Statistical methods for analyzing objectively measured physical activity.

用于分析客观测量的身体活动的统计方法。

• 批准号: 10531088
• 负责人: Chongzhi Di
• 金额: $ 46.87万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10531088
• 关键词: Accelerometer; Activity Cycles; Address; Advisory Committees; Affect; Aging; American; Ancillary Study; Area; Behavior; Cardiovascular Diseases; Categories; Clinical Research; Collaborations; Computer software; Data; Data Analyses; Development; Devices; Diabetes Mellitus; Dose; Epidemiology; Goals; Guidelines; Health; Health Benefit; Hour; Intervention; Lead; Length; Longitudinal Studies; Measurement; Measures; Methodology; Methods; Modeling; National Health and Nutrition Examination Survey; Nature; Outcome; Pattern; Physical activity; Population Surveillance; Principal Component Analysis; Reporting; Sleep; Statistical Methods; Time; Woman; Women' s Health; advanced analytics; analytical method; analytical tool; biobank; cardiovascular health; complex data; effective intervention; epidemiology study; feature extraction; flexibility; high dimensionality; improved; indexing; insight; lifestyle factors; light intensity; mortality; novel; older women; programs; response; sedentary; sedentary lifestyle; surveillance study; vigorous intensity; wearable device

Project Summary/Abstract This project aims to develop new analytic tools for understanding accumulation patterns of physical activity (PA), sedentary behavior (SB) and sleep in the 24-hour activity cycle and to flexibly model these patterns and health outcomes, such as cardiovascular diseases, and apply these methods in PA epidiological studies that collected objective measurements by accelerometry or wearable devices. In physical activity epidemiology, each inten- sity/behavior category has been investigated separately in association with health outcomes. However, this approach fails to account for the inter-relatedness and interactions among of these activities. In fact, the 2018 Physical Activity Guidelines Advisory Committee Scientific Report identified 24-hour cycle and dose-response PA/SB accumulation patterns among the most important and critical issues that clearly need future research for informing the next set of physical activity guidelines. Motivated by this critical need, we propose novel statistical methods to utilize the rich information collected by accelerometry in a few directions. First, we develop robust functional data analysis methods for flexibly modeling associations between accelerometry-measured PA trajectories and health outcomes. Second, we develop flexible functional data analysis methods for characterizing dose-response relationships between PA/SB accumulation patterns and health outcomes, using an interpretable functional principal component analysis approach. Third, we plan to develop nonparametric compositional data analysis (NCDA) methods for extracting patterns of the 24- hour activity cycle, extend the approach to longitudinal studies and to flexibly investigate associations between 24-hour activity compositional patterns and health. The proposed analytic tools are directly motivated by and will be immediately applied to ancillary studies of the Women's Health Initiative (WHI) that we are involved in, the Objective Physical Activity and Cardiovascular Health (OPACH) Study, WHI Strong and Healthy Trial (WHISH), the Sedentary Time and Aging (STAR) Program, the Women's Health Accelerometry Collaboration (WHAC), as well as the publicly available National Health and Nutrition Examination Survey (NHANES) and UK Biobank data.

项目概要/摘要 该项目旨在开发新的分析工具来理解体力活动（PA）的积累模式， 24 小时活动周期中的久坐行为 (SB) 和睡眠，并灵活地对这些模式和健康进行建模 成果，例如心血管疾病，并将这些方法应用于收集的 PA 流行病学研究中 通过加速度计或可穿戴设备进行客观测量。在体力活动流行病学中，每个人都 城市/行为类别与健康结果的关系已单独进行调查。然而，这 方法未能解释这些活动之间的相互关联性和相互作用。事实上，2018年 身体活动指南咨询委员会科学报告确定了 24 小时周期和剂量反应 PA/SB 积累模式是最重要和最关键的问题之一，显然需要未来的研究 告知下一组身体活动指南。 受这一迫切需求的推动，我们提出了新颖的统​​计方法来利用收集的丰富信息 几个方向的加速度测量。首先，我们开发强大的功能数据分析方法来灵活建模 加速度测量的 PA 轨迹与健康结果之间的关联。第二，我们开发灵活的 用于表征 PA/SB 积累之间剂量反应关系的功能数据分析方法 模式和健康结果，使用可解释的功能主成分分析方法。第三， 我们计划开发非参数成分数据分析（NCDA）方法来提取 24- 小时活动周期，将方法扩展到纵向研究并灵活调查之间的关联 24 小时活动构成模式和健康状况。 所提出的分析工具直接受到以下因素的推动，并将立即应用于以下方面的辅助研究： 我们参与的妇女健康倡议 (WHI)、客观身体活动和心血管 健康 (OPACH) 研究、WHI 强健健康试验 (WHISH)、久坐时间和衰老 (STAR) 计划、 妇女健康加速测量合作组织 (WHAC)，以及公开的国家健康和 营养检查调查 (NHANES) 和英国生物银行数据。