Little is known about the age
of onset of sexual and drug risk and their association with complex patterns of
recent drug use among male sex workers (MSW) in a developing country, such as
Vietnam.
The aim of this study was to determine whether latent class analysis
(LCA) would aid in the detection of current individual and polydrug use
combinations to predict how different trajectories of sexual and drug
initiation contribute to different patterns of current illicit drug use. Data
were collected from a cross-sectional survey administered to young MSWs between
2010 and 2011 in Vietnam (N = 710). LCA clustered participants into
recent drug use groups, incorporating both the specific types and overall count
of different drugs used. Men reported drug use within a 1 month period from an
11-item drug use list. LCA identified three distinct drug use classes: (1)
alcohol use, (2) alcohol and tobacco use, and (3) high polydrug use.
The
current drug use classes are associated with sex worker status, housing
stability, income level, educational attainment, marital status, sexual
identity, and sexual preferences. High levels of drug use are strongly
associated with being a recent sex worker, not having recent stable housing,
higher than median income, more than a high school education, less likely to be
currently in school and more likely to have non-homosexual preferences and
heterosexual partners. An event history analysis approach (time-event displays)
examined the timing of the age of onset of drug and sexual risks. Early ages of
drug and sexual initiation are seen for all three classes. High current drug
users show earlier onset of these risks, which are significantly delayed for
moderate and low current drug users. LCA incorporating an overall count of
different drugs detected three distinct current drug use classes.
The data
illustrates that the complexity of drug factors that must be accounted for,
both in advancing our epidemiological understanding of the complexity of drug
use and the use of drug and sexual risk initiation data to predict current drug
use subtypes among high-risk populations.
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By:
- 1New York University College of Nursing, 433 First Avenue, 7th Floor, New York, NY, 10010, USA. gy9@nyu.edu.
- 2New York University College of Nursing, 433 First Avenue, 7th Floor, New York, NY, 10010, USA.
- 3School of Public Health, University of Puerto Rico Medical Science Center, San Juan, PR, USA.
- 4Center for Research and Training on HIV/AIDS, Hanoi Medical University, 1 Tôn Thất Tùng Street, Room 601, Building A1, Hanoi, Vietnam.
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