OSW

SIGNATURE WORK
CONFERENCE & EXHIBITION 2022

Socioeconomic Status and Successful Aging Among the Elderly in China: Evidence from the China Health and Retirement Longitudinal Survey (CHARLS)

Name

Yifan Song

Major

Data Science

Class

2022

About

Yifan Song is a Data Science major at Duke Kunshan University who is passionate about solving practical problems through data science techniques.

Signature Work Project Overview

As the Chinese society is entering an advanced stage of aging, many problems regarding living conditions and health care are becoming alarming. However, the relationship between the aging condition and socio-economic status (SES) requires further examination. This paper is dedicated to evaluating the aging outcomes among the Chinese elderly using the successful aging (SA) model defined by Rowe and Kahn. It aims to examine the relationships between multiple aspects of SA and measures of SES in China. Based on the data of participants aged 60 or above from CHARLS 2018, 5 different indicators of SA measure are evaluated and three important SES indicators (education, occupation type, and the log of per capita expenditure) are included. Multivariable logistic regression, random forest regression, and OLS regression models are built for the association evaluation. The analysis shows that the overall prevalence of SA is 11.1% and the rate has significant variances among different demographical subgroups. SES is found to have a significant positive correlation with SA and each of the SA indicators. Meanwhile, each SES indicator shows a different emphasis in terms of its influence on the SA gradient. These results depict a holistic profile of the Chinese aging population and aging experiences from an SA perspective, which underlines the importance of taking the SES variations into account when understanding the aging process of Chinese elderly people, examining current plans, and formulating relevant policies for the future.

Signature Work Presentation Video