Relative deprivation patterns in social and geographical references for health trajectories in China: Investigations of gender and urban-rural disparities

A pervasive link between relative deprivation and health has been well-documented. However, prior studies suffered from inadequate relative deprivation measures that fail to define appropriate reference groups to which individuals compare themselves, and few provided longitudinal evidence. This study explores latent relative deprivation patterns based on multiple social and geographic reference groups, examining their impacts on health trajectories and variations by gender and urban-rural areas.Using three waves (2013, 2015, & 2018) of the China Health and Retirement Longitudinal Study (n = 6035), we conducted latent class analysis (LCA) to identify the baseline latent relative deprivation patterns among five social and geographic reference groups (relatives, schoolmates, colleagues, neighbors, and other people in the city or county). The LCA results were linked to the latent growth curve parallel process modeling (PPM) to investigate the impacts of deprivation patterns on dual health trajectories (depressive symptoms and self-rated health), and the results were stratified to explore gender and urban-rural differences.The LCA revealed a relatively deprived group (36.39%) and a non-deprived group (63.61%). The PPM results indicated that the relatively deprived group showed a higher initial level of depressive symptoms and a lower initial level of self-rated health than the non-deprived group. However, the relatively deprived group showed a slower growth rate in depressive symptoms than the non-deprived group. These findings were particularly evident among women and rural residents.Findings emphasize the negative impact of relative deprivation on health. Furthermore, there is a complex interplay in these effects intertwined with gender and locality. Policies aimed at promoting mental health should not only consider relatively deprived groups, but also non-deprived women and rural residents who are at higher risk for later-life depression.