Statistical methods for analyzing objectively measured physical activity data

分析客观测量的身体活动数据的统计方法

• 批准号: 9176713
• 负责人: Chongzhi Di
• 金额: $ 46.35万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH 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 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9176713
• 关键词: Accelerometer; Address; Biometry; Calibration; Cardiovascular Diseases; Cardiovascular system; Clinical Research; Complex; Computer software; Data; Data Analyses; Development; Devices; Disease; Dose; Environment; Epidemiologic Studies; Foundations; Frequencies; Future; Guidelines; Health; Intervention; Life; Measurement; Measures; Methods; Modeling; Monitor; Outcome; Output; Patient Self-Report; Pattern; Physical activity; Procedures; Property; Questionnaires; Reporting; Research; Research Personnel; Resolution; Sampling; Series; Statistical Methods; Technology; Testing; Time; Variant; Walking; Woman; Women' s Health; abstracting; cardiovascular health; design; improved; indexing; method development; novel; physical conditioning; public health intervention; randomized trial; response; sensor; statistics; study population

Project Summary/Abstract The major focus of this project is to develop novel statistical methods for objectively measured physical activity (PA) data by accelerometers or other wearable monitors, and to apply these methods to understand how specific patterns of activity intensity, frequency and duration are associated with health outcomes, such as cardiovascu- lar diseases. With rapid technological advances, it is now increasingly common to record accelerometer data in large-scale epidemiological studies. While the size and complexity of this type of data is exploding, the de- velopment of analytic methods is largely lacking. Novel analytic methods that are interpretable, robust, and yet computationally efficient are urgently needed, especially with the technology rapidly evolving. Motivated by the Women's Health Initiative (WHI) and other PA studies, we propose novel statistical meth- ods to summarize and effectively utilize objective physical activity measurements for health association analysis. Specifically, we will first develop a functional data analysis framework to extract novel summary indices from standard resolution accelerometer data and flexibly model the association between PA patterns and health. We next consider high-resolution raw accelerometer data and propose a systematic analytical framework for identifying walking in free-living environment, describing walking patterns and studying their association with health outcomes. Finally, we propose novel measurement error correction approaches for large-scale studies with complex sampling designs, where objective measurement is available only in a small subset of the study population. The proposed methodological research is motivated by PA studies of the WHI and will be directly applied to these projects. Applications of these methods to these studies will improve our understanding of PA, which will eventually help lay the foundation for future PA guidelines. These methods are generally applicable to other epidemiological studies that collect objective PA measurements, and software will be made publicly accessible.

项目概要/摘要 该项目的主要重点是开发新的统计方法来客观测量身体活动 （PA）加速度计或其他可穿戴监视器的数据，并应用这些方法来了解具体如何 活动强度、频率和持续时间的模式与健康结果相关，例如心血管疾病 拉尔病。随着技术的快速进步，记录加速度计数据现在越来越普遍 在大规模流行病学研究中。虽然此类数据的规模和复杂性呈爆炸式增长，但 分析方法的发展很大程度上缺乏。可解释、稳健且可靠的新颖分析方法 迫切需要高效的计算，特别是随着技术的快速发展。 在妇女健康倡议 (WHI) 和其他 PA 研究的推动下，我们提出了新的统计方法 ods 总结并有效利用客观的身体活动测量进行健康关联分析。 具体来说，我们将首先开发一个功能数据分析框架，从数据中提取新颖的汇总指数 标准分辨率加速度计数据并灵活地对 PA 模式与健康之间的关联进行建模。 接下来，我们考虑高分辨率原始加速度计数据，并提出一个系统的分析框架 识别在自由生活环境中行走，描述行走模式并研究它们与 健康结果。最后，我们提出了用于大规模研究的新颖的测量误差校正方法 具有复杂的抽样设计，仅在研究的一小部分中提供客观测量 人口。拟议的方法研究是由 WHI 的 PA 研究推动的，并将直接用于 应用于这些项目。这些方法在这些研究中的应用将提高我们对 PA 的理解， 这最终将有助于为未来的 PA 指南奠定基础。这些方法普遍适用 收集客观 PA 测量结果的其他流行病学研究，软件将公开 可以访问。