title: Employing community data to investigate social and structural dimensions of urban neighborhoods: an early childhood education example.
abstract: The present study sought to define neighborhood context by examining relationships among data from city-level administrative databases at the level of the census block group. The present neighborhood investigation included 1,801 block groups comprising a large, northeastern metropolitan area. Common factor analyses and multistage, hierarchical cluster analyses yielded two dimensions (i.e., Social Stress, Structural Danger) and two typologies (i.e., Racial Composition, Property Structure Composition) of neighborhood context. Simultaneous multiple regression analyses revealed small but statistically significant associations between neighborhood variables and academic outcomes for public school kindergarten children.
authors.affiliation: Department of Applied Psychology, The Steinhardt School of Education, New York University, 239 Greene Street, New York, NY 10003-6674, USA. cm106@nyu.edu
authors.forename: Christine M
authors.initials: CM
authors.lastname: McWayne
authors.forename: Paul A
authors.initials: PA
authors.lastname: McDermott
authors.forename: John W
authors.initials: JW
authors.lastname: Fantuzzo
authors.forename: Dennis P
authors.initials: DP
authors.lastname: Culhane
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D019992:Databases as Topic; D005260:Female; D006801:Humans; D008297:Male; D009511:New England; D011593:Psychology, Social; D012044:Regression Analysis; D012111:Residence Characteristics; D013223:Statistics as Topic; D014505:Urban Population