Retirement and elderly health in China: Based on propensity score matching.

Abstract

The relationship between retirement and health is important to the formulation of retirement related policies but is a controversial topic, perhaps because selection bias has not been well-addressed in previous studies through traditional analysis methods. Using data from the China Health and Retirement Longitudinal Study (CHARLS), this study explored the potential impact of retirement on the health of elderly Chinese individuals, adjusting for selection bias. We balanced the baseline differences between retirement groups and working groups based on nearest neighbor matching and genetic matching with a generalized boosted model (GBM), and regression analysis was used to evaluate the impact of retirement on the health of elderly individuals. No significant difference was found in any of the covariates between the two groups after matching. Genetic matching performed better than nearest neighbor matching in balancing the covariates. Compared to the working group, the retirement group had a 0.78 (95% CI: 0.65-0.94, P = 0.026) times higher probability of self-reported physical pain, a 0.76 (95% CI: 0.62-0.93, P = 0.023) times higher probability of depression, and a 0.57-point (95% CI: 0.37-0.78, P < 0.001) improvement in cognitive status score. Among male, the retirement group had a 0.89-point (95% CI: 0.45-1.33, P < 0.001) improvement in cognitive status score for low education, a 0.65 (95% CI: 0.46-0.92, P = 0.042) times higher probability of self-reported physical pain for middle education. For female with low education, the cognitive status of the retirement group was significantly higher by 0.99 points (95% CI: 0.42-1.55, P = 0.004), the probability of depression was 0.56 (95% CI: 0.36-0.87, P = 0.031) times higher in the retirement group than in the working group. There was no difference for the middle and high education. Retirement can exert a beneficial effect on the health of elderly individuals. Therefore, the government and relevant departments should consider this potential effect when instituting policies that delay retirement.