Abstract
Objectives: The objectives of this study were (1) to identify distinct subtypes of older Korean immigrants based on their levels of religiosity/spirituality (R/S) and (2) to determine if the identified subtypes differed by demographic characteristics, perceived health, depression, and life satisfaction.Method: Factor mixture models were evaluated with a nonprobability sample of older Korean immigrants (N = 200) residing in the New York City area in 2009 to classify typologies of R/S. Multiple regression was used to test the associations between the R/S subtypes and outcomes (perceived health, depression, and life satisfaction) while controlling for demographics.Results: Two substantively distinct latent profiles were identified: normally religious/spiritual (‘average R/S’) and minimally religious/spiritual (‘low R/S’). The average R/S subgroup (74.4%) showed higher means than those in the low R/S subgroup (25.6%) on all six R/S class indicators. Subtypes did not differ on age, education, income, marital status, living arrangements, or years in the USA. However, males were more likely than females to be ‘average R/S.’ The ‘average R/S’ subtype had significantly greater life satisfaction than their ‘low R/S’ counterpart. No differences between the two subtypes were found on perceived health or depression.Conclusion: Findings highlight the importance of the classifications of R/S for mental health outcomes, and they indicate that relationships among R/S, various demographic characteristics, and physical/mental health are complex. Future research should validate and refine this classification of R/S in order to help identify particular sources of health risks/behaviors, relevant treatments, and health-promoting interventions within homogenous subtypes of older Korean immigrants.
Acknowledgements
The authors are grateful to the Korean older adults who participated in the survey.
Note
Notes
1. Classification probability and entropy are not available for the one-class model and thus comparisons could not be made against this model.