Determinants of being diagnosed with STI or HIV differed remarkably between MSM recruited from STI clinics and MSM participating in internet surveys, whereas the data obtained from the two internet surveys were largely comparable. Moreover, the risk factors found via internet surveys for being diagnosed with STI/HIV are largely similar to findings from previous research [18, 19]. The outcome of having never tested for HIV differed from the outcomes of being diagnosed with STI/HIV. The differences between risk factors between the internet surveys and STI clinic are much less pronounced for this outcome. We will discuss each determinant in the context of the outcomes of this study, the Dutch situation, and previous research.
Determinants for being diagnosed with STI/HIV and never been tested for HIV
In all three databases, older MSM were more likely to be diagnosed with HIV, as is to be expected. Older MSM will have had more sexual contacts, and are more likely to be exposed to HIV. Moreover, older MSM are also less likely to never been tested for HIV, although multivariably this result only remains for STI clinic data.
Overall, younger and older MSM seem to be underrepresented assuming an equal fraction of MSM over age groups. However, younger MSM (<20 years) might genuinely be a smaller group, because they might not be sexually active or did not ‘come out’ yet. Similarly, there might be less older MSM (>55 years); due to HIV/AIDS or due to the political, legal and cultural climate of their youth [20]. Moreover, the Dutch sample seems somewhat more biased towards older, gay identified, HIV positive MSM as also mentioned in the introduction [10]. Notably, the age distribution is similar in all three databases. Furthermore, in a panel study from 2013, the age of a comparable group of MSM, is even higher than in our databases (mean age 50 years) [21]. This might suggest that people that participating in panel research might be older, but it is also an indication that the higher age of MSM in the Netherlands compared to other countries might not be a bias, but a true representation of the Dutch situation.
MSM from Amsterdam are more likely to be diagnosed with STI/HIV, they are also more likely to be tested for HIV. Because of the large MSM population in Amsterdam, there are more facilities for sexual contacts and testing. More temptations on the one hand, might increase chances to contract STI/HIV. On the other hand, this also affects openness towards and opportunities for testing. A lot of the STI/HIV prevention efforts focus on Amsterdam, and this shows that even though successful (fewer MSM never tested), there might still increased chance to contract STI/HIV. This research suggests that intervention aimed to increase testing uptake could focus more on people not living in Amsterdam, whereas STI and HIV prevention should still be targeted towards MSM in Amsterdam as well.
In the three databases, MSM were either asked about ethnic group, their country of birth, or their cultural background. Surprisingly, the overall composition of ethnicity seems similar over the databases. Indicating that, independent of recruitment method, some ethnic groups were not reached. This included some of the most important minority groups in the Netherlands (i.e., minorities from Turkey, Morocco, Surinam, and the Dutch Antilles). Future research on sexual behaviour should explicitly aim to recruit MSM with specific ethnic backgrounds, or find other ways to investigate behaviour among MSM from the biggest ethnic minority groups in the Netherlands.
Having more partners has divergent influence on being diagnosed with STI/HIV depending on whether data was obtained via internet surveys or from STI clinic attendees, but no difference was found between the databases for having never tested for HIV. Having more partners was a determinant associated with testing, which makes sense as having more partners implies more risk, hence more reasons to test for HIV. Furthermore, having more partners was indicative for being diagnosed with STI but not for being diagnosed with HIV in the internet surveys. STI were reported for the last 12 months, whereas HIV was naturally reported for lifetime, in that light finding an association between the number of partners (over the last 6 or 12 months) for having STI and not for HIV is logical.
Internet surveys and STI clinic data differed for condom use with last sexual partner. Despite the high number of missing data, condom use with the last partner in the internet surveys was protective against STI and HIV, whereas in the STI clinic it was a risk factor for STI and had no effect on HIV positivity. This difference could be explained by timing. Specifically, MSM might visit an STI clinic when there is an indication to do so. Possibly, people visiting an STI clinic suspect a STI, and therefore prospectively used condoms immediately before the visit.
The results for drug use were consistent. Unfortunately, we did not have information on drug use for STI clinic visitors. Using drugs was positively associated with STI diagnosis, diagnoses with HIV, and had tested for HIV. Possibly, drug use influenced risk behaviour directly with drug use resulting in more risky behaviours. Drug use could also influence outcomes indirectly, as people who are more likely to use drugs may also take risk in other domains, because they have an impulsive or sensation-seeking personality [22]. However, risk taking in one domain (doing drugs) is not necessarily indicative for risk taking in other domains [23]. It is important to notice that, frequency of use and the moment of drug use (before or during sexual intercourse) were not assessed. We found similar patterns of behaviour irrespective of the sort of drugs (i.e., uppers, downers, or party drugs); future research should take frequency, sort, and timing of drug use into account. Despite lack of details, drug use still was an important risk factor related to all three outcomes.
Finally, being diagnosed with one or more STI was also associated with being diagnosed with HIV and decreased the chance that MSM had never been tested for HIV. These factors are largely in line with previous studies using EMIS data [18, 19, 24]. In addition, being tested for HIV (and especially being tested positive) increased the risk of being diagnosed with STI.
Strengths and Limitations
One important limitation of this study is the possible overlap between the databases. The same MSM might have contributed data to all three databases. Moreover, MSM who took part in EMIS after being invited via e-mail the submitted previously to SMON probably filled out both, unfortunately we are unable to identify overlapping records. Since, the internet surveys contained many questions and took some effort to fill out, self-selection bias could have taken place. MSM who are sexually active and attach importance to STI and HIV prevention might be inclined to participate in one or both surveys. Despite our efforts to limit the chances of double participation by our selection of cases in the STI clinic data, we cannot entirely rule out overlap.
Another limitation is that these databases were not designed to be comparable, reflected most notably in difference in question phrasing, content of the questions, and the reference times. Obviously, there have been and still are initiatives for harmonization in the collection of behavioural data within Europe [25]. Notably, even though the surveys are not always comparable, their results are quite similar.
Finally, there is a limited availability of behavioural data in SOAP. This database is intended for surveillance and not research purposes. In the future, we plan to compare additional variables of EMIS and SMON, which were omitted in the current study because they were unavailable in SOAP. It will be possible to look at other psychosocial factors, such as unsafe anal intercourse with steady and casual partners, knowledge, and beliefs [18, 19, 24]. Besides limitations of overlap between the databases, strengths of this research are in the sample sizes of all three databases.
