Hospitalization rates associated with hepatitis B and HIV co-infection, age and sex in a population-based cohort of people diagnosed with hepatitis C

Epidemiol Infect. 2011 Aug;139(8):1151-8. doi: 10.1017/S095026881000258X. Epub 2010 Nov 19.

Abstract

To determine the extent age, sex and co-infection affect morbidity in people infected with hepatitis C virus (HCV), we performed a population-based study linking HCV notifications in New South Wales, Australia with their hospital (July 2000 to June 2006), hepatitis B virus (HBV) and HIV notification, and death records. Poisson models were used to calculate hospitalization rate ratios (RRs) for all-cause, illicit drug and liver-related admissions. Co-infection RRs were used to estimate attributable risk (AR). The 86 501 people notified with HCV contributed 422 761 person-years of observation; 0·8% had HIV, 3·7% HBV, and 0·04% had both. RRs for males were equal to or lower than for females in younger ages, but higher in older ages (P for interaction ⩽0·013). HBV/HIV co-infection resulted in ARs of over 70% for liver disease and 30-60% otherwise. However, at the cohort level the impact was minimal (population ARs 1·3-8·7%). Our findings highlight the importance and success of public health measures, such as needle and syringe exchange programmes, which have helped to minimize the prevalence of co-infection in Australia. The findings also suggest that the age of study participants needs to be considered whenever the burden of HCV-related morbidity is reported by sex. The results are likely to be representative of patterns in hospital-related morbidity for the entire HCV-infected population in Australia and the ARs generalizable to other developed countries.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Distribution
  • Female
  • HIV Infections / complications*
  • HIV Infections / epidemiology*
  • Hepatitis B / complications*
  • Hepatitis B / epidemiology*
  • Hepatitis C / complications*
  • Hepatitis C / epidemiology*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Male
  • Models, Statistical
  • New South Wales / epidemiology
  • Prevalence
  • Sex Distribution