Chlamydia trachomatis (Ct ) is the most common bacterial sexually transmitted infection (STI) in most high-income countries, and ongoing transmission in the population can cause serious complications if left untreated, such as pelvic inflammatory disease, ectopic pregnancies, and subfertility. To prevent transmission and with that minimalizing the risk on serious complications, several countries have adopted population-based screening programs on chlamydial infection for (high-risk) populations or pregnant women. One can think of programs such as the National Chlamydia Screening Program in the United Kingdom,1 2 3
One of the aspects of a screening program where insights are lacking is the effect of a Ct test result on sexual risk behavior in the subsequent period. In the last decades, a few studies have examined the effect of the STI test results on the subsequent sexual behavior.4–7 4,5,7,8 4–6,8 4,5 4,5,7,8 6,7 9–13
Especially about the influence of a negative Ct test result, little is known, whereas this is of importance for countries with a relatively low prevalence of chlamydia. Screening programs in these countries will result in many negative test results, and if a negative test result leads to increased sexual risk behavior, adoption of a screening program might change the cost-benefit ratio of the program. Another reason why it is important to gain more knowledge on the influence of test results on sexual risk behavior is because of the increase in home-based self-sampling. In a recent review, it is shown that home-based self-sampling results in greater uptake of STI screening than clinic-based testing, whereas specimen quality was not reduced14 Ct negatives might be needed.
The objective of this study is to examine the effect of a chlamydia test result on sexual risk behavior 1 year after the test, and we hypothesize that Ct positives will reduce their sexual risk behavior and that the test result will have no or a minimal effect with regard to sexual risk behavior for those who tested negative. In the Netherlands, a large Chlamydia Screening Implementation (CSI) for 16- to 29-year-old residents of 3 areas in the Netherlands was conducted.15
METHODS
Screening Set-Up
Details of the CSI program and design can be found elsewhere.15,16 Ct risk (measured by an online questionnaire) were eligible to participate (for cost-effectiveness reasons), whereas in Amsterdam and Rotterdam, all sexually active persons of that age could participate. Each year (2008–2011, a total of 4 rounds), all residents received an invitation letter by mail. The target population was invited with a personal letter to fill out a questionnaire and to request a chlamydia test kit online. The test kit included a home sample kit (men: urine sample, women: vaginal swab or urine sample). The questionnaire contained questions about age, sex, and characteristics such as self-reported sexual history and clinical symptoms. Participants who tested positive received a new test kit automatically after 6 months, but no questionnaire was sent along with this new test kit. Participants provided informed consent online, and the program was approved by the Medical Ethics Committee Free University Amsterdam (Identification No. 2007/239).
For this study, only participants who had Ct test results and completed questionnaires in 2 or more rounds were included. Measurements in round 4 were excluded because the response rate was not equally divided among the different regions, which made the population in round 4 less comparable with the first 3 rounds.
Statistical Analysis
In this study, the effect of a chlamydia test result on sexual risk behavior 1 year after the test is examined (Fig. 1 ). The outcome is defined as sexual risk behavior after a positive or negative chlamydia test result, and this is measured by 8 indicators. The sexual risk behavior indicators included frequency of condom use in the last 6 months with a steady partner (ordinal—5 levels), frequency of condom use in the last 6 months with a casual partner (ordinal—5 levels), condom use at last sexual contact with a steady partner (dichotomous), condom use at last sexual contact with a casual partner (dichotomous), the number of sexual partners in the last 6 months (count), having casual sexual partners in the last 6 months (dichotomous), having concurrent sexual partners in the last 6 months (dichotomous), and having sex with a new sexual partner in the last 2 months (dichotomous).
Figure 1: Flowchart of study design.
