Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Apr 1.
Published in final edited form as: Am J Perinatol. 2020 Oct 8;38(5):407–413. doi: 10.1055/s-0040-1717098

Effect of a non-optimal cervicovaginal microbiota and psychosocial stress on recurrent spontaneous preterm birth

Kristin D GERSON 1, Clare MCCARTHY 1, Jacques RAVEL 2, Michal A ELOVITZ 3, Heather H BURRIS 4,5
PMCID: PMC8026761  NIHMSID: NIHMS1651826  PMID: 33032329

Abstract

OBJECTIVE:

While select cervicovaginal microbiota and psychosocial factors are associated with spontaneous preterm birth, their effect on recurrence remains unclear. It is also unknown whether psychosocial factors amplify underlying biologic risk.

STUDY DESIGN:

This was a secondary analysis of a prospective pregnancy cohort. The Cohen’s Perceived Stress Scale (PSS-14) was administered and cervical swabs were obtained between 16–20 weeks of gestation. PSS-14 scores ≥30 reflected high stress. Cervicovaginal microbiota were analyzed using 16S rRNA sequencing and classified microbial communities into community state types (CST). CST IV is a non-optimal cervicovaginal microbial community characterized by anaerobes and a lack of Lactobacillus. Multivariable logistic regression modeled adjusted associations between CST IV, high stress, and recurrent spontaneous preterm birth.

RESULTS:

Among the 181 women with prior preterm birth, 45 (24.9%) had high stress. We did not detect a significant association between high stress and recurrent spontaneous preterm birth (aOR 1.67, 95% CI: 0.73–3.85). Among the 74 women with prior preterm birth and cervicovaginal microbiota analyzed, 29 (39.2%) had CST IV; this proportion differed significantly among women with recurrent spontaneous preterm birth (51.4%) compared to women with term birth (28.2%) (p=0.04). In adjusted models, the association between CST IV and recurrent spontaneous preterm birth persisted (aOR 3.58, 95% CI: 1.25–10.24). When both stress and CST IV were introduced into the model, their associations with recurrent spontaneous preterm birth were slightly stronger. Compared to women with neither exposure, women with both high stress and CST IV had the highest odds of recurrent spontaneous preterm birth (aOR=6.01, 95% CI: 1.002–36.03).

CONCLUSION:

Among a predominantly non-Hispanic black cohort of women with prior preterm birth, a non-optimal cervicovaginal microbiota is associated with increased odds of recurrent spontaneous preterm birth. Identification of modifiable behavioral factors may unveil novel non-pharmacologic interventions to decrease recurrence among women with underlying biologic risk.

Keywords: cervicovaginal microbiota, microbiome, perceived maternal stress, spontaneous preterm birth, recurrent spontaneous preterm birth

INTRODUCTION

A non-optimal cervicovaginal microbiota has been linked to adverse reproductive outcomes, including increased risk of spontaneous preterm birth (sPTB).18 Ravel et al. first described a hierarchical clustering scheme to classify cervicovaginal microbiota into five community state types (CSTs),9 an approach that has been subsequently applied by numerous others worldwide to evaluate the role of cervicovaginal ecosystems in health and disease.1015 CST I, II, III, and V are dominated by one of four Lactobacillus species (L. crispatus, L. gasseri, L. iner and L. jensenii), while CST IV comprises of an array of strict and facultative anaerobes and a lower proportion of Lactobacillus.

Our group recently published results from a large prospective nested case-control study that identified specific microbial and immune factors, including CST IV, associated with sPTB in a predominantly non-Hispanic black population.1 Our findings corroborate other reports in the literature that have linked a non-optimal microbiota to unfavorable pregnancy outcomes, including advanced cervical dilation, premature preterm rupture of membranes, neonatal sepsis, rescue cerclage failure, and sPTB.28

In addition to these biologic associations, select social and behavioral factors, such as perceived maternal stress, have also been linked to adverse perinatal outcomes.16,17,26,1825 While precise mechanisms remain unknown, it has been postulated that stress influences hormonal pathways leading to changes in host immune response, thereby affecting the cervicovaginal ecosystem.2730 These findings raise questions as to whether stress may promote colonization of the cervicovaginal space with a non-optimal microbiota in pregnancy.

