Patterns and Predictors of HIV, Sexually Transmitted Infections, and Staphylococcus Aureus Co-Infection among New York State Prison Inmates

Patterns and Predictors of HIV, Sexually Transmitted Infections, and Staphylococcus Aureus Co-Infection among New York State Prison Inmates

by Nowai L. Keleekai

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U.S. prisons are overextended, physically restrictive environments. Overcrowding in these facilities enhances the transmission of infectious, communicable diseases. At the same time, Staphylococcus aureus (S. aureus) colonization and infection rates are elevated in these settings. Moreover, HIV and sexually transmitted infections (STIs) are also prevalent. The purpose of this cross-sectional, correlational secondary analysis was to describe patterns of S. aureus co-infection with HIV and STIs in two New York State prisons and to identify risk factors for co-infection. Cultures were obtained from the anterior nares and oropharynx of a convenience sample of male (n = 383) and female (n = 373) prisoners in each facility. Descriptive and comparative statistics were used to accomplish the study aims. Overall S. aureus colonization rate was 53.8%. Among men, the rates of HIV-S. aureus and STI-S. aureus coinfection were 75% and 45.7%, respectively. Among women, the rates of HIV-S. aureus and STI-S. aureus co-infection were 47.4% and 59.1%, respectively. No statistically significant differences in S. aureus carriage rates were detected when comparing subjects with and without HIV or STIs. Multivariate logistic regression techniques were used to identify predictors of STIS. aureus co-infection in women. Insufficient numbers of subjects with HIV and men with STI-S. aureus limited regression modeling in these groups. After adjusting for age, race/ethnicity, and educational level, only taking more (10.1 vs 8.6) showers each week was significantly associated with increased risk of co-infection (p = .04). Results of this study suggested that rates of S. aureus carriage may be uniformly elevated across many risk groups in prisons. Suboptimal sample size limited interpretation of the study results.

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