County characteristics and racial and ethnic disparities in the use of preventive services

Prev Med. 2004 Oct;39(4):704-12. doi: 10.1016/j.ypmed.2004.02.039.

Abstract

Background: Studies examining predictors of preventive service utilization generally focus on individual characteristics and ignore the role of contextual variables. To help address this gap in the literature, the present study investigates whether county-level characteristics, such as racial and ethnic composition, are associated with the use of preventive services.

Methods: Data from the Medical Expenditure Panel Survey and the Area Resource Files (1996-1998) are used to identify the individual- and county-level predictors of five types of preventive services (n = 49,063).

Results: County racial or ethnic composition is associated with the utilization of certain preventive services, net of individual-level characteristics. Specifically, individuals in high percent Hispanic counties are more likely to report cholesterol screenings, while those in counties with more blacks are more likely to have regular mammograms. Moreover, county racial or ethnic composition modifies the relationship between individual race or ethnicity and preventive use. In particular, Hispanic individuals who reside in high percent black counties report higher levels of utilization for most preventive services compared to Hispanics living in other counties.

Conclusions: Physical and social environments are key determinants of health behaviors and outcomes. Future studies should take into account the racial or ethnic composition of an area and how this interacts with individual race or ethnicity when investigating predictors of preventive care use.

MeSH terms

  • Adult
  • Blood Pressure / physiology
  • Cholesterol / blood
  • Continental Population Groups / statistics & numerical data*
  • Ethnic Groups / statistics & numerical data*
  • Female
  • Humans
  • Influenza Vaccines / administration & dosage
  • Longitudinal Studies
  • Male
  • Mammography
  • Middle Aged
  • Models, Biological*
  • Multivariate Analysis
  • Preventive Health Services / statistics & numerical data*
  • Residence Characteristics / statistics & numerical data

Substances

  • Influenza Vaccines
  • Cholesterol