Census data are widely used for assessing neighborhood socioeconomic context. Research using census data has been inconsistent in variable choice and usually limited to single geographic areas. This paper seeks to a) outline a process for developing a neighborhood deprivation index using principal components analysis and b) demonstrate an example of its utility for identifying contextual variables that are associated with perinatal health outcomes across diverse geographic areas. Year 2000 U.S. Census and vital records birth data (1998-2001) were merged at the census tract level for 19 cities (located in three states) and five suburban counties (located in three states), which were used to create eight study areas within four states. Census variables representing five socio-demographic domains previously associated with health outcomes, including income/poverty, education, employment, housing, and occupation, were empirically summarized using principal components analysis. The resulting first principal component, hereafter referred to as neighborhood deprivation, accounted for 51 to 73% of the total variability across eight study areas. Component loadings were consistent both within and across study areas (0.2-0.4), suggesting that each variable contributes approximately equally to "deprivation" across diverse geographies. The deprivation index was associated with the unadjusted prevalence of preterm birth and low birth weight for white non-Hispanic and to a lesser extent for black non-Hispanic women across the eight sites. The high correlations between census variables, the inherent multidimensionality of constructs like neighborhood deprivation, and the observed associations with birth outcomes suggest the utility of using a deprivation, index for research into neighborhood effects on adverse birth outcomes.

• K01 HD047122/HD/NICHD NIH HHS/United States