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。
基本信息
- 批准号:10704669
- 负责人:
- 金额:$ 44.79万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AccelerometerActivity CyclesAddressAdvisory CommitteesAffectAgingAmericanAncillary StudyAreaBehaviorCardiovascular DiseasesCategoriesClinical ResearchCollaborationsComputer softwareDataData AnalysesDevelopmentDevicesDiabetes MellitusDoseEpidemiologyGoalsGuidelinesHealthHealth BenefitHourInterventionLengthLongitudinal StudiesMeasurementMeasuresMethodologyMethodsModelingNational Health and Nutrition Examination SurveyNatureOutcomePatternPhysical activityPopulation SurveillancePrincipal Component AnalysisReportingSleepStatistical MethodsTimeWomanWomen&aposs Healthadvanced analyticsanalytical methodanalytical toolbiobankcardiovascular healthcomplex dataeffective interventionepidemiology studyfeature extractionflexibilityhigh dimensionalityimprovedindexinginsightlifestyle factorslight intensitymortalitynovelolder womenprogramsresponsesedentarysedentary lifestylesurveillance studyvigorous intensitywearable device
项目摘要
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.
项目总结/摘要
该项目旨在开发新的分析工具,以了解身体活动(PA)的积累模式,
久坐行为(SB)和睡眠在24小时活动周期,并灵活地模拟这些模式和健康
结果,如心血管疾病,并应用这些方法在PA流行病学研究,收集
通过加速度计或可穿戴设备进行客观测量。在体育活动流行病学中,每一个inten-
已经单独研究了与健康结果相关的sity/behavior类别。但这
这种方法未能考虑到这些活动之间的相互关联和相互作用。事实上,2018年
身体活动指南咨询委员会科学报告确定的艾德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,显然需要进一步研究,
告知下一套身体活动指南。
出于这一关键需求,我们提出了新的统计方法来利用收集的丰富信息,
几个方向的加速度计首先,我们开发了强大的功能数据分析方法,用于灵活建模
加速度计测量的PA轨迹和健康结果之间的关联。第二,我们开发了灵活的
用于表征PA/SB蓄积之间剂量-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,用于提取24-
小时活动周期,扩展纵向研究的方法,并灵活地调查
24-小时活动组成模式和健康。
所提出的分析工具的直接动机,并将立即应用于辅助研究,
我们参与的妇女健康倡议(WHI),客观的身体活动和心血管
健康(OPACH)研究,WHI强壮和健康试验(WHISH),久坐时间和衰老(星星)计划,
妇女健康加速计合作(WHAC),以及公开提供的国家卫生和
营养检查调查(NHANES)和英国生物银行数据。
项目成果
期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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:
- 影响因子:0
- 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:
- 影响因子:1
- 作者:Harezlak,Jaroslaw;Di,Chongzhi
- 通讯作者:Di,Chongzhi
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{{ truncateString('Chongzhi Di', 18)}}的其他基金
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:
9981000 - 财政年份:2016
- 资助金额:
$ 44.79万 - 项目类别:
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:
10654504 - 财政年份:2016
- 资助金额:
$ 44.79万 - 项目类别:
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 - 财政年份:2016
- 资助金额:
$ 44.79万 - 项目类别:
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:
9281900 - 财政年份:2016
- 资助金额:
$ 44.79万 - 项目类别:
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 - 财政年份:2016
- 资助金额:
$ 44.79万 - 项目类别:
Statistical methods for GxE interactions: Measurement error & time varying exposu
GxE 交互的统计方法:测量误差
- 批准号:
8610313 - 财政年份:2013
- 资助金额:
$ 44.79万 - 项目类别:
Statistical methods for GxE interactions: Measurement error & time varying exposu
GxE 交互的统计方法:测量误差
- 批准号:
8428614 - 财政年份:2013
- 资助金额:
$ 44.79万 - 项目类别:
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