Elsevier

Women's Health Issues

Volume 23, Issue 1, January–February 2013, Pages e61-e67
Women's Health Issues

Original article
Perceived Experiences of Discrimination in Health Care: A Barrier for Cancer Screening Among American Indian Women with Type 2 Diabetes

https://doi.org/10.1016/j.whi.2012.10.004Get rights and content

Abstract

Purpose

Breast and cervical cancer-mortality disparities are prominent among American Indian women. These disparities, in part, may result from patients perceived experiences of discrimination in health care. This report evaluates the impact of perceived discrimination on screening for breast and cervical cancer in a sample of 200 American Indian women with type 2 diabetes.

Methods

Data were collected from patient report and medical records. Prevalence of breast and cervical cancer screening were assessed. Unadjusted and adjusted logistic regression analyses were used to assess associations between perceived discrimination, cancer screening status, and patients' health care-seeking behaviors.

Findings

Substantial proportions of AI women in our sample were behind the recommended schedules of screening for breast and cervical cancer. Adjusted estimates revealed that perceived discrimination was significantly associated with not being current for clinical breast examination and Pap test, and was close to statistical significance with not being current for mammography. The number of suboptimal health care-seeking behaviors increased with higher mean levels of perceived discrimination.

Conclusions

Among AI women, perceived discrimination in health care may negatively influence use of breast and cancer screening services, and health care-seeking behaviors. More research is needed among AIs to examine features of health care systems related to the phenomenon patients perceived experience of discrimination.

Introduction

American Indian (AI) women have higher mortality rates from breast and cervical cancer than non-Hispanic Whites (Espey, Paisano, & Cobb, 2005; Northwest Portland Area Indian Health Board, 2011). One factor that helps to explain these disparities is that AI women are more likely than their non-Native counterparts to be diagnosed with cancer at later stages (Clegg, Hankey, Chu, & Edwards, 2002). Among AI women, a late-stage cancer diagnosis strongly correlates with unmet cancer screening. AI women delay use of cancer screening services and generally receive fewer screenings than other groups (Eberth, Huber, & Rene, 2010; Giuliano, Papenfuss, de Guernsey de Zapien, Tilousi, & Nuvayestewa, 1998). Prominent barriers associated with cancer screening in AI women include availability of services and medical access (Coughlin, Leadbetter, Richards, & Sabatino, 2002; Eberth et al., 2010; Schumacher, Slattery, & Lanier et al., 2008); however, these factors do not entirely explain why AI women underuse cancer screening services.

Reducing cancer mortality rates among AI women may a require better understanding of patient experiences and their influence on patient engagement. For example, two recent studies demonstrate that, among AI women, a positive patient–provider relationship is associated with more favorable Pap test experiences and being current on breast and cervical cancer screening (Simonds, Christopher, Sequest, Colditz, & Rudd, 2011; Smith, Chriostopher, Lafromboise, Letiecq BL, & McCormick, 2008). However, little is known about the specific features of the patient experience for AI women that may undermine engagement in cancer screening.

A promising area of the research that links patient experiences and medical engagement is patients' perceived experiences of discrimination when obtaining health care (Bird & Bogart, 2001; Call et al., 2006; Johansson, Jacobsen, & Buchwald, 2006;Kressin, Raymond, & Manze, 2008). Perceived discrimination in health care (hereinafter “perceived discrimination”) is broadly defined as the belief that one has experienced unfair treatment in a medical setting based on characteristics including race, ethnicity, or other demographic or socioeconomic attributes (Kressin et al., 2008). Perceived discrimination has been associated with lower patient engagement, receipt of fewer health care services, and poorer health (Kressin et al., 2008; Shavers et al., 2012). The associations between perceived discrimination and cancer screenings, however, have been inconsistently demonstrated (Crawley, Ahn, & Winkleby, 2008; Hausmann, Jeong, Bost, & Ibrahim, 2008; Dailey, Kasl, Holford, & Jones, 2007; Shariff-Marco, Klassen, & Bowie, 2010; Simonds, Colditz, Rudd & Sequist, 2011).