The influence of a chlamydia test result on sexual behavior was analyzed by generalized estimating equation (GEE) models, using the SAS 9.3 statistical software program. Models were generated with the Ct test result of the previous round as an independent variable and the sexual risk behavior indicator as a dependent variable. This resulted in 8 different statistical models, one for each sexual risk behavior indicator. In the models with a dichotomous outcome (condom use at last sexual contact with steady or casual partner, having a casual or concurrent partner in the last 6 months or initiation of new sexual relationship), a binomial distribution with a logit link was used. In addition, a repeated-measurements statement with an autoregressive correlation matrix was included to account for dependency within participants. In the model with the total number of partners as outcome, a Poisson distribution with a log link was used with an autoregressive correlation matrix. For the indicators frequency of condom use with a steady or casual partner, a multinomial distribution with a cumulative logit link was used with an independent correlation matrix. The independent correlation matrix is currently the only matrix available in the above-mentioned procedure with a multinomial distribution. However, within GEE models, the covariance structure over time is treated as nuisance, and therefore, the estimates of the regression coefficients and their standard errors based on GEE are consistent even with mis-specification of the covariance structure for the data.17
All GEE models were adjusted for sexual behavior for that specific indicator in the previous round because, otherwise, we would not measure the change in sexual risk behavior, but only the sexual risk behavior after a Ct test result. By adjusting for the sexual risk behavior in the previous round, we basically removed all differences between the participants on baseline sexual risk behavior, and therefore, the differences in sexual risk behavior measured after the Ct test reflect the change in sexual risk behavior. We did not choose for a classic GEE model in which we could conduct formal statistical comparisons of sexual behavior over time, separately by Ct status, because we believe that this is only possible if the Ct status is static, which is not the case. The objective of this research is therefore not to estimate the effects of a Ct test result on sexual risk behavior over time, but to estimate the effect of a Ct test result on sexual risk behavior 1 year after the diagnosis.
In addition, to rule out other causes for a possible difference between Ct positives and Ct negatives, extended GEE models were constructed and these were adjusted for age, sexual preference, ethnicity, region of screening, participation/result of retest, time between participation in rounds (in days), and number of rounds participated. The extended GEE models other than condom use with a steady or casual partner as a sexual risk indicator were additionally adjusted for (currently) having a steady or casual partner. The covariates were selected based on prior knowledge and/or univariate analysis (α < 0.10). We added first-order interaction terms (all separate covariates with Ct test result) to the model to check for interaction, but none of these terms were found significant (α > 0.10, data not shown). We therefore excluded first-order interaction terms for further analyses.
RESULTS
Of 48,910 participants with completed questionnaires and test results, 14.1% (n = 6802) and 2.6% (n = 1272) completed 2 and 3 rounds, respectively, and were included in this study. The study population differed in baseline characteristics from the participants in the screening program with only 1 completed round. Compared with the participants with only 1 completed round, participants with 2 or 3 completed rounds were slightly younger; and more likely to be female, single, from Dutch origin and recruited for screening in the cities of Amsterdam and Rotterdam (Table 1 ). In addition, chlamydia positivity at first round of participation was 5.2% in those who completed only 1 round, 4.7% in those who completed 2 rounds, and 4.1% in those who completed 3 rounds of the screening program. Finally, when looking at the sexual risk behavior indicators at first round of screening (baseline), it can be seen that those who completed only 1 round showed slightly more risky sexual behavior.
TABLE 1: Basic Characteristics of the CSI Population by Rounds Completed, 2008–2011
In Table 2 , the results on sexual risk behavior indicators at the round of Ct test result and the round after Ct test result are shown for Ct positives and Ct negatives separately. In general, Ct positives were more likely to change their behavior after a Ct test result in a more positive and protective direction than Ct negatives, who were more likely to change their behavior toward more risky behavior. Big differences between the 2 groups were seen on the indicators of condom use with a casual partner. Ct positives less often reported to “never” use condoms with a casual partner (−5.7%; 95% confidence interval [CI], −10.3 to −0.9), whereas Ct negatives less often reported to “always” use condoms with a casual partner (−4.6%; 95% CI, −6.4 to −2.8). When looking at condom use at last sexual contact with a casual partner, Ct positives more often used condoms (+18.3%; 95% CI, 7.3 to 29.3), whereas Ct negatives decreased the use of condoms (−4.8%; 95% CI, −7.2 to −2.5). Differences between the 2 groups on condom use with a steady partner were smaller. Furthermore, Ct positives reduced sexual contact with a casual partner after the Ct test result (−6.4% [−12.2 to −0.6]), whereas Ct negatives did not change this sexual contact (+0.4% [−0.7 to 1.6]). In the same line, Ct -infected participants showed less sexual contact with concurrent partners (−6.2% [−12.2 to −0.3]), whereas Ct negatives slightly increased these sexual contacts (+1.3% [0.3 to 2.4]). Both Ct negatives and Ct positives did not change sexual contact with a new partner. Differences between the 2 groups on total number of partners were hard to quantify because most participants had no or one sexual partner, and therefore, differences were very small.
