Abstract
Objective. To identify correlates of incident bacterial vaginosis (BV) diagnosed with Nugent scoring among high-risk women. Study Design. We conducted both cohort and case-crossover analyses, stratified by HIV infection status, based on 871 HIV-infected and 439 HIV-uninfected participants in the HIV Epidemiology Research Study, conducted in 4 US sites in 1993–2000. Results. BV incidence was 21% and 19% among HIV-infected and -uninfected women, respectively. Fewer correlates of BV were found with case-crossover than with cohort design. Reporting frequent coitus (regardless of consistency of condom use) was correlated with BV in cohort analyses but not in case-crossover analyses. The sole correlate of BV in both types of analyses was the detection of spermatozoa on Gram stain, which is a marker of semen exposure. Conclusion. The inconsistent association between condom use and BV in prior studies could be from reporting bias. We found evidence of a relationship between semen exposure and incident BV.
1. Introduction
Bacterial vaginosis (BV) is a common vaginal condition with an estimated prevalence of 29% among U.S. women during 2001–2004 [1]. BV has been linked to a range of adverse reproductive outcomes, including infertility, spontaneous abortion, preterm premature rupture of the membranes, amniotic fluid infection, low birth weight, and preterm delivery [2–8]. BV also might increase women's risk for pelvic inflammatory disease although evidence on this possible association is inconsistent [9–11]. In addition, evidence suggests that BV increases women's risk for sexually transmitted infections (STIs), including gonorrhea, chlamydial infection, trichomoniasis, human papillomavirus, herpes simplex virus, and HIV [12–19].
Although the etiology of BV remains unknown, two competing hypotheses currently prevail [20–22]. In the first, BV is viewed as an imbalance of the vaginal microbiota caused by the colonization of endogenous organisms from the intestinal tract [23]. This imbalance could be precipitated by a variety of events, including coitus and vaginal cleansing or douching. The second hypothesis holds that BV is caused by the sexual transmission of a specific pathogen (e.g., Gardnerella vaginalis or unknown bacteria). The similarity between the epidemiology of BV and that of STIs supports the hypothesis that BV is sexually transmitted. For example, BV has been associated with risky sexual behaviors, including having new or a relatively high number of sexual partners, having sex frequently, not using condoms, using drugs during sex, and having sex with uncircumcised partners [1, 16, 22, 24, 25]. However, because these associations often have been found in observational studies, they could be the result of uncontrolled confounding. Use of a case-crossover analysis (in which each woman serves as her own control) would minimize the effects of time-independent confounders [25]. We conducted both cohort and case-crossover analyses to identify time-variant correlates of BV among a cohort of high-risk women in the U.S., who participated in a longitudinal study of the effects of HIV infection on women's health [26].
2. Materials and Methods
We analyzed data from the HIV Epidemiology Research Study (HERS), which was conducted at 4 U.S. sites (Bronx, NY; Detroit, MI; Baltimore, MD; and Providence, RI, USA) in 1993–2000 [26]. Participants consisted of 871 HIV-infected women and 439 uninfected women who, at the time they enrolled in the study, were 16–55 years of age, did not have an AIDS-defining clinical diagnosis, and either injected drugs or engaged in high-risk sexual behaviors (i.e., had >5 sexual partners in the previous 5 years, traded sex for money or drugs, or had sex with a male who injected drugs or who was suspected of being or known to be infected with HIV). After enrollment, participants completed follow-up visits scheduled at 6-month intervals. During these visits, HERS staff conducted interviews to collect demographic, health, and behavioral information, conducted physical examinations, and collected specimens to be tested for infections, including BV, HIV, human papillomavirus (HPV), and trichomoniasis. Study visits were not used to diagnose or treat symptoms, and less than 1% of participants reported using metronidazole or topical clindamycin [27]. Ethical review boards at the study sites and the Centers for Disease Control and Prevention approved the study, and only women who gave informed consent were enrolled.
Gram-stained slides prepared from swabs of posterior vaginal fornix specimens were air dried, fixed in methanol, and shipped to a central laboratory where a single technician used oil immersion with ×1000 magnification to quantify and score the specimens. Specimens with a Nugent score of 7–10 were considered positive for BV [28]. Gram stains also were evaluated for morphological identification of spermatozoa, which is specific for recent exposure to semen [29]. Spermatozoa usually clear from vaginal secretions by 12–36 hours after exposure to semen although they have been detected microscopically up to 10 days after exposure [30, 31]. Wet mount was used for diagnosing trichomoniasis, and vaginal specimens were cultured for Candida organisms. Aliquots of cervicovaginal lavage fluid were frozen for later testing for HPV by polymerase chain reaction.
We limited our analyses to data collected during participants' first 10 follow-up visits and excluded the 12 women who HIV seroconverted during the study. Participants' incident BV status was assessed at follow-up visits only if Nugent scores of samples collected at their preceding visit indicated that they were BV negative. If they tested positive for BV or their Nugent scores were missing, their incident BV status was coded as missing. We used unconditional (using generalized estimating equations to account for intrasubject correlation from multiple visits) and conditional logistic regression to analyze the data as if they were derived from a cohort and case-crossover study, respectively. For both analyses, we constructed individual models to evaluate the correlates of incident BV for HIV-infected and -uninfected women separately. While the analytic population for the cohort analysis included all follow-up visits with nonmissing data on incident BV, the case-crossover analysis was limited to follow-up visits from women who had ≥1 follow-up visit with and ≥1 follow-up visit without incident BV.
