Several steps/day indicators predict changes in anthropometric outcomes: HUB City Steps.
Several steps/day indicators predict changes in anthropometric outcomes: HUB City Steps.
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DOI：
10.1186/1471-2458-12-983
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发表时间：
2012-11-15
影响因子：
4.5
通讯作者：
Yadrick K
中科院分区：
文献类型：
--
作者：
Thomson JL;Landry AS;Zoellner JM;Tudor-Locke C;Webster M;Connell C;Yadrick K
散步锻炼仍然是最常被报道的休闲活动，可能是因为它简单、便宜，而且很容易融入大多数人的生活方式。计步器是一种简单、方便和经济的工具，可以用来量化由步长决定的体力活动。很少有研究试图确定计步器决定的步数/天的动态变化与人体测量学和临床结果的变化之间的直接关系。因此，二次分析的目的是评估几个由计步器确定的步数/天的描述性指标在预测人体测量和临床结果变化方面的实用性，使用在南部非裔美国人人口中进行的基于社区的步行干预HUB City Steps的数据。第二个目的是评估治疗步数/天数据中不可信的值是否影响了这些数据预测干预引起的临床和人体测量结果变化的能力。这项二次分析中使用的数据是在2010年从269名参与者那里收集的，这些参与者参加了为期六个月的旨在降低血压的步行干预。在整个干预过程中，参与者提交了基于计步器自我监测的每周步数/日日记。评估人体测量(体重指数、腰围、体脂百分比[%BF]、脂肪质量)和临床结果(血压、血脂、血糖)的变化(6个月减去基线)。通过控制人口统计学和基线协变量的双变量检验和多变量线性回归分析，评估步数/天指标与人体测量和临床结果变化之间的相关性。在步数/天指标和大多数人体测量和临床结果变化之间观察到显著的负二元关联(r=-0.3到-0.2：P<；0.05)。在回归分析中控制协变量后，只有步数/天指标与人体测量(非临床)结果变化之间的关系仍然显著。例如，每天1,000步/天的干预平均步数/天会导致%BF下降0.1%。三个计步器数据集(完全、截断和排除)的结果是相似的，在对结果的解释上几乎没有什么有意义的差异。步数/天的几个描述性指标可用于预测人体测量结果的变化。此外，操纵步数/天数据来处理不可信的值对预测这些人体测量变化的能力总体上几乎没有影响。
Walking for exercise remains the most frequently reported leisure-time activity, likely because it is simple, inexpensive, and easily incorporated into most people’s lifestyle. Pedometers are simple, convenient, and economical tools that can be used to quantify step-determined physical activity. Few studies have attempted to define the direct relationship between dynamic changes in pedometer-determined steps/day and changes in anthropometric and clinical outcomes. Hence, the objective of this secondary analysis was to evaluate the utility of several descriptive indicators of pedometer-determined steps/day for predicting changes in anthropometric and clinical outcomes using data from a community-based walking intervention, HUB City Steps, conducted in a southern, African American population. A secondary aim was to evaluate whether treating steps/day data for implausible values affected the ability of these data to predict intervention-induced changes in clinical and anthropometric outcomes. The data used in this secondary analysis were collected in 2010 from 269 participants in a six-month walking intervention targeting a reduction in blood pressure. Throughout the intervention, participants submitted weekly steps/day diaries based on pedometer self-monitoring. Changes (six-month minus baseline) in anthropometric (body mass index, waist circumference, percent body fat [%BF], fat mass) and clinical (blood pressure, lipids, glucose) outcomes were evaluated. Associations between steps/day indicators and changes in anthropometric and clinical outcomes were assessed using bivariate tests and multivariable linear regression analysis which controlled for demographic and baseline covariates. Significant negative bivariate associations were observed between steps/day indicators and the majority of anthropometric and clinical outcome changes (r = -0.3 to -0.2: P < 0.05). After controlling for covariates in the regression analysis, only the relationships between steps/day indicators and changes in anthropometric (not clinical) outcomes remained significant. For example, a 1,000 steps/day increase in intervention mean steps/day resulted in a 0.1% decrease in %BF. Results for the three pedometer datasets (full, truncated, and excluded) were similar and yielded few meaningful differences in interpretation of the findings. Several descriptive indicators of steps/day may be useful for predicting anthropometric outcome changes. Further, manipulating steps/day data to address implausible values has little overall effect on the ability to predict these anthropometric changes.
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影响因子：
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