Participants
This study’s protocol was approved by the Institutional Review Board of Tokyo Medical and Dental University (Approval ID: D2022-053-01). We recruited healthy asymptomatic adults in 10-year age segments from the 20’s to the 80’s for both male and female participants, respectively, from the community using advertising flyers distributed in public spaces. The inclusion criteria were healthy individuals over 20 years of age who could take part in the trial and had no pain or complaints regarding oral health at the time of participation. The exclusion criteria were neurological disorders and severe dysphagia. All participants provided written informed consent prior to enrollment in this investigation.
Based on previous reports[15, 16], we hypothesized a decline in OHF category measures in the elderly across age groups and sex. Assuming a mean difference of five among the groups and a standard deviation of 10, with α = 0.05 and β = 0.80, the required sample size was calculated to be 128. Therefore, we recruited a cohort of 140.
Measures
Oral function
OHF was proposed by the Japanese Society of Gerodontology in 2016 as the integrated deterioration of several oral functions. The measurement details and OHF cut-off thresholds are described in a previous report[11] and summarized below and in Table 1. OHF was diagnosed as meeting at least 3 of the 7 oral sub-symptom criteria.
Table 1
Seven oral sub-symptoms of oral hypofunction and their cut-off criteria
Oral sub-symptom | Cut-off criterion |
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Oral hygiene (Hygiene) | Total number of bacteria > 106.5 CFU/mL |
Oral dryness (Dryness) | Measured value with a moisture checker < 27.0 |
Maximum occlusal force (MOF) | Occlusal force < 200 N |
Lip-tongue motor function (LTMF) | Utterance count of /pa/, /ta/, or /ka/ <6/s |
Maximum tongue pressure (MTP) | Maximum tongue pressure < 30 kPa |
Masticatory function (Mast-F) | Glucose concentration in chewing test < 100 mg/dL |
Swallowing function (Swal-F) | Total Eating Assessment Tool (EAT-10) score ≥ 3 |
(1) Oral hygiene (Hygiene): A sterilized swab was swiped 3 times in a 10 mm swath on the middle of the dorsal tongue surface and then placed in distilled water into a bacteria detection apparatus (Bacteria counter; Panasonic Healthcare, Tokyo, Japan).[18, 19] Bacteria number was counted 3 times, and the calculated means were log transformed.
(2) Oral dryness (Dryness): The wetness of the buccal mucosal surface was measured by an oral moisture checker (Mucus; Life Co., Ltd., Saitama, Japan).[20, 21] The sensor of the instrument was attached to the right-side buccal surface of the participant for 2 seconds, and the degree of oral wetness was measured in triplicate at the same site for calculation of mean values.
(3) Maximum occlusal force (MOF): Occlusal force was measured by 3 seconds of clenching using pressure-indicating film (Dental Prescale II; GC Corp., Tokyo, Japan).[22] The area of changed color on the sheet caused by clenching was measured by analysis software, calculated as occlusal force, and log transformed for analysis.
(4) Lip-tongue motor function (LTMF): Participants were instructed to say the syllables /pa/, /ta/, or /ka/ as many times as possible within 5 seconds. The number of utterances was counted by a digital counter (Kenkokun Handy; Takei Scientific Instruments Co., Ltd., Niigata, Japan).[23] The minimum number per second for /pa/, /ta/, and /ka/ utterances was calculated and used for analysis.
(5) Maximum tongue pressure (MTP): A tongue pressure sensor balloon probe connected to a digital tongue pressure meter (JMS tongue pressure measuring instrument TPM-01; JMS Co. Ltd., Hiroshima, Japan) was placed on the dorsal tongue surface[15]. Participants were asked to press up against the probe with the tongue towards the hard palate at maximum strength for 3 seconds. After several practice movements, tongue pressure was assessed 3 times for calculation of mean values.
(6) Masticatory function (Mast-F): Masticatory function was measured using a gummy jelly. Participants were instructed to chew 2 g of gummy jelly without swallowing the bolus or saliva for 20 seconds. They were then asked to hold 10 mL of distilled water in their mouth and spit out the jelly and water into a cup fitted with a funneled mesh. The amount of eluted glucose was measured with a masticatory ability testing system (Gluco Sensor GS-II; GC Corp. Tokyo, Japan).[24]
(7) Swallowing function (Swal-F): Swallowing function was assessed by a self-administered questionnaire for swallowing (10-item Eating Assessment Tool; EAT-10) and expressed as a numerical score from 0 to 40.[25]
Physical properties and activities
(1) Body composition: Body mass index was calculated from measured height and weight for analysis. Body composition was measured by bioelectrical impedance analysis using an In Body 470 device (In Body Japan Inc., Tokyo, Japan). Participants stood on the apparatus during measurements. Appendicular muscle mass was divided by the square of the subject’s height and used for calculation of skeletal muscle mass index (SMI). Body fat percentage was determined as well.
(2) HGS: Measurements were carried out in triplicate for each hand with a digital hand dynamometer (Grip-D; Takei Instruments, Niigata, Japan). The maximum HGS in the trials for both hands were used for analysis.
Data analysis
Associations between oral function and physical function
To examine the association between oral function and physical function, simple correlation coefficients were calculated for bivariate analysis. Given the high collinearity between HGS and SMI, HGS was selected for multivariate analysis, for which multiple linear regression was employed. In the regression model, oral function was designated as the dependent variable, while age, sex, number of teeth, and HGS were set as independent variables. The age groups were established as the young group (20 to 39 years), middle group (40 to 64 years), and old group (65 years and older) for statistical analysis. Differences in oral function were scrutinized using one-way ANOVA segmented by age group and sex. If the main effect was significant, Tukey’s test was utilized for multiple comparisons. The proportions of participants who met the criteria for each OHF sub-symptom and overall OHF were calculated. Differences in the proportion of OHF among age groups and sex were evaluated using the chi-square test.
The critical value for rejecting the null hypothesis was P < 0.05. Statistical analyses were performed using IBM SPSS Statistics 28.0 software (IBM, Armonk, NY, USA).