Cancer Incidence and Multilevel Measures of Residential Economic and Racial Segregation for Cancer Registries. Issue 1 (25th April 2018)

• Record Type: Journal Article
• Authors: Krieger, Nancy; Feldman, Justin M; Kim, Rockli; Waterman, Pamela D
• Is Part Of: JNCI cancer spectrum. Volume 2:Issue 1(2018)
• Publication Date: 2018-04-25
• DOI: 10.1093/jncics/pky009
• Languages: English
• ISSNs: 2515-5091

Abstract

Abstract: Background: The handful of studies (<30) on cancer and residential segregation have focused on racial segregation, primarily at the city/town level. We tested a priori hypotheses about choice of measure and level by extending use of the Index of Concentration at the Extremes (ICE) to quantify both economic and racial residential segregation, singly and combined, and conducted analyses for the total population and stratified by race/ethnicity. Methods: Outcomes comprised Massachusetts incidence rates (2010–2014) for invasive breast, cervical, and lung cancer, analyzed in relation to census tract and city/town ICE measures for income, race/ethnicity, race/ethnicity + income, and the federal poverty line. Multilevel Poisson regression modeled observed counts of incident cases. Results: Both choice of metric and level mattered. As illustrated by cervical cancer, in models including both the census tract and city/town levels, the rate ratio for the worst to best quintile for the total population was greatest at the census tract level for the ICE for racialized economic segregation (3.0, 95% confidence interval [CI] = 2.1 to 4.3) and least for the poverty measure (1.9, 95% CI = 1.4 to 2.6), with null associations at the city/town level. In analogous models with both levels for lung cancer, however, for the non-Hispanic black and Hispanic populations, the rate ratios for, respectively, the ICE and poverty measures, were larger (and excluded 1) at the city/town compared with the census tract level. Conclusions: Our study suggests that the ICE for racialized economic segregation, at multiple levels, can be used to improve monitoring and analysis of cancer inequities.