Management of Age-Related Auditory Decline and Early Warning of Its Co-occurring Dementia

Against the backdrop of global population aging, age-related hearing loss (ARHL) has reached epidemic proportions and is increasingly recognized as an independent risk factor for cognitive decline and other major neurodegenerative diseases. This study aims to systematically develop an integrated framework for the early warning, precise assessment, and intervention management of ARHL.

Using a national multicenter design, the project will establish a prospective cohort of more than 3,000 older adults. We will integrate multimodal data including audiological tests, cognitive function assessments, and blood biomarkers, and employ artificial intelligence and unsupervised machine learning methods to address critical bottlenecks in the field: the unclear mechanistic link between ARHL and cognitive decline, and the lack of validated predictive tools.

Specifically, this study will: (1) develop data-driven clinical classification criteria for ARHL; (2) create a personalized "Hearing Health Clock" predictive model; (3) identify minimally invasive blood biomarkers for early detection of cognitive impairment; and (4) formulate a multidimensional early dementia screening program suitable for community-wide implementation. The findings will provide scientific evidence and practical tools for the prevention and control of hearing and cognitive health risks in older adults in China.