For both the cohort and case-crossover analyses, we fitted individual models to assess the bivariable relationship between each potential correlate and incident BV. For the multivariable analyses, we fitted full models with all potential correlates and used manual, backward elimination to exclude factors that were not significantly associated (based on an alpha of 0.05) with incident BV. Potential correlates were selected because of their prior identification in the literature. The cohort analyses included both time-independent and -dependent variables. However, because individual participants in the case-crossover analyses served both as case subjects and matching control subjects, the variables evaluated in these analyses were limited to time-dependent factors, which had the potential to vary between the participant's visits.
3. Results
Because of the differences in findings by HIV status in both the cohort and case-crossover analyses, we present results separately for HIV-infected and -uninfected participants. The cohort analyses were based on data collected during 3,050 visits by 799 HIV-infected women and 1,564 visits by 375 uninfected women. The case-crossover analyses were based on data collected during 1,543 visits by 332 HIV-infected women and 753 visits by 159 uninfected women. The incidence of BV during the study follow-up period was 21% among HIV-infected women and 19% among uninfected women.
3.1. HIV-Infected Participants
The four time-independent variables assessed (i.e., study site, age at baseline, race, and education at baseline) were significantly associated with incident BV in the bivariable, cohort analyses among HIV-infected women (Table 1). All variables except for study site were also significantly associated with incident BV in the multivariable analysis, the results of which showed risk for incident BV to be higher among women younger than 45 years of age than among those older, higher among black women than among white women, and higher among women with a high-school education or less than among those with post-high-school education. Seven time-dependent variables were correlated with incident BV in the bivariable, cohort analyses. Except for current injection drug use and cigarette use within six months, these also were associated with incident BV in the multivariable, cohort analysis. Visits with trichomoniasis at the preceding visit (adjusted odds ratio [aOR], 1.8; 95% confidence interval [CI], 1.4–2.4), HPV at the preceding visit (aOR, 1.3; 95% CI, 1.0–1.5), and spermatozoa detected (aOR, 1.5; 95% CI, 1.1–2.1) had more incident BV than visits without these diagnoses. Also, visits in which the woman reported inconsistent condom use and frequent coitus (aOR, 1.6; 95% CI, 1.2–2.2) or consistent condom use and frequent coitus (aOR, 1.6; 95% CI, 1.2–2.1) were associated with more incident BV than visits in which women reported no sexual activity. Finally, crack use within six months correlated with incident BV (aOR, 1.9; 95% CI, 1.4–2.6).
Table 1.
Control visits | Case visits | Bivariable model | Multivariable model† | |||
---|---|---|---|---|---|---|
No. | No. | OR | (95% CI) | aOR | (95% CI) | |
Time-independent factors | ||||||
Study site | ||||||
Site 1 | 749 | 138 | Referent | Referent | ||
Site 2 | 502 | 170 | 1.8 | (1.3, 2.4) | 1.3 | (0.9, 1.8) |
Site 3 | 410 | 173 | 2.4 | (1.7, 3.2) | 1.4 | (1.0, 2.0) |
Site 4 | 761 | 147 | 1.1 | (0.8, 1.5) | 1.1 | (0.8, 1.6) |
Age at baseline (in years) | ||||||
16–24 | 43 | 16 | 2.2 | (1.1, 4.3) | 1.4 | (0.7, 3.0) |
25–34 | 664 | 217 | 2.2 | (1.6, 3.0) | 2.0 | (1.4, 2.8) |
35–44 | 1235 | 324 | 1.7 | (1.3, 2.3) | 1.6 | (1.2, 2.1) |
45+ | 480 | 71 | Referent | Referent | ||
Race | ||||||
Black | 1239 | 430 | 2.1 | (1.6, 2.6) | 1.7 | (1.3, 2.3) |
Other | 1183 | 198 | Referent | Referent | ||
Education at baseline | ||||||
<High school | 906 | 289 | 1.8 | (1.4, 2.4) | 1.6 | (1.2, 2.1) |
High school | 763 | 209 | 1.5 | (1.2, 2.0) | 1.5 | (1.1, 1.9) |
>High school | 750 | 129 | Referent | Referent | ||
| ||||||
Time-dependent factors | ||||||
Visit (0–10) | 0.9 | (0.9, 1.0) | 1.0 | (0.9, 1.0) | ||
CD4+ group (cells/μL) | ||||||
0–199 | 567 | 147 | 1.0 | (0.8, 1.3) | ||
200–499 | 1213 | 308 | 1.1 | (0.9, 1.5) | ||
≥500 | 598 | 166 | Referent | |||
Trichomoniasis at preceding visit | ||||||
Yes | 180 | 117 | 2.2 | (1.7, 2.8) | 1.8 | (1.4, 2.4) |
No | 2240 | 510 | Referent | Referent | ||
Vaginal Candidal culture at preceding visit | ||||||
Yes | 804 | 247 | 1.2 | (1.0, 1.4) | ||
No | 1612 | 377 | Referent | |||
Human papillomavirus at preceding visit | ||||||
Yes | 1468 | 432 | 1.3 | (1.0, 1.5) | 1.3 | (1.0, 1.5) |
No | 934 | 188 | Referent | Referent | ||
Spermatozoa detected on Gram stain | ||||||
Yes | 139 | 70 | 1.7 | (1.3, 2.4) | 1.5 | (1.1, 2.1) |
No | 2283 | 558 | Referent | Referent | ||
Sexual behavior during previous 6 months‡ | ||||||
Frequent coitus, inconsistent condom use | 331 | 127 | 2.0 | (1.6, 2.7) | 1.6 | (1.2, 2.2) |
Frequent coitus, consistent condom use | 431 | 146 | 1.8 | (1.4, 2.4) | 1.6 | (1.2, 2.1) |
Infrequent coitus, inconsistent condom use | 240 | 65 | 1.4 | (1.0, 1.9) | 1.2 | (0.9, 1.7) |
Infrequent coitus, consistent condom use | 488 | 127 | 1.4 | (1.1, 1.8) | 1.3 | (1.0, 1.7) |
Not sexually active | 920 | 162 | Referent | Referent | ||
Female sex partner during previous 6 months | ||||||
Yes | 86 | 25 | 1.1 | (0.8, 1.7) | ||
No | 2320 | 601 | Referent | |||
Douching within previous 48 hours | ||||||
Yes | 72 | 24 | 1.0 | (0.6, 1.6) | ||
No | 2340 | 602 | Referent | |||
Current hormonal contraception use | ||||||
Yes | 101 | 29 | 1.2 | (0.8, 1.8) | ||
No | 2319 | 599 | Referent | |||
Current injection drug use | ||||||
Yes | 304 | 131 | 1.7 | (1.4, 2.2) | ||
No | 2114 | 497 | Referent | |||
Crack use during previous 6 months | ||||||
Yes | 199 | 117 | 2.2 | (1.6, 2.9) | 1.9 | (1.4, 2.6) |
No | 2219 | 511 | Referent | Referent | ||
Cigarette use during previous 6 months | ||||||
Yes | 1639 | 484 | 1.5 | (1.2, 1.9) | ||
No | 779 | 144 | Referent |
HERS = HIV Epidemiology Research Study; OR: odds ratio; aOR: adjusted odds ratio; CI: confidence interval.
