[Development of a risk prediction model and a sample risk chart for long-term care certification based on the functional health of older adults]

Objectives The first aim of this study was to develop risk prediction models based on age, sex, and functional health to estimate the absolute risk of the 3-year incidence of long-term care certification and to evaluate its performance. The second aim was to produce risk charts showing the probability of the incident long-term care certification as a tool for prompting older adults to engage in healthy behaviors.Methods This study's data was obtained from older adults, aged ≥65 years, without any disability (i.e., they did not certify≥care level 1) and residing in Yabu, Hyogo Prefecture, Japan (n=5,964). A risk prediction model was developed using a logistic regression model that incorporated age and the Kihon Checklist (KCL) score or the Kaigo-Yobo Checklist (KYCL) score for each sex. The 3-year absolute risk of incidence of the long-term care certification (here defined as≥care level 1) was then calculated. We evaluated the model's discrimination and calibration abilities using the area under the receiver operating characteristic curves (AUC) and the Hosmer-Lemeshow goodness-of-fit test, respectively. For internal validity, the mean AUC was calculated using a 5-fold cross-validation method.Results After excluding participants with missing KCL (n=4) or KYCL (n=1,516) data, we included 5,960 for the KCL analysis and 4,448 for the KYCL analysis. We identified incident long-term care certification for men and women during the follow-up period: 207 (8.2%) and 390 (11.3%) for KCL analysis and 128 (6.6%) and 256 (10.2%) for KYCL analysis, respectively. For calibration, the χ