Youth, unemployment, and male gender predict mortality in AIDS patients started on HAART in Nigeria

AIDS Care. 2009 Jan;21(1):70-7. doi: 10.1080/09540120802017636.

Abstract

This retrospective study identifies risk factors for mortality in a cohort of HIV-positive adult patients treated with highly active antiretroviral therapy (HAART) in Jos, Nigeria. We analyzed clinical data from a cohort of 1552 patients enrolled in a HIV/acquired immune deficiency syndrome treatment program and started on HAART between December 2004 and 30 April 2006. Death was our study endpoint. Patients were followed in the study until death, being lost to follow-up, or the end of data collection, 1 December 2006. Baseline patient characteristics were compared using Wilcoxon Rank Sum Test for continuous variables and Pearson Chi-Square test for categorical variables to determine if certain demographic factors were associated with more rapid progression to death. The Cox proportional hazard multivariate model analysis was used to find risk factors. As of 1 December 2006, a total of 104 cases progressed to death. In addition to the expected association of CD4 count less than 50 at initiation of therapy and active tuberculosis with mortality, the patient characteristics independently associated with a more rapid progression to death after initiation of HAART were male gender, age less than 30 years old, and unemployment or unknown occupation status. Future research is needed to identify the confounding variables that may be amenable to targeted interventions aimed at ameliorating these health disparities.

MeSH terms

  • AIDS-Related Opportunistic Infections
  • Adolescent
  • Adult
  • Age Factors
  • Antiretroviral Therapy, Highly Active / mortality*
  • CD4 Lymphocyte Count
  • Cohort Studies
  • HIV Infections / complications
  • HIV Infections / drug therapy
  • HIV Infections / mortality*
  • Humans
  • Male
  • Nigeria / epidemiology
  • Proportional Hazards Models
  • Retrospective Studies
  • Risk Factors
  • Sex Factors
  • Tuberculosis / epidemiology
  • Unemployment / statistics & numerical data*