research proposal on preterm birth

• Research article
• Open access
• Published: 30 December 2019

Top research priorities for preterm birth: results of a prioritisation partnership between people affected by preterm birth and healthcare professionals

• Sandy Oliver 1 ,
• Seilin Uhm 1 ,
• Lelia Duley   ORCID: orcid.org/0000-0001-6721-5178 2 ,
• Sally Crowe 3 ,
• Anna L. David 4 ,
• Catherine P. James 4 ,
• Zoe Chivers 5 ,
• Gill Gyte 6 ,
• Chris Gale 7 ,
• Mark Turner 8 ,
• Bev Chambers 9 ,
• Irene Dowling 10 ,
• Jenny McNeill 11 ,
• Fiona Alderdice 12 ,
• Andrew Shennan 13 &
• Sanjeev Deshpande 14  

BMC Pregnancy and Childbirth volume  19 , Article number:  528 ( 2019 ) Cite this article

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We report a process to identify and prioritise research questions in preterm birth that are most important to people affected by preterm birth and healthcare practitioners in the United Kingdom and Republic of Ireland.

Using consensus development methods established by the James Lind Alliance, unanswered research questions were identified using an online survey, a paper survey distributed in NHS preterm birth clinics and neonatal units, and through searching published systematic reviews and guidelines. Prioritisation of these questions was by online voting, with paper copies at the same NHS clinics and units, followed by a decision-making workshop of people affected by preterm birth and healthcare professionals.

Overall 26 organisations participated. Three hundred and eighty six people responded to the survey, and 636 systematic reviews and 12 clinical guidelines were inspected for research recommendations. From this, a list of 122 uncertainties about the effects of treatment was collated: 70 from the survey, 28 from systematic reviews, and 24 from guidelines. After removing 18 duplicates, the 104 remaining questions went to a public online vote on the top 10. Five hundred and seven people voted; 231 (45%) people affected by preterm birth, 216 (43%) health professionals, and 55 (11%) affected by preterm birth who were also a health professional. Although the top priority was the same for all types of voter, there was variation in how other questions were ranked.

Following review by the Steering Group, the top 30 questions were then taken to the prioritisation workshop. A list of top 15 questions was agreed, but with some clear differences in priorities between people affected by preterm birth and healthcare professionals.

Conclusions

These research questions prioritised by a partnership process between service users and healthcare professionals should inform the decisions of those who plan to fund research. Priorities of people affected by preterm birth were sometimes different from those of healthcare professionals, and future priority setting partnerships should consider reporting these separately, as well as in total.

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Preterm birth has major impacts on survival, quality of life, psychosocial and emotional stress on the family, and costs for health services [ 1 ]. Improving outcome for these vulnerable babies and their families is a priority, and prioritising research questions is advocated as a pathway to achieve this [ 2 , 3 ].

Traditionally the research agenda has been determined primarily by researchers, either in academia or industry, who have used processes for priority setting that lack transparency [ 4 , 5 ]. This has contributed to a mismatch between the available research evidence and the research preferences of patients and members of the public, and of clinicians [ 6 , 7 ]. Often, research does not address the questions about treatments that are of greatest importance to patients, their carers and practising clinicians [ 5 , 8 ]. The James Lind Alliance has developed methods for establishing priority setting partnerships between patient organisations and clinician organisations, which then identify and prioritise treatment uncertainties in order to inform publicly funded research [ 9 , 10 ]. These methods have been used for a range of health conditions [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ].

We report the outcomes of a process to identify and prioritise research questions in preterm birth that are most important to people affected by preterm birth and healthcare practitioners in the United Kingdom and Ireland using methods established by the James Lind Alliance [ 18 ]. This partnership differed from previous priority setting partnerships supported by the James Lind Alliance in that pregnancy is not an illness or disease, and that it involves at least two people (mother and child); in addition preterm birth can have life-long consequences for them, their families and for the health services and society. Our aim was first to identify unanswered questions about the prevention and treatment of preterm birth from people affected by preterm birth, clinicians and researchers. Then to prioritise those questions that people affected by preterm birth and clinicians agree are the most important.

The Preterm Birth Priority Setting Partnership was convened in November 2011, following an introductory meeting in July 2011. The partnership followed the four stages of the James Lind Alliance process (see Fig.  1 ) [ 9 ].

Flow chart of the JLA Preterm Birth Priority Setting Partnership

Organisations whose areas of interest included preterm birth were informed about the priority setting partnership and invited to participate in, or contribute to, the introductory workshop. Those who then joined the partnership are listed in Box 1. All participating organisations were asked to complete a declaration of interests, including disclosure of relationships with the pharmaceutical or medical devices industry. Subsequently a Steering Group was convened, with members of participating organisations who volunteered to take on this role. This group was chaired by a representative from the James Lind Alliance (SC).

At the introductory workshop it was clear that many participants felt the scope of the partnership should be wider than was initially envisaged. Additional topics proposed for inclusion in the scope were uncertainties about the causes of preterm birth, about the prognosis following being born preterm, and about treatments long before birth. As widening the scope too far would risk leaving the prioritisation unachievable within a reasonable time frame and the existing resources, the Steering Group decided the scope would be restricted to uncertainties about treatments, to interventions during pregnancy and around the time of birth or shortly afterwards (taken up to the time of hospital discharge for the baby after birth).

Consultation to gather research questions (treatment uncertainties)

Research questions were gathered from people affected by preterm birth, clinicians and researchers, using methods developed by the James Lind Alliance [ 10 ]. First, a survey was distributed on-line, including through partner organisations, to ask for suggestions about preterm birth experiences, services or treatments which needed to be researched, and why the research would be important (see Additional file  1 for paper version of this survey). Respondents were asked to say if they were people with personal or family experiences of preterm birth, and/or if they were a health professional.

At an interim review of demographic data about home ownership and ethnicity from this survey there was concern that the respondents were not representative of the population at risk of preterm birth. To try and access a more high risk group, paper copies of the survey (see Additional file 1 ) were distributed at high risk specialist prematurity antenatal clinics at two tertiary level hospitals (University College London Hospital and Queen’s Medical Centre Nottingham), and to parents visiting their babies in three level 3 neonatal intensive care units (University College London Hospital and Chelsea and Westminster Hospital, London; Liverpool Women’s Hospital) between March and December 2012. The survey closing date was extended to allow time to implement these changes. Respondents were invited to provide an email address to be notified about voting to prioritise the questions.

In addition, research questions were identified from systematic reviews of existing research and from national UK clinical guidelines (see Additional file  2 ).

Collation - checking and combining research questions

With support from an independent information specialist, submissions from the survey were formatted into research questions, which were checked against existing reviews and guidelines. Those already answered were removed. The remaining research questions were screened by the Steering Group, to remove those answered by a subsequent randomised trial or for which a large randomised trial was in progress, and those that were out of scope or unclear, and to combine similar research questions. This left the final long list of unanswered research questions which was sorted into similar categories, ordered chronologically from before pregnancy to hospital discharge following birth.

Prioritisation of the research questions

Prioritisation was by a two-stage process using a modified Delphi with individual voting, followed by a face-to-face workshop using nominal group technique [ 10 ]. First, the long list of unanswered research questions was made available online for public voting (from September to December 2013), with paper copies distributed to the same high risk antenatal clinics and neonatal units. Respondents were asked to pick the 10 they considered most important. Overall results and results by stakeholder group (people affected by preterm birth, health professional) were reviewed by the Steering Group to remove remaining repetition or overlap between questions. The final shortlist of 30 unanswered research questions to go forward to the prioritisation workshop was then agreed.

The aims of the prioritisation workshop were to agree a ranking for the short list, including the ‘top10’, and to consider next steps to ensure that the priorities are taken forward for research funding. Participants were invited from across the partnership, and included representatives from organisations representing both people affected by preterm birth and clinicians, parents of babies born preterm, and adults who were born preterm. Prior to the workshop, participants were sent the shortlist of unanswered research questions.

At the workshop (held in January 2014), after an introductory session participants were assigned to one of four small groups, each with a facilitator, to discuss ranking for each uncertainty. Groups were pre-specified in advance to include a mix of parents, people born preterm, clinicians and other health professionals. The groups were provided with a set of 30 large cards, each printed with one shortlisted research question. On the reverse were examples of wording from the original submissions, and a breakdown of how people affected by preterm birth and healthcare professionals had scored that question in their voting. Following discussion, these cards were placed in ranked order. Over the lunchtime break, rankings from the four groups were aggregated into a single ranking order. These aggregate rankings were presented at a plenary session, to demonstrate where there was existing consensus between groups, and where there were differences. Participants were then reconvened into three small groups, again pre-planned so each had a new mix of participants and retained a balance of backgrounds, to discuss the aggregate ranking. Similar processes were used as in the earlier small groups, with the aim of agreeing the top ten research questions and ranking all 30 questions. Aggregated ranking from the three small groups was taken to a final plenary session, with the 30 cards laid out on the floor in ranked order. Participants then debated and agreed the final ranking.

Forty two organisations were approached and invited to participate in the priority setting partnership (see Additional file 4 ); of these 25 accepted and joined the partnership (see Table  1 ). Ten organisations were represented on the Steering Group; four representing those affected by preterm birth, and six representing health professionals (obstetricians and neonatologists). Some Steering Group members were parents of infants born preterm, or had themselves been born preterm. The group also included four non-voting members: two researchers who co-ordinated the prioritisation partnership, one a clinical academic with a background in obstetrics and the other with expertise in public engagement in research; one charity representative, and one PhD student.

When the online survey closed it had been accessed by 1076 people, and completed by 349; an additional 37 paper survey forms were completed and returned. Hence a total of 386 people responded of whom 204 (53%) said that they were affected by preterm birth, 107 (28%) that they were health professionals, 43 (11%) that they were both affected by preterm birth and a health care professional, and 32 (8%) did not answer this question (Table  2 ). Of the 247 respondents affected by preterm birth, most 186 (75%) reported they were parents of a preterm baby, but some were grandparents and other family members.

The 386 responses contained 593 potential research questions. Submissions were formatted into research questions, with similar submission combined into one question (see Additional file 5 ), and screened to remove those already answered, out of scope or unclear, (see Additional file 6 ). Thirty eight submissions were removed as being outside the scope of this process. After merging similar questions and removing those that were fully answered, 70 unanswered questions were left from the survey.

The search of systematic reviews and clinical guidelines identified 540 potentially relevant questions. As there was such a large number, the Steering Group agreed a process to prioritise which would go forward to the next stage. Each member was asked to select the 60 questions from systematic reviews they considered to be most relevant and important. They then brought their list of 60 to a face-to-face meeting at which questions were only considered as potential priorities for the voting stage if they were supported by three or more members. This resulted in 28 questions from systematic reviews and 24 from clinical guidelines remaining in the process. Overall there were then 122 questions; as 18 of these overlapped with other questions, they were merged to give a final ‘long list’ of 104 unanswered research questions (see Additional file  3 ).

The 104 questions on the long list were sent for an online public vote, with paper copies distributed to the same high risk antenatal clinics and neonatal units. Overall 507 people voted (448 online and 59 on paper); 231 (45%) said they had been affected by preterm birth, 216 (43%) that they were a health professional, and 55 (11%) that they were affected by preterm birth and also a health professional (Table 2 ). Type of respondent was not known for 5 (1%) voters. Of the 271 who said they were a health professional (including those who had been affected by preterm birth themselves), 85 said they were an obstetrician, 51 a nurse, 44 a neonatologist, 24 a midwife, 4 a general practitioner, 32 were other health professionals and 31 preferred not to say. Of those who voted, 512 (87%) reported their ethnicity as white, and ethnicity was not known for 8 (2%). Responses were received from the four nations within the United Kingdom, and from the Republic of Ireland.

