The 130th Annual Meeting of APHA

Abstract #45177

Laura Anderko, RN PhD, School of Nursing, University of Wisconsin-Milwaukee, Cunningham Hall 699, P.O. Box 413, Milwaukee, WI 53201, 414 229-2313, landerko@uwm.edu

Although socioeconomic status (SES) and its association with cancer incidence, mortality, and survival have been studied for many years, findings are limited by the quality of data used to define SES. This study analyzed data from 9,496 women who participated in the Cancer Epidemiology Supplement of the 1987 National Health Interview Survey, to explore the relationships among various socioeconomic indicators and self-reported cancer history in U.S. women, using Syme’s Social Determinants of Health and Disease model to guide the analysis. This study is unique from previous studies in that it controlled for many potential risk factors and utilized a comprehensive definition of SES that included individual-level measures of education, occupation and income. Although past research findings have identified women in the upper SES level at greater risk for specific cancers (e.g., breast), this study points to a different at-risk population. Logistic regression resulted in statistically significant findings that were significantly modified by age. Women aged 20 to 35 years of age, classified in the lower SES Index level were 4.3 times more likely to report a history of cancer compared to those in the upper SES Index level (p<0.0004). This is a unique and potentially important finding, which suggests that disease outcomes may differ when age is treated as a modifier, rather than simply as a confounder. Findings also support the need for theory-driven research designs, comprehensive measures of SES, and the implementation of methodologies that will capture the complex, nonlinear nature of the association found between SES and disease.

Learning Objectives: At the conclusion of the session, the participant in this session will be able to

• Recognize the utility of Syme's model of Social Determinants for Health and Disease when investigating associations between SES and cancer.
• Identify how variables collected in the 1987 Cancer Epidemiology Supplement of the National Health Interview Survey can be used to create a comprehensive measure of SES using individual-level data.
• Discuss the importance of including interaction terms within the analysis model, particularly when age is a potential modifier of the association under study.
• Articulate potential policy initiatives related to findings from this study.

Keywords: Cancer, Social Class

Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.