ISSN: 2161-1165

Epidemiology: Open Access
Open Access

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
  • Research Article   
  • Epidemiol 2011, Vol 1(1): 101
  • DOI: 10.4172/2161-1165.1000101

Matching on Race and Ethnicity in Case-Control Studies as a Means of Control for Population Stratification

Anand P. Chokkalingam1*, Melinda C. Aldrich2, Karen Bartley1, Ling-I Hsu1, Catherine Metayer1, Lisa F. Barcellos1, Joseph L. Wiemels3, John K. Wiencke4, Patricia A. Buffler1 and Steve Selvin1
1School of Public Health, University of California Berkeley, , Berkeley, USA
2Vanderbilt University, Vanderbilt University Medical Center, Nashville, Tennessee, USA
3Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
4Department of Neurological Surgery, University of California, San Francisco San Francisco, California, USA
*Corresponding Author : Anand P. Chokkalingam, Division of Epidemiology, UC Berkeley School of Public Health, 1995 University Ave, Ste 460, Berkeley CA 94704, USA, Tel: (510) 642-8375, Fax: (510) 643-1735, Email: anandc@berkeley.edu

Received Date: Aug 24, 2011 / Accepted Date: Sep 20, 2011 / Published Date: Sep 29, 2011

Abstract

Some investigators argue that controlling for self-reported race or ethnicity, either in statistical analysis or in study design, is sufficient to mitigate unwanted influence from population stratification. In this report, we evaluated the effectiveness of a study design involving matching on self-reported ethnicity and race in minimizing bias due to population stratification within an ethnically admixed population in California. We estimated individual genetic ancestry using structured association methods and a panel of ancestry informative markers, and observed no statistically significant difference in distribution of genetic ancestry between cases and controls (P=0.46). Stratification by Hispanic ethnicity showed similar results. We evaluated potential confounding by genetic ancestry after adjustment for race and ethnicity for 1260 candidate gene SNPs, and found no major impact (>10%) on risk estimates. In conclusion, we found no evidence of confounding of genetic risk estimates by population substructure using this matched design. Our study provides strong evidence supporting the race- and ethnicity-matched case-control study design as an effective approach to minimize systematic bias due to differences in genetic ancestry between cases and controls.

Keywords: Population stratification; Genetic susceptibility; Case-control; Matching.

Citation: Chokkalingam AP, Aldrich MC, Bartley K, Hsu LI, Metayer C, et al. (2011) Matching on Race and Ethnicity in Case-Control Studies as a Means of Control for Population Stratification. Epidemiol 1:101. Doi: 10.4172/2161-1165.1000101

Copyright: © 2011 Chokkalingam AP, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Top