title: The influence of neighborhood socioeconomic status and race on survival from ovarian cancer: a population-based analysis of Cook County, Illinois.
abstract: OBJECTIVE
  Despite significant improvements in treatment for ovarian cancer, survival is poorer for non-Hispanic black (NHB) women compared to non-Hispanic white (NHW) women. Neighborhood socioeconomic status (SES) has been implicated in racial disparities across a variety of health outcomes and may similarly contribute to racial disparities in ovarian cancer survival. The purpose of this analysis is to assess the influence of neighborhood SES on NHB-NHW survival differences after accounting for differences in tumor characteristics and in treatment.
  
  
  METHODS
  Data were obtained from 2432 women (443 NHB and 1989 NHW) diagnosed with epithelial ovarian cancer in Cook County, Illinois between 1998 and 2007. Neighborhood (i.e., census tract) SES at the time of diagnosis was calculated for each woman using two well-established composite measures of affluence and disadvantage. Cox proportional hazard models measured the association between NHB race and survival after adjusting for age, tumor characteristics, treatment, year of diagnosis, and neighborhood SES.
  
  
  RESULTS
  There was a strong association between ovarian cancer survival and both measures of neighborhood SES (P < .0001 for both affluence and disadvantage). After adjusting for age, tumor characteristics, treatment, and year of diagnosis, NHB were more likely than NHW to die of ovarian cancer (hazard ratio [HR] = 1.47, 95% confidence interval [CI]: 1.28-1.68). The inclusion of neighborhood affluence and disadvantage into models separately and together attenuated this risk (HRaffluence = 1.37, 95% CI: 1.18-1.58; HRdisadvantage = 1.28, 95% CI: 1.08-1.52; and HRaffluence + disadvantage = 1.28, 95% CI: 1.08-1.52.
  
  
  CONCLUSIONS
  Neighborhood SES, as measured by composite measures of affluence and disadvantage, is a predictor of survival in women diagnosed with ovarian cancer in Cook County, Illinois and may contribute to the racial disparity in survival.
authors.affiliation: Division of Epidemiology and Biostatistics (MC 923), School of Public Health, University of Illinois at Chicago, Chicago.
authors.forename: Katherine C
authors.initials: KC
authors.lastname: Brewer
authors.affiliation: Division of Epidemiology and Biostatistics (MC 923), School of Public Health, University of Illinois at Chicago, Chicago; Cancer Control and Population Science Research Program, University of Illinois at Chicago Cancer Center, Chicago.
authors.forename: Caryn E
authors.initials: CE
authors.lastname: Peterson
authors.affiliation: Cancer Control and Population Science Research Program, University of Illinois at Chicago Cancer Center, Chicago; Department of Public Health Sciences, School of Public Health, University of Alberta, 3-317 Edmonton Clinic Health Academy, Alberta, Canada.
authors.forename: Faith G
authors.initials: FG
authors.lastname: Davis
authors.affiliation: Cancer Control and Population Science Research Program, University of Illinois at Chicago Cancer Center, Chicago; Department of Hematology and Oncology, University of Illinois at Chicago, Chicago.
authors.forename: Kent
authors.initials: K
authors.lastname: Hoskins
authors.affiliation: Institute for Health Research and Policy (IHRP), University of Illinois at Chicago, Chicago.
authors.forename: Heather
authors.initials: H
authors.lastname: Pauls
authors.affiliation: Division of Epidemiology and Biostatistics (MC 923), School of Public Health, University of Illinois at Chicago, Chicago; Cancer Control and Population Science Research Program, University of Illinois at Chicago Cancer Center, Chicago; Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago. Electronic address: charjosl@uic.edu.
authors.forename: Charlotte E
authors.initials: CE
authors.lastname: Joslin
mesh_terms: D001741:Black or African American / Q000706:statistics & numerical data*; D000368:Aged; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D000077216:Carcinoma, Ovarian Epithelial; D004812:Epidemiologic Methods; D005260:Female; D054625:Healthcare Disparities / Q000706:statistics & numerical data*; D006801:Humans; D007087:Illinois / Q000453:epidemiology; D008875:Middle Aged; D009375:Neoplasms, Glandular and Epithelial / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy; D010051:Ovarian Neoplasms / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy; D010052:Ovariectomy; D011159:Population Surveillance; D016016:Proportional Hazards Models; D012111:Residence Characteristics; D012923:Social Class; D015996:Survival Rate; D044465:White People / Q000706:statistics & numerical data*
keywords: Cancer survival; Neighborhood-level factors; Ovarian cancer; Racial disparities; SES