*Findings from unconditional logistic regression model, using generalized estimating equations, based on 628 case visits (i.e., visits with incident bacterial vaginosis) and 2422 control visits (i.e., visits without incident bacterial vaginosis) completed by 799 participants.
†Adjusted for all variables in column.
‡Frequent coitus defined as ≥4 times per month and infrequent coitus defined as <4 times per month.
The bivariable, case-crossover analyses yielded four correlates of incident BV among HIV-infected women: spermatozoa detection, sexual behaviors, current injection drug use, and crack use within six months (Table 2). Except for sexual behaviors, these variables remained significantly associated in the multivariable, case-crossover analysis. Visits with spermatozoa detection (aOR, 1.6; 95% CI, 1.1–2.5), reports of current injection drug use (aOR, 1.9; 95% CI, 1.1–3.3) and reports of crack use within six months (aOR, 1.6; 95% CI, 1.0–2.7) were more likely to have incident BV than visits without these factors.
Table 2.
Control visits | Case visits | Bivariable model | Multivariable model† | |||
---|---|---|---|---|---|---|
No. | No. | OR | (95% CI) | aOR | (95% CI) | |
Time-dependent factors | ||||||
CD4+ group (cells/μL) | ||||||
0–199 | 257 | 112 | 0.8 | (0.4, 1.3) | ||
200–499 | 544 | 228 | 0.8 | (0.5, 1.2) | ||
≥500 | 249 | 128 | Referent | |||
Trichomoniasis at preceding visit | ||||||
Positive | 100 | 74 | 1.2 | (0.8, 1.9) | ||
Negative | 967 | 400 | Referent | |||
Vaginal Candidal culture at preceding visit | ||||||
Positive | 371 | 181 | 1.1 | (0.9, 1.5) | ||
Negative | 695 | 290 | Referent | |||
Human papillomavirus at preceding visit | ||||||
Positive | 668 | 326 | 0.8 | (0.6, 1.2) | ||
Negative | 392 | 143 | Referent | |||
Spermatozoa detected on Gram stain | ||||||
Yes | 70 | 48 | 1.5 | (1.0, 2.3) | 1.6 | (1.1, 2.5) |
No | 998 | 427 | Referent | Referent | ||
Sexual behavior during previous 6 months‡ | ||||||
Frequent coitus, inconsistent condom use | 151 | 92 | 1.9 | (1.2, 3.1) | ||
Frequent coitus, consistent condom use | 177 | 113 | 1.7 | (1.1, 2.8) | ||
Infrequent coitus, inconsistent condom use | 118 | 46 | 1.2 | (0.7, 2.0) | ||
Infrequent coitus, consistent condom use | 225 | 96 | 1.2 | (0.8, 1.8) | ||
Not sexually active | 388 | 127 | Referent | |||
Female sex partner during previous 6 months | ||||||
Yes | 51 | 20 | 1.5 | (0.6, 3.9) | ||
No | 1010 | 453 | Referent | |||
Douching within 48 hours | ||||||
Yes | 38 | 19 | 0.7 | (0.4, 1.3) | ||
No | 1025 | 454 | Referent | |||
Current hormonal contraception use | ||||||
Yes | 30 | 23 | 2.4 | (0.9, 6.7) | ||
No | 1037 | 452 | Referent | |||
Current injection drug use | ||||||
Yes | 159 | 97 | 2.1 | (1.2, 3.5) | 1.9 | (1.1, 3.3) |
No | 907 | 378 | Referent | Referent | ||
Crack use during previous 6 months | ||||||
Yes | 107 | 81 | 1.8 | (1.1, 2.9) | 1.6 | (1.0, 2.7) |
No | 959 | 394 | Referent | Referent | ||
Cigarette use during previous 6 months | ||||||
Yes | 758 | 364 | 1.4 | (0.7, 2.7) | ||
No | 308 | 111 | Referent |
*Findings from conditional logistic regression model based on 475 case visits (i.e., visits with incident bacterial vaginosis) and 1068 control visits (i.e., visits without incident bacterial vaginosis) completed by 332 women with at least one case and one control visit.
