Unsafe Injection Is Associated with Higher HIV Testing after Bayesian Adjustment for Unmeasured Confounding

Arch Iran Med. 2020 Dec 1;23(12):848-855. doi: 10.34172/aim.2020.113.

Abstract

Background: To apply a novel method to adjust for HIV knowledge as an unmeasured confounder for the effect of unsafe injection on future HIV testing.

Methods: The data were collected from 601 HIV-negative persons who inject drugs (PWID) from a cohort in San Francisco. The panel-data generalized estimating equations (GEE) technique was used to estimate the adjusted risk ratio (RR) for the effect of unsafe injection on not being tested (NBT) for HIV. Expert opinion quantified the bias parameters to adjust for insufficient knowledge about HIV transmission as an unmeasured confounder using Bayesian bias analysis.

Results: Expert opinion estimated that 2.5%-40.0% of PWID with unsafe injection had insufficient HIV knowledge; whereas 1.0%-20.0% who practiced safe injection had insufficient knowledge. Experts also estimated the RR for the association between insufficient knowledge and NBT for HIV as 1.1-5.0. The RR estimate for the association between unsafe injection and NBT for HIV, adjusted for measured confounders, was 0.96 (95% confidence interval: 0.89,1.03). However, the RR estimate decreased to 0.82 (95% credible interval: 0.64, 0.99) after adjusting for insufficient knowledge as an unmeasured confounder.

Conclusion: Our Bayesian approach that uses expert opinion to adjust for unmeasured confounders revealed that PWID who practice unsafe injection are more likely to be tested for HIV - an association that was not seen by conventional analysis.

Keywords: Bayesian Analysis; Drug injections; HIV; Unmeasured confounder; Unsafe injection.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Bayes Theorem
  • Bias*
  • Drug Users
  • Expert Testimony*
  • Female
  • HIV Infections / transmission*
  • HIV Seropositivity / epidemiology*
  • HIV Testing
  • Humans
  • Male
  • Prospective Studies
  • Regression Analysis
  • Risk-Taking
  • San Francisco / epidemiology
  • Substance Abuse, Intravenous / epidemiology*
  • Young Adult