The trajectory of intrinsic capacity and its related factors among elderly Chinese patients with cardiovascular disease: a prospective cohort study

Abstract

Objectives: To track the dynamic trajectory of intrinsic capacity (IC) in elderly patients with cardiovascular disease (CVD), and systematically assess the statistical associations between baseline characteristics, time-varying factors and distinct trajectory groups. Methods: The data were procured from the China Health and Retirement Longitudinal Study in 2011, 2013, and 2015, encompassing 701 elderly patients with CVD. The Group-based Trajectory Model (GBTM) was used to fit the developmental trajectory of IC in these patients and to identify the types of longitudinal change trajectories of IC. Unordered multinomial logistic regression was utilized to evaluate the strength of the association between non-time-varying baseline characteristics and trajectory classifications, while a panel regression model was applied to analyze the association patterns between time-varying indicators and the dynamic evolution of these trajectories. Results: The GBTM model identified three categories of IC trajectories among elderly patients with CVD: the low-decreased group (n=162, 23.11%), the high-increased group (n=196, 27.96%), and the medium-stable group (n=343, 48.93%). The classification of the IC trajectories in elderly CVD patients is connected with baseline characteristics and time-varying factors. The analysis of associated factors show that non-time-varying characteristics such as educational level, residential area, housing type, toilet facilities, and energy sources, are significantly associated with the IC trajectories of CVD patients. Marital status, masticatory function, sleep disorders, chronic pain, comorbid chronic diseases, and the diversity of social activities exhibit a dynamic association with the evolution of the IC trajectory patterns. Conclusions: IC development in elderly patients with CVD is characterized by both group heterogeneity and individual variability. Consequently, healthcare providers can develop personalized health management programs based on the characteristics of different patients.