†Adjusted for all variables in column.
‡Frequent coitus defined as ≥4 times per month and infrequent coitus defined as <4 times per month.
3.2. HIV-Uninfected Participants
Among HIV-uninfected participants, study site and race were the only time-independent variables significantly associated with BV risk in the bivariable, cohort analyses, and both remained significantly associated with BV risk in the multivariable, cohort analysis (Table 3). Black women had a higher risk than women of other races (aOR, 1.9; 95% CI, 1.3–2.7). Results of the bivariable, cohort analyses results showed six time-dependent variables to be significantly associated with incident BV risk. All except one (crack use within the previous 6 months) also were associated with BV risk in the multivariable analyses. Factors significantly associated with incident BV risk in the multivariable analyses were trichomoniasis at the preceding visit (aOR, 1.7; 95% CI, 1.1–2.6), spermatozoa detection (aOR, 1.9; 95% CI, 1.3–2.9), coitus ≥4 times per month during the previous 6 months and either inconsistent condom use (aOR, 1.9; 95% CI, 1.3–2.8) or consistent condom use (aOR, 1.9; 95% CI, 1.2–3.1) cigarette use during previous 6 months (aOR, 1.5; 95% CI, 1.0–2.1), and current use of hormonal contraception (aOR, 0.4; 95% CI, 0.2–0.8).
Table 3.
Control visits | Case visits | Bivariable model | Multivariable model† | |||
---|---|---|---|---|---|---|
No. | No. | OR | (95% CI) | aOR | (95% CI) | |
Time-independent factors | ||||||
Study site | ||||||
Site 1 | 437 | 65 | Referent | Referent | ||
Site 2 | 185 | 77 | 2.7 | (1.7, 4.2) | 1.9 | (1.2, 3.1) |
Site 3 | 271 | 94 | 2.4 | (1.5, 3.7) | 1.7 | (1.0, 2.7) |
Site 4 | 372 | 63 | 1.1 | (0.7, 1.7) | 1.5 | (1.0, 2.3) |
Age at baseline (in years) | ||||||
16–24 | 51 | 7 | 0.9 | (0.3, 2.1) | ||
25–34 | 386 | 106 | 1.4 | (0.9, 2.2) | ||
35–44 | 597 | 139 | 1.1 | (0.7, 1.6) | ||
45+ | 231 | 47 | Referent | |||
Race | ||||||
Black | 568 | 201 | 2.5 | (1.8, 3.5) | 1.9 | (1.3, 2.7) |
Other | 697 | 98 | Referent | Referent | ||
Education at baseline | ||||||
<High school | 367 | 99 | 1.4 | (1.0, 2.1) | ||
High school | 436 | 101 | 1.1 | (0.8, 1.6) | ||
>High school | 457 | 99 | Referent | |||
| ||||||
Time-dependent factors | ||||||
Visit (0–15) | 0.9 | (0.9, 1.0) | 0.94 | (0.9, 1.0) | ||
Trichomoniasis at preceding visit | ||||||
Yes | 100 | 60 | 2.1 | (1.4, 3.2) | 1.7 | (1.1, 2.6) |
No | 1163 | 239 | Referent | Referent | ||
Vaginal Candidal culture at preceding visit | ||||||
Yes | 393 | 91 | 1.0 | (0.8, 1.3) | ||
No | 864 | 208 | Referent | |||
Human papillomavirus at preceding visit | ||||||
Yes | 278 | 84 | 1.3 | (0.9, 1.7) | ||
No | 975 | 210 | Referent | |||
Spermatozoa detected on Gram stain | ||||||
Yes | 76 | 43 | 2.3 | (1.6, 3.3) | 1.9 | (1.3, 2.9) |
No | 1189 | 256 | Referent | Referent | ||
Sexual behavior during previous 6 months‡ | ||||||
Frequent coitus, inconsistent condom use | 411 | 139 | 2.3 | (1.6, 3.3) | 1.9 | (1.3, 2.8) |
Frequent coitus, consistent condom use | 129 | 35 | 1.8 | (1.1, 2.9) | 1.9 | (1.2, 3.1) |
Infrequent coitus, inconsistent condom use | 244 | 49 | 1.4 | (0.9, 2.0) | 1.2 | (0.8, 1.8) |
Infrequent coitus, consistent condom use | 138 | 23 | 1.1 | (0.6, 1.9) | 1.1 | (0.6, 2.0) |
Not sexually active | 341 | 52 | Referent | Referent | ||
Female sex partner during previous 6 months | ||||||
Yes | 92 | 25 | 1.2 | (0.7, 1.8) | ||
No | 1169 | 272 | Referent | |||
Douching within 48 hours | ||||||
Yes | 44 | 13 | 1.1 | (0.6, 2.0) | ||
No | 1215 | 285 | Referent | |||
Current hormonal contraception use | ||||||
Yes | 92 | 9 | 0.4 | (0.2, 0.9) | 0.4 | (0.2, 0.8) |
No | 1171 | 289 | Referent | Referent | ||
Current injection drug use | ||||||
Yes | 160 | 58 | 1.5 | (1.0, 2.2) | ||
No | 1104 | 241 | Referent | |||
Crack use during previous 6 months | ||||||
Yes | 139 | 66 | 2.0 | (1.3, 2.9) | ||
No | 1125 | 233 | Referent | |||
Cigarette use during previous 6 months | ||||||
Yes | 837 | 230 | 1.7 | (1.2, 2.4) | 1.5 | (1.0, 2.1) |
No | 427 | 69 | Referent | Referent |
*Findings from unconditional logistic regression model, using generalized estimating equations, based on 299 case visits (i.e., visits with incident bacterial vaginosis) and 1265 control visits (i.e., visits without incident bacterial vaginosis) completed by 375 participants.
