前和搬迁后的居住地点测量。在搬家前后测量的结果包括行走、BMI、腰围、血压、胰岛素抵抗、甘油三酯、胆固醇、致动脉粥样硬化性血脂异常和C反应蛋白。固定效应（FE）模型用于估计步行能力的人内变化与每个结果的人内变化之间的关联。将这些估计值与随机效应（RE）模型的估计值进行比较，以评估未测量混杂因素的影响。在FE模型中，步行能力增加一个SD与收缩压降低0.81 mmHg [95% CI：（-1.55，-0.07）]和C反应蛋白增加7.36%[95% CI：（0.60，14.57）]相关。尽管在RE模型中观察到了几个显著的相关性，但Hausman检验表明这些估计值对大多数结局都有偏倚。RE估计值最常偏离零值或与FE估计值的影响方向相反。在FE模型中，更大的步行性与更低的血压和更高的C反应蛋白相关，这可能反映了密集的步行环境中相互竞争的健康风险和益处。可再生能源模型往往夸大或以其他方式歪曲步行和健康之间的关系。基于个体之间差异的估计方法可能会受到来自未测量混杂因素的偏倚，例如住宅自我选择。
While many studies have found the built environment to be associated with walking, most have used cross-sectional research designs and few have examined more distal cardiometabolic outcomes. This study contributes longitudinal evidence based on changes in walking, body mass index (BMI), and cardiometabolic risk following residential relocation. We examined 1,079 participants in the CARDIA study who moved residential locations between 2000 and 2006 (ages 32–46 in 2000, 49% white/51% black, 55% female). We created a walkability index from measures of population density, street connectivity, and food and physical activity resources, measured at participants’ pre- and post-move residential locations. Outcomes measured before and after the move included walking, BMI, waist circumference, blood pressure, insulin resistance, triglycerides, cholesterol, atherogenic dyslipidemia, and C-reactive protein. Fixed effects (FE) models were used to estimate associations between within-person change in walkability and within-person change in each outcome. These estimates were compared to those from random effects (RE) models to assess the implications of unmeasured confounding. In FE models, a one-SD increase in walkability was associated with a 0.81 mmHg decrease in systolic blood pressure [95% CI: (−1.55, −0.07)] and a 7.36 percent increase in C-reactive protein [95% CI: (0.60, 14.57)]. Although several significant associations were observed in the RE models, Hausman tests suggested that these estimates were biased for most outcomes. RE estimates were most commonly biased away from the null or in the opposite direction of effect as the FE estimates. Greater walkability was associated with lower blood pressure and higher C-reactive protein in FE models, potentially reflecting competing health risks and benefits in dense, walkable environments. RE models tended to overstate or otherwise misrepresent the relationship between walkability and health. Approaches that base estimates on variation between individuals may be subject to bias from unmeasured confounding, such as residential self-selection.