For public voting, the top priority (which treatments (including diagnostic tests) are most effective to predict or prevent preterm birth?) was the same for all three types of respondent (Table  3 ), but there was considerable variation in how other questions were ranked. Several questions were in the overall top 10 for only one type of voter. Questions ranked 1–40 in the public vote were reviewed by the Steering Group, taking into account the voting preferences of people affected by preterm birth and the overall balance of the topics. Four questions were removed: one had already been answered, one was being addressed by an ongoing trial, and two were merged with another broader question (all three being about infant feeding). A shortlist of the top 30 questions was then taken forward to the prioritisation workshop (Table  4 ).

The workshop to prioritise these 30 questions was attended by 34 participants; 13 parents or adults who had been born preterm and 21 health professions (neonatology, obstetrics, midwifery, speech therapy and psychology). Several of the health professionals also had personal experience of preterm birth. In addition, there were four facilitators (two from the James Lind Alliance and two non-voting members of the Steering Group), five observers (one from the James Lind Alliance, one from a research funding organisation in Canada, one from the Institute of Education University of London, and two who were non-voting members of the Steering Group).

During the prioritisation workshop, two questions were merged as it was agreed they overlapped, and the wording of a few others was modified for clarification. Following the first round of small group discussion, there was considerable variation in the top priorities between the four groups. Following the second round of small group discussion there was agreement about the top few priorities. During the final plenary discussion about the aggregated ranking there was consensus about the top seven questions, less consensus about the next three, and disagreement about those ranked as between 10 and 20. As it was not possible to achieve consensus about the top 10 questions within the timeframe, a proposal to expand this to a top 15 was agreed. Consensus about the top 15 was then achieved (Table 4 ). This top 15 had some significant differences to the ranking following public voting. The most noticeable was two questions ranked 18 (How do stress, trauma and physical workload contribute to the risk of preterm birth, are there effective ways to reduce those risks and does modifying those risks alter outcome?) and 26 (What treatments can predict reliably the likelihood of subsequent infants being preterm?) at the workshop were ranked 3 and 4 respectively in the overall public vote, and 2 and 3 by service users in the public vote (Table 3 ).

The unanswered research questions relevant to preterm birth identified during this process were prioritised in the United Kingdom and Republic of Ireland by people affected by preterm birth (parents, grandparents, adults who were born preterm, and others affected by preterm birth), by a range of health professionals, and by people who were both personally affected by preterm birth and a health professional. To our knowledge this is the first such process in preterm birth. People affected by preterm birth and health professionals had many shared priorities, but our process demonstrates that on some questions they have different perspectives. Priorities may also change over time and in different settings, Hence, although the top research priorities from this process should be considered by those who plan and fund research in this area, the full list of 104 unanswered questions is also relevant to decision-making about research funding. This is particularly true if we wish to make research more relevant to those whose lives have been affected by preterm birth, and the healthcare workers who care for them.

While several of the top priorities for research are broad topics already well recognised as important, such as what is the optimum milk feeding regimen for preterm infants and prevention of infection, others are indicative of areas previously underrepresented in research; for example packages of care to support families after discharge, and what is the role of stress, trauma and physical workload in the risk of preterm birth, and are there effective ways to reduce this risk and does this influence outcome. This is in keeping with findings from previous James Lind Alliance partnerships, which suggests and highlights the value of partnership and shared decision making with an inclusive stakeholder group with balanced representation of service users and clinicians [ 7 ].

In line with the literature on consensus development [ 19 ], the strengths of this Preterm Birth Priority Setting Partnership include the large numbers of participants in the process, the range of stakeholders involved, the formality of the processes, the use of facilitators for face-to-face debate to ensure that all options were discussed and all participants had a chance to voice their views, providing feedback and repeating the judgment, and ensuring that judgements were made confidentially. The first three features applied to both the consultation and the workshop; the last applied only to the consultation. The change in priorities between the survey and the workshop deserves further investigation. Although the choice of individuals within the professional groups represented is unlikely to have made a difference to the priorities, [ 20 ] difference in status across workshop participants may have [ 19 ].

Preterm birth is associated with factors such as lower socio-economic status, ethnicity (such as African origin), and maternal age (being lower than 18 years or above 35 years) [ 21 ]. Despite implementing strategies to reach a more representative population, our respondents remained primarily white and with a relatively high proportion of homeowners, hence not representative of the population affected by preterm birth. This could limit generalisablity of these priorities to other populations. A wide range of relevant health professionals participated in the public voting, including neonatologists, obstetricians, neonatal nurses, midwives, speech and language therapists, psychologists and general practitioners; strengthening generalisablity.

Maintaining balanced representation between people affected by preterm birth and the different groups of health professionals for the final prioritisation workshop was challenging. This may have had implications for the final decisions, as happens in guideline development, where consensus development research concludes that differences in how groups are constituted (but not individual members) leads to different decisions [ 22 ]. At our workshop differences in priorities between the various professional groups contributed to the difficulty in achieving consensus for a top 10 list, and to the two ‘lost priorities’ which although ranked in the top 5 at the public vote were not included in the final top 15. The difficulty in agreeing a top 10 underlines the complexity of priority setting for research, particularly for topics such as preterm birth, which involve mother and baby, as well as their wider family. This complexity, and the differing priorities of different stakeholders, make it important to publicise the top 30 list, and the full long list of 104 questions, as well as the top 15 priorities [ 23 ].

Large changes in ranking following the public vote and the final prioritisation appeared to be related to difficulty in the perspective of people affected by preterm birth being heard in the large group session, and an imbalance between the different priorities of two key types of health professional (neonatologists and obstetricians). This was further complicated by fewer obstetricians than expected attending the workshop, and by some of the healthcare professionals also being researchers. Another element of our work, reported in detail elsewhere, was a nested observational study of how service users and healthcare professionals interact when making collective decisions about research priorities [ 24 ]. This suggested that health care professionals and service users tended to use different pathways for persuasion in a group discussion, and communication patterns depended on the stage of group development. The Steering Group had worked together for some time, and when new participants joined for the workshop communication patterns returned to an earlier stage. This may have influenced quality of the consensus.

Reporting of the process for prioritisation is therefore important for transparency, and to identify ways to improve it. Future prioritisation processes, particularly those with a similar wide range of healthcare professionals, should endeavour to anticipate potential different perspectives and mitigate any imbalance where possible, and should report voting separately by ‘service users’ and healthcare professionals. Similarly, whilst it may be appropriate to include healthcare professionals who are also researchers in prioritisation, this potential conflict of interest should be declared and taken into account.

This priority setting was limited to the United Kingdom and Ireland, and is therefore most readily generalisable to settings with a similar population and health system. Previous research prioritisation processes for preterm birth [ 3 , 25 ] did not include people affected by preterm birth and were for low and middle income settings. The most recent neonatal prioritisation exercise in the UK did not include people affected by preterm birth and considered only medicines for neonates [ 26 ]. Although unanswered research questions are universal, prioritisation of these questions depends on the local values, context and setting. Nevertheless, there are common priorities across these different settings and our prioritisation process in the UK, such as prevention of preterm birth, postnatal infection and lung damage.

Failure to take account of the views of users of research (i.e. clinicians and the patients who look to them for help) contributes to research waste [ 27 ]. James Lind Alliance priority setting partnerships brings together ‘patients, carers and clinicians’ to identify unanswered research questions and to agree a list of the top priorities, ( http://www.jla.nihr.ac.uk/about-the-james-lind-alliance/about-psps.htm ) which can then shape the health research agenda [ 12 , 13 , 14 ]. The aim is to ensure that those who fund health research, and also those who support and conduct research, are aware of what really matters to both patients and clinicians. In our priority setting partnership, people affected by preterm birth and the different groups of health care professionals had different priorities. This underlines the importance of this paper presenting the full list of 30 questions taken forward to the prioritisation workshop, and the respective priorities of people affected by preterm birth and health professionals, as well as the long list of 104 unanswered questions sent out for public voting.

We present the top 30 unanswered research questions identified and prioritised by the priority setting partnership, along with the full list of 104 questions. These include treatment and prevention as well as how care should be organised and staff training. They should be publicised to the public, to research funders and commissioners, and to those who support and conduct research.

People affected by preterm birth and health professionals sometimes had different priorities. Future priority setting partnerships should consider reporting the priorities of service users and healthcare professionals separately, as well as in total. Those with a wide range of healthcare professionals involved should anticipate potential different perspectives and mitigate any imbalance where possible. Healthcare professionals who are also researchers should declare this potential conflict before participating in prioritisation, so that it can be taken into account.

Availability of data and materials

Datasets generated and analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgments

Our thanks to all the organisations which contributed to the partnership, to all the people who responded to our survey and voting, and to the participants in the final workshop. Thanks also to Ann Daly, Drew Davy, Elizabeth Oliver and Claire Stansfield for their help with the systematic reviews.

This paper presents work funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research funding scheme (RP-PG- 0609-10107). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. ALD is supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. During this work CG was funded by the NIHR as a Clinical Lecturer and an Academy of Medical Sciences Starter Grant for Clinical Lecturers, supported by the Medical Research Council, Wellcome Trust, British Heart Foundation, Arthritis Research UK, Prostate Cancer UK and The Royal College of Physicians.

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Sandy Oliver & Seilin Uhm

Nottingham Clinical Trials Unit, University of Nottingham, Nottingham, UK

Lelia Duley

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Sally Crowe

Institute for Women’s Health, University College London, 86-96 Chenies Mews, London, WC1E 6HX, UK

Anna L. David & Catherine P. James

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Zoe Chivers

National Childbirth Trust (NCT), 30 Euston Square, London, NW1 2FB, UK

Neonatal Medicine, School of Public Health, Faculty of Medicine, Imperial College London, Chelsea and Westminster Hospital campus, London, SW10 9NH, UK

Institute of Translational Medicine, University of Liverpool, Liverpool, UK

Mark Turner

Bev Chambers

Irene Dowling

School of Nursing & Midwifery, Queen’s University Belfast, Medical Biology Centre, Belfast, BT9 7BL, UK

Jenny McNeill

National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK

Fiona Alderdice

Kings College London, St. Thomas Hospital, London, SE1 7EH, UK

Andrew Shennan

Sanjeev Deshpande, Princess Royal Hospital, Apley Castle, Grainger Drive, Telford, TF1 6TF, UK

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Contributions

All authors were members of the Steering Group, and so planned the study, and reviewed data. SC chaired the Steering Group, and the final workshop. SU conducted the survey, managed the voting, and analysed the data. LD drafted the paper, with feedback from all authors. All authors agree the final draft.

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Correspondence to Lelia Duley .

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Research Ethics Committee approval for the whole priority setting exercise was obtained from the Institute of Education, University of London (reference FCL 318), and for distribution of paper versions of the survey and voting was from the North Wales REC (Central & East) Research Ethics Committee (reference 12 /WA/0286). Forms for both the survey of uncertainties and voting were self-completed, and consent was assumed if the form was completed and submitted (online) or returned (paper version). Consent for public surveys of this type of was not required by the NHS research ethics committees. For the nested qualitative study, consent to sound record meetings was given verbally by members of the steering group and the workshop participants.

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The authors declare that they have no competing interests.

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Supplementary information

Additional file 1..

Survey form.

Additional file 2.

Mapping systematic reviews.

Additional file 3.

Long list of questions sent for voting.

Additional file 4.

Organisations invited to participate.

Additional file 5.

Submissions formatted as research questions.

Additional file 6.

Reasons for excluding submissions.