†Adjusted for all variables in column.
‡Frequent coitus defined as ≥4 times per month and infrequent coitus defined as <4 times per month.
Two factors were associated with incident BV in the bivariable, case-crossover analyses among HIV-uninfected participants, and both remained associated in the multivariable analysis (Table 4). Visits with spermatozoa detected were more likely to have incident BV (aOR, 2.1; 95% CI, 1.1–4.0) than visits without its detection. Visits with self-reported frequent coitus and either inconsistent condom use (aOR, 3.0; 95% CI, 1.5–5.9) or consistent condom use (aOR, 3.1; 95% CI, 1.3–7.4) had more incident BV than visits with self-reported lack of sexual activity.
Table 4.
Control visits | Case visits | Bivariable model | Multivariable model† | |||
---|---|---|---|---|---|---|
No. | No. | OR | (95% CI) | aOR | (95% CI) | |
Time-dependent factors | ||||||
Trichomoniasis at preceding visit | ||||||
Yes | 76 | 41 | 1.2 | (0.7, 2.1) | ||
No | 446 | 189 | Referent | |||
Vaginal Candidal culture at preceding visit | ||||||
Yes | 143 | 70 | 1.1 | (0.7, 1.6) | ||
No | 377 | 160 | Referent | |||
Human papillomavirus at preceding visit | ||||||
Yes | 126 | 55 | 1.0 | (0.6, 1.5) | ||
No | 393 | 171 | Referent | |||
Spermatozoa detected on Gram stain | ||||||
Yes | 36 | 29 | 2.4 | (1.3, 4.5) | 2.1 | (1.1, 4.0) |
No | 487 | 201 | Referent | Referent | ||
Sexual behavior during previous 6 months‡ | ||||||
Frequent coitus, inconsistent condom use | 159 | 100 | 3.3 | (1.7, 6.6) | 3.0 | (1.5, 5.9) |
Frequent coitus, consistent condom use | 46 | 29 | 3.1 | (1.3, 7.3) | 3.1 | (1.3, 7.4) |
Infrequent coitus, inconsistent condom use | 114 | 36 | 1.7 | (0.8, 3.4) | 1.6 | (0.8, 3.2) |
Infrequent coitus, consistent condom use | 58 | 19 | 1.1 | (0.5, 2.4) | 1.1 | (0.5, 2.5) |
Not sexually active | 145 | 45 | Referent | Referent | ||
Female sex partner during previous 6 months | ||||||
Yes | 48 | 25 | 1.7 | (0.6, 4.6) | ||
No | 472 | 204 | Referent | |||
Douching within 48 hours | ||||||
Yes | 23 | 10 | 0.8 | (0.3, 2.2) | ||
No | 497 | 220 | Referent | |||
Current hormonal contraception use | ||||||
Yes | 22 | 8 | 0.4 | (0.1, 1.3) | ||
No | 500 | 221 | Referent | |||
Current injection drug use | ||||||
Yes | 93 | 42 | 1.5 | (0.7, 3.2) | ||
No | 429 | 188 | Referent | |||
Crack use during previous 6 months | ||||||
Yes | 93 | 45 | 1.4 | (0.8, 2.5) | ||
No | 429 | 185 | Referent | |||
Cigarette use during previous 6 months | ||||||
Yes | 373 | 173 | 1.4 | (0.6, 3.5) | ||
No | 149 | 57 | Referent |
*Findings from conditional logistic regression model based on 230 case visits (i.e., visits with incident bacterial vaginosis) and 523 control visits (i.e., visits without incident bacterial vaginosis) completed by 159 women with at least one case and one control visit.
†Adjusted for all variables in column.
‡Frequent coitus defined as ≥4 times per month and infrequent coitus defined as <4 times per month.
4. Discussion
The sole correlate of incident BV that emerged in both the cohort and case-crossover analyses among HIV-infected and -uninfected women was the detection of spermatozoa on Gram stain, which is a biological marker of recent exposure to semen. The cohort analyses among HIV-infected and -uninfected women also found that incident BV was more common among those reporting frequent coitus (regardless of the consistency of condom use); however, this association was not found in the case-crossover analyses. A protective effect of condoms against BV has been demonstrated in some prior studies (including a case-crossover analysis), but not in all studies [22, 32–34]. The failure to find a relationship between condom use and decreased BV risk in earlier studies could have been the result of misclassification in participant reporting of coitus and condom use. This misclassification could have occurred if studies collected inaccurate reports of condom use, as a result of social desirability or recall bias, or did not collect comprehensive data on condom use, including possible malfunctions or misuse. A protective effect of condoms against BV also could have been obscured in previous studies because of the role of recurring cases of BV. That is, if unprotected coitus can cause incident BV but is not a necessary component for its recurrence, establishing the link between unprotected coitus, and incident BV could be difficult.
We found fewer correlates of incident BV in our case-crossover analyses than in our cohort analyses. Results of the adjusted case-crossover analyses of incident BV among HIV-infected women showed only spermatozoa detection, current injection drug use, and crack use within the previous 6 months to be associated with incident BV, whereas results of the cohort analyses among HIV-infected women also showed trichomoniasis at the previous visit, HPV at the previous visit and coitus ≥4 times per month during the previous 6 months to be associated with incident BV. Similarly, results of the case-crossover analyses of risk among HIV-uninfected women only found spermatozoa detection and coitus ≥4 times per month during the previous 6 months to be associated with incident BV, whereas results of the cohort analyses among HIV-uninfected women also showed trichomoniasis at the previous visit, current hormonal contraception use, and cigarette use within the previous 6 months to be associated with incident BV. The case-crossover analyses might have identified fewer correlates of incident BV as a result of reduced confounding from each woman serving as both a case subject (visits with incident BV) and a matching control subject (visits without incident BV) [25]. Alternatively, reduced power in the case-crossover analyses might have prevented the detection of correlates of BV.
