Model to Predict Oral Frailty Based on a Questionnaire: A Cross-Sectional Study

Tatsuo Yamamoto (), Tomoki Tanaka, Hirohiko Hirano, Yuki Mochida and Katsuya Iijima
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Tatsuo Yamamoto: Department of Dental Sociology, Kanagawa Dental University, Yokosuka 238-8580, Japan
Tomoki Tanaka: Institute of Gerontology, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656, Japan
Hirohiko Hirano: Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Itabashi-ku, Tokyo 173-0015, Japan
Yuki Mochida: Department of Dental Sociology, Kanagawa Dental University, Yokosuka 238-8580, Japan
Katsuya Iijima: Institute of Gerontology, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656, Japan

IJERPH, 2022, vol. 19, issue 20, 1-9

Abstract: A statistical model to predict oral frailty based on information obtained from questionnaires might help to estimate its prevalence and clarify its determinants. In this study, we aimed to develop and validate a predictive model to assess oral frailty thorough a secondary data analysis of a previous cross-sectional study on oral frailty conducted on 843 patients aged ≥ 65 years. The data were split into training and testing sets (a 70/30 split) using random sampling. The training set was used to develop a multivariate stepwise logistic regression model. The model was evaluated on the testing set and its performance was assessed using a receiver operating characteristic (ROC) curve. The final model in the training set consisted of age, number of teeth present, difficulty eating tough foods compared with six months ago, and recent history of choking on tea or soup. The model showed good accuracy in the testing set, with an area of 0.860 (95% confidence interval: 0.806–0.915) under the ROC curve. These results suggested that the prediction model was useful in estimating the prevalence of oral frailty and identifying the associated factors.

Keywords: oral frailty; prediction model; questionnaire; older people; receiver operating characteristic curve; cross-sectional study (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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