Multidimensional Factors Associated With Social Isolation Trajectories Among Older Chinese Immigrants

Social isolation is prevalent among older immigrants, yet the multidimensional factors contributing to it remain understudied. Using data from five waves of the Population Study of Chinese Elderly in Chicago (<i>N</i> = 2,835), this study identified social isolation change trajectory patterns over eight years and examined contributing factors across ecological systems. Social isolation was measured by the social disconnectedness index. The multidimensional factors included socio-demographic and health conditions, interpersonal relationships, immigration experiences, and neighborhood characteristics. Latent class growth analysis identified four distinct change trajectories, including "Persistent Low", "Persistent Medium", "Persistent High", and "Increasing" isolation. Multinomial logistic regression indicated that older age, being female, lower social support and social strain, longer U.S. residence, and neighborhood physical disorder predicted greater social isolation. Stronger sense of community and social cohesion unexpectedly heightened the likelihood of "Persistent High" isolation. Findings highlight the need for culturally sensitive and multidimensional interventions to address social isolation among older immigrants.

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Publication Details

Journal
Research on Aging
Published
2026-02-15
DOI
https://doi.org/10.1177/01640275261427313
Primary Topic
Health disparities and outcomes
Type
article
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article

Multidimensional Factors Associated With Social Isolation Trajectories Among Older Chinese Immigrants

Wendi Da, Fengyan Tang, Yanping Jiang, BoRin Kim et al.
Research on Aging
Health disparities and outcomes
article

Multidimensional Factors Associated With Social Isolation Trajectories Among Older Chinese Immigrants

Wendi Da, Fengyan Tang, Yanping Jiang, BoRin Kim, Ke Li
article en

Abstract

Social isolation is prevalent among older immigrants, yet the multidimensional factors contributing to it remain understudied. Using data from five waves of the Population Study of Chinese Elderly in Chicago (<i>N</i> = 2,835), this study identified social isolation change trajectory patterns over eight years and examined contributing factors across ecological systems. Social isolation was measured by the social disconnectedness index. The multidimensional factors included socio-demographic and health conditions, interpersonal relationships, immigration experiences, and neighborhood characteristics. Latent class growth analysis identified four distinct change trajectories, including "Persistent Low", "Persistent Medium", "Persistent High", and "Increasing" isolation. Multinomial logistic regression indicated that older age, being female, lower social support and social strain, longer U.S. residence, and neighborhood physical disorder predicted greater social isolation. Stronger sense of community and social cohesion unexpectedly heightened the likelihood of "Persistent High" isolation. Findings highlight the need for culturally sensitive and multidimensional interventions to address social isolation among older immigrants.

Research on Aging
Rutgers, The State University of New Jersey (US), University of Pittsburgh (US), University of New Hampshire at Manchester (US), Ohio University (US)
Reduced inequalities
Openalex Percentile: Top 64%
Health disparities and outcomes
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Multidimensional Factors Associated With Social Isolation Trajectories Among Older Chinese Immigrants — Wendi Da, Fengyan Tang, et al. · Research on Aging (2026) | TGRS Research Map | TGRS