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Oliver, S., Uhm, S., Duley, L. et al. Top research priorities for preterm birth: results of a prioritisation partnership between people affected by preterm birth and healthcare professionals. BMC Pregnancy Childbirth 19 , 528 (2019). https://doi.org/10.1186/s12884-019-2654-3

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Received : 01 May 2018

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DOI : https://doi.org/10.1186/s12884-019-2654-3

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The pregnancy microbiome and preterm birth

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• Published: 14 August 2020
• Volume 42 , pages 487–499, ( 2020 )

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• Erna Bayar 1 ,
• Phillip R. Bennett 1 , 2 ,
• Denise Chan 1 ,
• Lynne Sykes 1 , 2 &
• David A. MacIntyre 1 , 2  

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Preterm birth is a global health concern and continues to contribute to substantial neonatal morbidity and mortality despite advances in obstetric and neonatal care. The underlying aetiology is multi-factorial and remains incompletely understood. In this review, the complex interplay between the vaginal microbiome in pregnancy and its association with preterm birth is discussed in depth. Advances in the study of bacteriology and an improved understanding of the human microbiome have seen an improved awareness of the vaginal microbiota in both health and in disease.

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Introduction

Preterm birth (PTB) is a multi-aetiological disease state that causes almost 1 million deaths each year making it the primary cause of mortality in children under 5 years of age worldwide [ 1 ]. Infection is thought to contribute to at least one third of these cases [ 2 , 3 ]. Whilst systemic maternal infection and colonisation of the lower reproductive tract by known pathogens such as Trichomonas vaginalis and Chlamydia trachomatis have long been associated with increased risk of PTB, recent applications of molecular-based profiling methods have provided new insights into the role that microbe-host interactions in pregnancy play in shaping PTB risk [ 4 , 5 ]. In this review, we examine the current evidence linking maternal microbiota composition and host response to high-risk PTB phenotypes.

Culture- and molecular-based profiling of microbial communities

Bacteriology in the late nineteenth and twentieth centuries was largely limited to the investigation of microorganisms that were easily amenable to isolation and culture outside of the human body. However, advances in microscopy quickly led to the realisation that human body niches were colonised by many different microbial morphotypes of a complexity that culture-based methods alone failed to capture. In the twenty-first century, the application of culture-free, molecular-based approaches such as high-throughput DNA sequencing techniques has provided a step change in our ability to rapidly and comprehensively characterise polymicrobial communities and has led to a greater appreciation of the vast numbers of bacteria, viruses, fungi and archaea that inhabit the human body [ 6 ]. The sum total of microorganisms present in a defined community is referred as the ‘microbiota’, whereas the ‘microbiome’ refers to the entire habitat, including the microbiota, their genomes and the surrounding environmental conditions [ 7 ].

Broadly, two sequencing-based strategies are commonly used to study the microbiota; ‘metagenomics’ and ‘metataxonomics’. The metagenome refers to the collection of genomes and genes from the members of a microbiota community and is obtained through shotgun sequencing of all of DNA present in a given sample [ 7 ]. Metataxonomics involves amplification and sequencing of specific, often short-length regions of microbial taxonomic marker genes. For bacteria, the 16S ribosomal RNA gene (16S rRNA) is most commonly targeted, whereas the internal transcribed spacer (ITS) region is often used for characterisation of fungi. The bacterial 16S rRNA gene is composed of highly conserved regions and nine ‘hyper-variable’ regions (V1-V9). PCR primers designed to bind to the conserved regions permit amplification of the variable regions, which are generally diverse and distinctive thus facilitating classification of bacterial taxonomy to species, and in some cases strain level, by mapping the resulting sequences to existing 16S rRNA gene databases [ 8 ]. Accurate identification of bacterial species using metataxonomics is therefore prone to bias depending on the choice of amplification region, primer design and even the database that the sequence reads are mapped to. For example, the ‘conserved’ regions of the 16S rRNA gene are not fully conserved so PCR primers may selectively bind to some but not all bacterial DNA in the sample. Moreover, ‘hyper-variable’ regions will not always provide sufficient variability to distinguish between species, let alone strains of bacteria. Such issues are important to consider when examining and interpreting results of microbiota studies particular in the context of studies focussed on the reproductive tract microbiota [ 9 ]. For example, the targeting of the V4 hyper-variable region, which is commonly used to examine the gut microbiota, gives poor resolution of Lactobacillus species, a keystone commensal species of the cervicovaginal niche. Conversely, whilst the VI–V2 region differentiates Lactobacillus species well, universal primers may fail to amplify the important vaginal pathobiont, Gardnerella vaginalis , due to it having a less conserved sequence in the pre-V1 conserved region. Such difficulties can be overcome by careful design and use of degenerate PCR primers; however, it is important to recognise that rare, but physiologically important, taxa may be missed through selective amplification of high-abundance species.

In contrast to metataxonomic profiling, metagenomics approaches provide strain-level resolution through shotgun sequencing and bioinformatic assembly of microbial genomes, which can then be mapped and annotated using reference databases. Metagenomic sequencing avoids PCR bias and captures information of the collective genomes from all then constituents of the microbiome kingdom. The resulting information can be leveraged to provide insight into potential metabolic function in additional to compositional structure of the community under investigation. Disadvantages have historically included higher costs, greater computation burden and inability to detect rare or low-abundance taxa in low-biomass samples that are overwhelmed by DNA from host and highly abundant commensals. These issues are increasingly less of a concern as sequencing costs continue to fall and new methods for sample preparation and bioinformatics approaches are developed [ 10 ].

The vaginal microbiota in health and disease

The vaginal microbiota plays a key role in female genital tract health and disease [ 11 ]. Throughout a woman’s lifespan, the composition of the vaginal microbiota is shaped by both intrinsic and extrinsic factors. Prior to the menarche low levels of circulating oestrogen associate with a high-diversity microbial structure consisting of aerobic, anaerobic and enteric bacteria [ 12 ]. Menarche is associated with increasing circulating oestrogen levels which promote proliferation of vaginal epithelial cells and glycogen deposition, the breakdown products of which can be preferentially utilised by Lactobacillus spp. as a primary carbon source, favouring their dominance and leading to a fall in pH [ 13 ]. This acidic environment, enriched by bacteriocins and other antimicrobial compounds produced by Lactobacillus spp., results in a hostile mucosal microenvironment that they have evolved and adapted to thrive in, which is hostile to many other microbial species. In this way, Lactobacillus spp. are considered to be keystone members of the vaginal microbiome during a woman’s reproductive years and are often associated with states of health and protection against bacterial vaginosis (BV), pelvic inflammatory disease, candidiasis, sexually transmitted infections, HIV, HSV-2 and carcinogenic human papilloma virus [ 14 , 15 , 16 , 17 , 18 , 19 ].

The first application of next-generation sequencing–based approaches to characterise the bacterial component of the vaginal microbiota was published by Ravel et al. [ 15 ]. Using hierarchical clustering of relative abundance data derived from metataxonomic profiling of vaginal samples collected from asymptomatic women, they described five distinct vaginal community state types (CST). Four of these state types were dominated by Lactobacillus spp. ( L. crispatus , L. gasseri , L. iners or L. jensenii , designated CST I, II, II and V respectively). The remaining CST, CST IV, was Lactobacillus spp. depleted and characterised by a highly diverse, polymicrobial community that compositionally resembled that of women with a clinical diagnosis of bacterial vaginosis. This schema was later modified to account for differences within the Lactobacillus spp. deplete, high-diversity groups with CST IV-A, characterised by enrichment for Peptoniphilus and Prevotella species, and CST IV-B, characterised by a higher relative abundance of Atopobium and Gardnerella species and other taxa previously associated with bacterial vaginosis. Whilst other statistical methodologies have since been used to classify vaginal microbiota profiles (also referred to as ‘vagitypes’ or ‘vaginal microbial communities’), their compositional characteristics remain relatively consistent despite rarer vaginal microbial community types increasingly being reported (e.g. Bifidobacteria-dominated profiles).

Longitudinal profiling of vaginal microbiota has shown that whilst some women maintain a level of compositional stability throughout the menstrual cycle and at the time of menstruation, falling oestrogen and progesterone, endometrial shedding and vaginal bleeding lead to dynamic shifts in composition, often characterised by reduced Lactobacillus sp. relative abundance, which recovers during the follicular phase of the cycle [ 20 ]. Pregnancy brings endocrine stability, a substantial increase in circulating oestrogen concentrations and an end to menstrual bleeding which favours Lactobacillus sp. dominance of the vaginal microbiota [ 21 ]. Several cohort studies have shown that healthy pregnant women with normal outcomes generally maintain a vaginal microbiota dominated by Lactobacillus spp. throughout the entire pregnancy. The shift towards Lactobacillus sp. dominance appears to occur early in pregnancy and is most dramatically observed in women of African ancestry. Following delivery, maternal oestrogen levels fall to menopausal levels, which, coupled with the passage of lochia, changes the vaginal environment resulting in decreased Lactobacillus spp. and a shift towards Lactobacillus spp. [ 21 ] depleted community structures that have been reported to persist for up to one year postpartum [ 22 ].

Intrauterine infection leading to PTB is widely hypothesised to be secondary to pathogen ascension from the vagina [ 23 , 24 ]. In humans, this notion is supported by the similarity observed between bacterial species found in the placenta and fetal membranes (amnion and chorion) of PTB cases and those found in the vagina [ 25 , 26 ]. The fact that histological chorioamnionitis is most frequently observed at the site of membrane rupture in the lower part of the uterus close to the cervix [ 27 ] and in twin pregnancies, where histological chorioamnionitis and microbial invasion of the amniotic cavity are most commonly observed in the presenting and first born twin further supports the notion [ 25 , 28 ]. The process of ascending vaginal infection leading to PTB can also be readily replicated in a number of animal models [ 29 , 30 , 31 , 32 , 33 , 34 ].

Given this evidence, characterisation of the vaginal microbiota in women with PTB or preterm prelabour rupture of the membranes (PPROM) has gained increasing attention. As commonly occurs in burgeoning research areas, the earliest of these studies were limited by a lack of power and a lack of consideration of underlying aetiology, which lead to inconsistent reports of relationships, or lack thereof, between vaginal microbiota and PTB. In the earliest of such molecular-based studies of vaginal microbiota in PTB, Hyman et al. reported that bacterial diversity was greater in Caucasians with PTB but that species diversity was generally higher among African Americans [ 35 ]. In contrast, Romero et al. found no differences in bacterial taxa abundance or community state types between women delivering preterm or term; however, this cohort was almost entirely African American [ 36 ]. The concept that ethnicity is a strong determinant of the vaginal microbiome and its effect upon PTB rates was further developed in two studies from the Relman group in Stanford. The first in a mostly White population correlated Lactobacillus -depleted vaginal community state types with reduced gestational age at delivery and showed that risk for PTB was greater in women with high abundances of Gardnerella or Ureaplasma [ 22 ]. The subsequent study compared two populations, White women in California and Black women in Alabama, and showed that whilst Lactobacillus depletion and greater abundance of Gardnerella were more common in Black women, it represented a risk factor for PTB only in White women. Lactobacillus crispatus was found to be protective against PTB in both groups [ 37 ].

A study on a small group of nulliparous African American women reported a trend between spontaneous PTB and lower vaginal bacterial diversity, although this was not statistically significant [ 38 ]. Similarly in a cohort of Black women, abundance of specific Lactobacillus species did not correlate to risk or protection from PTB, but a decrease in vaginal diversity was associated with PTB in African American women [ 39 ]. Recently, differences between bacterial taxa and PTB between African American and non-African American women have been explored [ 40 ]. Again, whilst more African Americans had reduced abundance of Lactobacillus species, this was only a significant risk factor for PTB in White women. This study also reported the identification of specific bacterial taxa that were significantly associated with spontaneous PTB, with a stronger effect observed in African American women. However, in this cohort, higher β-defensin-2 lowered the risk of spontaneous PTB in Black women.