TABLE 2: Results of Sexual Risk Behavior Indicators at Round of Ct Test Result and Round After Ct Test Result, for Ct Positives and Ct Negatives
To test if these differences remained significant after adjustment for confounding, GEE models were used. When first looking at the models on condom use with a casual partner (frequency and at last sexual contact), it can be seen in Table 3 that both models showed borderline significant results when unadjusted for confounding (respectively, odds ratio [OR; 95% CI], 1.34 [0.98 to 1.81] and 1.48 [1.03 to 2.13]). After controlling for confounding, only, the model on frequency of condom use with a casual partner remained significant (OR [95% CI], 1.75 [1.09 to 2.80]), indicating that Ct positives and Ct negatives really differed in the frequency of condom use after a Ct test result: Ct positives changed their behavior toward more protective behavior, whereas Ct negatives changed their behavior in a more risky direction. One other model showed a significant result after correction for confounding, namely, the model on total number of partners. Ct positives were 1.14 times as likely as Ct negatives to have 1 more sexual partner (95% CI, 1.01 to 1.29). The other differences described above on sexual risk behavior indicators between Ct positives and Ct negatives were not significant after adjustment for confounding (Table 3 ).
TABLE 3: The Influence of Positive Ct Test Result in the Previous Round on Sexual Risk Behavior, for 8 Sexual Risk Behavior Indicators (GEE Models)
DISCUSSION
In this study, we examined the association of a positive or negative chlamydia test result with subsequent sexual risk behavior. In general, it can be concluded that Ct positives were more likely to change their behavior after a Ct test result in a more positive and protective direction than Ct negatives, who were more likely to change their behavior toward more risky behavior. The strongest effects were found on condom use with a casual partner; after a positive Ct test result, participants less frequently “never” used condoms with a casual partner, whereas after a negative Ct test result, participants less frequently “always” used condoms with a casual partner. In addition, a smaller effect was found on total number of sexual partners; after a positive Ct test result, participants were slightly more likely to have more sexual partners than after a negative Ct test result.
When comparing the results of this study with earlier studies, similar findings were reported by Crosby et al.5 7 4 9–11,13
In our study, a relatively long follow-up period of 1 year was present compared with other studies,5,7 7
As far as we know, this is the first study examining the association of a Ct test result on subsequent sexual risk behavior in such a large study population. However, although the population was large, the number of Ct positives was quite small given the low prevalence of chlamydia in the population. One limitation of our study design was that we could only include participants with 2 or more completed rounds. This resulted in a study population that showed less risky behavior than the ones excluded from this study (lower Ct positivity, more women, more participants from Dutch origin, and less risky sexual behavior at baseline for those included; Table 1 ). Therefore, the results of this study can easily be generalized to a low-risk population, but generalizability to a more risky population might be limited.
There was one other aspect in this study design that could have influenced our results. If a participant was found Ct positive, they were asked to return for an additional Ct test after 6 months, giving participants of this retest an additional contact moment and this could therefore possibly have increased awareness and have influenced sexual risk behavior. Because no questionnaire was taken at this time point for the first 2 screening rounds, we could not incorporate this measurement in our study design. We therefore adjusted our analysis for participation in this retest. Additional analysis (data not shown) showed that if we did not adjust for participation in the retest, results remained the same.
The results of this study implicate that it remains questionable if harm with respect to more risky sexual behavior was done by introducing a chlamydia screening program in a low-risk population. We showed that if Ct negatives changed their behavior after the test result, it was toward more risky behavior. After a positive Ct test result, the behavior change was more likely to be in a safe direction than in a more risky direction. However, because a screening program will yield more negative Ct test results, we would suggest to conduct further research on the effects over time after a negative Ct test result. Especially because it can be expected that by an increasing popularity of home-based self-sampling by participation in all kinds of e-health programs for prevention of STI, a bigger and probably less risky population will be reached. It is then important to know what happens after a negative Ct test result over time.
To conclude, Ct test results were associated with subsequent sexual risk behavior. Ct positives less often reported to “never” use condoms with a casual partner and reported slightly more sexual partners at follow-up. Ct negatives less often reported to “always” use condoms with a casual partner. Effects over time after a Ct test should be investigated further, especially in the Ct negatives.
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