title: Examining neighbourhood confounding in a survey: an example using the National Health and Nutrition Examination Survey II.
abstract: This paper demonstrates a methodology for examining whether neighbourhood stratification lessens the confounding bias of some specific risk-factor/disease associations in analysis of the National Health and Nutrition Examination Survey II (NHANES II). The fortuitous clustering of the sample design of NHANES allows us to estimate risk-factor/disease associations with and without controlling for neighbourhood effects on the same population. We briefly discuss the implications of this methodology for neighbourhood matching in case-control studies.
authors.affiliation: Department of Biomathematics, UCLA School of Medicine 90024.
authors.forename: E L
authors.initials: EL
authors.lastname: Korn
authors.forename: B I
authors.initials: BI
authors.lastname: Graubard
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001794:Blood Pressure; D002136:Calcium, Dietary / Q000008:administration & dosage; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007223:Infant; D007854:Lead / Q000097:blood; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009748:Nutrition Disorders / Q000453:epidemiology*; D011336:Probability; D012307:Risk Factors; D012494:Sampling Studies; D012931:Social Environment; D013029:Space-Time Clustering
chemical_list: D002136:Calcium, Dietary; D007854:Lead