While a myriad of factors influence psychosocial stress throughout gestation, women with a history of prior pregnancy complications, including sPTB, experience higher levels of stress in subsequent pregnancies.31 A history of sPTB is the greatest identifiable risk factor for sPTB; women with a prior sPTB have an 18–54% risk of recurrence.32,33 Progesterone supplementation has been utilized as a therapeutic agent targeting sPTB prevention in women with a history or sPTB;33 however, a recent randomized controlled trial failed to demonstrate risk reduction with progesterone over placebo, calling into question the utility of this pharmacologic intervention.34 New therapies are needed for recurrent sPTB prevention, and as such, identification of biologic mechanisms and drivers of recurrent sPTB is critical.

Though select non-optimal cervicovaginal microbiota and psychosocial factors are known risk factors for sPTB, their effect on recurrent sPTB has not been studied. It is also unknown whether psychosocial factors magnify underlying biologic risk. This study sought to determine the effect of non-optimal cervicovaginal microbial communities and perceived psychosocial stress on the odds of recurrent sPTB.

MATERIALS AND METHODS

Study Setting

This was a secondary analysis of a prospective nested case-control study entitled Motherhood and Microbiome (M&M) in which 2,000 pregnant women enrolled from December 2013 through February 2017. The methods from this original study, including IRB approval from the University of Pennsylvania, have been previously published.1 In brief, women receiving prenatal care at the Hospital of the University of Pennsylvania enrolled after informed consent between 16 to 20 weeks of gestation. Exclusion criteria included a major fetal anomaly, HIV seropositive status, history of organ transplant, chronic steroid use, enrollment into the study during a previous pregnancy, or multiple gestations. This analysis includes cervical swabs that were collected at 16 to 20 weeks of gestation. This study was approved by the Institutional Review Board at the University of Pennsylvania (IRB #818914) on October 23, 2013.

Perceived stress was measured using Cohen’s Perceived Stress Scale (PSS-14), a validated stress assessment questionnaire and completed by women at their study visit, between 16 to 20 weeks of gestation. Scoring and interpretation of results were performed as previously reported.35 Based on published literature,36 a PSS-14 score of ≥30 was considered high perceived stress, and women with a PSS-14 score of <30 were used as the reference group in this analysis.

Cervicovaginal specimens were self-collected by the participant or collected by a research coordinator if a clinical exam was indicated. These included an ESwabs (COPAN) stored in 1 ml of Amies Transport Medium and a Dacron swab stored without buffer. All samples were immediately frozen at −80°C until processing. Samples were chosen for analysis if they were from women with sPTB and among frequency, race-matched term birth controls ≥38 weeks of gestation (1:4 case-control ratio). Cervicovaginal microbiota were analyzed by 16S rRNA gene sequencing via amplification of the V3-V4 regions of the 16S rRNA gene. Microbial communities were classified into CST as previously reported using hierarchical clustering with Jensen-Shannon divergence and Ward linkage.10,37 CST I is predominated with L. crispatus, CST II with L. gasseri, CST III with L. iners and CST V with L. jensenii. CST IV is defined by a paucity of Lactobacillus species and a diverse set of strict and facultative anaerobes. CST was dichotomized into CST IV and non-CST IV groups, and the latter was used as the reference group in this analysis.

History of PTB and cases of PTB were individually adjudicated by a maternal-fetal medicine physician (MAE) to determine whether cases were medically-indicated or spontaneous. PTB was considered spontaneous when a woman presented with either cervical dilation and/or premature rupture of membranes and delivered prior to 37 weeks of gestation. PTB was considered medically-indicated (mPTB) when a woman delivered for maternal indications (e.g. preeclampsia) or fetal indications (e.g. fetal growth restriction) prior to 37 weeks of gestation.1 Women with mPTB or with missing birth outcome data were excluded from the analytic dataset. The final cohort included 181 women with prior sPTB and stress data available. Analyses that included cervicovaginal microbiota data were limited to a subset of these women (n=74).

