Use of community-level data in the National Children’s Study to establish the representativeness of segment selection in the Queens Vanguard Site

Autor: Rundle Andrew, Rauh Virginia A, Quinn James, Lovasi Gina, Trasande Leonardo, Susser Ezra, Andrews Howard F
Jazyk: angličtina
Rok vydání: 2012
Předmět:
Zdroj: International Journal of Health Geographics, Vol 11, Iss 1, p 18 (2012)
Druh dokumentu: article
ISSN: 1476-072X
DOI: 10.1186/1476-072X-11-18
Popis: Abstract Background The WHO Multiple Exposures Multiple Effects (MEME) framework identifies community contextual variables as central to the study of childhood health. Here we identify multiple domains of neighborhood context, and key variables describing the dimensions of these domains, for use in the National Children’s Study (NCS) site in Queens. We test whether the neighborhoods selected for NCS recruitment, are representative of the whole of Queens County, and whether there is sufficient variability across neighborhoods for meaningful studies of contextual variables. Methods Nine domains (demographic, socioeconomic, households, birth rated, transit, playground/greenspace, safety and social disorder, land use, and pollution sources) and 53 indicator measures of the domains were identified. Geographic information systems were used to create community-level indicators for US Census tracts containing the 18 study neighborhoods in Queens selected for recruitment, using US Census, New York City Vital Statistics, and other sources of community-level information. Mean and inter-quartile range values for each indicator were compared for Tracts in recruitment and non-recruitment neighborhoods in Queens. Results Across the nine domains, except in a very few instances, the NCS segment-containing tracts (N = 43) were not statistically different from those 597 populated tracts in Queens not containing portions of NCS segments; variability in most indicators was comparable in tracts containing and not containing segments. Conclusions In a diverse urban setting, the NCS segment selection process succeeded in identifying recruitment areas that are, as a whole, representative of Queens County, for a broad range of community-level variables.
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