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Eur J Cancer Prev. 2017 Nov;26(6):453-460. doi: 10.1097/CEJ.0000000000000267.

Cancer mortality disparities among New York City's Upper Manhattan neighborhoods.

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aDepartment of Preventive Medicine and Tisch Cancer Institute bDepartment of Preventive Medicine cDivision of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, Tisch Cancer Institute, New York, New York, USA dDepartment of Cancer Epidemiology, Maria Skłodowska-Curie Cancer Centre and Institute of Oncology, Warsaw, Poland eDivision of Occupational Medicine, University of Brescia, Brescia, Italy.


The East Harlem (EH), Central Harlem (CH), and Upper East Side (UES) neighborhoods of New York City are geographically contiguous to tertiary medical care, but are characterized by cancer mortality rate disparities. This ecological study aims to disentangle the effects of race and neighborhood on cancer deaths. Mortality-to-incidence ratios were determined using neighborhood-specific data from the New York State Cancer Registry and Vital Records Office (2007-2011). Ecological data on modifiable cancer risk factors from the New York City Community Health Survey (2002-2006) were stratified by sex, age group, race/ethnicity, and neighborhood and modeled against stratified mortality rates to disentangle race/ethnicity and neighborhood using logistic regression. Significant gaps in mortality rates were observed between the UES and both CH and EH across all cancers, favoring UES. Mortality-to-incidence ratios of both CH and EH were similarly elevated in the range of 0.41-0.44 compared with UES (0.26-0.30). After covariate and multivariable adjustment, black race (odds ratio=1.68; 95% confidence interval: 1.46-1.93) and EH residence (odds ratio=1.20; 95% confidence interval: 1.07-1.35) remained significant risk factors in all cancers' combined mortality. Mortality disparities remain among EH, CH, and UES neighborhoods. Both neighborhood and race are significantly associated with cancer mortality, independent of each other. Multivariable adjusted models that include Community Health Survey risk factors show that this mortality gap may be avoidable through community-based public health interventions.

[Available on 2018-11-01]
[Indexed for MEDLINE]

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