Data Analysis

First, we performed bivariate analyses of high stress and recurrent sPTB, CST IV and recurrent sPTB, as well as high stress and CST IV. Covariates were included in the final model if each variable remained statistically significant at p≤0.05 in bivariate models, or if its inclusion in the multivariable model modified other associations of interest by ≥10%. Multivariate logistic regression was used to model adjusted associations of stress with recurrent sPTB and CST IV with recurrent sPTB separately. Subsequently they were introduced into the same model. Given that race is highly correlated with cervicovaginal microbiota, we also performed analyses restricted to non-Hispanic black women who comprise the majority of the cohort. Additionally, we tested for an interaction between CST IV and high stress on the outcome of recurrent sPTB by adding a multiplicative interaction term to the multivariable model. Lastly, we created a 4-level variable of the four possible combinations of low and high stress with CST IV and non-CST IV to determine whether there was an additive effect of both high stress and CST IV on the odds of recurrent sPTB. Odds ratios (OR) were obtained from these models and p-values of ≤0.05 were considered statistically significant. Statistical analyses were conducted using SAS 9.4 (Carey, NC).

RESULTS

Demographic characteristics of participants

Demographic characteristics stratified by birth outcome are presented in Table 1. Women with recurrent sPTB versus term birth were similar in regards to age, body mass index (BMI), marital status, race, and PSS-14 score. Women with recurrent sPTB were more likely to have a short cervix compared to term birth (p=0.018).

Table 1.

Characteristics among the 181 participants of the Motherhood and Microbiome study with prior spontaneous preterm birth stratified by subsequent birth outcome.

Recurrent sPTB* (n=39) Term birth (n=142)
mean (SD) mean (SD) p-value
Maternal age in years, mean (SD) 30.1 (5.2) 30.0 (5.4) 0.941
BMI^ (kg/m2), mean (SD) 29.1 (8.3) 30.9 (8.2) 0.226
GA at delivery in weeks, mean (SD) 29.8 (6.4) 38.3 (1.07) <0.001
n (row %) n (row %) p-value
Race 0.393
 White 3 (12.0) 22 (88.0)
 Black 33 (22.6) 113 (77.4)
 Other 3 (30.0) 7 (70.0)
Marital status 0.236
 Single/separated/divorced 26 (19.4) 108 (80.6)
 Married 13 (27.7) 34 (72.3)
Cervical lengtha 0.010
 Short (<25 mm) 7 (38.9) 11 (61.1)
 Normal (≥25 mm) 13 (13.5 83 (86.5)

Continuous variables are compared using two-sided t-test; categorical variables are compared using chi-square.

a

n=67 missing cervical length measurements

*

Spontaneous preterm birth (sPTB)

^

Body mass index (BMI)

Gestational age (GA)

Stress analyses

Among the 181 women in the analytic dataset, 45 (24.9%) had high stress. In bivariate analyses, this proportion did not differ statistically between women who had recurrent sPTB (30.8%) versus term birth (23.2%) as presented in Table 2. Mean PSS-14 scores also did not differ between women with recurrent sPTB (mean 24.7, SD 7.2) and subsequent term birth (mean 23.3, SD 8.4) (p=0.35). In adjusted models, we did not detect a difference in the odds of recurrent sPTB among women with high versus low stress (aOR 1.67, 95% CI 0.73–3.85) as presented in Table 3, Model 1a. When we restricted to the 146 non-Hispanic black women, the odds ratio was similar (aOR 1.56, 95% CI 0.66–3.70).

Table 2.

Bivariate associations of perceived stress and cervicovaginal microbiota with recurrent spontaneous preterm birth among women with prior spontaneous preterm birth.

Exposures All births (n=181) Recurrent sPTB* (n=39) Term birth (n=142)
n col(%) n col(%) n col(%) p-value
Perceived stress^ 0.335
 High 45 (24.9) 12 (30.8) 33 (23.2)
 Low 136 (75.1) 27 (69.2) 109 (76.8)
All births (n=74) Recurrent sPTB (n=41) Term birth (n=43)
n (col %) n (col %) n (col %) p-value
Cervicovaginal microbiota 0.041
 CST IV 29 (39.2) 18 (51.4) 11 (28.2)
 Non-CST IV 45 (60.8) 17 (48.6) 28 (71.8)

Variables are compared using chi-square.

*

Spontaneous preterm birth (sPTB)

^

High stress defined as PSS-14 ≥30, low stress defined as PSS-14 <30

Community state type IV (CST IV) is a non-optimal cervicovaginal microbiota with a relative deficiency in Lactobacillus.

Table 3.

Associations of stress and cervicovaginal microbiota with adjusted odds of recurrent spontaneous preterm birth.

