Relationship Between Cognitive Function, Oral Conditions and Systemic Metabolic Function in the Elderly.

Systemic metabolic disorders, including lifestyle-related diseases, are known risk factors for dementia. Furthermore, oral diseases such as periodontal disease and tooth decay are also associated with systemic metabolic disorders such as lifestyle-related diseases, and have also been reported to be indicators of risk factors for developing dementia. In this study, we investigated the relationship between cognitive function, oral conditions and systemic metabolic function in the elderly. We investigated the number of healthy teeth, the number of prosthetic teeth fitted, the number of missing prosthetic teeth, etc., in 41 elderly patients (69.7 ± 5.6 years old). Cognitive function was evaluated by the Mini Mental State Examination (MMSE). We also estimated MMSE scores for each subject using deep learning-based assessment of MMSE scores. This deep learning method enables the estimation of the MMSE score based on basic blood test data from medical examinations and reflects the systemic metabolic state including lifestyle-related diseases. The estimated MMSE score correlated negatively with age (r = -0.381), correlated positively with the number of healthy teeth (r = 0.37), and correlated negatively with the number of missing prosthetic teeth (r = -0.39). This relationship was not found in the measured MMSE scores. A negative correlation (r = -0.36) was found between age and the current number of teeth and a positive correlation (r = 0.37) was found between age and the number of missing prosthetic teeth. A positive correlation was found between the number of teeth requiring prosthesis and lifestyle-related diseases. The deep learning-based estimation method of cognitive function clearly demonstrated the close relationship between oral health condition, systemic metabolic function and the risk of cognitive impairment. It was determined that the smaller the number of existing teeth and the larger the number of missing prosthetic teeth, the higher is the risk of cognitive impairment. Systemic metabolic function is presumed to affect oral health and cognitive function. Interestingly, no such relationship was found in the measured MMSE scores. There are two possible reasons for this. The first is that MMSE is a subjective test and is less accurate in assessing cognitive function. The second is that because the MMSE estimated based on blood data using deep learning is calculated based on the metabolic function, it has a stronger correlation with the oral health condition affected by the metabolic function. In conclusion, oral health condition may predict cognitive impairment in the elderly.