Campus Alert: Find the latest UMMS campus news and resources at umassmed.edu/coronavirus

Search Close Search
Search Close Search
Page Menu

Yiyang Yuan received an NIH-funded F99/K00 research award for Predoctoral Students

Doctoral candidate Yiyang Yuan received an NIH-funded F99/K00 research award for Predoctoral Students entitled “Concurrent trajectories of physical frailty and cognitive impairment among nursing home residents and community-dwelling older adults.”

Physical frailty and cognitive impairment are prevalent age-related conditions that often co-occur and are strongly correlated with depression in older adults. Studies on the burden and development of these two conditions in nursing home residents are limited, and the findings on the underlying mechanisms between physical frailty and cognitive impairment and the role of depression and antidepressants on their progression are inconsistent.

In this study, the prevalence, heterogeneous clinical presentation, and trajectories of physical frailty and cognitive impairment in older U.S. nursing home residents will be characterized. Next, the relationship between physical frailty and cognitive impairment will be elucidated and the impact of depressive symptoms and antidepressants in the development of both conditions explored in U.S. community-dwelling older adults. Data sources include the national nursing home database Minimum Data Set 3.0, the nationally-representative Health and Retirement Study linked to Medicare Part D Drug Event Files, and the Harmonized Cognitive Assessment.

Methodological innovations include the use of latent class analysis, group-based trajectory models, structural equation models (autoregressive cross-lagged panel analysis; autoregressive latent trajectory model), and causal mediation. This work is directly relevant to the growing aging population in the U.S., including those residing in the nursing homes and those living in the community.

This project will shed light on the concurrent progression of age-related physical and cognitive conditions. Results will inform future work to develop diagnostic tools and prediction models to facilitate timely identification of older adults at risk for accelerated functional decline, and implement care tailored to older adults’ need to effectively delay the onset of negative health outcomes, enhance quality of life, and foster a healthy longevity.