Model 1a Model 1b Model 2 Model 3
Exposure* aOR (95% CI) aOR (95% CI) aOR (95% CI) aOR (95% CI)
High stress 1.67 (0.73–3.85) 1.73 (0.57– 5.26) 2.02 (0.61–6.71)
Low stress ref ref ref
CST IV 3.58 (1.25–10.24) 3.83 (1.30–11.33)
Non-CST IV ref ref
*

High stress defined as PSS-14 ≥30, low stress defined as PSS-14 <30; community state type IV (CST IV) is a non-optimal cervicovaginal microbiota with a relative deficiency in Lactobacillus.

All models are adjusted for black race and marital status.

Model 1a includes stress but not CST (n=181), 1b is model 1a restricted to women with CST available (n=74).

Model 2 includes CST but not stress (n=74).

Model 3 includes both stress and CST (n=74).

Cervicovaginal microbiota analyses

There were 74 women in the analytic dataset with cervicovaginal microbiota data, of whom 29 (39.2%) had CST IV. A higher proportion of women with recurrent sPTB had CST IV compared to non-CST IV (51.4% versus 28.2%, respectively; p=0.041). In logistic models adjusted for black race and marital status, CST IV was associated with increased odds of recurrent sPTB (aOR 3.58, 95% CI 1.25–10.24) as presented in Table 3, Model 2. When we restricted to non-Hispanic black women (n=64), the adjusted odds of recurrent sPTB was 3.48 (95% CI 1.16–10.43) among those with CST IV.

Analyses including both stress and cervicovaginal microbiota

Within the subset of 74 participants for whom both stress and cervicovaginal microbiota data were available, we did not detect an association between high perceived stress and odds of recurrent sPTB (aOR 1.73; 95% CI 0.57–5.26) as presented in Table 3, Model 1b. With respect to the relationship between stress and cervicovaginal microbiota, we did not detect a difference in the proportion of women with CST IV among those with high compared to low stress (42.1% versus 38.2%, respectively; p=0.76). We also did not detect an interaction between high stress and CST IV on the outcome of recurrent sPTB (p=0.328). However, when both high stress and CST IV were included in the adjusted model, the effect estimates for both stress and CST IV increased, suggesting potential negative confounding (Table 3, Model 3). Results were similar when we restricted to non-Hispanic black women; the aOR for stress was 2.04 (95% CI 0.58–7.16) and the aOR for CST IV was 3.88 (95% CI 1.23–12.19). When we created a 4-level variable, women with recurrent sPTB were over-represented in the group of women with high stress and CST IV, but this difference was not statistically significant (Table 4). The odds of recurrent sPTB were greater among women with high stress and CST IV (aOR=6.01, 95% CI: 1.002–36.03) compared to women with neither factor, although with a wide confidence interval.

Table 4.

Combinations of stress and cervicovaginal microbiota states among 74 women with prior spontaneous preterm birth with recurrent spontaneous preterm birth versus subsequent term birth.

All births (n=74) Recurrent sPTB* (n=35) Term birth (n=39)
n col(%) n col(%) n col(%) p-value^
Exposure 0.214
Low stress, non-CST IV 34 (45.9) 12 (34.3) 22 (56.4)
Low stress, CST IV 21 (28.4) 13 (37.1) 8 (20.5)
High stress, non-CST IV 11 (14.9) 5 (14.3) 6 (15.4)
High stress, CST IV 8 (10.8) 5 (14.3) 3 (7.7)
*

Spontaneous preterm birth (sPTB)

^

Fisher’s exact.

High stress defined as PSS-14 ≥30, low stress defined as PSS-14 <30

Community state type IV (CST IV) is a non-optimal cervicovaginal microbiota with a relative deficiency in Lactobacillus.

DISCUSSION

Principal Findings

We demonstrate that CST IV, a cervicovaginal microbial community enriched in anaerobes and relatively devoid of Lactobacillus, is a risk factor for recurrent sPTB in a predominantly non-Hispanic black cohort of women. In the setting of this non-optimal microbiota, high levels of perceived maternal stress may magnify underlying biologic risk. However, as demonstrated by wide confidence intervals, we were likely underpowered to detect an association between psychosocial stress and sPTB.

Results in the context of what is known

Our study is the first to report increased odds of recurrent sPTB with a non-optimal cervicovaginal microbiota, findings that are consistent with prior literature linking CST IV to sPTB in general.18 These observations suggest that mechanisms driving antecedent and recurrent sPTB may be similar with regard to the role of the cervicovaginal ecosystem. However, we do not have data describing microbial community classification in the prior sPTB among women in this cohort. Future studies exploring the stability of the cervicovaginal microbiota across pregnancies, as well as pre-pregnancy, and their impact on birth outcomes are warranted.

