title: Vulnerability and the receipt of recommended preventive services: the influence of multiple risk factors.
abstract: BACKGROUND
  Previous studies have confirmed the independent associations of race/ethnicity, socioeconomic status, and potential access with the receipt of preventive care. More pragmatic models of vulnerability are needed to examine the concomitant influence of multiple risk factors.
  
  
  OBJECTIVE
  To operationalize vulnerability as risk profiles of predisposing (race/ethnicity and education) and enabling (eg, income, health insurance, and having a regular source of care) factors, and their association with the receipt of preventive care.
  
  
  METHODS
  Cross-sectional data on 14,983 adults from the Household Component of the 1996 Medical Expenditure Panel Survey.
  
  
  METHODS
  Receipt of recommended preventive care: blood pressure and cholesterol screening, flu shot, Papanicolaou test, mammogram, and dental visit.
  
  
  RESULTS
  Controlling for other factors, analyses of risk profiles revealed a clear dose-response relationship with the receipt of preventive care regardless of race/ethnicity. In the total sample, having more risk factors was associated with a lower prevalence of, for example, receiving a cholesterol screening: 1 risk (PR=0.77; CI, 0.71-0.84), 2 risks (PR=0.56; CI, 0.49-0.64), and 3+ risks (PR=0.34; CI, 0.25-0.43).
  
  
  CONCLUSIONS
  Sizeable disparities in the receipt of recommended preventive services were found in relation to increasing vulnerability risk profiles. Without attention to such co-occurring risks, it is unlikely that substantial gains will be made in reducing disparities in the incidence of and mortality from the most common preventable diseases in the United States.
authors.affiliation: Johns Hopkins University Bloomberg School of Public Health, Department of Health Policy and Management, Baltimore, Maryland, USA.
authors.forename: Leiyu
authors.initials: L
authors.lastname: Shi
authors.forename: Gregory D
authors.initials: GD
authors.lastname: Stevens
mesh_terms: D003430:Cross-Sectional Studies; D003695:Delivery of Health Care / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D015999:Multivariate Analysis; D010342:Patient Acceptance of Health Care; D011314:Preventive Health Services / Q000706:statistics & numerical data*; D012307:Risk Factors; D012959:Socioeconomic Factors