In this report, we use a multi-item measure to evaluate the impact of perceived discrimination on screening for breast and cervical cancer in a sample of AI women with type 2 diabetes, a group previously characterized to have low cancer screening despite routine access to health care (Giroux et al., 2000). We hypothesized that perceived discrimination is associated with cancer screening status among AI women. Specifically, we examined 1) status for breast and cervical cancer screening, 2) correlates associated with not being current on cancer screenings, 3) whether perceived discrimination is independently associated with cancer screening status, and 4) associations between perceived discrimination and health care–seeking behaviors.

Section snippets

Methods

During 2008, we collected survey and medical records data from a sample of 270 AI women. The sample was generated from electronic patient medical records managed by four tribally administered health care facilities located on Indian reservations in the Northwest region of the United States. These facilities have similar systems for maintaining patient health data, medical staffing, and health-related services. Demographic information about providers was not obtained. Clinical breast examination

Results

More of the participants were middle-aged (50–64 years of age), had attained a high school education or less, and were unemployed (Table 1). More had diabetes for 1 to 5 years, all had health insurance through the IHS, and 77% had additional sources of health insurance. Fifty-eight percent were not current for clinical breast examination, 45% were not current for mammography, and 39% were not current for Pap testing. Sixty-seven percent perceived discrimination in their health care.

Results from

Discussion

We found substantial proportions of AI women in our sample to be behind on the recommended schedules of screening for breast and cervical cancer, which is consistent with prior research among AIs (Northwest Portland Area Indian Health Board, 2011; Giuliano et al., 1998; Ebert et al., 2010; Simonds & Colditz et al., 2011). Most of the women in our sample had multiple sources of health insurance that could be used to help them access cancer screening elsewhere. Our data show that IHS-only health

Acknowledgments

This research was supported by a number of awards received by Dr. Gonzales including: National Institute of Diabetes and Digestive and Kidney Diseases Award Number F31DK082279; National Cancer Institute (NCI) grant no. UO1-CA 86098; Northwest Health Foundation (NWHF) grant no. F03890; and Northwest Native American Research Center for Health (NW NARCH) grant no. U26IHS300003. The content is solely the responsibility of the authors and does not necessarily represent the official views of the

Kelly L. Gonzales, MPH, PhD, is an Assistant Professor of the School of Community Health in the College of Urban & Public Affairs at PSU. Her research focuses on diabetes-related health disparities experienced by AI/ANs, emphasizing connections with discrimination and health care.

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    Kelly L. Gonzales, MPH, PhD, is an Assistant Professor of the School of Community Health in the College of Urban & Public Affairs at PSU. Her research focuses on diabetes-related health disparities experienced by AI/ANs, emphasizing connections with discrimination and health care.

    Anna K. Harding, PhD, is a Professor and Co-Director of the School of Biological & Population Health Sciences in the College of Public Health & Human Sciences at OSU. Her research expertise is in environmental contamination and population-based risk, tribal environmental exposures, and community engagement.

    Dr. William E. Lambert, PhD, is Associate Professor and Head of the Division of Epidemiology in the OHSU Department of Public Health and Preventive Medicine. His research focuses on health disparities and the prevention of chronic disease.

    Rongwei Fu, PhD, is an associate professor of biostatistics at OHSU Department of Public Health and Preventive Medicine. She has expertise in meta-analysis, Bayesian statistics, categorical data analysis and longitudinal models, and are interested in Bayesian meta-analysis, mixture models and applied methodological research in health science.

    William G. Henderson, MPH, PhD, is a Professor of Biostatistics at the University of Colorado Health Outcomes Program and the Department of Biostatistics and Informatics, School of Public Health, University of Colorado Denver. Dr. Henderson's areas of expertise and interests are clinical trials and health outcomes research.

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