Although likely underpowered, we did not observe an association between stress and recurrent sPTB, consistent with some of the existing literature.38,39 In a large (n=9,470) cohort of nulliparous women examining adverse pregnancy outcomes that focused largely on racial disparities, Grobman et al. demonstrated not only that racial disparities in sPTB were not explained by differences in psychosocial factors, but also that no psychosocial factors except social support were independently associated with pregnancy outcomes.38 While stress alone may not modify the risk of sPTB, there are some data to support the concept that psychosocial factors act in concert with other variables to influence birth outcome. Ferguson et al. recently reported an association between maternal urinary phthalate levels and PTB that was modified by exposure to stressors during pregnancy.40 Our findings substantiate this concept that psychosocial stress in combination with other factors may enhance risk.

While we did not detect an association between stress and CST IV in our sample, whether this psychosocial factor contributes to the composition or stability of the cervicovaginal microbiota remains unknown. Other published literature supports the notion that select psychosocial factors may lead to adverse pregnancy outcomes through various physiologic pathways, including neuroinflammatory, infectious, microbiome-mediated, and neuroendocrine mechanisms.17 Psychosocial stress, both during and outside of pregnancy, is associated with increased incidence of bacterial vaginosis.41,42 Notably, predominant microbial species in this vaginal infection, inducing Gardnerella vaginalis, are prevalent in cervicovaginal communities characterized as CST IV. Associations between psychosocial factors and composition of microbial communities have been reported in other biologic niches, including the gut.43

Strengths and limitations

Strengths of this study include its prospective enrollment with multiple covariates allowing for assessment of confounding. This study contains a large proportion of non-Hispanic black women, an ethnic minority with increased risk of sPTB. This cohort is well-phenotyped with respect to spontaneous versus iatrogenic PTB. As these two subsets of PTB may be driven by distinct biologic pathways, exclusion of women who delivered preterm for obstetrical or fetal indications elevates the rigor of modeled associations between clinical variables and birth outcomes.

With respect to limitations, assessments of perceived maternal stress and cervicovaginal microbiota were performed concurrently, thus, precluding investigation of temporality or causality. As this study focuses specifically on women with prior sPTB, these data may not be generalizable to nulliparas or multiparas without a history of sPTB. While social and behavioral determinants of adverse health outcomes are numerous, our study captured only a single psychosocial metric. Finally, the cervicovaginal microbiota was only analyzed in a subset of women selected on the basis of birth outcome.

Clinical implications

We report findings of key clinical interest in this study: (1) effect estimates between both high stress and CST IV with sPTB appeared larger when both exposures were included in the model together; and (2) a significant association was detected between the combination of high stress and CST IV on the outcome of recurrent sPTB compared to women with neither exposure. These findings suggest that consideration of biologic and psychosocial factors together may enhance risk prediction for recurrent sPTB. This potential is particularly compelling in light of recent data calling into question the clinical efficacy of existing pharmacologic interventions.34

Research implications

Our observations underscore the need for further investigation into mechanisms through which psychosocial stress may modify underlying biologic risk. Future studies exploring the role of protective psychosocial factors in possibly mediating tolerance of a non-optimal microbiota in pregnancy are also warranted. Given that stress and cervicovaginal microbiota were measured concurrently, we were unable to determine temporality or causality. However, the pregnancy study was prospective, and these exposures were collected prior to the outcome of recurrent sPTB, suggesting that they variables may play in birth outcome. Future research is needed to establish temporality and causality as related to stress and cervicovaginal microbiota, as well as to isolate specific aspects of perceived stress that may be modifiable.

CONCLUSION

A non-optimal cervicovaginal microbiota is associated with increased odds of recurrent sPTB in a predominantly non-Hispanic black cohort of women, which may be magnified in the setting of high perceived stress.

Figure 1.

Figure 1.

Flowchart of study participants.

Medically indicated preterm birth (mPTB), spontaneous preterm birth (sPTB), Cohen’s Perceived Stress Scale (PSS-14), cervicovaginal microbial community state type (CST)

KEY POINTS.

