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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.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
Testing homogeneity in semiparametric mixture case-control models.
测试半参数混合病例对照模型的均匀性。
DOI: 10.1080/03610926.2016.1205612
发表时间: 2017
期刊: Communications in statistics: theory and methods
影响因子: --
作者: [Di,Chong-Zhi, Chan,KwunChuenGary, Zheng,Cheng, Liang,Kung-Yee]
通讯作者: Liang,Kung-Yee
Editorial for the Special Issue "Medical Device Data: Challenges, Statistical Methods and Applications".
“医疗器械数据:挑战、统计方法和应用”特刊的社论。
DOI: 10.1007/s12561-019-09247-1
发表时间: 2019
期刊: Statistics in biosciences
影响因子: 1
作者: [Harezlak,Jaroslaw, Di,Chongzhi]
通讯作者: Di,Chongzhi
Statistical methods for analyzing objectively measured physical activity data
Statistical methods for analyzing objectively measured physical activity data
  • 批准号:
    10654504
  • 项目类别:
  • 资助金额:
    $7.55万
  • 财政年份:
    2016
  • 负责人:
    Chongzhi Di
  • 依托单位:
Statistical methods for analyzing objectively measured physical activity data
Statistical methods for analyzing objectively measured physical activity data
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