A Measurement Error Approach to Estimating Usual Daily Physical Activity Distribu

估计日常体力活动分布的测量误差方法

• 批准号: 8013369
• 负责人: Greg J Welk
• 金额: $ 0.85万
• 依托单位: IOWA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2012-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8013369
• 关键词: Accounting; Address; Adult; African American; Age; Area; Arts; Behavior; Calibration; Characteristics; Cognitive; Complex; County; Data; Data Analyses; Development; Devices; Diagnostic Sensitivity; Diet; Dietary Assessment; Dietary History; Dietary intake; Eating; Energy Intake; Energy Metabolism; Environment; Epidemic; Epidemiologic Studies; Ethnic Origin; Evaluation; Expenditure; Food; Foundations; Frequencies; Future; Gender; Goals; Health; Hispanics; Hour; Household; Individual; Intake; Interest Group; Interview; Investigation; Iowa; Lead; Light; Literature; Measurement; Measures; Methodology; Methods; Modeling; Monitor; National Health and Nutrition Examination Survey; Nature; Nutrient; Obesity; Occupational; Outcome; Outcome Measure; Participant; Patient Self-Report; Pattern; Pattern Recognition; Persons; Physical activity; Pilot Projects; Population; Population Surveillance; Prevalence; Procedures; Process; Property; Protocols documentation; Public Health; Qualifying; Questionnaires; Race; Recruitment Activity; Reporting; Research; Research Personnel; Rural; Sampling; Self-Administered; Series; Social Desirability; Solutions; Statistical Models; Structure; Study models; Surveys; Techniques; Telephone; Telephone Interviews; Testing; Time; Work; base; cost; cost effective; data modeling; design; experience; food consumption; improved; innovation; instrument; nutrition; public health priorities; public health relevance; response; tool

DESCRIPTION (provided by applicant): Measurement error in physical activity assessment has made it difficult to answer important questions about the prevalence of physical activity and associations with various health-related outcomes. The objective in the present application is to develop and evaluate statistical procedures to model, quantify and adjust for measurement error in a commonly used and accepted physical activity recall instrument (24 hour physical activity recall 24hPAR). To develop appropriate statistical models, we will conduct a Physical Activity Measurement Survey (PAMS) to obtain recall and objective physical activity data from a representative sample of 1200 adults (19- 70 yrs) who reside in rural and urban environments in Iowa. Participants will complete two days of physical activity monitoring with the BodyMedia Sensewear Pro III (SP3), a multi-channel pattern recognition device that provides accurate estimates of PA and energy expenditure. After each monitoring day, participants will complete a telephone-administered 24hPAR assessment. After replicate measures of the SP3 and 24hPAR are obtained, self-reported physical activity propensity data will be obtained to provide auxiliary information for estimating models and distributions of usual physical activity. The sequential series of Specific Aims will address unique questions about measurement error in physical activity and lead to the development of procedures and methodologies to facilitate the application of these methods in future research. In Aim 1, we will develop a self- administered physical activity propensity questionnaire (PAPQ) and a 24 hr PA recall (24hPAR) telephone interview that can be administered in a large-scale survey setting. In Aim 2, measurement error models will be estimated for the recall and reference measures in order to estimate the bias and random measurement error structure of measurements. A unique aspect of the proposed modeling is that we will utilize new propensity-based approaches to address the fact that many adults in the population report no physical activity. In Aim 3, the 24PAR will be calibrated against the temporally matched SP3 data so that the measurements essentially behave as if they had been collected using a reference instrument. In Aim 4, the measurement error model and calibration procedures will be used to estimate usual daily physical activity of individuals in subpopulations. The approach in this research is innovative, because it utilizes state of the art monitors and will lead to the development of new statistical techniques to model and correct physical activity measurement error. The proposed research is significant, because it will directly address a complex and long-standing measurement problem in the physical activity field (i.e. obtaining accurate indicators of usual physical activity). This information will help to improve physical activity epidemiology research and facilitate the development of more effective public health surveillance research. The resulting physical activity measurement model from this study will also facilitate future research aimed at jointly modeling error in energy intake and energy expenditure. The project is guided by a strong research team with expertise in all necessary facets of the study (physical activity assessment, survey design and administration, and measurement error modeling).

描述(由申请者提供)：体力活动评估中的测量误差使回答有关体力活动流行率及其与各种与健康相关的结果的关系的重要问题变得困难。本申请的目的是开发和评估统计程序，以对常用和公认的体力活动回忆工具(24小时体力活动回忆24hPAR)中的测量误差进行建模、量化和调整。为了开发合适的统计模型，我们将进行一项体力活动测量调查(PAMS)，从居住在爱荷华州城乡环境中的1200名具有代表性的成年人(19-70岁)中获得回忆和客观的体力活动数据。参与者将使用BodyMedia SenseWear Pro III(SP3)完成为期两天的体力活动监测，这是一种多通道模式识别设备，可以提供PA和能量消耗的准确估计。在每个监测日之后，参与者将完成电话管理的24hPAR评估。在获得SP3和24hPAR的重复测量后，将获得自我报告的体力活动倾向数据，为估计通常体力活动的模型和分布提供辅助信息。连续的一系列具体目标将解决有关体力活动中测量误差的独特问题，并导致制定程序和方法，以促进这些方法在未来研究中的应用。在目标1中，我们将开发一份自我管理的体力活动倾向问卷(PAPQ)和24小时PA回忆(24hPAR)电话访谈，可以在大规模调查环境中进行。在目标2中，将为回忆测量和参考测量估计测量误差模型，以估计测量的偏差和随机测量误差结构。拟议模型的一个独特方面是，我们将利用新的基于倾向的方法来解决人口中许多成年人报告没有体育活动的事实。在目标3中，24PAR将根据时间上匹配的SP3数据进行校准，以便这些测量基本上就像是使用参考仪器收集的一样。在目标4中，将使用测量误差模型和校准程序来估计亚群中个人的日常体力活动。这项研究的方法是创新的，因为它利用了最先进的监测器，并将导致新的统计技术的发展，以建模和纠正体力活动测量误差。拟议的研究意义重大，因为它将直接解决体力活动领域中一个复杂和长期存在的测量问题(即获得通常体力活动的准确指标)。这些信息将有助于改进体力活动流行病学研究，并促进更有效的公共卫生监测研究的发展。这项研究得到的体力活动测量模型也将促进未来旨在联合模拟能量摄入和能量消耗的误差的研究。该项目由一支强大的研究团队指导，该团队在研究的所有必要方面(体力活动评估、调查设计和管理以及测量误差建模)具有专业知识。