  • CST IV, a non-optimal microbiota, is associated with increased odds of recurrent spontaneous preterm birth

  • Adjustment for perceived stress amplified associations between CST IV and recurrent spontaneous preterm birth

  • Identification of modifiable social or behavioral factors may unveil novel non-pharmacologic interventions to decrease recurrent spontaneous preterm birth among women with underlying biologic risk

ACKNOWLEDGEMENT

Financial support: NIH R01NR014784 (PI Elovitz); K23 ES022242 (PI Burris). Funding sources had no role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the article for publication.

Footnotes

CONFLICT OF INTEREST

The authors report no conflict of interest.

Paper presentation information: This work was presented as an oral presentation at the Society for Maternal-Fetal Medicine’s 40th Annual Pregnancy Meeting, Grapevine, TX, February 6, 2020.

Contributor Information

Jacques RAVEL, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD.

Michal A. ELOVITZ, Maternal and Child Health Research Center, Division of Maternal Fetal Medicine, Department of OB/GYN, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.

Heather H. BURRIS, Maternal and Child Health Research Center, Division of Maternal Fetal Medicine, Department of OB/GYN, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Children’s Hospital of Philadelphia, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.

REFERENCES

  • 1.Elovitz MA, Gajer P, Riis V, et al. Cervicovaginal microbiota and local immune response modulate the risk of spontaneous preterm delivery. Nat Commun. 2019;10(1):1305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.DiGiulio DB, Callahan BJ, McMurdie PJ, et al. Temporal and spatial variation of the human microbiota during pregnancy. Proc Natl Acad Sci. 2015;112(35):11060–11065. doi: 10.1073/pnas.1502875112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Callahan BJ, DiGiulio DB, Goltsman DSA, et al. Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women. Proc Natl Acad Sci. 2017;12(114):9966–9971. doi: 10.1073/pnas.1705899114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Stout MJ, Zhou Y, Wylie KM, Tarr PI, Macones GA, Tuuli MG. Early pregnancy vaginal microbiome trends and preterm birth. Am J Obstet Gynecol. 2017;217(3):356.e1–356.e18. doi: 10.1016/j.ajog.2017.05.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Brown RG, Chan D, Terzidou V, et al. Prospective observational study of vaginal microbiota pre- and post-rescue cervical cerclage. BJOG An Int J Obstet Gynaecol. 2019;126(7):916–925. doi: 10.1111/1471-0528.15600. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Kindinger LM, MacIntyre DA, Lee YS, et al. Relationship between vaginal microbial dysbiosis, inflammation, and pregnancy outcomes in cervical cerclage. Sci Transl Med. 2016;8(350):350ra102. doi: 10.1126/scitranslmed.aag1026. [DOI] [PubMed] [Google Scholar]
  • 7.Kindinger LM, Bennett PR, Lee YS, et al. The interaction between vaginal microbiota, cervical length, and vaginal progesterone treatment for preterm birth risk. Microbiome. 2017;5(1):6. doi: 10.1186/s40168-016-0223-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Fettweis JM, Serrano MG, Brooks JP, et al. The vaginal microbiome and preterm birth. Nat Med. 2019;25(6):1012–1021. doi: 10.1038/s41591-019-0450-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Ravel J, Gajer P, Abdo Z, et al. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci. 2011;108(Suppl 1):4680–4687. doi: 10.1073/pnas.1002611107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Gajer P, Brotman RM, Bai G, et al. Temporal dynamics of the human vaginal microbiota. Sci Transl Med. 2012;4(132):132ra53. doi: 10.1126/scitranslmed.3003605. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Borgdorff H, Verwijs MC, Wit FWNM, et al. The impact of hormonal contraception and pregnancy on sexually transmitted infections and on cervicovaginal microbiota in african sex workers. Sex Transm Dis. 2015;42(3):143–152. doi: 10.1097/OLQ.0000000000000245. [DOI] [PubMed] [Google Scholar]
