Predicting cognitive function changes from oral health status: a longitudinal cohort study

This prospective longitudinal study protocol was approved by the Institutional Review Board (IRB) of Hyogo Medical University (approval no. Rinhi 0342) and the Ethics Committee of the Faculty of Dentistry, Niigata University (G2021-0027). All participants provided written informed consent. All study methods were performed in accordance with relevant guidelines and regulations. This study was part of the Frail Elderly in the Sasayama-Tamba Area (FESTA) study, which was a medical-dental joint academic survey. From April 2016 to December 2022, the survey included independent, healthy older adults who volunteered and resided in the Sasayama-Tamba area of Hyogo Prefecture. The older adults participated in the survey every two years except from 2019 to September 2021 when the FESTA study was suspended due to the COVID-19 pandemic.

Study participants

Participants were recruited through advertisements in local publications and poster announcements from Hyogo Medical University, Sasayama Medical Centre. The inclusion criteria were as follows: (i) individuals aged 65 years and older living in the Sasayama-Tamba area, Hyogo Prefecture, (ii) independent older adults requiring less than level 1 care under the long-term care insurance system in Japan17 and (iii) participants who had taken part in the survey at least twice. Exclusion criteria were: (i) cognitive impairment (Mini-Mental State Examination [MMSE] score < 20), (ii) a history of cerebrovascular or neuromuscular disease, (iii) missing data, and (iv) participants who did not consent to undergo oral function examination. Before participating, all participants were provided with an explanation of the purpose and methodology of the assessment and were requested to provide a written agreement.

Survey items

Participants completed a self-administered questionnaire that aimed to gather information on their age, sex, and medical history. Additionally, participants were interviewed to gather details on their educational level, history of smoking, hypertension, stroke, and diabetes mellitus, as well as their instrumental activities of daily living, and quality of life. We assessed education level based on the number of years required for completion within the Japanese education system (≤ 12 years or > 12 years of education). To assess instrumental activities of daily living status, we utilized the 13-item Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC), categorized into self-maintenance, intellectual activity, and social role18. A higher score indicates higher levels of competence.

For quality of life assessment, we used the World Health Organization Quality of Life Brief Version (WHOQOL-BREF) questionnaire, a 26-item self-report questionnaire that generates four domain scores19. This questionnaire asked respondents to rate their overall quality of life and their satisfaction with their health, as well as 24 additional items from four domains: physical health, psychological health, social relationships, and environmental health. Overall, quality of life was rated on a five-point scale (very poor, poor, neither poor nor good, good, or very good). The other items were rated on a five-point scale, either as type A (not at all, a little, moderately, mostly, and completely) or type B (very dissatisfied, dissatisfied, neither satisfied nor dissatisfied, satisfied, and very satisfied). Each domain score was calculated, with higher scores indicating a better quality of life.

Assessment of cognitive function

The Japanese version of the Mini-Mental State Examination (MMSE) was used to assess cognitive function. The MMSE score ranges from 0 to 30, with higher scores indicating better performance20. A qualified examiner administered the MMSE at both baseline and follow-up assessments, allowing sufficient time for each. For participants with more than two follow-ups, we selected the follow-up MMSE score that was the furthest from the baseline. To calculate the relative change in the MMSE (rMMSE), we used the following formula: the difference between the follow-up MMSE and baseline MMSE divided by the baseline MMSE.

$$\:rMMSE=\fracFollow\text-up\:MMSE\:-Baseline\:MMSEBaseline\:MMSE$$

Assessment of oral health status

Oral health assessments were conducted by trained and calibrated dental examiners. The participants were seated in reclinable nursing chairs and underwent oral examinations under well-lit conditions. Various factors, such as the number of remaining teeth, occlusal force, masticatory performance, tongue pressure, and oral diadochokinesis, were evaluated.

The term “remaining teeth” refers to the total number of teeth, including both residual teeth and wisdom teeth.

To assess masticatory performance, we adopted a scoring method (ranging from 0 to 9). The participants were given a test gummy jelly (UHA Mikakuto Co., Ltd., Osaka, Japan) and instructed to chew it freely. After 30 chews, they were asked to spit it out into a paper cup covered with gauze21.

We measured the maximum occlusal force of the first left and right molars using an occlusal force meter (Occlusal Force-Meter GM10, NAGANO KEIKI) and calculated the sum of these measurements22. In cases in which the first molar was missing, we measured the maximum occlusal force of the immediately adjacent tooth. For participants wearing removable dentures, measurements were taken while wearing the removable dentures.

Using a tongue pressure measuring device (JMS Co. Ltd., Hiroshima, Japan), we conducted two assessments of maximum tongue pressure23. We recorded the highest value obtained, as low tongue pressure reflects dysphagia24.

To evaluate tongue motor function (oral diadochokinesis), we used oral function measurement equipment (KENKOU-KUN handy; Takei Scientific Instruments Co., Ltd., Niigata, Japan) to measure the articulatory velocity of /ta/25.

Assessment of physical function

The physical function of each participant was assessed by measuring their normal walking speed, knee extension strength, retention time of standing on one leg, and hand grip strength.

During the walking speed test, participants were instructed to walk at their normal speed. We recorded the normal walking speed (m/sec) (referred to as the “walking speed” hereafter) and analysed the data. We also evaluated any changes in walking speed from the start to the end of the walking range, which was a total of 12 m (10 m measurement range with 1 m from the front and 1 m from the end).

To measure knee extension strength, we used a manual muscle strength meter (Mobie, SAKAI Medical). The subjects were asked to sit upright with their knee joints bent at a 90-degree angle to prevent their gluteal region from rising. We measured the dominant leg twice and recorded the maximum torque (N) from the two measurements26.

For the retention time of standing on one leg with eyes open (referred to as “one-leg standing”), we began measuring when the subjects’ dominant leg left the floor and their hands touched their waist. The time (in seconds) until the patient’s hands moved away from their waist, the position of their foot changed, or any part of their body outside from the supporting foot touched the floor was measured27. The duration of the one-leg standing test was limited to a maximum of 60 seconds, and the test was terminated once this time was achieved.

We measured the participants’ hand grip strength using a digital grip strength meter (Takei Kikai Kogyo Co., Ltd., Niigata, Japan). Measurements were taken while the participants were standing, and the maximum grip strength of the dominant hand was recorded after two trials using the highest value as the grip strength measurement28.

Statistical analysis

The data were checked for normality using the Shapiro-Wilk method. The Student’s t-test was used to compare data that followed a normal distribution. For non-parametric data, the Mann-Whitney U test was used. To assess the relationships between the rMMSE and various explanatory variables, including oral health factors and factors related to cognitive function, Pearson’s correlation analysis was performed. Additionally, to assess the factors associated with changes in cognitive function, multiple linear regression analysis was conducted, using the rMMSE as the dependent variable and considering confounding variables such as physical function and medical history. Explanatory variables with a p-value < 0.1 in the univariate correlation coefficient were included in the multiple linear regression analysis after adjusting for age, sex, and follow-up duration. Statistical analysis was performed using SPSS (version 24, IBM, Tokyo, Japan), and the significance level was set at 5%.

link

By admin

Leave a Reply

Your email address will not be published. Required fields are marked *