title: Choosing area based socioeconomic measures to monitor social inequalities in low birth weight and childhood lead poisoning: The Public Health Disparities Geocoding Project (US).
abstract: OBJECTIVE
  : To determine which area based socioeconomic measures can meaningfully be used, at which level of geography, to monitor socioeconomic inequalities in childhood health in the US.
  
  
  METHODS
  Cross sectional analysis of birth certificate and childhood lead poisoning registry data, geocoded and linked to diverse area based socioeconomic measures that were generated at three geographical levels: census tract, block group, and ZIP code.
  
  
  METHODS
  Two US states: Massachusetts (1990 population=6,016,425) and Rhode Island (1990 population=1,003,464).
  
  
  METHODS
  All births born to mothers ages 15 to 55 years old who were residents of either Massachusetts (1989-1991; n=267,311) or Rhode Island (1987-1993; n=96 138), and all children ages 1 to 5 years residing in Rhode Island who were screened for lead levels between 1994 and 1996 (n=62,514 children, restricted to first test during the study period).
  
  
  RESULTS
  Analyses of both the birth weight and lead data indicated that: (a) block group and tract socioeconomic measures performed similarly within and across both states, while ZIP code level measures tended to detect smaller effects; (b) measures pertaining to economic poverty detected stronger gradients than measures of education, occupation, and wealth; (c) results were similar for categories generated by quintiles and by a priori categorical cut off points; and (d) the area based socioeconomic measures yielded estimates of effect equal to or augmenting those detected, respectively, by individual level educational data for birth outcomes and by the area based housing measure recommended by the US government for monitoring childhood lead poisoning.
  
  
  CONCLUSIONS
  Census tract or block group area based socioeconomic measures of economic deprivation could be meaningfully used in conjunction with US public health surveillance systems to enable or enhance monitoring of social inequalities in health in the United States.
authors.affiliation: Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA 02115, USA. nkrieger@hsph.harvard.edu
authors.forename: N
authors.initials: N
authors.lastname: Krieger
authors.forename: J T
authors.initials: JT
authors.lastname: Chen
authors.forename: P D
authors.initials: PD
authors.lastname: Waterman
authors.forename: M-J
authors.initials: MJ
authors.lastname: Soobader
authors.forename: S V
authors.initials: SV
authors.lastname: Subramanian
authors.forename: R
authors.initials: R
authors.lastname: Carson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002648:Child; D003430:Cross-Sectional Studies; D004522:Educational Status; D005260:Female; D006798:Housing; D006801:Humans; D007182:Income; D007223:Infant; D007230:Infant, Low Birth Weight; D007231:Infant, Newborn; D007854:Lead / Q000097:blood; D007855:Lead Poisoning / Q000097:blood / Q000453:epidemiology*; D008297:Male; D008404:Massachusetts / Q000453:epidemiology; D008875:Middle Aged; D011203:Poverty / Q000706:statistics & numerical data*; D012237:Rhode Island / Q000453:epidemiology; D012307:Risk Factors; D012923:Social Class; D012959:Socioeconomic Factors; D014478:Unemployment
chemical_list: D007854:Lead