  • 12.MacIntyre DA, Chandiramani M, Lee YS, et al. The vaginal microbiome during pregnancy and the postpartum period in a European population. Sci Rep. 2015;5:8988. doi: 10.1038/srep08988. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Vodstrcil LA, Twin J, Garland SM, et al. The influence of sexual activity on the vaginal microbiota and Gardnerella vaginalis clade diversity in young women. PLoS One. 2017;12(2):e0171856. doi: 10.1371/journal.pone.0171856. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Ravel J, Brotman RM, Gajer P, et al. Daily temporal dynamics of vaginal microbiota before, during and after episodes of bacterial vaginosis. Microbiome. 2013;1(1):29. doi: 10.1186/2049-2618-1-29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Brooks JP, Buck GA, Chen G, et al. Changes in vaginal community state types reflect major shifts in the microbiome. Microb Ecol Health Dis. 2017;28(1):1303265. doi: 10.1080/16512235.2017.1303265. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.McDonald SW, Kingston D, Bayrampour H, Dolan SM, Tough SC. Cumulative psychosocial stress, coping resources, and preterm birth. Arch Womens Ment Health. 2014;17(6):559–568. doi: 10.1007/s00737-014-0436-5. [DOI] [PubMed] [Google Scholar]
  • 17.Shapiro GD, Fraser WD, Frasch MG, Séguin JR. Psychosocial stress in pregnancy and preterm birth: Associations and mechanisms. J Perinat Med. 2013;41(6):631–645. doi: 10.1515/jpm-2012-0295. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Loomans EM, Van Dijk AE, Vrijkotte TGM, et al. Psychosocial stress during pregnancy is related to adverse birth outcomes: Results from a large multi-ethnic community-based birth cohort. Eur J Public Health. 2013;23(3):485–491. doi: 10.1093/eurpub/cks097. [DOI] [PubMed] [Google Scholar]
  • 19.Staneva A, Bogossian F, Pritchard M, Wittkowski A. The effects of maternal depression, anxiety, and perceived stress during pregnancy on preterm birth: A systematic review. Women and Birth. 2015;28(3):179–193. doi: 10.1016/j.wombi.2015.02.003. [DOI] [PubMed] [Google Scholar]
  • 20.Nkansah-Amankra S, Luchok KJ, Hussey JR, Watkins K, Liu X. Effects of maternal stress on low birth weight and preterm birth outcomes across neighborhoods of South Carolina, 2000–2003. Matern Child Health J. 2010;14(2):215–226. doi: 10.1007/s10995-009-0447-4. [DOI] [PubMed] [Google Scholar]
  • 21.Seravalli L, Patterson F, Nelson DB. Role of Perceived Stress in the Occurrence of Preterm Labor and Preterm Birth Among Urban Women. J Midwifery Women’s Heal. 2014;59(4):374–379. doi: 10.1111/jmwh.12088. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Ruiz RJ, Fullerton J, Brown CEL, Schoolfield J. Relationships of Cortisol, Perceived Stress, Genitourinary Infections, and Fetal Fibronectin to Gestational Age at Birth. Biol Res Nurs. 2001;3(1):39–48. doi: 10.1177/109980040100300106. [DOI] [PubMed] [Google Scholar]
  • 23.Gennaro S, Shults J, Garry DJ. Stress and preterm labor and birth in black women. JOGNN - J Obstet Gynecol Neonatal Nurs. 2008;37(5):538–545. doi: 10.1111/j.1552-6909.2008.00278.x. [DOI] [PubMed] [Google Scholar]
  • 24.Yonkers KA, Smith MV., Forray A, et al. Pregnant women with posttraumatic stress disorder and risk of preterm birth. JAMA Psychiatry. 2014;71(8):897–904. doi: 10.1001/jamapsychiatry.2014.558. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Dole N, Savitz DA, Hertz-Picciotto I, Siega-Riz AM, McMahon MJ, Buekens P. Maternal stress and preterm birth. Am J Epidemiol. 2003;157(1):14–24. doi: 10.1093/aje/kwf176. [DOI] [PubMed] [Google Scholar]
  • 26.Lobel M, Cannella DL, Graham JE, DeVincent C, Schneider J, Meyer BA. Pregnancy-Specific Stress, Prenatal Health Behaviors, and Birth Outcomes. Heal Psychol. 2008;27(5):604–615. doi: 10.1037/a0013242. [DOI] [PubMed] [Google Scholar]
