Amsterdam 2015
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| Abstract #2172 - Boystown - MSM I | ||||
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Session: 15.6: Boystown - MSM I (Symposium) on Wednesday @ 14.30-16.00 in C104 Chaired by Udi Davidovich, Kenneth Mayer Authors: Presenting Author: Dr Chantal den Daas - RIVM, Netherlands |
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| Additional Authors: | ||||
| Aim: Early detection and treatment of STIs/HIV are important public health priorities. Our objective was to compare characteristics of men who have sex with men (MSM) in Dutch data available in 2010 from EMIS, an international internet survey, Schorer Monitor, a Dutch internet survey, as well as data from STI-clinic visits, since these might be subject to different and unknown biases. | ||||
| Method / Issue: Data from Dutch MSM Internet Surveys (EMISNL N=3,787 Schorer Monitor, SMON N=3,602), and 3,800 STI clinic visits (SOAP) were combined into one dataset. We included factors that were measured in all three databases. The socio-demographics included were age (at the time of the survey), zip code, and ethnicity. Behavioural variables included were the number of sexual partners, condom use with last sexual partner, drug use, being diagnosed with STI(s), being diagnosed with HIV, and HIV testing. The outcomes we investigated were being diagnosed with HIV, and never been tested for HIV. | ||||
| Results / Comments: Logistic regressions showed that determinants for being diagnosed with HIV were being older, living in Amsterdam, and having more partners (aORs 1.8 to 4.4). In EMIS and SMON, drug use, condom use, and having STI(s) were additional determinants (aORs 1.6 to 8.9). Finally, determinants associated with never been tested for HIV were being younger (only SOAP), living outside of Amsterdam, having fewer partners, no drug use, and no STI(s) (aORs 0.2 to 0.8). | ||||
| Discussion: Risk factors from internet surveys were largely similar, but differed from STI clinics, possibly because it involves self-reports rather than diagnoses or because of differences in timing. Specifically, when interested in risk factors for contracting STI and HIV, recruitment method seems important. The difference between the internet surveys and STI clinic data is much less pronounced for having never been tested, suggesting both are appropriate for this outcome. These findings shed light on the comparability of recruitment strategies, the robustness of risk factors, consequences of phrasing questions differently, and on (policy) implications based on different data sources. Finally, this research sheds light on the differences in conclusions drawn based on different data sources, which are pronounced between internet surveys and data from STI clinics. | ||||
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