title: Public Health Monitoring of Privilege and Deprivation With the Index of Concentration at the Extremes.
abstract: OBJECTIVE
  We evaluated use of the Index of Concentration at the Extremes (ICE) for public health monitoring.
  
  
  METHODS
  We used New York City data centered around 2010 to assess cross-sectional associations at the census tract and community district levels, for (1) diverse ICE measures plus the US poverty rate, with (2) infant mortality, premature mortality (before age 65 years), and diabetes mortality.
  
  
  RESULTS
  Point estimates for rate ratios were consistently greatest for the novel ICE that jointly measured extreme concentrations of income and race/ethnicity. For example, the census tract-level rate ratio for infant mortality comparing the bottom versus top quintile for an ICE contrasting low-income Black versus high-income White equaled 2.93 (95% confidence interval [CI] = 2.11, 4.09), but was 2.19 (95% CI = 1.59, 3.02) for low versus high income, 2.77 (95% CI = 2.02, 3.81) for Black versus White, and 1.56 (95% CI = 1.19, 2.04) for census tracts with greater than or equal to 30% versus less than 10% below poverty.
  
  
  CONCLUSIONS
  The ICE may be a useful metric for public health monitoring, as it simultaneously captures extremes of privilege and deprivation and can jointly measure economic and racial/ethnic segregation.
authors.affiliation: Nancy Krieger and Pamela D. Waterman are with the Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA. Jasmina Spasojevic, Wenhui Li, Gil Maduro, and Gretchen Van Wye are with the Bureau of Vital Statistics, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY.
authors.forename: Nancy
authors.initials: N
authors.lastname: Krieger
authors.affiliation: Nancy Krieger and Pamela D. Waterman are with the Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA. Jasmina Spasojevic, Wenhui Li, Gil Maduro, and Gretchen Van Wye are with the Bureau of Vital Statistics, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY.
authors.forename: Pamela D
authors.initials: PD
authors.lastname: Waterman
authors.affiliation: Nancy Krieger and Pamela D. Waterman are with the Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA. Jasmina Spasojevic, Wenhui Li, Gil Maduro, and Gretchen Van Wye are with the Bureau of Vital Statistics, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY.
authors.forename: Jasmina
authors.initials: J
authors.lastname: Spasojevic
authors.affiliation: Nancy Krieger and Pamela D. Waterman are with the Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA. Jasmina Spasojevic, Wenhui Li, Gil Maduro, and Gretchen Van Wye are with the Bureau of Vital Statistics, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY.
authors.forename: Wenhui
authors.initials: W
authors.lastname: Li
authors.affiliation: Nancy Krieger and Pamela D. Waterman are with the Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA. Jasmina Spasojevic, Wenhui Li, Gil Maduro, and Gretchen Van Wye are with the Bureau of Vital Statistics, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY.
authors.forename: Gil
authors.initials: G
authors.lastname: Maduro
authors.affiliation: Nancy Krieger and Pamela D. Waterman are with the Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA. Jasmina Spasojevic, Wenhui Li, Gil Maduro, and Gretchen Van Wye are with the Bureau of Vital Statistics, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY.
authors.forename: Gretchen
authors.initials: G
authors.lastname: Van Wye
mesh_terms: D000328:Adult; D003430:Cross-Sectional Studies; D003710:Demography / Q000706:statistics & numerical data*; D005006:Ethnicity; D054625:Healthcare Disparities / Q000208:ethnology; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D061213:Mortality, Premature; D009519:New York City / Q000453:epidemiology; D011203:Poverty / Q000208:ethnology / Q000706:statistics & numerical data; D011634:Public Health / Q000379:methods*; D044469:Racial Groups; D012959:Socioeconomic Factors