As part of the integrative Human Microbiome Project, Fettweiss et al. compared the vaginal microbiome and cytokine profile between 45 women delivering preterm and 90 women delivering term of African descent, matched for age and income. Metaxonomic, metagonomic and cytokine analyses showed those delivering preterm had significantly lower levels of Lactobacillus crispatus , higher levels of BVAB1, Sneathia amnii , TM7-HI and a group of Prevtolla species [ 41 ]. Women that delivered term were more likely to have Lactobacillus crispatus and decreased prevalence of A. vaginae and G. vaginalis . PTB was also associated with a vaginal cytokine profile richer in pro-inflammatory cytokines, including eotaxin, IL-1β, IL-6 and MIP-1β.

European studies have tended to comprise mostly of White women. In a study of women of European, Middle Eastern or Asiatic origin, an increased risk of PTB associated with Lactobacillus iners and a protective effect for Lactobacillus crispatus dominance was shown [ 42 ]. Similarly, we previously showed that in a UK population, Lactobacillus iners dominance at 16 weeks was significantly associated with both a short cervix and PTB before 34 weeks [ 43 ]. In contrast, Lactobacillus crispatus dominance was highly predictive of term birth. In this study, neither cervical shortening nor PTB were associated with high-diversity community compositions; however, the prevalence of Lactobacillus depletion in our cohort was relatively low. The concept that the vaginal microbiota may be more important in relation to early preterm birth is supported by Canadian data from predominantly White European women which showed that the predominance of microbial profiles dominated by Lactobacillus gasseri / Lactobacillus johnsonii , Lactobacillus crispatus / Lactobacillus acidophilus , Lactobacillus iners / Ralstonia solanacearum or Bifidobacterium longum / Bifidobacterium breve is associated with a decreased risk of PTB before 34 weeks of gestation [ 44 ]. High-diversity compositions and the presence of BV-associated bacteria (e.g. G. vaginalis , A. vaginae and Veillonellaceae bacterium ) were linked to an increased risk of early PTB.

Approximately 30–40% of PTB cases are preceded by PPROM [ 45 ]. Rupture of the fetal membranes provides an entry point for ascending microbes, but infection may be both a cause and a consequence of PPROM. Pathogenic vaginal bacteria may ascend and trigger inflammatory cascades, leading to remodelling of the cervix and fetal membranes. Following PPROM, ascending pathogens contribute to the development of chorioamnionitis and funisitis [ 46 , 47 , 48 ].

Four studies have examined the vaginal microbiota at the time of PPROM. These show that up to half of women who present with PPROM have a vaginal microbiota characterised by intermediate or low Lactobacillus sp. dominance and high diversity [ 49 , 50 , 51 , 52 ]. Our study found that in individual case samples sampled both before and after PPROM, about half of those with Lactobacillus sp. dominance prior to PPROM became dysbiotic post rupture, and that treatment with erythromycin further exacerbates vaginal dysbiosis, characterised by Lactobacillus sp. depletion and enrichment for potentially pathogenic bacteria [ 52 ]. In this cohort, vaginal dysbiosis was a risk factor for both chorioamnionitis and early onset neonatal sepsis. In a later prospective cohort study, we observed reduced Lactobacillus sp. abundance and high diversity in a quarter of women prior to PPROM, but in only 3% of women who delivered at term without membrane rupture [ 53 ]. PPROM associated with a shift towards higher diversity, predominately occurring during the second trimester, although a vaginal bacterial community dominated by any species other than Lactobacillus was associated with subsequent PPROM at all gestational time windows, including during the first trimester.

Progesterone is now commonly offered to women at risk of PTB particularly in the context of second trimester cervical shortening. In vitro studies have shown that progesterone inhibits inflammatory pathways in amnion and myometrium, reducing cytokine and prostaglandin production [ 54 , 55 , 56 ]. Therapeutic progesterone may reduce myometrial contractility, prevent cervical remodelling and increase levels of local antimicrobial proteins, so reducing the risk of PTB [ 54 , 57 , 58 , 59 ]. A small study which randomised women to progesterone or cervical cerclage showed that whilst cerclage leads to increased levels of inflammatory cytokines in cervicovaginal fluid, progesterone has no effect [ 60 ]. Progesterone action similarly does not appear to act through modulation of the vaginal microbiota. In non-pregnant women, Borgdorff et al. found that both injectable progestin contraception and combined oral contraception (progestin and oestrogen) do not significantly alter the vaginal microbiota, but may increase the risk of HIV transmission [ 61 , 62 , 63 ]. We have shown that administration of progesterone to women with a short cervix in pregnancy does not lead to changes in the abundance of either Lactobacillus iners or Lactobacillus crispatus. We showed through longitudinal sampling of women receiving progesterone for a short cervix that L. iners dominance persisted and was associated with all women who subsequently delivered preterm. It is therefore likely that the mode of action of progesterone is non-microbial [ 43 ].

The management of women presenting with cervical shortening and exposed membranes in the second trimester is challenging. Without intervention, delivery usually follows within 2–3 weeks [ 64 , 65 ]. Insertion of an emergency or rescue cervical cerclage prolongs gestation and improves birth weight and neonatal survival [ 66 , 67 ]. However, the take home baby rate following rescue cerclage is only 50% and identifying which women would benefit from a rescue cerclage is challenging [ 65 ]. Although management remains contentious, many obstetricians would offer ‘rescue’ cervical cerclage in such cases provided there was no clinical evidence of established preterm labour or chorioamnionitis. Data suggests that a bimodal distribution of the gestational age of delivery in women offered rescue cerclage is due to the underlying aetiology of cervical dilation with a subset of women likely to deliver early because of subclinical infection [ 66 ]. Consistent with this, we recently reported in a small cohort of women presenting with a dilated cervix and exposed fetal membranes that reduced Lactobacillus sp. relative abundance was observed in 40% of cases prior to cerclage compared with 10% of gestational age-matched controls [ 68 ]. Gardnerella vaginalis was overrepresented in women presenting with symptoms and those in whom rescue cerclage failed to usefully prolong pregnancy. The insertion of a rescue cerclage, which was using inert monofilament material, did not affect the underlying bacterial composition. These findings point towards at least two underlying aetiologies in women presenting with silent cervical dilatation prior to PPROM, one of which is linked to pathogen colonisation of the cervicovaginal niche and poor response to cervical cerclage, and another which includes a high proportion of women with genuine cervical mechanical abnormality, and who may respond well to cerclage.

Vaginal microbiota and background PTB risk

There exists a small background increase in the rate of PTB in women with untreated cervical intraepithelial neoplasia (CIN), but the principal risk of PTB relates to the degree of tissue destruction caused by a pre-pregnancy history of a large loop excision of the transformation zone of the cervix (LLETZ) or cone biopsy. In particular, there is a ‘depth-dependent’ relationship between depth of excision of cervical tissue and subsequent risk of PTB [ 69 ]. We have shown that in non-pregnant women, CIN associates with an increased prevalence of vaginal microbiota characterised by high diversity and low levels of Lactobacillus spp. and that increasing severity of CIN is associated with decreasing relative abundance of Lactobacillus spp. [ 70 ]. A subsequent study of a cohort of adolescent and young women with histologically confirmed, untreated CIN2 lesions showed that women with Lactobacillus -dominant vaginal microbiota at baseline are more likely to have regressive disease at 12 months [ 71 ]. Current evidence suggests that LLETZ and similar procedures may improve vaginal microbiota composition. Wiik et al. demonstrated a reduction in the relative abundance of non- Lactobacillus spp. following LLETZ procedures [ 72 ]. Similarly, a follow-up of women 3 months after LLETZ procedures for CINI/II demonstrated a shift towards Lactobacillus iners dominance of vaginal communities [ 73 ]. This data collectively highlights vaginal dysbiosis in women with CIN or a previous LLETZ as a possible causal factor for increased risk of PTB in these women. Whilst to the best of our knowledge no published studies of the effect of pregnancy upon the vaginal microbiota in women who have had LLETZ have been reported, we have, however, seen excellent outcomes in women with a prior LLETZ who are managed by surveillance of cervical length during pregnancy with targeted cervical cerclage [ 74 ]. The association between PTB and local cervical treatment may therefore be microbial as well as mechanical.

From compositional awareness to mechanistic understanding

The great majority of studies linking the vaginal microbiota have been essentially associative, with little or no focus upon mechanism. A consistent finding across most studies is the protective effect of Lactobacillus species, particularly L. crispatus . In addition to producing bacteriocins and other antimicrobial compounds, L. crispatus produces mainly d -lactate as its primary metabolic end product, which not only acts to maintain a low pH but also has been reported to inhibit activation of extracellular matrix metalloproteinase inducer (EMMPRIN), an activator of MMP-9 and so of collagen degradation [ 75 ]. L. crispatus also has beneficial immunomodulatory functions and can inhibit adhesion of other bacteria such as G. vaginalis to vaginal epithelial cells [ 76 ]. In contrast, the role of L. iners in the vaginal microbiota is less clear, since it can be detected in normal conditions as well as during vaginal dysbiosis and as mentioned earlier, a number of studies have identified dominance of vaginal microbiota by L. iners as a risk factor for preterm labour. A major difference between L. iners and L. crispatus is genome size. L. iners has an unusually small genome (ca. 1 Mbp compared with 3–4 Mbp) resulting in a lack of key functional metabolic genes. As a result, it seems to have evolved a level of tolerance to co-colonise alongside other vaginal bacteria, including potential pathogens, and is associated with a transitionary state of vaginal microbiota composition compared with L. crispatus , which is highly exclusionary [ 77 ]. L. iners dominance of vaginal communities is also associated with activation of EMMPRIN, and mucin-degrading enzymes which disrupts the immune barrier [ 75 ]. It may therefore be the case that unlike L. crispatus , L. iners fails to prevent pathogen colonisation of the vagina during pregnancy and is therefore indirectly ‘causative’ of high-risk vaginal microbiota communities that associate with PTB or that its ability to coexist with pathobionts and pathogens means that it simply acts as a marker.

Several studies have now reported findings suggesting that one of the ways in which high-diversity vaginal microbiota may increase risk of PTB is through untimely activation of inflammatory pathways involved in the initiation of parturition. In one of the first of such studies, we showed that in women with cervical cerclage, the use of a braided suture material induces a persistent shift towards vaginal microbiome dysbiosis and activation of local inflammation accompanied by ultrasound evidence of premature cervical remodelling [ 78 ]. Analyses of retrospective data from multiple centres across the UK also showed that braided cerclages associate with a threefold increase in numbers of intrauterine fetal deaths and a doubling in the rate of PTB compared with cerclage with monofilament suture, which had no significant impact upon the vaginal microbiota, cytokine concentrations or cervical changes. This evidence suggests a direct effect of microbiome-activated inflammation on the cervix developing as the pregnancy progresses. That concept is supported by the finding from our prospective studies of PPROM described earlier that in the majority of cases, PPROM is associated with a shift towards higher diversity occurring during the second or early third trimester, relatively close to the time of PPROM [ 53 ]. Fetal leukocyte telomere length is reduced at the time of normal term labour and is a marker for oxidative stress and fetal membrane senescence [ 79 ]. Fetal leukocyte telomere length is also reduced in PPROM compared with PTB without prior PPROM but is similar to term births, supporting the hypothesis that PPROM may be in part caused by oxidative stress–induced senescence. A range of factors, including infection or inflammation, can lead to oxidative stress. Mechanical stress may also activate sterile inflammation within the fetal membranes, thus providing an attractive hypothesis for a final common pathway to membrane rupture in the context of both abnormal mechanical forces, the context of cervical mechanical damage, polyhydramnios or multiple pregnancy, or vaginal dysbiosis–driven inflammation within the vagina cervix and lower uterine segment [ 79 ].

