Area characteristics and individual-level socioeconomic position indicators in three population-based epidemiologic studies

A. V. Diez Roux, C. I. Kiefe, D. R. Jacobs, M. Haan, S. A. Jackson, F. J. Nieto, C. C. Paton, R. Schulz

Research output: Contribution to journalArticlepeer-review

292 Scopus citations


PURPOSE: There is growing interest in incorporating area indicators into epidemiologic analyses. Using data from the 1990 U.S. Census linked to individual-level data from three epidemiologic studies, we investigated how different area indicators are interrelated, how measures for different sized areas compare, and the relation between area and individual-level social position indicators. METHODS: The interrelations between 13 area indicators of wealth/income, education, occupation, and other socioenvironmental characteristics were investigated using correlation coefficients and factor analyses. The extent to which block-group measures provide information distinct from census tract measures was investigated using intraclass correlation coefficients. Loglinear models were used to investigate associations between area and individual-level indicators. RESULTS: Correlations between area measures were generally in the 0.5-0.8 range. In factor analyses, six indicators of income/wealth, education, and occupation loaded on one factor in most geographic sites. Correlations between block-group and census tract measures were high (correlation coefficients 0.85-0.96). Most of the variability in block-group indicators was between census tracts (intraclass correlation coefficients 0.72-0.92). Although individual-level and area indicators were associated, there was evidence of important heterogeneity in area of residence within individual-level income or education categories. The strength of the association between individual and area measures was similar in the three studies and in whites and blacks, but blacks were much more likely to live in more disadvantaged areas than whites. CONCLUSIONS: Area measures of wealth/income, education, and occupation are moderately to highly correlated. Differences between using census tract or block-group measures in contextual investigations are likely to be relatively small. Area and individual-level indicators are far from perfectly correlated and provide complementary information on living circumstances. Differences in the residential environments of blacks and whites may need to be taken into account in interpreting race differences in epidemiologic studies.

Original languageEnglish (US)
Pages (from-to)395-405
Number of pages11
JournalAnnals of epidemiology
Issue number6
StatePublished - 2001

Bibliographical note

Funding Information:
This work was supported by R29 HL59386 (Dr. Diez-Roux) from the National Heart, Lung, and Blood Institute. CHS was supported by contracts N01-HC-85079—N01-HC-85086 from the National Heart, Lung, and Blood Institute, and Georgetown Echo RC-HL 35129 JHU MRI RC-HL 15103. The ARIC Study was supported by Contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, N01-HC-55022 from the National Heart, Lung, and Blood Institute. The CARDIA Study was supported by Contracts N01-HC-48047, N01-HC-48048, N01-HC-48049, N01-HC-48050, and N01-HC-95095 from the National Heart, Lung, and Blood Institute. The authors thank the following: Sharon Merkin for assistance with the analyses; the CARDIA investigators and staff, and especially Dan Garside, Karen Virnig, Jerry Hamilton, Debbie Parker, Heather McGrath, and Rex Bomhold for their assistance in geocoding the CARDIA data; the ARIC investigators and staff for their important contributions; and the following CHS investigators and staff: Forsyth County, NC: Bowman Gray School of Medicine of Wake Forest University: Gregory L. Burke, Sharon Jackson, Alan Elster, Curt D. Furberg,, Gerardo Heiss, Dalane Kitzman, Margie Lamb, David S. Lefkowitz, Mary F. Lyles, Cathy Nunn, Ward Riley, John Chen, Beverly Tucker; Forsyth County, NC-Wake Forest University-ECG Reading Center: Farida Rautaharju, Pentti Rautaharju; Sacramento County, CA; University of California, Davis: William Bonekat, Charles Bernick, Michael Buonocore, Mary Haan, Calvin Hirsch, Lawrence Laslett, Marshall Lee, John Robbins, William Seavey, Richard White, Washington County, MD, The Johns Hopkins University: M. Jan Busby-Whitehead, Joyce Chabot, George W. Comstock, Adrian Dobs, Linda P. Fried, Joel G. Hill, Steven J. Kittner, Shiriki Kumanyika, David Levine, Joao A. Lima, Neil R. Powe, Thomas R. Price, Jeff Williamson, Moyses Szklo, Melvyn Tockman; MRI Reading Center, Washington County, MD, The Johns Hopkins University: Norman Beauchamp, R. Nick Bryan, Douglas Fellows, Melanie Hawkins, Patrice Holtz, Naiyer Iman, Michael Kraut, Cynthia Quinn, Grace Lee, Carolyn C. Meltzer, Larry Schertz, Earl P. Steinberg, Scott Wells, Linda Wilkins, Nancy C. Yue; Allegheny County, PA, University of Pittsburgh: Diane G. Ives, Charles A. Jungreis, Laurie Knepper, Lewis H. Kuller, Elaine Meilahn, Peg Meyer, Roberta Moyer, Anne Newman, Richard Schulz, Vivienne E. Smith, Sidney K. Wolfson; Echocardiography Reading Center (Baseline), University of California, Irvine: Hoda Anton-Culver, Julius M. Gardin, Margaret Knoll, Tom Kurosaki, Nathan Wong; Echocardiography Reading Center (Follow-Up), Georgetown Medical Center: John Gottdiener, Eva Hausner, Stephen Kraus, Judy Gay, Sue Livengood, Mary Ann Yohe, Retha Webb; Ultrasound Reading Center, New England Medical Center, Boston: Daniel H. O'Leary, Joseph F. Polak, Laurie Funk; Central Blood Analysis Laboratory, University of Vermont: Elaine Cornell, Mary Cushman, Russell P. Tracy; Pulmonary Reading Center, University of Arizona-Tucson: Paul Enright; Coordinating Center, University of Washington, Seattle: Alice Arnold, Annette L. Fitzpatrick, Richard A. Kronmal, Bruce M. Psaty, David S. Siscovick, Will Longstreth, Patricia W. Wahl, David Yanez, Paula Diehr, Corrine Dulberg, Bonnie Lind, Thomas Lumley, Ellen O'Meara, Jennifer Nelson, Chuck Spiekerman; NHLBI Project Office: Robin Boineau,Teri A. Manolio, Peter J. Savage, Patricia Smith.


  • Ethnicity
  • Neighborhoods
  • Race
  • Social Class
  • Socioeconomic Status


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