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

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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.

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Abbreviations

ADQ:

Adherence Determinants Questionnaire

ANOVA:

Analysis of variance

BCS:

Breast cancer survivors

BCSS:

Breast cancer specific subscale (from the FACT)

CCR:

California Cancer Registry

FACT:

Functional Assessment of Cancer Therapy

HRQOL:

Health related quality of life

SES:

Socio-economic status

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Acknowledgements

Research supported by a Grant from the CDBMRP-DOD (17-99-1-9106).

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Authors and Affiliations

  1. Center of Community Alliance for Research and Education (CCARE), Division of Population Sciences, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, CA, USA

    Kimlin T. Ashing-Giwa & Judith S. Tejero

  2. Center for Culture and Health, UCLA School of Medicine, Los Angeles, CA, USA

    Kimlin T. Ashing-Giwa & Judith S. Tejero

  3. Department of Community Health Sciences, UCLA School of Public Health, Los Angeles, CA, USA

    Jinsook Kim

  4. Department of Nursing, University of California, San Francisco, CA, USA

    Geraldine V. Padilla

  5. Semel Institute of Neuropsychiatry — Biostatistics Core, UCLA, Los Angeles, CA, USA

    Gerhard Hellemann

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  1. Kimlin T. Ashing-Giwa
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  2. Judith S. Tejero
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Correspondence to Kimlin T. Ashing-Giwa.

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Ashing-Giwa, K.T., Tejero, J.S., Kim, J. et al. Examining predictive models of HRQOL in a population-based, multiethnic sample of women with breast carcinoma. Qual Life Res 16, 413–428 (2007). https://doi.org/10.1007/s11136-006-9138-4

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