Evidence for an oral-placental microbiome axis in preterm birth

Haematogenous spread of microbes and subsequent colonisation of the placenta have also been proposed as a potential secondary route of invasion and infection leading to PTB [ 80 ]. It has been suggested that the origin of these bacteria is the oral cavity [ 81 ] and oral-to-placental transmission of pathogens can been demonstrated in murine models [ 82 , 83 ]. Further evidence for an oral-placental axis involved in PTB includes the identification of common oral pathogens (e.g. Fusobacterium nucleatum , Dialister spp., Prevotella spp., and Porphyromonas gingivalis ) in the placenta of women with periodontal disease [ 84 , 85 ], which is associated with increased risk of PTB [ 84 , 86 , 87 ]. However, interventions that improve periodontal health during pregnancy do not prevent PTB [ 88 , 89 , 90 ] and many bacterial species that were historically considered to be limited to the oral cavity are now recognised as being commonly observed members of the vaginal niche.

Regardless, a large amount of research effort over the last decade has been invested into work describing the existence of a placental microbiome that may influence pregnancy outcome. Controversy continues to plague research in this area, much of which appears to stem from definition of terms with some investigators considering that the term ‘microbiome’ should only be applied to microbial communities that have a well-described biological or physiological function (e.g. gut or vaginal microbiome) in host health. For example, the human gut microbiome plays a wide range of essential physiological functions including nutrient absorption, metabolism, maintenance of mucosal integrity and immunomodulation. The human vaginal microbiome plays important roles in protecting the vagina from overgrowth of pathobionts and pathogens, and prevention of ascending pelvic inflammatory disease or chorioamnionitis. These two ‘microbiomes’ clearly have essential physiological functions. Aagaard et al. published the first study suggesting that the placenta contains a genuine microbiome composed of non-pathogenic microbiota [ 91 ]. The placental microbiome profiles were most akin to the human oral microbiome, and differences were seen in women with a history of antenatal urinary tract infection in the first trimester, and with PTB. Metagenomic analysis implied a wide range of potential metabolic functions for these organisms. However, the total biomass of organisms suggested to be in the placenta was very low, which is inconstant with an essential metabolic role. Further, some of the microbes identified in the placenta had previously only been reported in environments very dissimilar to the human placenta, such as soda lakes, alkaline and saline habitats, and marine environments. One organism purportedly associated with PTB was Gloeobacter , which is a genus of cyanobacteria (also known as blue-green algae), which obtain their energy through oxygenic photosynthesis.

Subsequent studies using a combination of culture-based, metagenomic and metataxonomic analyses have failed to identify a genuine placental microbiome in normal pregnancy. Lauder et al. compared placental samples from healthy deliveries with a matched set of contamination controls, and oral and vaginal samples from the same women [ 92 ]. Placental samples and negative controls contained very low and indistinguishable copy numbers of the 16S rRNA gene. Oral and vaginal swab samples had six orders of magnitude higher copy numbers. It was concluded that all of the bacterial DNA amplified from placental samples derived from environmental or reagent contamination and that results diverged radically in association with the kit used to purify the DNA. Similarly, Theis et al. used a combination of cultivation, quantitative real-time PCR, 16S rRNA gene sequencing and metagenomics to study placentas from a cohort of women who had been delivered by Caesarean-section without labour at term [ 93 ]. They also concluded that a normal resident microbiota could not be identified in the human placenta and found no difference in microbiota between placental samples and background technical controls. Recently, Goffau et al. performed metagenomic and metataxonomic analysis to determine whether pre-eclampsia, small for gestational age infants or spontaneous PTB were associated with bacterial DNA in the placenta [ 94 ]. No bacteria were found in most placental samples, from either complicated or uncomplicated pregnancies. Almost all signals were related either to the acquisition of bacteria during labour and delivery, or to sources of laboratory contamination. The exception was Streptococcus agalactiae (group B streptococcus), for which non-contaminant signals were detected in 5% of samples collected. It therefore seems highly unlikely that there is genuine consistent and physiological relevant normal microbiome within the human placenta.

It does seem likely, however, that some cases of spontaneous preterm labour, particularly those associated with chorioamnionitis, harbour detectable bacteria within the placenta. A large recent UK study of 400 placental samples from 256 singleton pregnancies found no convincing evidence for the existence of a reproducible ‘preterm placental microbiome’ but did find evidence of Mycoplasma spp. and Ureaplasma spp. associated with PTB [ 95 ]. A further study from the Aagaard laboratory has shown that specifically, preterm subjects with severe chorioamnionitis have high abundances of Ureaplasma parvum , Fusobacterium nucleatum and Streptococcus agalactiae within the placenta, supporting the idea of either ascending or haematogenous infection [ 96 ].

The gut microbiome

The gastrointestinal tract (GIT) has the largest surface area in the body that is exposed to foreign material consisting of a diverse community of fungi, protozoa, viruses, archaea and bacteria. The most abundant phyla of bacteria that exist in the human GIT are Firmicutes , Bacteroidetes , Actinobacteria and Proteobacteria with Firmicutes and Bacteroidetes occupying 70–90% of the total GIT bacteria [ 97 , 98 ]. As many as 1000 species have been identified as having critical physiological roles that are essential to the host, including regulation of immune homeostasis. Evidence for this is supported by germ-free mice exhibiting an altered immune phenotype with deficits in the local innate and adaptive immune components [ 99 , 100 ].

Several studies have sampled the gut microbiota across longitudinal timepoints in pregnancy as gestational age advances, with the majority reporting that the diversity and composition of bacterial communities remain largely stable throughout pregnancy [ 22 , 97 , 101 ]. However, the largest study of 91 women by Koren et al. showed a decrease in α-diversity and an expansion of β-diversity between the first and third trimesters, which was associated with an increase in pro-inflammatory cytokine concentrations in stool [ 102 ]. They also describe an increase in the relative abundance of Proteobacteria and Actinobacteria in the third trimester in 69% and 57% of women respectively. OTUs overrepresented in the third trimester were of the Enterobacteriaceae family and Streptococcus genus, whereas OTUs overrepresented in the first trimester were the anti-inflammatory butyrate producers Eubacterium and Faecalibacterium . In addition, transfer of third trimester maternal microbiota to germ-free mice induced a mild inflammatory response, with higher stool IL-1β. It is therefore plausible that microbiome remodelling follows a distinct temporal adaptation in order to allow for gestational age–dependent immunomodulation to facilitate successful pregnancy and timely parturition.

The concept of both local and systemic temporal immune adaptation in healthy pregnancy is well-established. The beneficial anti-inflammatory state allows to accommodate the developing fetus during pregnancy, until a shift towards a pro-inflammatory state occurs in the third trimester to allow for parturition [ 103 ]. Given the evidence supporting the role of a systemic immunological clock in the timing of delivery, it is plausible that unfavourable and premature alterations in composition and diversity of the gut microbiota, resulting in systemic inflammation, could play a role in the aetiology of spontaneous preterm labour [ 104 ]. In addition, since there are close anatomical links between the lower reproductive tract and the lower intestinal tract, it is also plausible that microbial seeding between the gut and vagina can influence the microbial environment of both sites, leading to aberrant local inflammation.

Dahl et al. examined day 4 postpartum faecal samples from 19 women who delivered preterm and 102 women who delivered at term and revealed a reduction in α-diversity and lower operational taxonomic unit (OTU) abundances of the Bifidobacterium and Streptococcus genera, and of families in the Clostridiales order [ 105 ]. Bifidobacterium has many anti-inflammatory properties with multiple strains able to inhibit LPS-induced NF-κB activation, IL-8 and COX-2 production in vitro [ 106 , 107 ]. Therefore, a reduction in Bifidobacterium could lead to increased susceptibility to inflammation/infection-induced preterm labour. Shiozaki et al. showed a reduction in OTUs from several species of Clostridium and Bacteroides in 10 women who delivered preterm compared with 10 women who delivered at term [ 108 ]. Clostridia spp. are potent inducers of T regulatory cell number and activation [ 109 , 110 ]. Bacteroides fragilis promotes an anti-inflammatory response in the gut by activating IL-10 secreting T-reg cells via polysaccharide A. This suppresses the Toll-like receptor (TLR) 2 signalling pathway and dampens Th17 responses [ 111 ]. The authors elude to the alteration in gut microbial composition causing increased susceptibility to inflammation due to a reduction in T-reg cells, which is commonly reported in cases of PTB [ 112 ]. Whilst these studies provide some support for a potential role for gut microbial inflammation in mediating PTB risk, there is clearly the need for more investigation in this area [ 113 , 114 ].

Manipulation of vaginal microbiota to modify PTB risk

Given that substantial evidence supports a link between specific vaginal microbiota composition and increased PTB risk, it is not surprising that numerous studies have examined the efficacy of antibiotics for the treatment and prevention PTB. These have almost entirely been targeted towards pregnant women with bacterial vaginosis (BV), and the results of these trials have proven highly inconsistent [ 115 , 116 ]. In part, this is due to heterogeneity between trial designs (e.g. differences in the timing of treatment, types of antibiotic used, administration routes, patient cohorts selected and erroneous indications) [ 117 , 118 ]. In the largest such trial to date, the double-blinded PREMEVA trial of oral clindamycin in early pregnancy [ 119 ] screened 85,000 women for BV with 1904 BV-positive participants (out of 5630 diagnosed) with low background risk for PTB assigned to the treatment arm and 956 participants assigned placebo consistent with the pre-trial defined 2:1 treatment:placebo ratio. No difference in the primary outcome of the composite of late miscarriage (16–21 weeks) or spontaneous very PTB (22–32 weeks) was detected between the two groups. Aspects of the PREMEVA trial design have come under scrutiny [ 117 ] [ 120 ], and there remain some experts who believe that a randomised, placebo-controlled trial of screening and treating BV in women with a history of PTB is still warranted [ 116 ]. However, there are a number of issues that need to be carefully considered in any such future trial. Treatment of women with existing BV implies that associated ascending infection or inflammatory pathway activation may have already commenced. Secondly, the use of some antibiotics (e.g. metronidazole) may cause lysing of bacteria and release of endotoxins [ 121 ], which are strong activators of inflammation in gestational tissues and therefore may potentiate an inflammatory phenotype [ 122 , 123 , 124 ]. Certain antibiotic treatments may be particularly effective against commensal species such as Lactobacillus , but not against pathogens associated with BV leading to inadvertent enrichment of these species in the vaginal niche [ 52 , 125 , 126 ]. Such trials would also need to be conducted with careful consideration of antibiotic resistance genes commonly found within BV-associated bacteria [ 127 , 128 ].

The failure of antibiotic therapy to improve PTB in the context of abnormal vaginal flora, previous PTB or positive fetal fibronectin status has led to interest in the positive modulation of the vaginal microbiota using of live bio-therapeutic products (LBPs, live microorganisms, administered for the prevention or treatment of human disease) or probiotics (non-pathogenic microorganisms of human origin, given to provide health benefits). Probiotics may be given orally or less commonly vaginally. A systematic review of generally oral probiotic use in pregnancy found no evidence of any effect upon the PTB rate [ 129 ]. An observational study in Norway however found that probiotic milk consumption in early, but not mid to late pregnancy associates with a lower risk of PTB [ 130 ]. Two recently reported randomised controlled studies have found that oral probiotics, containing Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14, do not modify the vaginal microbiota in pregnancy [ 131 ] [ 132 ].

