Race and socioeconomic differences in post-settlement outcomes for African American and Caucasian Workers' Compensation claimants with low back injuries

Pain. 2005 Apr;114(3):462-472. doi: 10.1016/j.pain.2005.01.011.

Abstract

The purpose of this study was to predict post-settlement pain intensity, psychological distress, disability, and financial struggle among African American (n=580) and non-Hispanic Caucasian (n=892) Workers' Compensation claimants with single incident low back injury. The study was a population-based telephone survey conducted in three population centers in Missouri. Post-settlement outcomes were predicted from claimant demographics (race, age, gender); socioeconomic status (SES); diagnosis and legal representation; and Workers' Compensation resolution variables (treatment costs, temporary disability status, disability rating, settlement costs). Simultaneous-entry, hierarchical multiple linear regression analyses indicated that African American race and lower SES predicted higher levels of post-settlement pain intensity, psychological distress (general mental health, pain-related catastrophizing), disability (pain-related role interference), and financial struggle, independent of age, gender, diagnosis, legal representation, and Workers' Compensation resolution variables. The results suggest that African American race and lower SES-relative to Caucasian race and higher SES-are risk factors for poor outcomes after occupational low back injury. Mechanisms to explain these associations are discussed, including patient-level, provider-level, legal, and Workers' Compensation system-level factors.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Black or African American / statistics & numerical data*
  • Data Collection
  • Disability Evaluation
  • Female
  • Health Services Accessibility
  • Humans
  • Low Back Pain / economics*
  • Low Back Pain / epidemiology*
  • Male
  • Middle Aged
  • Missouri / epidemiology
  • Occupational Diseases / economics
  • Occupational Diseases / epidemiology
  • Occupational Health / statistics & numerical data
  • Predictive Value of Tests
  • Risk Factors
  • Social Class
  • White People / statistics & numerical data*
  • Workers' Compensation / statistics & numerical data*