title: Population-level correlates of preterm delivery among black and white women in the U.S.
abstract: OBJECTIVE
  This study examined the ability of social, demographic, environmental and health-related factors to explain geographic variability in preterm delivery among black and white women in the US and whether these factors explain black-white disparities in preterm delivery.
  
  
  METHODS
  We examined county-level prevalence of preterm delivery (20-31 or 32-36 weeks gestation) among singletons born 1998-2002. We conducted multivariable linear regression analysis to estimate the association of selected variables with preterm delivery separately for each preterm/race-ethnicity group.
  
  
  RESULTS
  The prevalence of preterm delivery varied two- to three-fold across U.S. counties, and the distributions were strikingly distinct for blacks and whites. Among births to blacks, regression models explained 46% of the variability in county-level risk of delivery at 20-31 weeks and 55% for delivery at 32-36 weeks (based on R-squared values). Respective percentages for whites were 67% and 71%. Models included socio-environmental/demographic and health-related variables and explained similar amounts of variability overall.
  
  
  CONCLUSIONS
  Much of the geographic variability in preterm delivery in the US can be explained by socioeconomic, demographic and health-related characteristics of the population, but less so for blacks than whites.
authors.affiliation: Division of Neonatology and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America.
authors.forename: Suzan L
authors.initials: SL
authors.lastname: Carmichael
authors.affiliation: General Medical Disciplines, Stanford University School of Medicine, Stanford, California, United States of America.
authors.forename: Mark R
authors.initials: MR
authors.lastname: Cullen
authors.affiliation: Division of Neonatology and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America.
authors.forename: Jonathan A
authors.initials: JA
authors.lastname: Mayo
authors.affiliation: Division of Neonatology and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America.
authors.forename: Jeffrey B
authors.initials: JB
authors.lastname: Gould
authors.affiliation: General Medical Disciplines, Stanford University School of Medicine, Stanford, California, United States of America.
authors.forename: Pooja
authors.initials: P
authors.lastname: Loftus
authors.affiliation: Division of Neonatology and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America.
authors.forename: David K
authors.initials: DK
authors.lastname: Stevenson
authors.affiliation: Division of Neonatology and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America.
authors.forename: Paul H
authors.initials: PH
authors.lastname: Wise
authors.affiliation: Division of Neonatology and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America.
authors.forename: Gary M
authors.initials: GM
authors.lastname: Shaw
mesh_terms: D000328:Adult; D001741:Black or African American; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D016014:Linear Models; D015999:Multivariate Analysis; D007752:Obstetric Labor, Premature / Q000208:ethnology*; D011247:Pregnancy; D047928:Premature Birth / Q000453:epidemiology; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology; D044465:White People
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