An alternative approach is direct vaginal administration of Lactobacillus LBP . L. crispatus has been shown to inhibit growth of Streptococcus agalactiae (group B streptoccocus) in vitro. In non-pregnant women with a history of recurrent urinary tract infection, vaginal administration of L. crispatus following antibiotic treatment showed effective vaginal colonisation and a reduction in urinary tract infection recurrence [ 133 ]. Vaginal administration of both L. acidophilus and L. rhamnosus combined and L. crispatus has been shown a significantly reduced risk of recurrence in BV [ 134 , 135 ]. Trials in pregnancy are currently in progress, but given the evidence for its protective effects, vaginal administration of suitable strains of L. crispatus represents a promising approach for beneficial modulation of the vaginal microbiota in pregnancy.

Conclusions

The introduction of high-throughput DNA sequencing techniques into microbiological research has confirmed what was previously known from culture-based classical microbiology and greatly expanded our ability to study communities of microorganisms. Whilst it is doubtful that a physiologically essential placental microbiome exists, it remains possible that some cases of preterm labour may be due to haematogenous spread of organisms to the placenta and uterus. Studying the role of the gut microbiota in pregnancy and the potential for gut microbial inflammation to be linked to PTB risk will be challenging, but could potentially be paradigm changing. The strongest evidence for the role of the microbiome in preterm birth relates to the vaginal microbiota. But there remain significant geographical and ethnic differences, the underlying mechanisms of which are yet unknown and whose elucidation will provide valuable insights into the mechanisms of preterm birth in different ethnic groups and communities. The most consistent finding across almost all studies is the benefit of a vaginal microbiota characterised by Lactobacillus crispatus . This opens the door to modulation through the use of live bio-therapeutic products.

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This work was supported by the March of Dimes European Preterm Birth Research Centre Funding and by the National Institute for Health Research Comprehensive Biomedical Research Centre at Imperial College Healthcare NHS Trust and Imperial College London. The views expressed are those of the authors and not necessarily those of Imperial College, the NHS, the NIHR, the Department of Health or the March of Dimes.

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Bayar, E., Bennett, P.R., Chan, D. et al. The pregnancy microbiome and preterm birth. Semin Immunopathol 42 , 487–499 (2020). https://doi.org/10.1007/s00281-020-00817-w

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Research Article

Effect of maternal age on the risk of preterm birth: A large cohort study

Roles Investigation, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Division of Obstetric Medicine, Department of Obstetrics and Gynecology CHU Sainte Justine, Montréal, Québec, Canada, Inserm, CESP Centre for research in Epidemiology and Population Health, U1018, Reproduction and child development, Villejuif, France, Department of Obstetrics and Gynecology CHU Montpellier, 371 Avenue du Doyen Gaston Giraud, Montpellier, France

Roles Investigation, Writing – original draft

Affiliation Division of Obstetric Medicine, Department of Obstetrics and Gynecology CHU Sainte Justine, Montréal, Québec, Canada

Roles Formal analysis, Software

Affiliation CHU Sainte-Justine Research Center, Université de Montréal, Montréal, Québec, Canada

Roles Investigation, Supervision, Validation

Affiliation Clinical Research Center Étienne-Le Bel, CHU Sherbrooke, Sherbrooke, Québec, Canada

Roles Supervision, Validation, Writing – original draft, Writing – review & editing

• Florent Fuchs, 
• Barbara Monet, 
• Thierry Ducruet, 
• Nils Chaillet, 
• Francois Audibert

• Published: January 31, 2018
• https://doi.org/10.1371/journal.pone.0191002
• Reader Comments

Maternal age at pregnancy is increasing worldwide as well as preterm birth. However, the association between prematurity and advanced maternal age remains controversial.

To evaluate the impact of maternal age on the occurrence of preterm birth after controlling for multiple known confounders in a large birth cohort.

Study design

Retrospective cohort study using data from the QUARISMA study, a large Canadian randomized controlled trial, which collected data from 184,000 births in 32 hospitals. Inclusion criteria were maternal age over 20 years. Exclusion criteria were multiple pregnancy, fetal malformation and intra-uterine fetal death. Five maternal age categories were defined and compared for maternal characteristics, gestational and obstetric complications, and risk factors for prematurity. Risk factors for preterm birth <37 weeks, either spontaneous or iatrogenic, were evaluated for different age groups using multivariate logistic regression.

165,282 births were included in the study. Chronic hypertension, assisted reproduction techniques, pre-gestational diabetes, invasive procedure in pregnancy, gestational diabetes and placenta praevia were linearly associated with increasing maternal age whereas hypertensive disorders of pregnancy followed a “U” shaped distribution according to maternal age. Crude rates of preterm birth before 37 weeks followed a “U” shaped curve with a nadir at 5.7% for the group of 30–34 years. In multivariate analysis, the adjusted odds ratio (aOR) of prematurity stratified by age group followed a “U” shaped distribution with an aOR of 1.08 (95%CI; 1.01–1.15) for 20–24 years, and 1.20 (95% CI; 1.06–1.36) for 40 years and older. Confounders found to have the greatest impact were placenta praevia, hypertensive complications, and maternal medical history.

Even after adjustment for confounders, advanced maternal age (40 years and over) was associated with preterm birth. A maternal age of 30–34 years was associated with the lowest risk of prematurity.

Citation: Fuchs F, Monet B, Ducruet T, Chaillet N, Audibert F (2018) Effect of maternal age on the risk of preterm birth: A large cohort study. PLoS ONE 13(1): e0191002. https://doi.org/10.1371/journal.pone.0191002

Editor: Julie Gutman, Centers for Disease Control and Prevention, UNITED STATES

Received: May 25, 2017; Accepted: December 18, 2017; Published: January 31, 2018

Copyright: © 2018 Fuchs et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data underlying this study are restricted by the Research Ethics Board of CHU Sainte-Justine in order to protect participant privacy. Data are available from the IRB of CHU Sainte Justine [email protected] for researchers who meet the criteria for access to confidential data.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

During the last decades, a gradual increase of maternal age has been observed worldwide. In the United States, between 1970 and 2006, the proportion of pregnant women aged over 35 years has increased almost eight times [ 1 ] and therefore researchers have been interested in outcomes of pregnancy in women of advanced age [ 2 – 5 ]. Pregnancy complications such as placenta praevia, intra-uterine growth restriction or fetal demise, gestational diabetes, hypertensive disorders of pregnancy, and caesarean delivery are well known to be more common in older pregnant women [ 6 – 10 ]. Therefore, guidelines have emerged, both in North America and Europe, for the management of pregnancy in patient with advanced maternal age [ 11 – 13 ].

Preterm birth is the most important factor determining neonatal morbidity and mortality, and has a major impact on it. However, in literature, the association between prematurity and advanced maternal age remains controversial. A study on more than 80,000 women revealed that 36% of the increase in prematurity, between 1990 and 1996 in Canada, was attributable to the change towards increasing maternal age [ 10 ]. Various studies have tried to study the specific influence of advanced maternal age after adjustment for hypertensive disorders of pregnancy, maternal medical history or assisted reproduction technologies [ 9 , 14 , 15 ], but the evidence is still conflicting. Thus, as outlined in a systematic review, further research is needed to determine if advanced maternal age is an independent factor for prematurity[ 16 ].

The aim of this study was to evaluate the relationship between advanced maternal age and prematurity (both spontaneous and iatrogenic) after controlling for multiple confounders.

Materials and methods

This is a retrospective cohort study using data obtained from the QUARISMA randomized controlled trial [ 17 ]. QUARISMA was a cluster intervention trial designed to assess the effectiveness of a complex intervention with background information and audits targeting a general population in terms of safe and sustainable reduction in the rate of caesarean sections. The intervention targeted physicians and nurses, involved audits of indications for cesarean delivery, provision of feedback to health professionals, and implementation of best practices. It took place in 32 hospitals in the province of Quebec, Canada, from 2008 to 2011 and enabled to collect information on more than 184 000 pregnancies. Trained staff collected information on standardized individual records. In this trial, hospitals were the units of randomization and women were the units of analysis. By designating hospitals as the units of randomization (clusters), the study ensured that all women within a given maternity unit were assigned to the same trial group, thereby reducing the risk of contamination of the intervention effect. Ethics approval was obtained by the Ethics research board of CHU Sainte-Justine (Montreal) under the Study Number 2604, for the completion of the trial, for the creation of the database and for the present study.

Inclusion criteria were those of the QUARISMA trial: birth at or after 24 gestational weeks of a fetus weighing >500 grams; and maternal age >20 years. Non-inclusion criteria were multiple pregnancies, fetal malformations and intra-uterine fetal demise.

Five maternal age categories were defined: 20–24, 25–29, 30–34, 35–39 and 40 years and older. Groups of age were compared based on maternal history: past drug use, nulliparity, and medical history including chronic hypertension, diabetes mellitus, renal and cardiac disease, thrombophilia, systemic erythematous lupus and inflammatory bowel disease. Characteristics of the current pregnancy were also studied: drug use, smoking, use of assisted reproductive technologies, and occurrence of an invasive procedure (chorionic villus sampling or amniocentesis). Additionally, groups of age were also compared according to maternal and obstetrical complications: hypertensive complications (gestational hypertension, pre-eclampsia and eclampsia), gestational diabetes and placenta praevia. All comparisons used chi-square test.

The odds ratios for preterm birth (<37 weeks) and very preterm birth (< 32 weeks) were calculated for different age groups before and after adjustment by multivariate logistic regression for known risk factors, maternal characteristics and gestational complications. For these analyses, the reference group corresponded to the group with the lowest rate of prematurity. As our analyses did not focus on the intervention of the primary trial (caesarean section) and since this intervention did not condition the relationship between the explanatory variables and the outcome studied in our paper; we did not performed mixed model analyses accounting for cluster (hospitals).

Preterm birth <37 weeks was divided into spontaneous and iatrogenic preterm birth. For both conditions, risk factors were studied using multivariate logistic analyses after adjustment on covariates. Iatrogenic delivery was defined as performance of a cesarean delivery before onset of labor or induction of labor using cervical ripening or oxytocin.

Results were considered significant when p<0.05. All statistical analyses were performed with the use of SAS software, version 9.3 (SAS Institute)

QUARISMA trial reported the outcome of 184,952 deliveries. After exclusions, a total of 165,195 births were finally included in the study and distributed as follows: 24 650 aged 20–24 years; 59 124 aged 25–29 years; 55 867 aged 30–34 years; 21 416 aged 35–39 years; 4138 aged 40 years or more ( Fig 1 ).

