Evaluate Five Different Diagnostic Tests for Dry Mouth Assessment in Geriatric Residents in Long-term Institutions in Taiwan

Yao-Ming Cheng; Shao-Huan Lan; Yen-Ping Hsieh; Shou-Jen Lan; Shang-Wei Hsu


BMC Oral Health. 2019;19(106) 

In This Article


The researchers excluded residents who were confirmed to have neurocognitive disorders by physicians because of physical and psychological diseases, and explored the factors influencing the measurement of residents' oral moisture levels. CHAID analysis revealed that the RSST result, tooth brushing frequency, and age were three best predictors for oral moisture levels. These finding can assist frontline care professionals in performing quick assessments of oral moisture levels among residents in LTC institutions.

The first significant predictor variable was RSST which correlated with the oral moisture levels of residents. Persson et al. (2018) used the absorbent method to collect residents' saliva, and discovered that the measured saliva values did not affect the RSST,[53] which was inconsistent with the results in the present study. The present authors believe this may be caused by different research methods producing different results. Dry mouth is one of the factors affecting oropharyngeal dysphagia.[54] Because dry mouth is a subjective feeling, people with sufficient and insufficient saliva secretion may report symptoms of dry mouth[55] and dysphagia.[16] The results of this study were similar to those of relevant studies in that higher oral moisture levels indicated more satisfactory swallowing function.[16,56]

Shunsuke et al. (2018) reported that a diagnosis of oral dryness was required when the oral moisture value (Mucus, Life Co., Ltd.) was < 27.[57] This result is similar to that of node 1 in the present study; the average value of the residents' oral moisture was lower than 26.392 and the RSST ≤1, indicating that node 1 residents experienced dry mouth and dysphagia. Therefore, caregivers should contact the oral medical team to conduct diagnosis and treatment of dry mouth among node 1 residents.

In addition, node 2 residents exhibited symptoms of dry mouth (average value of oral moisture = 27.96) and dysphagia (RSST = 1–3). The second significant predictor variable was tooth brushing frequency, which correlated with the oral moisture levels of residents of node 2. A brushing frequency of > 1 yielded an average oral moisture value of 28.591, which indicated borderline dry mouth; by contrast, a brushing frequency of ≤1 yielded an average oral moisture value of 27.203, which indicated dry mouth.

The authors believed that tooth brushing frequency was the protective factor for node 5 residents in maintaining oral moisture. Kakudate et al. (2014) reported that mechanical stimulation of the salivary glands during tooth brushing can increase the amount of saliva.[58] Studies have suggested that older adults whose brushing frequency was less than twice per day have a high probability of dry mouth;[58,59] furthermore, switching to using an electric toothbrush increased the residents' salivary flow,[60] indicating that increased salivary flow helps smooth swallowing.[56] Additionally, the intervention results of oral function training programs indicated that they helped increase salivary flow and RSST,[61,62] suggesting that caregivers should focus more on oral hygiene and oral health promotion programs for node 2 residents.

Node 3 residents had borderline dry mouth (average oral moisture value = 28.827); however, they did not exhibit any symptoms of dysphagia (RSST > 3). The third significant predictor variable was age, which associated with the oral moisture levels of residents of node 3. Dry mouth is closely correlated with aging and salivary gland degeneration.[3,15] Previous studies have used varying cut-off points for age. For example, some studies have identified older participants by age of ≥65 years,[11,63] ≥75 years,[64] or ≥ 85 years.[65,66] In the present study, age of 68 years was determined as the cut-off point. The results of this study might have been influenced by limited sample size or methodological differences. We found that the oral moisture level of residents with RSST results ≥3 and age ≤ 68 years were at approximately normal levels; however, those of residents age > 68 years were borderline. This finding furtherly verified that more attention should be directed to oral health status among residents aged > 68 years in LTC institutions even if they possess normal swallowing function.

We believe that the results highlight the importance of enhancing care professionals' knowledge in LTC institutions that lack medical personnel specializing in oral health care or facilities for dry mouth assessment. Teaching such professionals about oral moisture checking and RSST methods, which help ensure the tooth brushing frequency and age indicators of residents, can assist caregivers in simply and conveniently providing assessment and oral care.[49,67] In addition, collaboration with professional dental and medical teams can provide residents with more satisfactory oral health care.

This study had four research limitations. First, we excluded residents who were verified to have neurocognitive disorder by physicians, and the respondents' average ADL score was 67.71 (95% CI, 65.28–70.14), indicating the residents' need for minor help in performing ADLs. Therefore, the results cannot be extended to all LTC residents. However, because oral moisture checking instruments enable easy and quick assessment of residents' level of oral dryness, such instruments can be used in the future to evaluate the level of oral dryness of patients who are bedridden, have severe disabilities, or have neurocognitive disorders.

Second, the aim of this study was to conduct a straightforward measurement of saliva moisture to examine factors influencing residents' dry mouth status. Furthermore, the aim was to help institution personnel focus on simple observation indicators and provide oral health care assessments for residents. We did not specifically focus on the effect of different diseases on dry mouth because the level of dry mouth caused by systematic diseases (e.g., Sjögren syndrome, diabetes, kidney disease, and thyroid diseases) requires various differential diagnoses to be performed (e.g., serum biochemistry, examination of immunology, radiological examination of salivary glands, pathological examination, and examination of salivary cytokines).[68] Furthermore, diagnoses and medical treatments must be performed by a professional medical team.[69]

Third, most residents knew the functions of the medicine they should take, but were unable to correctly provide its product or scientific name. Therefore, this study did not account for the type and dosage of medications that the residents took. More than 500 types of medication can cause dry mouth, clinically such as antihistamines (e.g., diphenhydramine, and chlorpheniramine), anticholinergic agents (e.g., dicyclomine and oxybutynin), and hypotensive agents (e.g., captopril and methyldopa).[70] Tan et al. (2018) reported that using medication with antimuscarinic properties for urinary frequency and incontinence and medication usage for the genitourinary and nervous systems in addition to antidepressants and psycholeptics were associated with dry mouth occurrence.[71] Moreover, the use of antihypertensive and cardiovascular drugs increases the risk of dry mouth.[72] A total of 70% of older adults in care institutions used more than 5 types of medications every day, which showed that the numbers and doses of medications are complex factors in such an analysis.[73] Future research should include doctor and pharmacy teams to evaluate the correlation between medication usage in older adults in care institutions and their dry mouth statuses.

Fourth, the self-developed questionnaires included "The Characteristics of the Residents," "Self-perceived levels of dry mouth," and "Self-perceived ability to chew food." The questionnaire content may have featured a risk of bias and was not subject to verification by different groups. Although we adopted measures such as expert validity and statistical verification to ensure validity and reliability, some potential factors of dry mouth-related care were not considered. Therefore, the results may be biased and should be treated with caution.

Despite these limitations, this study provided empirical evidence for determining factors that influence levels of dry mouth among residents living in LTC institutions. The results can facilitate assessment of dry mouth among high-risk residents, thereby promoting individualized oral care measures. Our results provide frontline care professionals with a set of simple indices for dry mouth. Although the results indicated that the residents' self-perceived oral statuses (i.e., oral health status, dry mouth status, and chewing ability) do not associated with their oral moisture levels.

Future research should explore other possible methods that could be employed for self-assessed detection of dry mouth. Moreover, the interaction effect between diseases of different levels and oral moisture is a pertinent topic for future studies.