A Latent Class Analysis of Intergenerational Relationships Among the Elderly Migrants in Nanjing, China

OBJECTIVE: This study aimed to identify (1) different types of intergenerational relationships among the elderly migrants, (2) factors influencing each type of relationship, and (3) the types significantly associated with psychological well-being of the elderly migrants. METHODS: Data were collected from 654 elderly migrants in Nanjing, China. Incorporating ten solidarity conflict indicators, the latent class analysis (LCA) was performed to classify intergenerational relationships. Logistic regression were used to analyze influencing factors, and ordinary least squares (OLS) regression was used to analyze the relationship of each type of intergenerational relationship with depression and life satisfaction. RESULTS: Three types of intergenerational relationships were classified: tight-knit (65%), conflicting (25%), distant intimate (10%). Gender, marital status, education level, annual income, subjective health, number of children and parentage were influencing factors for the three types. The tight-knit type predicted a healthy mental status. DISCUSSION: Three intergenerational relationships exist between elderly migrants and their children in Nanjing, China. A closer relationship predicts a better mental health in the elderly migrants.