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https://doi.org/10.1371/journal.pone.0191002.g001

Comparison of excluded (19,757) and included (165,195) births did not show any discrepancy regarding maternal distribution of age or maternal characteristics. Risk factors for prematurity by age category are presented in Table 1 . Compared to the 30–34 years old group, the rate of chronic hypertension almost tripled in the >40 years group (4.1% versus 1.4%) and the rate of gestational diabetes more than doubled (19.4% versus 8.7%). The rates of pre-existing diabetes, assisted reproductive technologies, invasive procedure, placenta praevia and obesity also increased with maternal age. The prevalence of hypertensive disorders were higher among extreme of ages: the rates of gestational hypertension were lowest in patients aged 30 to 34 years, and the rates of preeclampsia were lowest in patients aged 25 to 34 years.

https://doi.org/10.1371/journal.pone.0191002.t001

Rates of preterm birth <37 weeks and very preterm birth <32 weeks were lowest in the 30–34 years old group (5.7% and 0.6% respectively) and highest in women over 40 years (7.8% and 1.0% respectively) ( Table 2 and Fig 2 ). Crude and adjusted odds ratios (ORs, aORs) for preterm birth, very preterm birth, iatrogenic and spontaneous preterm delivery before 37 weeks, are presented in Table 2 . For mothers younger than 24 years and older than 35 years, preterm birth was significantly more frequent compared to the reference group (30–34 years). There was a trend towards increased risk in women aged 25–29 years. ORs for preterm birth, extreme preterm birth, and spontaneous preterm birth in the group of 40 years or more were respectively 1.39 (95% CI 1.24–1.57), 1.68 (95% CI 1.21–1.31) and 1.20 (1.04–1.39). Iatrogenic prematurity was almost twice as common in this group (OR 1.91 (95% CI 1.56–2.34)).

https://doi.org/10.1371/journal.pone.0191002.g002

https://doi.org/10.1371/journal.pone.0191002.t002

After adjustment for potential confounders, advanced maternal age (40 years and over), compared to the reference group (30–34 years), was associated with preterm birth <37 weeks and iatrogenic preterm birth (aOR 1.20 (95% CI 1.06–1.36) and aOR 1.31 (95% CI 1.05–1.64) respectively). Age 35–39 years was also associated with iatrogenic prematurity (aOR 1.15 (1.01–1.31)). Younger women (20–24 years) had an increased risk of preterm birth (aOR 1.08 (95% CI 1.01–1.15) and spontaneous preterm birth (aOR 1.09 (95% CI 1.02–1.18). Detailed results of the multivariate analysis are presented in Table 3 . Placenta praevia and hypertensive disorders were associated with the highest risk for preterm birth <37 weeks, due to the increase risk in iatrogenic preterm birth<37 weeks.

https://doi.org/10.1371/journal.pone.0191002.t003

We found that advanced maternal age (40 years and over) was associated with an increased risk of preterm birth even after adjustment for confounders. The lowest risk of prematurity was found in mothers aged 30–34 years. Preterm birth was mainly spontaneous in younger women (20–24 years) whereas it was more frequently of iatrogenic origin in women over 40.

Our results are in accordance with those of two recently published cohort studies. Lawlor et al, in a population of Danish women, found a U shaped relationship between maternal age and risk of preterm birth, with the lowest risk age at 24–30 years [ 18 ]. A more recent nationwide register-based cohort study in Finland found that the threshold-ages for preterm birth was 28 years (OR 1.10, 1.02–1.19) [ 5 ]. However the authors used different inclusion criteria and they did not stratify their results according to the onset of preterm birth (spontaneous or iatrogenic)

Confounders identified in our study are known risk factors for prematurity. Placenta praevia, gestational diabetes, medical history, use of assisted reproduction technologies and occurrence of an invasive procedure were all more common in aged mothers. On the other hand, nulliparity, past drug use and smoking were more prevalent in younger mothers. Furthermore, the prevalence of hypertensive disorders was lowest in middle-aged groups. This distribution of risks factors probably accounts for the “U” shaped distribution of preterm birth risk among age groups. Past research has already shown that younger mothers tend to have higher prematurity rates, but the persistence of this effect until 30 years old has rarely been identified [ 19 ]. In contrast, some studies have found a higher risk of preterm birth risk among women of the age group 30–34 years [ 3 , 5 , 20 – 22 ]. This difference could be explained by variations in socio-demographic or clinical risk factors across different studies.

A common hypothesis is that the increased risk of preterm birth among aged mothers is largely explained by early labor induction for medical conditions. However, our analysis of iatrogenic versus spontaneous prematurity rates among aged mothers does not confirm this hypothesis. Khalil et al. found opposite results in a recent cohort study [ 23 ]. This discrepancy could be due to a different definition of iatrogenic preterm birth. In our study, the variable “iatrogenic preterm birth” was generated using a combination of other variables describing the method of induction of labor. Such data are exposed to classification bias by data abstractors, and some preterm births could have been misclassified. For example, preterm births by caesarean section secondary to preterm premature rupture of membranes could have been misclassified as iatrogenic because of an “elective caesarean section” at 34 or 36 weeks. Iatrogenic preterm births could have been misclassified as spontaneous if oxytocin induction was confounded with oxytocin augmentation. Nevertheless, in light of our results, we cannot rule out that advanced maternal age is independently associated with spontaneous prematurity, as McIntyre et al. concluded in a population based cohort study [ 20 ]. Regarding younger women (20–24 years), we confirmed that preterm birth was mainly spontaneous rather than iatrogenic. As most women delay their first pregnancy at a later age, women who still become pregnant at a young age mainly correspond to low socioeconomic status women with higher risk of medical complication of pregnancy. Even if this study controlled a large number of variables, we could not adjust on educational level or social insurance as this was not reported in the initial study.

The principal strength of this study is the size of the cohort with more than 165 000 patients studied. Furthermore, the sampling represents a broad spectrum of patients, including patients from rural and urban communities across a Canadian province. This prospective cohort nested in a large and well-designed randomized controlled trial allowed controlling for a large number of variables, with a standardized data collection and a strict quality control. Hence, the confounding effect of data such as the use of assisted reproductive technologies and occurrence of an invasive procedure has rarely been studied. Yet these factors are important, with aORs for extreme prematurity of 1.58 (95% IC 1.06–2.33) and 1.67 (95% IC 1.29–2.16).

This study has some limitations. Some potential confounders could not be studied. BMI information was missing in 28% of patients, therefore, it was not used in multivariate analysis. In the population studied, obesity was more common in advanced maternal age mothers. Previous research has shown that excess weight is associated with overall prematurity before 32 weeks and induced prematurity before 37 weeks [ 24 ]. Thus, controlling for BMI could have yielded different results. Moreover, socio-economic data were not available in the database we used. However, a previous study has shown that in older mothers, the association between maternal age and preterm birth was not explained by a confounding effect of socio-economic status[ 18 ]. Another limitation of the study is that we could not adjust for history of preterm delivery. Even though this variable was reported in the database, it was excluded from the final analysis, due to misclassification and lack of reliability after quality control. However, it is unlikely that previous preterm delivery would be more frequent in older women, thus reducing the risk of a confounding effect of previous preterm delivery.

In conclusion, this study based on a large birth cohort was able to demonstrate that even after adjustment for many potential confounders known to be associated with preterm birth, advanced maternal age was independently associated with preterm delivery. Women of 30–34 years had the lowest risk of preterm delivery.

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The vaginal microbiome and the risk of preterm birth: a systematic review and network meta-analysis

Affiliations.

• 1 Department of Microbiology, Tumor and Cell Biology (MTC), Centre for Translational Microbiome Research, Karolinska Institutet, Tomtebodavägen 16, 171 65, SolnaStockholm, Sweden. [email protected].
• 2 Department of Microbiology, Tumor and Cell Biology (MTC), Centre for Translational Microbiome Research, Karolinska Institutet, Tomtebodavägen 16, 171 65, SolnaStockholm, Sweden.
• 3 Science for Life Laboratory, 171 65, Solna, Sweden.
• 4 Sach's Children's and Youth Hospital, Södersjukhuset, Stockholm, Sweden.
• 5 Department of Women's and Children's Health, Uppsala University, 751 85, Uppsala, Sweden.
• 6 Global Health Institute, University of Antwerp, 2610, Antwerp, Belgium.
• 7 Department of Head and Skin, Ghent University, 9000, Ghent, Belgium.
• PMID: 35562576
• PMCID: PMC9106729
• DOI: 10.1038/s41598-022-12007-9

Preterm birth is a major cause of neonatal morbidity and mortality worldwide. Increasing evidence links the vaginal microbiome to the risk of spontaneous preterm labour that leads to preterm birth. The aim of this systematic review and network meta-analysis was to investigate the association between the vaginal microbiome, defined as community state types (CSTs, i.e. dominance of specific lactobacilli spp, or not (low-lactobacilli)), and the risk of preterm birth. Systematic review using PubMed, Web of Science, Embase and Cochrane library was performed. Longitudinal studies using culture-independent methods categorizing the vaginal microbiome in at least three different CSTs to assess the risk of preterm birth were included. A (network) meta-analysis was conducted, presenting pooled odds ratios (OR) and 95% confidence intervals (CI); and weighted proportions and 95% CI. All 17 studies were published between 2014 and 2021 and included 38-539 pregnancies and 8-107 preterm births. Women presenting with "low-lactobacilli" vaginal microbiome were at increased risk (OR 1.69, 95% CI 1.15-2.49) for delivering preterm compared to Lactobacillus crispatus dominant women. Our network meta-analysis supports the microbiome being predictive of preterm birth, where low abundance of lactobacilli is associated with the highest risk, and L. crispatus dominance the lowest.

© 2022. The Author(s).

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Conflict of interest statement

The authors declare no competing interests.

PRISMA flowchart of selection of…

PRISMA flowchart of selection of articles included in the network meta-analysis.

Forest plots showing all 17…

Forest plots showing all 17 included studies and the pooled and weighted proportion…

Network map of all 17…

Network map of all 17 included studies by vaginal microbiome composition, showing how…

Forest plots comparing community state…

Forest plots comparing community state types (CSTs) and their risk of preterm birth…

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Preterm births and associated factors among mothers who gave birth in Axum and Adwa Town public hospitals, Northern Ethiopia, 2018

Gebrekiros aregawi.

1 Department of Midwifery, College of Medicine and Health Science, Aksum University, Aksum, Ethiopia

Nega Assefa

2 School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, P. O. Box 235, Harar, Ethiopia

Firehiwot Mesfin

Fissaha tekulu.

3 Department of Midwifery, College of Medicine and Health Sciences, Arba Minch University, Arba Minch, Ethiopia

Tesfay Adhena

4 Department of Midwifery, College of Health Science, Aksum University, Aksum, Ethiopia

Mussie Mulugeta

Guesh gebreayezgi.

5 Department of Public Health, College of Health Science, Aksum University, Aksum, Ethiopia

Associated Data

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request due to ethical restriction and privacy.

The objective of this study was to determine the prevalence and associated factors of preterm births among mothers who gave birth in Axum and Adwa public hospitals, Tigray, North Ethiopia, 2018.

This study showed that 13.3% from the total 472 mothers gave a preterm birth. Being a rural resident (AOR = 2.13, 95% CI (1.07,4.22), short inter pregnancy interval (AOR = 5.4, 95% CI (1.32, 22.05), previous preterm birth (AOR = 3.74, 95% CI (1.03, 16.34), Premature rupture of membrane (AOR = 4.14, 95% CI (1.92, 8.89), induced onset of labor (AOR = 2.49, 95% CI (1.06, 5.85) multiple pregnancy (AOR = 5.69, 95% CI (2.27, 14.28), malaria during pregnancy (AOR = 4.71, 95% CI (1.98, 11.23), Presence of chronic illness (AOR = 4.55, 95% CI (1.83, 11.26) were significantly associated with preterm birth.

Introduction

Preterm birth (PTB) refers to the birth of a baby that occurs before 37 completed weeks of gestation [ 1 ]. The complications of preterm birth are the single largest direct cause of neonatal deaths, responsible for 35% of the world’s 3.1 million deaths a year [ 2 ].

Preterm birth has many long and short term consequences like cerebral palsy, mental retardation, visual and hearing impairments, learning difficulties, poor health and growth [ 3 , 4 ].

Globally WHO estimates of global rates of preterm births indicate that of the 135 million live births in 2010, 15 million babies were born too early, representing a preterm birth rate of 11.1% and over 60% of preterm births occurred in sub-Saharan Africa and South Asia [ 5 ].

