Latent Classification and Predictors for AIP Attitudes of the Elderly

This study aims to provide basic data for establishing customized housing policies for the elderly by analyzing attitudes toward aging in place (AIP) among the elderly in an aging society, classifying heterogeneous latent classes, and identifying factors influencing the probability of belonging to each class. the responses of 10,078 elderly people aged 65 or older were analyzed using the data from the 2023 Survey on Seniors. Through Latent Class Analysis, the AIP attitude of the elderly was classified into three types: 'mobile when health deteriorates', 'active AIP high-level', and 'facility conversion if necessary'. Multinomial logistic regression analysis identified age over 75, city/province, housing type, living arrangements, quality of life, debt, annual household income, and employment status as key factors in classifying AIP attitudes. The findings show that older adults' housing preferences are diverse and multidimensional. This necessitates differentiated policies, including staged care systems tailored to health and location, balanced infrastructure, and customized economic support.