A major study limitation was that BV was only assessed at six-month intervals. Studies with frequent sampling have suggested that women may have rapid fluctuations in vaginal microbiota, including short episodes of BV that resolve spontaneously [35, 36]. Thus, our study might have missed cases of BV. We were also unable to determine the temporal relationship between exposure to semen and the development of BV; as a result, we cannot rule out the possibility that the association between the two factors is the result of BV causing longer persistence of spermatozoa in vaginal fluid rather than semen exposure actually causing BV. Previous case-crossover analyses also suggest that recent menses, use of vaginal lubricants, rectal sex, douching for cleansing after menstruation, and psychosocial stress could be risk factors for incident BV [36–38]. None of these factors, though, were evaluated in the present analysis. Finally, although the detection of spermatozoa is specific for recent exposure to semen, it is not a sensitive marker and cases of exposure might have been missed [29, 39]. Strengths of our study included our use of data from a large, prospective study in which semen exposure was assessed by an objective measure and our use of case-crossover analyses, which allowed us to reduce possible effects of unmeasured time-independent confounding by comparing women to their own control visits.
The detection of BV among women who have reported being sexually abstinent has been an argument against the role of sexual activity as a necessary component in causing BV [40, 41]. However, results of a recent study among young adults with a laboratory-diagnosed case of chlamydial infection, gonorrhea, or trichomoniasis showed that 10% reported having abstained from penile-vaginal intercourse in the previous year and that 6% reported never having had intercourse [42]. Thus, imperfect validity of self reports could explain the occurrence of BV among women reporting abstinence in prior studies. While study findings implicate the role of sexual exposure in the development of incident BV, this does not necessarily mean that BV is caused by the transmission of specific organism(s) during intercourse. Semen exposure could also increase women's risk for incident BV by increasing vaginal pH levels, changing the growth patterns in bacteria populations, or exposing women to an unidentified component of semen. The present study found biological evidence of an association between semen exposure and incident BV, which provides new support for the sexual transmission of BV; however, the mechanism remains unknown.
Acknowledgments
This study was supported by cooperative agreement Nos. U64/CCU106795, U64/CCU206798, U64/CCU306802, and U64/CCU506831 with the Centers for Disease Control and Prevention. The HIV Epidemiology Research Study Group consists of the following: Robert S. Klein, MD, Ellie Schoenbaum, MD, Julia Arnsten, MD, MPH, Robert D. Burk, MD, Chee Jen Chang, PhD, Penelope Demas, PhD, and Andrea Howard, MD, MSc, from Montefiore Medical Center and the Albert Einstein College of Medicine; Paula Schuman, MD, and Jack Sobel, MD, from the Wayne State University School of Medicine; Anne Rompalo, MD, David Vlahov, PhD, and David Celentano, PhD, from the Johns Hopkins University School of Medicine; Charles Carpenter, MD, and Kenneth Mayer, MD, from the Brown University School of Medicine; Ann Duerr, MD, Lytt I. Gardner, PhD, Scott Holmberg, MD, Denise Jamieson, MD, MPH, Jan Moore, PhD, Ruby Phelps, Dawn Smith, MD, and Dora Warren, PhD, from the Centers for Disease Control and Prevention; Katherine Davenny, PhD, from the National Institute of Drug Abuse. The findings and conclusions in this report are those of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention.
References
- 1.Koumans EH, Sternberg M, Bruce C, et al. The prevalence of bacterial vaginosis in the United States, 2001–2004; associations with symptoms, sexual behaviors, and reproductive health. Sexually Transmitted Diseases. 2007;34(11):864–869. doi: 10.1097/OLQ.0b013e318074e565. [DOI] [PubMed] [Google Scholar]
- 2.Mania-Pramanik J, Kerkar SC, Salvi VS. Bacterial vaginosis: a cause of infertility? International Journal of STD & AIDS. 2009;20(11):778–781. doi: 10.1258/ijsa.2009.009193. [DOI] [PubMed] [Google Scholar]
- 3.Schoeman J, Steyn PS, Odendaal HJ, Grové D. Bacterial vaginosis diagnosed at the first antenatal visit better predicts preterm labour than diagnosis later in pregnancy. Journal of Obstetrics & Gynaecology. 2005;25(8):751–753. doi: 10.1080/01443610500314660. [DOI] [PubMed] [Google Scholar]
- 4.Leitich H, Bodner-Adler B, Brunbauer M, Kaider A, Egarter C, Husslein P. Bacterial vaginosis as a risk factor for preterm delivery: a meta-analysis. American Journal of Obstetrics & Gynecology. 2003;189(1):139–147. doi: 10.1067/mob.2003.339. [DOI] [PubMed] [Google Scholar]