About 350,000 under five children die annually due to the complication of preterm birth in Africa including Ethiopia. And the highest rates of preterm morality are in West Africa, particularly in the countries currently being decimated by Ebola, notably Sierra Leone and Liberia [ 6 ].

In the previous studies, previous history of preterm birth was the strongest predictor of risk for subsequent preterm delivery and if these risk factors are not correctly identified and adequately managed, they contribute to the increasing incidence of preterm births. So, Identification and timely referral for further evaluation and management of these risky women during early pregnancy, is important in decreasing the consequences of preterm birth [ 7 ].

Developing countries like Ethiopia lacks reliable data on preterm birth depending largely on estimates from delivery records but the records lack consistency and completeness. Despite tremendous improvement in newborn care, prevention of preterm birth has remained largely unaddressed. Therefore, this study has gone a long way in providing relevant data regarding the factors associated with preterm birth among women gave birth in Axum and Adwa Town public hospitals.

Study design and setting

Institutional based cross-sectional study was conducted in Axum and Adwa town public hospitals from February 08-March 08, 2017. There are four health centers, two general hospitals and one referral hospital in Axum and Adwa town and all are governmental hospitals.

Sample size and Sampling procedure

The sample size was determined using single population proportion formula by considering confidence level (95%), margin of error = 0.04 and 11.6% of prevalence taken from the study done in Debre Markos [ 8 ]. By adding 10% non-response rate, the final sample size was 482. Mothers who gave birth in Axum and Adwa town public hospitals with known LNMP or had ultrasound result during the first trimester of pregnancy were included. Sample sizes were proportionally allocated to each hospital. By using Systematic random sampling method every second mother was recruited into the study.

Data collection tools and techniques

Face-to-face interviewer administered questionnaires and mother’s profile card was used to collect the data from postpartum mothers and gestational age was determined by last normal menstrual period and by early ultrasound check up result.

Data quality control

Questionnaire was pretested on 5% of the sample size in suhul shire hospital to ensure its completeness. Data entry was done by two data clerks. Finally, multivariate analysis was run in the binary logistic regression model to control the confounding factors.

Data processing and analysis

Data was entered in Epi Data 3.1 and exported into SPSS version 22 for analysis. Both bivariable and multivariable logistic regression analysis were carried out to identify factors associated with preterm birth. In bivariate logistic regression analysis, variables with p value less than 20% were considered into the multivariable analysis. Adjusted odds ratio with a 95% confidence interval was calculated to see the strength and significant association. Variables having a p-value less than 0.05 in the multivariable logistic regression analysis were considered as significant.

Socio-demographic characteristics of the respondents

A total of 472 mothers were included in this study with a response rate of 97.9%. The median age of the study participants was 26.00 with interquartile range of ± 8. 75.6% of the study participants were between 20 and 34 years old. Concerning to maternal level of education status of the respondents, 72.8% of the mothers were attended a formal education (Table  1 ).

Table 1

Socio-demographic characteristics of women who give birth in Axum and Adwa town public hospitals, Tigray, Northern Ethiopia, February 08–March 08, 2018

Asterisk represent the list of other ethinicities like Oromo, Wolayta, Guragge other than Tigray and Amara

Obstetrics related information of the mothers

Out of 472 mothers, 264 (55.9%) of them were multipara and the rest 208 (44.1%) mothers were prim Para. Regarding the mode of delivery for recent pregnancy, 367 (77.8%) out of 472 mothers were gave birth via spontaneous vaginal delivery. the rest 32 (6.8%) and 73 (15.5%) of mothers gave birth via assistance of instrumental and caesarean section, respectively (Table  2 ).

Table 2

Obstetrics related information of mothers who gave birth in Axum and Adwa town public hospitals, Tigray, North Ethiopia, and February 08–March 08, 2018

Health care service use characteristics

From 472 mothers, 452 (95.8%) had ANC follow up for the recent pregnancy. Among these mothers who had ANC follow up about 325 (71.9%) of interviewed mothers had four or more visits.

Medical related information of the mothers

Out of 472 interviewed mothers, 461 (97.7%) were tested for HIV and 449 (97.4%) of them were negative. Concerning to the mothers haemoglobin level check-up, 462 (97.9%) of them were checked for their haemoglobin level (Additional file 1 : Table S1).

Prevalence of preterm birth

Out of 472 mothers, 63 (13.3%) mothers gave preterm babies. These preterm babies were diagnosed by calculating the gestational age from the last normal menstrual period/using early ultrasound result.

Factors associated with preterm births

In this study, Mothers who were living in rural area were two times more likely [(AOR = 2.1 (1.05, 4.12)] to have preterm birth compared to those who live in urban area. Concerning to inter pregnancy interval, mothers with inter pregnancy interval less than 24 months four [(AOR = 4.24, 95% CI (1.15, 16.26)] times were more likely to give preterm births compared to mothers who had inter pregnancy interval greater. Regarding the previous history of preterm birth, mothers who had history of preterm births were four [(AOR = 3.74, 95% CI (1.03, 16.34)] times more likely to give preterm birth compared to mothers who had no previous preterm births.

Coming to the obstetric complications during the pregnancy like PROM, mothers who encountered PROM [(AOR = 3.76 (1.73, 8.19)] during the pregnancy were almost four times more likely to have preterm birth compared to mothers who had no PROM. Mothers with multiple pregnancy outcomes [(AOR = 5.59 (2.17, 14.40)] were six times more likely to have preterm birth compared with mothers who gave birth singleton.

Concerning to the medical factors, mothers who had exposed for malaria during pregnancy [(AOR = 5.43 (2.19, 13.38)] and chronic medical disorders [(AOR = 6.79 (2.83, 16.26)] were seven times more likely to have preterm births than the counterpart (Additional file 2 : Table S2).

In this study, the prevalence of preterm births in this study was found to be 13.3%.

The result of this study was consistent with the study done in Debre Markos (2013) and India (2010) which reported with the prevalence of 11.6% and 15% [ 8 , 9 ]. This similarity might be due to health care system in our country and service provided for mothers are almost uniform through out the different area of the country.

The finding of this study was higher than the study conducted in Gondar (2012), Iran Asali Hospital (2007) and Egypt (2014) which reported that the prevalence of preterm birth was 4.4% 6.3% and 8.2% [ 10 – 12 ], respectively. This discrepancy might be due to difference in inclusion and exclusion criteria, study areas and due to difference in health care services provided.

The finding of this study was found to be lower than studies conducted in Nigeria (2010) with the prevalence rate of 24% [ 13 ]. This might be due to the higher rate of multiple gestations in Nigeria, as this cause over distended uterus and can precipitate to preterm birth and multiple gestations is a known predisposing factor for preterm birth.

The finding in this study was also lower than the study done in Kenya (2013), Brazil (2009) and India (2010) which reported that the prevalence were 18.3% and 21.7% [ 14 , 15 ]. These discrepancies might be due to difference in study areas, methodological differences.

This study showed that residence was associated significantly with preterm birth. This finding was in line with the study done in Bahirdar [ 16 ]. This might be due low access of maternal care services and awareness differences of the mothers in the rural area with mother found in the urban area.

Short inter pregnancy (< 24 months) was significantly associated with preterm birth. This finding was in consistence with the study conducted in Debre Markos since 2013 [ 8 ]. This is a risk factor for preterm birth and it might be due to existence of unidentified factors which precipitating preterm births in mothers with short inter pregnancy interval.

Previous preterm birth was another factor significantly associated with preterm birth found in this study. Mothers who had previous history of preterm births seven times were more likely to have preterm births compared to mothers who had no previous history of preterm births in the subsequent deliveries. This finding was in consistence with the secondary data analysis report of Malawi (2014): [ 17 ]. The possible reason might be due to existence of unidentified factors which precipitating preterm births in the subsequent deliveries.

According to this study, mothers who had premature rupture of membranes (PROM) during pregnancy were four times more likely to have preterm birth compared to those had no premature rupture of membrane. This finding was in consistence with findings of cross sectional studies conducted in Debre Markos (2013) and Kenya (2013) [ 8 , 15 ]. This may be due to the fact that PROM elevated fetal plasma interleukin-6 indicating that this fetal response may trigger preterm labor correlated strongly with spontaneous delivery [ 18 ].

Multiple gestations were significantly associated with preterm birth in this study. Mothers with multiple pregnancies were almost six times more likely to have preterm birth compared with mothers who gave birth singleton This finding was in line with the finding of study done in Kenya (2013) [ 15 ]. This might be due to multiple gestation is associated with uterine over distension and this may result in spontaneous preterm labour and also Multiple pregnancies can stretch the myometrium; this induces the oxytocin receptors, which results in preterm labor and delivery [ 19 ].

Chronic medical illnesses are significant variable associated with Preterm birth. Mothers with chronic medical disorders were almost seven times more likely to have preterm births compared to mothers who had not chronic medical disorders. This finding was in consistence with cross sectional study conducted in Debre Markos (2013) [ 8 ]. This might be might be due to maternal illnesses can limit or minimize the placental delivery of oxygen and nutrients to the developing fetus in the uterus possibly increase the risk of preeclampsia and, thus, increases the risk preterm birth [ 20 ].

Besides to this, mothers who had malaria during their pregnancy were more and mothers who had exposed for malaria during pregnancy were five times were more likely to have preterm births than mothers who had not exposed to malaria during the pregnancy. This result was in line with the study done in Iran (2011–2013) [ 21 ]. This might be due to malaria affects placenta and contributes to maternal anaemia and placental parasitemia which leads to preterm labor which in turn result preterm birth [ 22 ].

Residence, short inter pregnancy, previous history of preterm birth, PROM, induced onset of labor, multiple gestation, Presence of chronic medical illness, being exposed for malaria during the pregnancy were statistically significant with preterm birth. Therefore, efforts have to be made to decrease the magnitude of preterm births and further improvements of antenatal care as well as early screening are important recommendations.

Limitation of the study

Being a cross-sectional study design attempt to our work did not establish the possible temporal relationship between dependent and independent variables. Besides, recall bias in finding out the gestational age of pregnant women was not ruled out.

Supplementary information

Acknowledgements.

Our gratitude goes to the staffs of Aksum saint Mary hospital, Aksum university referral hospital and Adwa hospital, data collectors, supervisors, study participants, and questionnaire translators into the local languages.

Abbreviations

Authors’ contributions

GA initiated the research, wrote the research proposal, conducted the research, did data entry and analysis, and wrote the research and manuscript. NA, FM, FT, TA, MM and GG involved in the write up of the proposal, data analysis, interpretation, and manuscript writing. All authors read and approved the final manuscript.

The study was funded by the Ethiopian Ministry of Education and Aksum University that do not involved in the study design, data collection, analysis and interpretation.

Availability of data and materials

Ethics approval and consent to participate.

Ethical clearance was secured by Haramaya University Institutional Health Research Ethics Review Committee (IHRERC) and official permission was obtained from Aksum and Adwa Town Health Offices and respected health institutions. Informed written consent was also obtained from each participant after the purpose of the study and confidentiality issues were clearly explained.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Gebrekiros Aregawi, Email: moc.liamg@iwagerakg .

Nega Assefa, Email: moc.oohay@afessaagen .

Firehiwot Mesfin, Email: moc.liamg@mtowiherifm .

Fissaha Tekulu, Email: moc.liamg@0807uluketahassif .

Tesfay Adhena, Email: moc.liamg@asetosset .

Mussie Mulugeta, Email: moc.liamg@ategulumeissum .

Guesh Gebreayezgi, Email: moc.liamg@069iwamug .

Supplementary information accompanies this paper at 10.1186/s13104-019-4650-0.