使用部分线性Fréchet单指标模型预测NHANES数据库中身体活动谱的分布
Predicting Distributions of Physical Activity Profiles in the NHANES Database Using a Partially Linear Fréchet Single Index Model
AI总结：
本文提出部分线性Fréchet单指标模型，将加速度计身体活动数据表示为分布对象，分析NHANES 2011-2014数据中年龄非线性效应及种族、性别等线性效应，为美国亚人群身体活动干预提供依据。
摘要：
面向对象的数据分析是现代统计科学中一个迷人且不断发展的领域，具有为生物医学应用做出重要贡献的潜力。这一统计框架有助于开发新方法来分析复杂数据对象，这些对象比传统临床生物标志物捕获更多信息。本文将面向对象的框架应用于分析由加速度计测量的身体活动水平，并将其作为回归模型中的响应对象。与传统汇总指标不同，我们采用最近提出的一种将身体活动数据表示为分布对象的方法，从而在所有监测强度范围内提供个体能量消耗的更细致、更完整的谱。我们提出了一种新颖的混合Fréchet回归模型，并将其应用于来自2011-2014年美国国家健康与营养调查（NHANES）的美国人群加速度计数据。该模型的半参数性质允许纳入关键变量（如年龄）的非线性效应，从生物学上已知年龄对身体活动有微妙影响。同时，纳入线性效应保持了其他变量的可解释性，特别是种族和性别等分类协变量。从公共卫生角度看，所获得的结果具有重要价值，并可能为优化特定美国亚人群的身体活动干预提供新策略。
英文摘要：
Object-oriented data analysis is a fascinating and evolving field in modern statistical science, with the potential to make significant contributions to biomedical applications. This statistical framework facilitates the development of new methods to analyze complex data objects that capture more information than traditional clinical biomarkers. This paper applies the object-oriented framework to analyze physical activity levels, measured by accelerometers, as response objects in a regression model. Unlike traditional summary metrics, we utilize a recently proposed representation of physical activity data as a distributional object, providing a more nuanced and complete profile of individual energy expenditure across all ranges of monitoring intensity. A novel hybrid Fréchet regression model is proposed and applied to US population accelerometer data from National Health and Nutrition Examination Survey (NHANES) 2011-2014. The semi-parametric nature of the model allows for the inclusion of nonlinear effects for critical variables, such as age, which are biologically known to have subtle impacts on physical activity. Simultaneously, the inclusion of linear effects preserves interpretability for other variables, particularly categorical covariates such as ethnicity and sex. The results obtained are valuable from a public health perspective and could lead to new strategies for optimizing physical activity interventions in specific American subpopulations.
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