- 5.Ralph SG, Rutherford AJ, Wilson JD. Influence of bacterial vaginosis on conception and miscarriage in the first trimester: cohort study. British Medical Journal. 1999;319(7204):220–223. doi: 10.1136/bmj.319.7204.220. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Hillier SL, Nugent RP, Eschenbach DA, et al. Association between bacterial vaginosis and preterm delivery of a low-birth-weight infant. The New England Journal of Medicine. 1995;333(26):1737–1742. doi: 10.1056/NEJM199512283332604. [DOI] [PubMed] [Google Scholar]
- 7.Hay PE, Lamont RF, Taylor-Robinson D, Morgan DJ, Ison C, Pearson J. Abnormal bacterial colonisation of the genital tract and subsequent preterm delivery and late miscarriage. British Medical Journal. 1994;308(6924):295–298. doi: 10.1136/bmj.308.6924.295. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Gravett MG, Nelson HP, DeRouen T, Critchlow C, Eschenbach DA, Holmes KK. Independent associations of bacterial vaginosis and Chlamydia trachomatis infection with adverse pregnancy outcome. Journal of the American Medical Association. 1986;256(14):1899–1903. [PubMed] [Google Scholar]
- 9.Ness RB, Kip KE, Hillier SL, et al. A cluster analysis of bacterial vaginosis-associated microflora and pelvic inflammatory disease. American Journal of Epidemiology. 2005;162(6):585–590. doi: 10.1093/aje/kwi243. [DOI] [PubMed] [Google Scholar]
- 10.Ness RB, Hillier SL, Kip KE, et al. Bacterial vaginosis and risk of pelvic inflammatory disease. Obstetrics & Gynecology. 2004;104(4):761–769. doi: 10.1097/01.AOG.0000139512.37582.17. [DOI] [PubMed] [Google Scholar]
- 11.Peipert JF, Montagno AB, Cooper AS, Sung CJ. Bacterial vaginosis as a risk factor for upper genital tract infection. American Journal of Obstetrics & Gynecology. 1997;177(5):1184–1187. doi: 10.1016/s0002-9378(97)70038-3. [DOI] [PubMed] [Google Scholar]
- 12.Brotman RM, Klebanoff MA, Nansel TR, et al. Bacterial vaginosis assessed by gram stain and diminished colonization resistance to incident gonococcal, chlamydial, and trichomonal genital infection. Journal of Infectious Diseases. 2010;202(12):1907–1915. doi: 10.1086/657320. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Atashili J, Poole C, Ndumbe PM, Adimora AA, Smith JS. Bacterial vaginosis and HIV acquisition: a meta-analysis of published studies. AIDS. 2008;22(12):1493–1501. doi: 10.1097/QAD.0b013e3283021a37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Rugpao S, Sriplienchan S, Rungruengthanakit K, et al. Risk factors for bacterial vaginosis incidence in young adult thai women. Sexually Transmitted Diseases. 2008;35(7):643–648. doi: 10.1097/OLQ.0b013e31816f70f2. [DOI] [PubMed] [Google Scholar]
- 15.Kaul R, Nagelkerke NJ, Kimani J, et al. Prevalent herpes simplex virus type 2 infection is associated with altered vaginal flora and an increased susceptibility to multiple sexually transmitted infections. Journal of Infectious Diseases. 2007;196(11):1692–1697. doi: 10.1086/522006. [DOI] [PubMed] [Google Scholar]
- 16.Thorsen P, Vogel I, Molsted K, et al. Risk factors for bacterial vaginosis in pregnancy: a population-based study on Danish women. Acta Obstetricia et Gynecologica Scandinavica. 2006;85(8):906–911. doi: 10.1080/00016340500432655. [DOI] [PubMed] [Google Scholar]
- 17.Watts DH, Fazzari M, Minkoff H, et al. Effects of bacterial vaginosis and other genital infections on the natural history of human papillomavirus infection among HIV-1-infected and high-risk HIV-1-uninfected women. Journal of Infectious Diseases. 2005;191(7):1129–1139. doi: 10.1086/427777. [DOI] [PubMed] [Google Scholar]
- 18.Cherpes TL, Meyn LA, Krohn MA, Lurie JG, Hillier SL. Association between acquisition of herpes simplex virus type 2 in women and bacterial vaginosis. Clinical Infectious Diseases. 2003;37(3):319–325. doi: 10.1086/375819. [DOI] [PubMed] [Google Scholar]
- 19.Wiesenfeld HC, Hillier SL, Krohn MA, Landers DV, Sweet RL. Bacterial vaginosis is a strong predictor of Neisseria gonorrhoeae and Chlamydia trachomatis infection. Clinical Infectious Diseases. 2003;36(5):663–668. doi: 10.1086/367658. [DOI] [PubMed] [Google Scholar]
- 20.Marrazzo JM, Martin DH, Watts DH, et al. Bacterial vaginosis: identifying research gaps proceedings of a workshop sponsored by DHHS/NIH/NIAID. Sexually Transmitted Diseases. 2010;37(12):732–744. doi: 10.1097/OLQ.0b013e3181fbbc95. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Josey WE, Schwebke JR. The polymicrobial hypothesis of bacterial vaginosis causation: a reassessment. International Journal of STD & AIDS. 2008;19(3):152–154. doi: 10.1258/ijsa.2007.007260. [DOI] [PubMed] [Google Scholar]
- 22.Fethers KA, Fairley CK, Hocking JS, Gurrin LC, Bradshaw CS. Sexual risk factors and bacterial vaginosis: a systematic review and meta-analysis. Clinical Infectious Diseases. 2008;47(11):1426–1435. doi: 10.1086/592974. [DOI] [PubMed] [Google Scholar]
