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Try out PMC Labs and tell us what you think. Learn More. Among adolescents and young adults, the extent that partner characteristics for sexually transmitted diseases STDs in context of individual sexual activities and demographic characteristics is unclear.
We used exact logistic regression to calculate odds ratios OR for several sexual partner characteristics age discordance, incarceration, STD diagnosis, other partners, alcohol problem, marijuana problem, and a calculated composite variable adjusting for demographics and individual sexual activities, including condom use.
In the United States, 9 million cases of sexually transmitted diseases STDs occurred among 15 to year-olds in The relative importance of partner characteristics and individual sexual activities e.
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Among urban STD clinic attendees ages 15 to 24 years, we pursued 2 objectives to improve understanding of the influence of partner characteristics on STD risk. First, we assessed the association between STD diagnosis and a composite measure of partner characteristics incorporating age discordance, incarceration, STD diagnosis, other partners, alcohol problem, and marijuana problem. Second, we compared the association between STDs and partner characteristics to the association between STDs and individual sexual activities. STDs were assessed Sex partners in Pittsburgh mo and an interviewer administered a questionnaire about demographic variables, alcohol use, sexual activities, and sexual partner characteristics.
The present analysis includes the black and white participants who reported having heterosexual sex. Institutional Review Board approval was obtained for the study procedures from the University of Pittsburgh and for this analysis from the University of Florida.
Participants reported each characteristic for both their main partner and their most recent, not main partner. Responses for each partner were considered equally.
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Using a predetermined method, we created a simple composite partner characteristic variable that could be incorporated into clinical practice and maximized the existing data. For each of the 6 partner characteristics described above, we ased a value of 0 to the referent category and 1 to the risk category.
For each participant, we calculated the proportion of the responses in the risk category. This yielded a score ranging from 0 to 1 for each participant; 0 indicated all characteristics were in the referent category and 1 indicated all characteristics in the high risk category. For sensitivity analysis, we also created the composite without the measure of partner had a STD.
Based on the literature of individual sexual risk factors, 91215 — 19 we selected 9 measures of individual sexual activities: 1 age at first intercourse, 2 of lifetime sexual partners, 3 of past year sexual partners, 4 concurrent sex partners, 5 new sexual partner in the past month, 6 casual sex in the past 12 months, 7 sex under the influence of alcohol, 8 condom use during last sex, and 9 frequency of condom use in past 12 months. Age at first intercourse, of lifetime sex partners, and of sex partners in the past year were collected as continuous variables and categorized by the overall median response for analysis.
We also created a composite of individual sexual activities. Sex partners in Pittsburgh mo we detected moderate correlation Pearson correlation coefficient between 0.
We created the individual sexual activities composite variable with the 8 other individual sexual activities measures using the same methodology as we used to create the partner characteristic composite. In brief, we created a score from 0 to 1 by calculating the proportion of responses of increased risk among the individual sexual activities variables.
Syphilis was tested among serum samples for both sexes.
Viral culture of genital herpes was performed for suspicious lesions and genital warts were diagnosed by clinical observation. Similar to our analysis from this study, 12 an individual diagnosed with any of the above diseases was defined as having a confirmed STD. Based on the STD literature, we selected 5 covariates: race, sex, age, marital status, and type of medical insurance. Type of medical insurance was analyzed as any insurance Medicaid or private insurance versus no insurance.
We used SAS software, version 9. For each variable, we used both race-adjusted and multivariate covariates included race, sex, age, and type of medical insurance exact logistic regression to estimate the association between partner characteristics and STD diagnosis. Common to models with Sex partners in Pittsburgh mo covariates, 2122 we found that the exact permutation distribution for the sufficient statistic was computationally infeasible to calculate for our multivariate models; therefore, for multivariate models we used the LogXact network-based Monte Carlo sampling approach for conditional logistic regression to estimate unbiased exact confidence intervals.
The mean age of the study participants was All of the participants were sexually experienced. The median of lifetime sex partners was 10 range: 1— and the median of partners in the past year was 3 range: 1— We found differences between women and men on reporting of partner characteristics and individual sexual activities Table 1. Women were more likely than men to report partners with risk characteristics including discordant ages, ly in jail, and had alcohol, or marijuana problems. Men were more likely than women to report individual sexual activities with increased risk, except for condom use and sex under the influence of alcohol that were reported equally by men and women.
The odds ratios in this table compare women with men by each characteristic. For example, an odds ratio of 2. For most of the STDs examined, a similar percent of men and Sex partners in Pittsburgh mo were infected, but genital warts were more common among men than women Table 1. Compared with individuals with age concordant partners, individuals with age discordant partners were approximately 3 times as likely to have a STD. were similar for other analyses considered: adjusting for race only, analyzing blacks and whites separately, and analyzing the 4 race-sex groups separately.
