A functional joint model with baseline functional covariates: linking sitting accumulation patterns to physical function and mortality among older women

2026-08-17

AI Summary

研究通过提出一种新的功能联合模型，将加速度计数据转换为每日静坐累积模式，并结合基线功能协变量，探讨了静坐行为累积模式与老年女性身体机能和死亡率之间的关系。

Abstract

In large-scale epidemiological studies, it is often of interest to investigate joint relationships between longitudinal and time-to-event outcomes with exposures that are trajectories or functions. Our motivation study is the Objective Physical Activity and Cardiovascular Health (OPACH) Study, which collected accelerometry-measured physical activity in 6,489 older women. One of the scientific aims is to understand sedentary behavior accumulation patterns and its association with physical function (longitudinal) and mortality (time-to-event). We propose a novel approach that first converts raw accelerometry data into daily sitting bout accumulation profiles, which are treated as functional covariates, and then develop a functional joint model for longitudinal and time-to-event outcomes that incorporates a baseline functional covariate. The longitudinal process is modeled using functional data methods and linked to the survival process through functional principal component scores. Both sub-models include interpretable linear scalar-on-function regression coefficients to capture flexible dose-response associations between sitting accumulated across varying bout durations and health outcomes. Estimation is carried out via an efficient expectation-maximization (EM) algorithm with penalized spline approximations. Simulation studies demonstrate accurate parameter estimation and reliable model selection. Application to the OPACH data reveals flexible and interpretable dose-response relationships between sitting bout durations, physical function, and mortality.

Problem

• sedentary behavior
• physical function
• mortality
• functional joint model
• accelerometry

Innovation

• functional joint model
• baseline functional covariates
• accelerometry data
• sitting accumulation patterns
• EM algorithm