Modeling the need for hip and knee replacement surgery. Part 1. A two-stage cross-cohort approach.
Judge A., Welton NJ., Sandhu J., Ben-Shlomo Y.
OBJECTIVE: To explore inequalities in the need for hip/knee replacement surgery using a 2-stage cross-cohort approach. METHODS: In the first stage, a small-area population-based survey, the Somerset and Avon Survey of Health, was used to provide a high-quality measure of need for hip/knee replacement using the New Zealand (NZ) score. Receiver operating characteristic curve analyses were used to validate a simplified NZ score, excluding information from clinical examination. In the second stage, a nationally representative population-based survey, the English Longitudinal Study of Ageing, was used to explore inequalities in need for hip/knee replacement using the simplified NZ score. Multilevel Poisson regression modeling was used to estimate rates of need for surgery. Exposures considered were age, sex, social class, ethnicity, obesity, Index of Multiple Deprivation 2004 deprivation quintiles, rurality, and ethnic mix of area. RESULTS: Rates of need for hip/knee replacement increase with age and are lower in men than in women (rate ratio [RR] 0.7, 95% confidence interval [95% CI] 0.6-0.9 for hips; RR 0.8, 95% CI 0.7-1.0 for knees). Those of lowest social class have greater need. Need was greatest for people living in more deprived areas. Individual ethnic group did not predict the need for surgery. For hip replacement, there was no rurality effect; for knee replacement, those in town and fringe areas had greater need. Obesity was a strong predictor of need for surgery (RR 2.3, 95% CI 1.9-2.8 for hips; RR 2.4, 95% CI 2.0-2.8 for knees). CONCLUSION: This study provides evidence of greater variations of inequalities in need for hip/knee replacement than previous studies. Further research should explore geographic variation and produce small-area estimates of need to inform local health planning. It is important to complement data on need with willingness to undergo surgery.