Methods:Data were used from the 533 participants aged 60 and older who were part of the Asian American Quality of Life (AAQoL) survey (N = 2,614). Given the interrelated but distinct natures of risk factors and the different weight that each risk factor carries, latent profile analysis was conducted on general (health insurance, financial status, and the existence of usual place for care) and immigrant-specific (length of stay in the U.S., English proficiency, racial/ethnic discrimination, and acculturation) risk factors of the use of preventive health care. The optimal cluster model was selected based on a number of model fit criteria. In the final step of analyses, the logistic model of the use of preventive health care was estimated by including risk cluster types only (unadjusted model) and adding background characteristics (age, gender, ethnicity, education, marital status, and self-rated health) as covariates (adjusted model).
Results: More than 21% of the sample reported that they had not used any preventive health care services. Latent profile analysis identified a three-cluster model (low-risk, moderate-risk and high-risk groups). The low-risk group (n=193) had the most favorable characteristics in terms of their access to health care and cultural and linguistic familiarity to mainstream U.S. society. The high-risk group (n=151) fared worst in all risk variables. In the results of adjusted logistic regression models testing the effect of risk cluster type on the use of preventive health care after controlling after covariates, the high-risk group was 89% less likely to use preventive health care than the low-risk group (95% Confidence Interval [CI] = 0.06−0.22, p< .001). As for background characteristics, Asian Indian and Filipino participants showed greater odds of using preventive health care than Chinese participants.
Conclusions:Findings from latent profile analysis help better understanding of the underlying issues of health care access and the use of preventive health care, suggesting the high-risk group demonstrated heightened vulnerabilities. Findings highlight the importance of not only general access variables but also immigrant-specific variables in identifying risk groups of healthcare access. Further attention in policies and services should be paid to individuals who are in an early stage of immigration and/or with linguistic and cultural barriers.