Abstract

To develop a human immune deficiency virus (HIV) infection risk appraisal model suitable for men who has sex with men (MSM) in Guangzhou, and to provide tools for follow-up the outcomes on health education and behavior intervention. A cros-sectional study was conducted in Guangzhou from 2008 to 2010. Based on the HIV surveillance data, the main risk factors of HIV infection among MSM were screened by means of logistic regression. Degree on relative risk was transformed into risk scores by adopting the statistics models. Individual risk scores, group risk scores and individual infection risk in comparison with usual MSM groups could then be calculated according to the rate of exposure on those risk factors appeared in data from the surveillance programs. Risk factors related to HIV infection among MSM and the quantitative assessment standard (risk scores and risk scores table of population groups) for those factors were set up by multiple logistic regression, including age, location of registered residence, monthly income, major location for finding their sexual partners, HIV testing in the past year, age when having the first sexual intercourse, rate of condom use in the past six months, symptoms related to sexually transmitted diseases (STDs) and syphilis in particular. The average risk score of population was 6.06, with risk scores for HIV positive and negative as 3.10 and 18.08 respectively (P < 0.001). The rates of HIV infection for different score groups were 0.9%, 2.0%, 7.0%, 14.4% and 33.3%, respectively. The sensitivity and specificity on the prediction of scores were 54.4% and 75.4% respectively, with the accuracy rate as 74.2%. HIV infection risk model could be used to quantify and classify the individual's infectious status and related factors among MSM more directly and effectively, so as to help the individuals to identify their high-risk behaviors as well as lifestyles. We felt that it could also serve as an important tool used for personalized HIV health education and behavior intervention programs.

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