Using latent class analysis to identify money boys at highest risk of HIV infection

Abstract

ObjectivesLimited research has been conducted to investigate the characteristics of money boys (MBs) in China. This study was aimed to identify the subgroups of MBs based on sexual behaviors, Net-based venue sex-seeking, and substance abuse. Study designCross-sectional study. MethodsConvenience sampling was used to recruit MBs from December 2014 to June 2015 in Tianjin, China. Face-to-face interviews were conducted for 330 MBs, and trained interviewers collected data. ResultsThe laboratory-confirmed human immunodeficiency virus (HIV)–positive rate was 11.52% among 330 MBs. Four classes were identified through latent class analysis (LCA) method: ‘relatively safe behavior’ group, ‘higher sexual risk’ group, ‘multiple sexual-partners’ group, and ‘unprotected sex and substance abuse’ group, and there is a significant difference based on the HIV status. Significant differences were found in original residence, monthly income, duration in sex trade, employment, history of sexually transmitted infection (STI), HIV testing, knowledge of free antiviral treatment policy, and awareness of free AIDS testing between the four latent classes (P < 0.05). MBs who used Net-based venues to seek sexual partners; who have inconsistent condom use, substance abuse, a longer duration in sex trade, multiple sexual clients, and multiple anal sex; and who were full-time employed had the highest risk of HIV infection. ConclusionsThe utility of LCA to identify subgroups based on risky behaviors attributes to formulating targeted intervention strategy.