Racial and ethnic disparities in cancer survival by neighborhood socioeconomic status in Surveillance, Epidemiology, and End Results (SEER) Registries

J Natl Cancer Inst Monogr. 2014 Nov;2014(49):236-43. doi: 10.1093/jncimonographs/lgu020.


Introduction: Reducing cancer disparities is a major public health objective. Disparities often are discussed in terms of either race and ethnicity or socioeconomic status (SES), without examining interactions between these variables.

Methods: Surveillance, Epidemiology, and End Results (SEER)-18 data, excluding Alaska Native and Louisiana registries, from 2002 to 2008, were used to estimate five-year, cause-specific survival by race/ethnicity and census tract SES. Differences in survival between groups were used to assess absolute disparities. Hazard ratios were examined as a measure of relative disparity. Interactions between race/ethnicity and neighborhood SES were evaluated using proportional hazard models.

Results: Survival increased with higher SES for all racial/ethnic groups and generally was higher among non-Hispanic white and Asian/Pacific Islander (API) than non-Hispanic black and Hispanic cases. Absolute disparity in breast cancer survival among non-Hispanic black vs non-Hispanic white cases was slightly larger in low-SES areas than in high-SES areas (7.1% and 6.8%, respectively). In contrast, after adjusting for stage, age, and treatment, risk of mortality among non-Hispanic black cases compared with non-Hispanic white cases was 21% higher in low-SES areas and 64% higher in high-SES areas. Similarly, patterns of absolute and relative disparity compared with non-Hispanic whites differed by SES for Hispanic breast cancer, non-Hispanic black colorectal cancer, and prostate cancer cases. Statistically significant interactions existed between race/ethnicity and SES for colorectal and female breast cancers.

Discussion: In health disparities research, both relative and absolute measures provide context. A better understanding of the interactions between race/ethnicity and SES may be useful in directing screening and treatment resources toward at-risk populations.

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Child
  • Child, Preschool
  • Ethnicity / statistics & numerical data*
  • Female
  • Health Status Disparities*
  • Humans
  • Infant
  • Male
  • Middle Aged
  • Neoplasms / mortality*
  • Racial Groups / statistics & numerical data*
  • SEER Program
  • Social Class
  • Survival Rate
  • Young Adult