A cross-sectional study was conducted involving community-dwelling participants aged 65 years or older in Kaohsiung, Taiwan from May 2018 to January 2019. The study adopted a multistage, stratified cluster sampling method to select individuals from the older adults population. Kaohsiung City has 39 districts in three geographic classifications (urban, rural, and mountainous areas). In the first stage of sampling, 25 districts were randomly selected from the 39 districts according to the probability proportional to size sampling method. In the second stage, community care centers in the 25 districts were randomly selected. In the final stage, older adults aged 65 years or older were recruited from each community care center selected. In total, 1180 participants were recruited from urban areas (n = 609), rural areas (n = 555), and mountainous areas (n = 16).
Participants were excluded if they self-reported any of the following: (a) mental disorders, (b) expressive language disorders, (c) moderate or severe cognitive impairment, as determined by a short portable mental status questionnaire (SPMSQ) (15), (d) high-to-total dependence in Activities of Daily Living (ADL) (16), or (e) moderate-to-severe depression, as assessed using the Geriatric Depression Scale (GDS) (17). The final analysis included 1,076 participants (response rate: 91.2%).
According to the sample size criteria for SEM analysis, a large sample size was required for our highly complex model with numerous free parameters. The ideal sample size is generally considered to be 20 participants per free parameter (18). This study had 11 free parameters, and 220 was therefore set as the minimum sample size.
Instrument
A structured questionnaire was developed to collect data on demographics (i.e., age, sex, education level), depression level, oral function (i.e., xerostomia and dysphagia), physical function (i.e., frailty, sarcopenia), and OHRQoL. All instruments were translated from English to Chinese and back-translated to English by bilingual research staff and then verified for accuracy by two senior researchers. Items were reviewed by a panel of experts to assess content validity. The content validity index was 0.89–1.00. To ensure that the study participants understood the content, the questionnaires were pilot tested on 30 older adults. The reliability of each scale was assessed in terms of internal consistency (Cronbach’s alpha coefficient). Masticatory performance was assessed using color-changeable chewing gum (Xylitol, 3.0 g; Lotte, Saitama, Japan).
Dental Examination
Dental examinations were performed by seven dentists according to World Health Organization criteria. The kappa coefficient of tooth decay was 0.77 for interrater agreement. The Kendall’s W coefficient for the plaque index was 0.87 for interrater agreement. The dental status and oral hygiene (i.e. plaque index and tongue coating) were recorded.
Oral Health-related Quality of Life
OHRQoL was measured using the Geriatric Oral Health Assessment Index (GOHAI), which is a 12-item instrument with three domains: physical function (eating, speech, and swallowing), psychosocial function (worry or concern regarding oral health, dissatisfaction with appearance, self-consciousness regarding oral health, and avoidance of social interaction because of oral problems), and pain or discomfort (medication use to relieve oral pain or discomfort). The English version of the GOHAI was translated into Chinese for the participants (GOHAI-T) (19). Each item in the GOHAI was rated on a 5-point Likert scale ranging from, 1 (always) to 5 (never). The total score ranged from 12 to 60 points, with a higher score indicating a more favorable OHRQoL. The Cronbach’s alpha indicated an internal consistency of 0.75 for the scales.
Xerostomia
A condenced version of the Xerostomia Inventory was used to identify and classify mouth dryness. Participants responded to five items: (a) “My mouth feels dry when I eat a meal,” (b) “My mouth feels dry,” (c) “I have difficulty eating dry foods,” (d) “I have difficulty swallowing certain foods,” and (e) “My lips feel dry.” Each item was assigned a score of 1 (never), 2 (occasionally), or 3 (often) (20). The total score ranged from 5 to 15 points, with a higher score reflecting a higher level of mouth dryness. Participants with total scores of ≥10 points represented the top 50% of total xerostomia scores (21). The Cronbach’s alpha indicated an internal consistency of 0.88 for the scale.
Dysphagia
The dysphagia variable was measured using 15 questions in the Ohkuma questionnaire to rapidly screen the community members; examples of questions included “Do you ever have difficulty swallowing?” “Do you ever have difficulty as a result of cough up phlegm during or after a meal?” “Does it take you longer to eat a meal than it used to?” “Do you feel that it is becoming difficult to eat solid foods?” and “Do you ever have difficulty sleeping because of coughing during the night?” (22). Possible responses were “obviously” (frequently), “slightly” (sometimes), or “no” (never). Respondents with at least one severe symptom were classified as having dysphagia. The Cronbach’s alpha value was 0.85, indicating satisfactory internal consistency.