- 23.Holst E. Reservoir of four organisms associated with bacterial vaginosis suggests lack of sexual transmission. Journal of Clinical Microbiology. 1990;28(9):2035–2039. doi: 10.1128/jcm.28.9.2035-2039.1990. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.McClelland RS, Richardson BA, Graham SM, et al. A prospective study of risk factors for bacterial vaginosis in HIV-1-seronegative African women. Sexually Transmitted Diseases. 2008;35(6):617–623. doi: 10.1097/OLQ.0b013e31816907fa. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Maclure M. The case-crossover design: a method for studying transient effects on the risk of acute events. American Journal of Epidemiology. 1991;133(2):144–153. doi: 10.1093/oxfordjournals.aje.a115853. [DOI] [PubMed] [Google Scholar]
- 26.Smith DK, Warren DL, Vlahov D, et al. Design and baseline participant characteristics of the human immunodeficiency virus epidemiology research (HER) study: a prospective cohort study of human immunodeficiency virus infection in US women. American Journal of Epidemiology. 1997;146(6):459–469. doi: 10.1093/oxfordjournals.aje.a009299. [DOI] [PubMed] [Google Scholar]
- 27.Jamieson DJ, Duerr A, Klein RS, et al. Longitudinal analysis of bacterial vaginosis: findings from the HIV epidemiology research study. Obstetrics & Gynecology. 2001;98(4):656–663. doi: 10.1016/s0029-7844(01)01525-3. [DOI] [PubMed] [Google Scholar]
- 28.Nugent RP, Krohn MA, Hillier SL. Reliability of diagnosing bacterial vaginosis is improved by a standardized method of gram stain interpretation. Journal of Clinical Microbiology. 1991;29(2):297–301. doi: 10.1128/jcm.29.2.297-301.1991. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Young WW, Bracken AC, Goddard MA, Matheson S. Sexual assault: review of a national model protocol for forensic and medical evaluation. Obstetrics & Gynecology. 1992;80(5):878–883. [PubMed] [Google Scholar]
- 30.Silverman EM, Silverman AG. Persistence of spermatozoa in the lower genital tracts of women. Journal of the American Medical Association. 1978;240(17):1875–1877. doi: 10.103/00006450-09000-00010. [DOI] [PubMed] [Google Scholar]
- 31.Davies A, Wilson E. The persistence of seminal constituents in the human vagina. Forensic Science. 1974;3(1):45–55. doi: 10.1016/0300-9432(74)90006-5. [DOI] [PubMed] [Google Scholar]
- 32.Hutchinson KB, Kip KE, Ness RB. Condom use and its association with bacterial vaginosis and bacterial vaginosis-associated vaginal microflora. Epidemiology. 2007;18(6):702–708. doi: 10.1097/EDE.0b013e3181567eaa. [DOI] [PubMed] [Google Scholar]
- 33.Yotebieng M, Turner AN, Hoke TH, Van Damme K, Rasolofomanana JR, Behets F. Effect of consistent condom use on 6-month prevalence of bacterial vaginosis varies by baseline BV status. Tropical Medicine & International Health. 2009;14(4):480–486. doi: 10.1111/j.1365-3156.2009.02235.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Riggs M, Klebanoff M, Nansel T, Zhang J, Schwebke J, Andrews W. Longitudinal association between hormonal contraceptives and bacterial vaginosis in women of reproductive age. Sexually Transmitted Diseases. 2007;34(12):954–959. [PubMed] [Google Scholar]
- 35.Priestley GJF, Jones BM, Dhar J, Goodwin L. What is normal vaginal flora? Genitourinary Medicine. 1997;73(1):23–28. doi: 10.1136/sti.73.1.23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Brotman RM, Ravel J, Cone RA, Zenilman JM. Rapid fluctuation of the vaginal microbiota measured by Gram stain analysis. Sexually Transmitted Infections. 2010;86(4):297–302. doi: 10.1136/sti.2009.040592. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Brotman RM, Ghanem KG, Klebanoff MA, Taha TE, Scharfstein DO, Zenilman JM. The effect of vaginal douching cessation on bacterial vaginosis: a pilot study. American Journal of Obstetrics & Gynecology. 2008;198(6):628.e1–628.e7. doi: 10.1016/j.ajog.2007.11.043. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Nansel TR, Riggs MA, Yu KF, Andrews WW, Schwebke JR, Klebanoff MA. The association of psychosocial stress and bacterial vaginosis in a longitudinal cohort. American Journal of Obstetrics & Gynecology. 2006;194(2):381–386. doi: 10.1016/j.ajog.2005.07.047. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Culhane JF, Nyirjesy P, McCollum K, Casabellata G, Di Santolo M, Cauci S. Evaluation of semen detection in vaginal secretions: comparison of four methods. American Journal of Reproductive Immunology. 2008;60(3):274–281. doi: 10.1111/j.1600-0897.2008.00632.x. [DOI] [PubMed] [Google Scholar]
- 40.Yen S, Shafer MA, Moncada J, Campbell CJ, Flinn SD, Boyer CB. Bacterial vaginosis in sexually experienced and non-sexually experienced young women entering the military. Obstetrics & Gynecology. 2003;102(5, part 1):927–933. doi: 10.1016/s0029-7844(03)00858-5. [DOI] [PubMed] [Google Scholar]
- 41.Bump RC, Buesching WJ. Bacterial vaginosis in virginal and sexually active adolescent females: evidence against exclusive sexual transmission. American Journal of Obstetrics & Gynecology. 1988;158(4):935–939. doi: 10.1016/0002-9378(88)90097-x. [DOI] [PubMed] [Google Scholar]
- 42.DiClemente RJ, Sales JM, Danner F, Crosby RA. Association between sexually transmitted diseases and young adults' self-reported abstinence. Pediatrics. 2011;127(2):208–213. doi: 10.1542/peds.2009-0892. [DOI] [PMC free article] [PubMed] [Google Scholar]