# Identifying mechanisms between hearing loss and falls

> **NIH NIH R01** · DUKE UNIVERSITY · 2024 · $663,401

## Abstract

ABSTRACT
Falls result in substantial morbidity, mortality, and disability among older adults. Recently, hearing loss and
hearing handicap have been identified as independent risk factors for falls. It is unclear the factors that mediate
the association between hearing loss and falls. The long-term goal is to to develop novel interventions that will
modify falls risk in the hearing impaired patient population. The current objective is to identify and understand
the auditory and vestibular related factors that explain the association between falls and hearing loss and to
characterize performance on these candidate factors. To that end, our proposal aims to examine the vestibular-
related factors, centrally mediated auditory factors (spatial hearing and listening effort), cognitive, and
psychosocial factors in an older adult patient population of fallers and non-fallers. The current proposal is
innovative as the work will characterize the extent to which key theoretical factors explain the link between falls
and hearing loss and specifically the extent to which unrecognized vestibular dysfunction may explain the
association. These contributions will be significant, as they will inform strategies to implement targeted
rehabilitation programs to reduce falls and falls-risk in this patient population.

## Key facts

- **NIH application ID:** 10890840
- **Project number:** 5R01DC020440-02
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Kristal Mills Riska
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $663,401
- **Award type:** 5
- **Project period:** 2023-08-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10890840

## Citation

> US National Institutes of Health, RePORTER application 10890840, Identifying mechanisms between hearing loss and falls (5R01DC020440-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10890840. Licensed CC0.

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