Masticatory Performance
Masticatory performance was evaluated using color-changeable chewing gum. The gum changes to red when chewed because the yellow and blue dyes seep into saliva, and citric acid elution produces the red color (23). Participants were asked to chew for 2 minutes. The observer assessed the color of the gum by using a color chart with five color gradations ranging from 1 (very good) to 5 (very poor). The masticatory performance scoring was simplified into three categories, 1–3 = good, 4 = moderate, 5 = poor.
Occlusal Condition
Occlusal condition was measured using the Eichner index (24), which is based on the number of posterior occlusal contacts of functional teeth in the premolar and molar regions—called support zones. The posterior regions are divided into four support zones on both sides and are classified in Eichner categories A, B, or C. Class A has contacts in four support zones; class B has contacts in one to three support zones or only in the anterior region; and class C has no contact with any support zones, although a few teeth may remain.
Dental Status
The variables related to dental status were the numbers of remaining natural teeth, functional teeth, fixed artificial teeth, complete dentures, and removable partial dentures. The number of functional teeth was defined as the number of natural teeth, excluding teeth with grade III mobility and residual roots, and fixed artificial teeth (i.e., abutment teeth, bridge, and implant-supported prostheses).
Oral Hygiene Status
The plaque index was used to record plaque scores for four surfaces (buccal, lingual, mesial, and distal) of tooth numbers 12, 16, 24, 32, 36, and 44; scores ranged from 0 to 3. Tongue coating was assessed using the Winkel tongue coating index (25). The tongue was divided into six areas (three posterior and three anterior), and the coating was scored as 0 = no coating, 1 = light coating, or 2 = severe coating; scores ranged from 0 to 12 points.
Covariates
Physiological and psychologic or psychiatric state may potentially be affected by oral health status. Therefore, we examined age, sex, educational level, frailty and sarcopenia as the covariates. Moreover, because a self-reported data collection process was adopted, participants with cognitive impairment (moderate or severe cognitive impairment) were excluded from the study. Frailty was assessed using the Study of Osteoporotic Fractures index (SOF) (26). Sarcopenia was assessed using the SARC-F self-administered questionnaire (27). Finally, all covirates collected during the study were retained in the final model for pathway analysis.
Data Collection
Data were collected by thoroughly trained interviewers during face-to-face interviews in accordance with standard protocol. To prevent information bias during interviews, each interviewer attended a 1-hour training course on the standard process and data collection criteria. The data collection process comprised three steps. First, a dentist performed a dental examination, and a dental hygienist recorded the dental status, plaque index score, and tongue coating score. Second, a structured questionnaire was administered by an interviewer in Mandarin or Taiwanese. The entire interview process took approximately 30−45 minutes. Finally, the research staff collected data on masticatory performance, assessed according to the results of participants chewing color-changing gum, and on physical function and frailty.
Statistical Analysis
Stata 13.1 (StataCorp LP, College Station, TX, USA) was used for statistical analysis. Participants were divided into two groups according to their xerostomia status. The demographic characteristics, dental status, oral function, and physical function were compared between the two groups by using chi-square tests and two-sample t tests. A multiple linear regression model was adjusted using the hierarchical method to obtain a predictive model for OHRQoL. To adjust the final model, changes in the adjusted R2 and F values were considered for each new independent variable added, and the variance inflation factor (VIF) was used to assess multicollinearity among all independent variables. Path analysis was then used to test a model exploring the relationships of xerostomia, dental status, oral function with OHRQoL and to identify both direct and indirect relationships in the model. Path analysis is specific to SEM and invloves the simultaneous analysis of the assumed relationships in multivariate data. SEM is one of the most favored statistical techniques in the social sciences and has become popular in dental science (28, 29). In the present study, the following criteria were used to define model goodness of model fit: χ2/df < 3.00, root mean square error of approximation (RMSEA) < 0.08, and comparative fit index (CFI) ≥ 0.90. To obtain an acceptable model, initial fit, modification (using the motivational interviewing method in Stata), and rafting steps were followed (30). After the fit of the full model was estimated, nonsignificant direct paths were removed to generate a statistically parsimonious model, after which reestimation was performed for comparison with the full model using a chi-square test. Finally, all the steps were repeated until a good fit was achieved for the model. Significance was set at p < .05 for all statistical tests.