Oejin Shin1, Sojung Park2, Ji Young Kang3, Minyoung Kwak4. 1. School of Social Work, University of Illinois Urbana-Champaign, Urbana, IL, USA. 2. Brown School of Social Work, Washington University, Saint Louis, MO, USA. 3. School of Social Work, Hannam University, Daejeon, Republic of Korea. 4. Department of Social Welfare, Daegu University, Gyeongsan-si, Republic of Korea.
Abstract
BACKGROUND: An extensive study investigated the risk factors for low well-being in post-retirement. Most previous studies have taken a unidimensional perspective, focusing on single factors such as financial status, physical health, and mental health. OBJECTIVE: Drawing on the vulnerability framework, we first identify and describe the empirical subgroups of vulnerability among retirees in the United States across four major domains of later life: material, physical, social, and mental vulnerability. Then, we investigate the association between vulnerability profiles and well-being. METHOD: The sample included 3,158 retirees aged 65+ who participated in the Health and Retirement Study (HRS). Latent class analysis was utilized to identify the heterogeneous subgroups of vulnerability, and then a series of OLS regression analyses was conducted to examine the relationship between patterns of vulnerability and well-being. RESULTS: Five vulnerability patterns were identified: material vulnerable (12%), health & social vulnerable (14%), material, health & social vulnerable (6%), least vulnerable (34%), and social vulnerable (35%). The health & social vulnerable group had the strongest negative influence on well-being among all subgroups. As the largest subgroup, the social vulnerable group's negative influence on well-being stood out, with a stronger effect than that of material privation experienced by those in the material vulnerable group. CONCLUSION: By empirically identifying subgroups of differential vulnerability patterns among retirees, this study showed that post-retirement vulnerability reflects complex interactions among multiple disadvantages. Findings of this study enhance understanding of the disparities in well-being within the retired population, pointing to the possibility of targeted policy and program development.
BACKGROUND: An extensive study investigated the risk factors for low well-being in post-retirement. Most previous studies have taken a unidimensional perspective, focusing on single factors such as financial status, physical health, and mental health. OBJECTIVE: Drawing on the vulnerability framework, we first identify and describe the empirical subgroups of vulnerability among retirees in the United States across four major domains of later life: material, physical, social, and mental vulnerability. Then, we investigate the association between vulnerability profiles and well-being. METHOD: The sample included 3,158 retirees aged 65+ who participated in the Health and Retirement Study (HRS). Latent class analysis was utilized to identify the heterogeneous subgroups of vulnerability, and then a series of OLS regression analyses was conducted to examine the relationship between patterns of vulnerability and well-being. RESULTS: Five vulnerability patterns were identified: material vulnerable (12%), health & social vulnerable (14%), material, health & social vulnerable (6%), least vulnerable (34%), and social vulnerable (35%). The health & social vulnerable group had the strongest negative influence on well-being among all subgroups. As the largest subgroup, the social vulnerable group's negative influence on well-being stood out, with a stronger effect than that of material privation experienced by those in the material vulnerable group. CONCLUSION: By empirically identifying subgroups of differential vulnerability patterns among retirees, this study showed that post-retirement vulnerability reflects complex interactions among multiple disadvantages. Findings of this study enhance understanding of the disparities in well-being within the retired population, pointing to the possibility of targeted policy and program development.
Entities:
Keywords:
Latent Class Analysis (LCA); Retirement; vulnerability; well-being
Authors: Jessica R Fernandez; Francisco A Montiel Ishino; Faustine Williams; Natalie Slopen; Allana T Forde Journal: J Am Heart Assoc Date: 2022-06-14 Impact factor: 6.106