Adolescents reporting condom use during their last sexual encounter were half as likely to have a STD compared with adolescents reporting no condom use Table 2. A similar association was found between condom use and STD diagnosis when considering the frequency of condom use in the past year. The associations between individual sexual activities and STD diagnosis Sex partners in Pittsburgh mo weaker than associations found between partner characteristics and STD diagnosis Table 2.
Each category of the composite variables separated the sexual activity markers well. For example, we found a ificant linear trend by category of partner composite risk low, intermediate, high in median age discordance with the most discordant sex partner 2, 3, 5 years of age difference and median of sex partners of the not-main partner 2, 3, 4 partners. Across of the individual sexual activities composite low, intermediate, highwe found ificant linear trends by the median reported of lifetime sex partners 4, 10, 23 partners and the median age at first intercourse 16, 15, years-old.
When adjusting for demographic characteristics, the partner characteristic composite was ificantly associated with STD diagnosis Table 3. When adjusting for demographic characteristics, individual sexual activity was ificantly associated with STD diagnosis Table 3. Similar to the analyses for each measure, the association between composite individual sexual activity and STD diagnosis was weaker than the association between composite partner risk and STD diagnosis Sex partners in Pittsburgh mo 3.
Partner characteristics and individual sexual activities identified different individuals Fig. Within each category of individual sexual activity, we found adolescents and young adults classified as high partner risk. Proportion of adolescents in each individual sexual risk category by composite partner characteristics. When adjusting for demographic covariates, partner characteristics, and individual sexual activities, blacks individuals remained 4 times more likely than whites to have a STD Table 4. Partner characteristics did not explain the racial disparity in STD diagnosis.
Even when controlling for individual sexual activities, including condom use, partner characteristics identified adolescents and young adults at high risk of STDs.
Incorporation of a composite measure of partner characteristics into routine assessment of STD risk would be beneficial because partner characteristics identified different individuals than individual sexual activities and partner characteristics may Sex partners in Pittsburgh mo more predictive of STD risk than individual sexual activities.
Despite the importance of partner characteristics in STD risk assessment, partner characteristics did not explain the racial disparity in STD diagnosis. The stronger association we found between partner characteristics and STD diagnosis than between individual sexual activities and STD diagnosis supports and expands findings from black 14 to year-old girls to both black and white men and women ages 15 to 24 years.
One reason partner selection may be more important for STD acquisition than individual sexual activities is that sexual activities with an uninfected partner present no risk of STD acquisition.
Individuals may have come to the STD clinic because their partner was diagnosed with a STD; therefore, the adolescents and young adults in our study may be more likely than the general population to have a partner who had a STD in the past year. This potential selection bias may have resulted in a stronger association between partner characteristics and STDs in our study than would be found in the general population.
The persistence of an association between composite partner characteristics and STD diagnosis when disregarding whether the partner had a STD suggests that even if selection bias was present it would not for the association between partner characteristics and STD prevalence.
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The 4-fold racial difference in STD diagnosis was not explained when controlling for partner characteristics. It is possible that some of the racial disparity in STDs is explained by partner characteristics other than those measured in our study e. This study had limitations. This study had several strengths. First, STDs among adolescents were diagnosed clinically as opposed to relying on self-report that may underestimate STDs because of social desirability bias in reporting and undiagnosed infections. Third, our measure of age discordance included both older and younger partners for both men and women, incorporating the multidimensions of age discordance that are rarely considered.
Incorporating an assessment of the composite partner characteristic measure described in Sex partners in Pittsburgh mo study may aid clinicians in identifying individuals at increased risk of STDs.
Materials and methods
First, over half of individuals with high-risk partners had a STD. Second, among the measures assessed, STDs were most strongly associated with composite partner characteristics. Third, the strong association between STDs and the partner characteristic composite persisted when considering individual sexual activities, including condom use. We thank Diane M. Comer for data management and technical assistance. National Center for Biotechnology InformationU. Sex Transm Dis. Author manuscript; available in PMC Jan 7. Stephanie A.
Robert L. Duncan B. Author information Copyright and information Disclaimer. Correspondence: Stephanie A. Copyright notice.
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The publisher's final edited version of this article is available at Sex Transm Dis. See other articles in PMC that cite the published article. Abstract Background Among adolescents and young adults, the extent that partner characteristics for sexually transmitted diseases STDs in context of individual sexual activities and demographic characteristics is unclear.
Individual Sexual Activities Based on the literature of individual sexual risk factors, 91215 — 19 we selected 9 measures of individual sexual activities: 1 age at first intercourse, 2 of lifetime sexual partners, 3 of past year sexual partners, 4 concurrent sex partners, 5 new sexual partner in the past month, 6 casual sex in the past 12 months, 7 sex under the influence of Sex partners in Pittsburgh mo, 8 condom use during last sex, and 9 frequency of condom use in past 12 months.
Demographic Covariates Based on the STD literature, we selected 5 covariates: race, sex, age, marital status, and type of medical insurance. Open in a separate window.
Individual Sexual Activities Adolescents reporting condom use during their last sexual encounter were half as likely to have a STD compared with adolescents reporting no condom use Table 2.