Dose-Response Relationship Between Age and Pension Patterns in People Aged 60 and Above in the Context of Precision Pension: Evidence From the CHARLS Database

Speaker(s)

ABSTRACT WITHDRAWN

OBJECTIVES: With the aging population in China, home-eldercare is inadequate for the diverse needs of seniors. Due to various factors, elderly individuals of varying ages opt for different pension models. Hence, this study investigated the dose-response relationship between age and elderly people’s selection of pension modes, based on the concept of precision eldercare.

METHODS: A total of 10,818 elderly people aged 60 years and older were selected from the CHARLS 2018 database, with SPSS 23.0 and R 4.3.3 for statistical analysis. Lasso regression and a multi-factor Logistic regression model was established to analyze the influencing factors of pension model selection.The dose-response relationship between age and pension mode choice was studied by restricted cubic spline, and the gender difference was analyzed.

RESULTS: The average age of the subjects was (69±7.16) years, and the male to female ratio was 1:1. The old-age care model includes home-care and non-home- care , of which 10,594 people choose home-care (97.9%). lasso regression screen out six key variables: age, residence region, marital status, pension insurance, income, and job type. Combined with multivariate Logistic regression model and restricted cubic spline, it is found that the elderly aged 60~67 tend to choose home care and with the increase of age, OR is gradually close to 1; The elderly aged 68 and above tended to choose non-home-care and the OR gradually increased, At age 70, there began to be a positive and significant association between age and choice of non-home care (OR: 1.07, 95%CI: 1~1.16). In addition, it is found that men are more inclined to choose home care than women.

CONCLUSIONS: There is a dose-response relationship between age and aged care mode selection in people aged 60 and above.

Code

HSD34

Disease

Geriatrics, Personalized & Precision Medicine