Article

The increasing racial disparity in infant mortality rates: Composition and contributors to recent US trends

Department of Pediatrics, University of South Florida College of Medicine, Tampa, FL, USA.
American journal of obstetrics and gynecology (Impact Factor: 3.97). 02/2008; 198(1):51.e1-9. DOI: 10.1016/j.ajog.2007.06.006
Source: PubMed

ABSTRACT We examined trends in birthweight-gestational age distributions and related infant mortality for African American and white women and calculated the estimated excess annual number of African American infant deaths.
Live births to US-resident mothers with a maternal race of white or African American were selected from the National Center for Health Statistics' linked live birth-infant death cohort files (1985-1988 and 1995-2000).
The racial disparity in infant mortality widened despite an increasing rate of white low-birthweight infants. White preterm infants had relatively greater gains in survival and the white advantage in survival at term increased. Annually, African American women experience approximately 3300 more infant deaths than would be expected.
The increasing US racial disparity in infant mortality is largely influenced by changes in birthweight-gestational age-specific mortality, rather than the birthweight-gestational age distribution. Improvement in the survival of white preterm and low-birthweight infants, probably reflecting advances in and changing access to medical technology, contributed appreciably to this trend.

1 Follower
 · 
230 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Large disparities in adverse birth outcomes persist between African American and white women in the US despite decades of research, policy, and public health intervention. Allostatic load is an index of dysregulation across multiple physiologic systems that results from chronic exposure to stress in the physical and socio-cultural environment which may lead to earlier health deterioration among racially or socio-economically disadvantaged groups. The purpose of this investigation was to examine relationships between maternal biomarkers of allostatic load prior to conception and the occurrence of preterm birth and small for gestational age infants among a cohort of white and African American women participants in the Bogalusa Heart Study. Data from women participants were linked to the birth record of their first-born infant. Principal components analysis was used to construct an index of allostatic load as a summary of the weighted contribution of nine biomarkers representing three physiologic domains: cardiovascular, metabolic, and immune systems. A series of Poisson regression models based on samples ranging from 1467 to 375 women were used to examine race, individual biomarkers of allostatic load, and quartiles of the allostatic load index as predictors of preterm birth (n = 150, 10.2%) and small for gestational age (n = 135, 9.2%). There was no evidence of a relationship between maternal preconception allostatic load and either adverse birth outcome in this sample. Further, there was no evidence of effect modification of by race or education. More work is needed in understanding the biological mechanisms linking social inequities to racial disparities in adverse birth outcomes.
    Paediatric and Perinatal Epidemiology 10/2013; 27(6). DOI:10.1111/ppe.12091 · 2.81 Impact Factor
  • Source
  • [Show abstract] [Hide abstract]
    ABSTRACT: Birthweight shows complex patterns of heterogeneity and has strong implications for in- fant mortality and later-life demographic outcomes. Using NCHS registration data from 1968-2005, we model the joint distribution of birthweight and gestational age as a two- component Gaussian mixture. The mixture has an intuitive interpretation: the first com- ponent represents the majority of the population and the second component represents a high-risk sub-population with lower mean birthweight and higher variance in both birth- weight and gestational age. Using a Bayesian framework, we estimate the joint posterior distribution of the mixture model via MCMC simulation. The flexibility aorded by fitting the mixture model by the Gibbs sampler allows us to model the (binary) indicator for com- ponent membership as a function of covariates. Our interest focuses primarily in mother's and father's race, their interaction, and proxies of SES available from birth certificate infor- mation. The model fits well, though the posterior distributions of most of the coecients in the hierarchical model have wide credible intervals. In particular, we find no strong evidence that race predicts component membership. We conclude with a discussion of potentially productive extensions to the model.