Geographical variation in the provision of elective primary hip and knee replacement: the role of socio-demographic, hospital and distance variables

J Public Health (Oxf). 2009 Sep;31(3):413-22. doi: 10.1093/pubmed/fdp061. Epub 2009 Jun 19.


Background: To explore inequalities in the provision of hip/knee replacement surgery and produce small-area estimates of provision to inform local health planning.

Methods: Hospital Episode Statistics were used to explore inequalities in the provision of primary hip/knee operations in English NHS hospitals in 2002. Multilevel Poisson regression modelling was used to estimate rates of surgical provision by socio-demographic, hospital and distance variables. GIS software was used to estimate road travel times and create hospital catchment areas.

Results: Rates of joint replacement increased with age before falling in those aged 80+. Women received more operations than men. People living in the most deprived areas obtained fewer hip, but more knee operations. Those in urban areas received less hip surgery, but there was no association for knee replacement. Controlling for hospital and distance measures did not attenuate the effects. Geographical variation across districts was observed with some districts showing inequality in socio-demographic factors, whereas others showed none at all.

Conclusions: This study found evidence of inequalities in the provision of joint replacement surgery. However, before we can conclude that there is inequity in receipts of healthcare, future research must consider whether these patterns are explained by variations in need across socio-demographic groups.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Arthroplasty, Replacement, Hip / statistics & numerical data*
  • Arthroplasty, Replacement, Knee / statistics & numerical data*
  • Databases, Factual
  • Elective Surgical Procedures / statistics & numerical data
  • England
  • Ethnicity / statistics & numerical data
  • Female
  • Health Services Accessibility / statistics & numerical data*
  • Healthcare Disparities / statistics & numerical data*
  • Hospitals, State / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Regression Analysis
  • Sex Factors
  • Socioeconomic Factors
  • State Medicine