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

Area of Science:

• Gerontology
• Public Health
• Biostatistics

Background:

• Oral frailty is a growing concern in aging populations, impacting overall health and quality of life.
• Estimating the prevalence and understanding the determinants of oral frailty are crucial for targeted interventions.
• Existing assessment methods may be resource-intensive, necessitating simpler predictive tools.

Purpose of the Study:

• To develop and validate a statistical predictive model for oral frailty.
• To utilize readily available questionnaire data for assessing oral frailty risk.
• To identify key factors associated with oral frailty in older adults.

Main Methods:

• Secondary data analysis of a cross-sectional study involving 843 patients aged ≥ 65 years.
• Data split into training (70%) and testing (30%) sets using random sampling.
• Development of a multivariate stepwise logistic regression model, validated using Receiver Operating Characteristic (ROC) curve analysis.

Main Results:

• The final predictive model incorporated age, number of teeth present, difficulty eating tough foods, and recent choking incidents.
• The model demonstrated good predictive accuracy in the testing set, achieving an Area Under the ROC Curve (AUC) of 0.860.
• The 95% confidence interval for the AUC was 0.806–0.915, indicating robust performance.

Conclusions:

• The developed statistical model is effective in predicting oral frailty among older adults.
• The model aids in estimating oral frailty prevalence and identifying significant associated factors.
• This questionnaire-based approach offers a practical tool for early detection and management of oral frailty.