MULTIDIMENSIONAL POVERTY OF OLDER ADULTS IN JAVA ISLAND: A MULTILEVEL BINARY LOGISTIC REGRESSION ANALYSIS - Putra, Dwima Agus Nurcahya; Istiana, Nofita (LPPM Universitas Negeri Jakarta, 2025)
Population aging is a global phenomenon, including in Indonesia, which poses socio-economic challenges. Many older adults still belong to the lowest 40% of household expenditure groups, indicating poor quality of life. Previous studies have generally used monetary measurements, while poverty in older adults is multidimensional, involving health, education, and living standards. This study addresses this gap by analyzing multidimensional poverty among older adults in Java in 2022 using multilevel binary logistic regression with a hierarchical data structure (individuals at level 1 and districts at level 2). The data sources include SUSENAS March 2022 and Province in Figures 2023. The results show that individual factors such as gender, marital status, type of occupation, functional impairment, savings ownership, and residential area, as well as regional factors like GRDP per capita and healthcare facilities ratio, significantly affect multidimensional poverty status among adults. The Intraclass Correlation Coefficient (ICC) is 0.383, confirming substantial variation at the district level, highlighting the importance of multilevel analysis. Furthermore, the model’s goodness-of-fit test concluded that the model is appropriate for explaining the multidimensional poverty status among older adults in Java in 2022. The findings provide comprehensive insights into targeted policy interventions to improve older adults' welfare.