Examining predictive models of HRQOL in a population-based, multiethnic sample of women with breast carcinoma

Abstract

Background: This study examined health related quality of life (HRQOL) and its predictors among African-, Asian-, Latina-, and European American breast cancer survivors (BCS) using a socio-ecologically and culturally contextual theoretical model of HRQOL.

Methods: We employed a case-control, cross sectional design with a population-based sample from the California Cancer Registry. Descriptive, bivariate, and multivariate regression analyses were conducted.

Results: The sample included 703 BCS: 135 (19%) African-, 206 (29%) Asian-, 183 (26%) Latina-, and 179 (26%) European Americans. Latinas reported the lowest HRQOL (p < 0.0001). The final regression model explained 70% of variance in HRQOL. Years since diagnosis, number of comorbidities, role limitation, emotional wellbeing, quality of doctor-patient relationship, social support, and life stress are significant HRQOL determinants. Exploratory regression analyses indicate ethnic differences in significant predictors for HRQOL.

Conclusions: HRQOL among this multiethnic sample ranged from fair to good. Bivariate analysis suggests that ethnic differences in HRQOL exist. However, regression analyses demonstrated that socio-ecological factors in conjunction with medical characteristics are more salient to HRQOL outcomes, and that ethnic group membership may be a proxy for socio-ecological context. Furthermore, the influence of ethnicity, culture, and social-ecology are complex; research with large, population-based samples are necessary to disentangle the impact of contextual factors on HRQOL.