Bias Adjustment Techniques Are Underutilized in HIV Sexual Risk Estimation: A Systematic Review

Nguyen K. Tran, Neal D. Goldstein and Seth L. Welles
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Nguyen K. Tran: Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA 19104, USA
Neal D. Goldstein: Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA 19104, USA
Seth L. Welles: Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA 19104, USA

IJERPH, 2018, vol. 15, issue 8, 1-15

Abstract: Background: Valid measurement of determinants of HIV infection among men who have sex with men (MSM) is critical for intervention planning and resource allocation. However, sexual minority research concerning HIV risk often relies on proxy exposures of sexual behaviors such as sexual orientation and partner gender. Inferring high risk sexual behaviors (i.e., condomless anal intercourse) from these proxies inaccurately captures HIV risk, but few studies have attempted to correct for this bias. Methods: We performed a systematic review of methodological practices for estimating risk of HIV infection among MSM. Results: We identified 32 studies in which high risk sexual behavior was assessed: 82% ( n = 26) measured and used sexual risk behaviors (e.g., condomless anal intercourse or sexual positioning) to assess risk of HIV infection; 9% ( n = 3) used proxy measures; and 9% ( n = 3) used both behavior and proxy variables. Various treatments of misclassification reported by investigators included the following: 82% ( n = 26) discussed misclassification of sexual behavior as a potential limitation; however, among these studies, no attempts were made to correct misclassification; 12% ( n = 4) did not report exposure misclassification, and 6% ( n = 2) explicitly considered this information bias and conducted a Bayesian approach to correct for misclassification. Conclusions: Our systematic review indicates that a majority of studies engaging in collecting primary data have taken additional steps to acquire detailed information regarding sexual risk behaviors. However, reliance on population-based surveys may still lead to potentially biased estimates. Thus, bias analytic techniques are potential tools to control for any suspected biases.

Keywords: HIV/AIDS; men who have sex with men; misclassification; exposure assessment (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
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