Racial/Ethnic Differences in Expectations Regarding Aging Among Older Adults

老年人对衰老的期望存在种族/民族差异

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Abstract

PURPOSE OF THE STUDY: The study identifies differences in age-expectations between older adults from Korean, Chinese, Latino, and African American backgrounds living in the United States. DESIGN AND METHODS: This study uses baseline demographic, age-expectation, social, and health data from 229 racial/ethnic minority seniors in a stroke-prevention intervention trial. Unadjusted regression models and pair-wise comparisons tested for racial/ethnic differences in age-expectations, overall, and across domain subscales (e.g., physical-health expectations). Adjusted regression models tested whether age-expectations differed across racial/ethnic groups after controlling for demographic, social, and health variables. Regression and negative binomial models tested whether age-expectations were consistently associated with health and well-being across racial/ethnic groups. RESULTS: Age-expectations differed by race/ethnicity, overall and for each subscale. African American participants expected the least age-related functional decline and Chinese American participants expected the most decline. Although African American participants expected less decline than Latino participants in unadjusted models, they had comparable expectations adjusting for education. Latino and African American participants consistently expected less decline than Korean and Chinese Americans. Acculturation was not consistently related to age-expectations among immigrant participants over and above ethnicity. Although some previously observed links between expectations and health replicated across racial/ethnic groups, in adjusted models age-expectations were only related to depression for Latino participants. IMPLICATIONS: With a growing racial/ethnic minority older population in the United States, it is important to note older adults' age-expectations differ by race/ethnicity. Moreover, expectation-health associations may not always generalize across diverse samples.

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