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Updated: Jul 13, 2025

Oral Health Assessment by Lay Personnel for Older Adults
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Relationship Between Cognitive Function, Oral Conditions and Systemic Metabolic Function in the Elderly.

Kenji Karako1, Yu Chen2, Katsunori Oyama3

  • 1Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan. k.karako@edu.k.u-tokyo.ac.jp.

Advances in Experimental Medicine and Biology
|October 16, 2023
PubMed
Summary

Maintaining good oral health may predict cognitive decline in the elderly. Poor oral health, indicated by fewer teeth and more missing prosthetic teeth, is linked to a higher risk of cognitive impairment, especially when considering systemic metabolic function.

Keywords:
Cognitive functionOral healthSystemic metabolic function

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Area of Science:

  • Gerontology
  • Oral Health
  • Neurology

Background:

  • Systemic metabolic disorders and lifestyle-related diseases are established risk factors for dementia.
  • Oral diseases, such as periodontal disease and tooth decay, are linked to metabolic disorders and may indicate dementia risk.
  • The interplay between oral health, systemic metabolic function, and cognitive decline in the elderly requires further investigation.

Purpose of the Study:

  • To investigate the relationship between cognitive function, oral health status, and systemic metabolic function in an elderly population.
  • To evaluate the efficacy of a deep learning model in estimating cognitive function based on metabolic data and its correlation with oral health.

Main Methods:

  • Study involved 41 elderly participants (average age 69.7 years).
  • Oral health assessed by counting healthy, prosthetic, and missing prosthetic teeth.
  • Cognitive function measured using the Mini Mental State Examination (MMSE) and estimated via a deep learning model using basic blood test data.

Main Results:

  • The deep learning-estimated MMSE scores showed a positive correlation with the number of healthy teeth (r=0.37) and a negative correlation with missing prosthetic teeth (r=-0.39).
  • Estimated cognitive function correlated negatively with age and positively with the number of teeth requiring prosthesis, which also correlated with lifestyle-related diseases.
  • No significant correlation was found between measured MMSE scores and oral health indicators, suggesting the deep learning approach better captures metabolic-oral-cognitive links.

Conclusions:

  • Oral health condition, particularly the number of natural teeth and missing prosthetic teeth, may serve as a predictor for cognitive impairment in the elderly.
  • Deep learning-based cognitive function estimation, reflecting systemic metabolic state, highlights a strong association between oral health and cognitive decline risk.
  • Systemic metabolic function likely influences both oral health and cognitive function, underscoring the importance of integrated health assessments.