  • 27.Amabebe E, Anumba DOC. Psychosocial stress, cortisol levels, and maintenance of vaginal health. Front Endocrinol (Lausanne). 2018;9:568. doi: 10.3389/fendo.2018.00568. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Guendelman S, Lang Kosa J, Pearl M, Graham S, Kharrazi M. Exploring the relationship of second-trimester corticotropin releasing hormone, chronic stress and preterm delivery. J Matern Neonatal Med. 2008;21(11):788–795. doi: 10.1080/14767050802379031. [DOI] [PubMed] [Google Scholar]
  • 29.Levine TA, Alderdice FA, Grunau RE, McAuliffe FM. Prenatal stress and hemodynamics in pregnancy: a systematic review. Arch Womens Ment Health. 2016;19(5):721–739. doi: 10.1007/s00737-016-0645-1. [DOI] [PubMed] [Google Scholar]
  • 30.Ruiz RJ, Gennaro S, O’Connor C, et al. CRH as a Predictor of Preterm Birth in Minority Women. Biol Res Nurs. 2015;18(3):316–321. doi: 10.1177/1099800415611248. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Shapiro GD, Séguin JR, Muckle G, Monnier P, Fraser WD. Previous pregnancy outcomes and subsequent pregnancy anxiety in a Quebec prospective cohort. J Psychosom Obstet Gynecol. 2017;38(2):121–132. doi: 10.1080/0167482X.2016.1271979. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Laughon SK, Albert PS, Leishear K, Mendola P. The NICHD Consecutive Pregnancies Study: Recurrent preterm delivery by subtype. Am J Obstet Gynecol. 2014;210(2):131.e1–131.e8. doi: 10.1016/j.ajog.2013.09.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Meis PJ, Klebanoff M, Thom E, et al. Prevention of recurrent preterm delivery by 17 alpha-hydroxyprogesterone caproate. N Engl J Med. 2003;348(24):2379–2385. doi: 10.1056/NEJMoa035140. [DOI] [PubMed] [Google Scholar]
  • 34.Blackwell SC, Gyamfi-Bannerman C, Biggio JR, et al. 17-OHPC to Prevent Recurrent Preterm Birth in Singleton Gestations (PROLONG Study): A Multicenter, International, Randomized Double-Blind Trial. Am J Perinatol. 2019:Epub ahead of print. [DOI] [PubMed] [Google Scholar]
  • 35.Cohen S, Kamarck T, Mermelstein R. A Global Measure of Perceived Stress. J Health Soc Behav. 1983;24(4):385. doi: 10.2307/2136404. [DOI] [PubMed] [Google Scholar]
  • 36.Silveira ML, Pekow PS, Dole N, Markenson G, Chasan-Taber L. Correlates of high perceived stress among pregnant hispanic women in western massachusetts. Matern Child Health J. 2013;17(6):1138–1150. doi: 10.1007/s10995-012-1106-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Faulkner JR, Minin VN. Locally adaptive smoothing with Markov random fields and shrinkage priors. Bayesian Anal. 2018;13(1):225–252. doi: 10.1214/17-BA1050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Grobman WA, Parker CB, Willinger M, et al. Racial disparities in adverse pregnancy outcomes and psychosocial stress. Obstet Gynecol. 2018;131(2):328–335. doi: 10.1097/AOG.0000000000002441. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Kramer MS, Lydon J, Goulet L, et al. Maternal stress/distress, hormonal pathways and spontaneous preterm birth. Paediatr Perinat Epidemiol. 2013;27(3):237–246. doi: 10.1111/ppe.12042. [DOI] [PubMed] [Google Scholar]
  • 40.Ferguson K, Rosen E, Barrett E, et al. Joint impact of phthalate exposure and stressful life events in pregnancy on preterm birth. Environ Int. 2019;133(Pt B):105254. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Culhane JF, Rauh V, McCollum KF, Hogan VK, Agnew K, Wadhwa PD. Maternal stress is associated with bacterial vaginosis in human pregnancy. Matern Child Health J. 2001;5(2):127–134. doi: 10.1023/A:1011305300690. [DOI] [PubMed] [Google Scholar]
  • 42.Nansel TR, Riggs MA, Yu KF, Andrews WW, Schwebke JR, Klebanoff MA. The association of psychosocial stress and bacterial vaginosis in a longitudinal cohort. Am J Obstet Gynecol. 2006;194(2):381–386. doi: 10.1016/j.ajog.2005.07.047. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Gur TL, Bailey MT. Effects of stress on commensal microbes and immune system activity. In: Advances in Experimental Medicine and Biology.; 2016:289–300. doi: 10.1007/978-3-319-20215-0_14. [DOI] [PubMed] [Google Scholar]

RESOURCES