Interconception care for women with a history of gestational diabetes for improving maternal and infant outcomes

  • Review
  • Intervention

Authors

  • Joanna Tieu,

    Corresponding author
    1. The University of Adelaide, ARCH: Australian Research Centre for Health of Women and Babies, The Robinson Institute, Discipline of Obstetrics and Gynaecology, Adelaide, South Australia, Australia
    • Joanna Tieu, ARCH: Australian Research Centre for Health of Women and Babies, The Robinson Institute, Discipline of Obstetrics and Gynaecology, The University of Adelaide, Women's and Children's Hospital, 1st floor, Queen Victoria Building, 72 King William Road, Adelaide, South Australia, 5006, Australia. joanna.tieu@gmail.com. joanna.tieu@mh.org.au.

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  • Emily Bain,

    1. The University of Adelaide, ARCH: Australian Research Centre for Health of Women and Babies, The Robinson Institute, Discipline of Obstetrics and Gynaecology, Adelaide, South Australia, Australia
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  • Philippa Middleton,

    1. The University of Adelaide, ARCH: Australian Research Centre for Health of Women and Babies, The Robinson Institute, Discipline of Obstetrics and Gynaecology, Adelaide, South Australia, Australia
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  • Caroline A Crowther

    1. The University of Adelaide, ARCH: Australian Research Centre for Health of Women and Babies, The Robinson Institute, Discipline of Obstetrics and Gynaecology, Adelaide, South Australia, Australia
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Abstract

Background

Gestational diabetes mellitus (GDM) is associated with adverse health outcomes for both mother and infant both perinatally and long-term. Women with a history of GDM are at risk of recurrence in subsequent pregnancies and may benefit from intervention in the interconception period to improve maternal and infant health outcomes.

Objectives

To investigate the effects of interconception care for women with a history of GDM on maternal and infant health outcomes.

Search methods

We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (31 January 2013).

Selection criteria

Randomised controlled trials, including quasi-randomised controlled trials and cluster-randomised trials evaluating any protocol of interconception care with standard care or other forms of interconception care for women with a history of GDM in a previous pregnancy on maternal and infant health outcomes.

Data collection and analysis

Two review authors independently assessed study eligibility. In future updates of this review, at least two review authors will extract data and assess the risk of bias of included studies.

Main results

One ongoing trial was identified. No eligible completed trials were identified.

Authors' conclusions

The role of interconception care for women with a history of gestational diabetes remains unclear. Randomised controlled trials are required evaluating different forms and protocols of interconception care for these women on perinatal and long-term maternal and infant health outcomes, acceptability of such interventions and cost-effectiveness.

Résumé scientifique

Soins d'interconception pour les femmes ayant des antécédents de diabète gestationnel pour améliorer les critères d'évaluation pour la mère et le nourrisson

Contexte

Le diabète sucré gestationnel (DSG) est associé à des risques pour la santé aussi bien pour la mère que pour le nourrisson tant dans la période périnatale qu'à long terme. Les femmes ayant des antécédents de DSG présentent un risque de récidive lors des grossesses suivantes et peuvent tirer un bénéfice d'une intervention au cours de la période d'interconception pour améliorer leur santé et celle des nourrissons.

Objectifs

Etudier les effets des soins d'interconception pour les femmes ayant des antécédents de DSG sur leur santé et celle des nourrissons.

Stratégie de recherche documentaire

Nous avons effectué des recherches dans le registre d'essais du groupe Cochrane sur la grossesse et la naissance (31 janvier 2013).

Critères de sélection

Les essais contrôlés randomisés, y compris les essais contrôlés quasi-randomisés et les essais randomisés en cluster, évaluant l'effet d'un protocole de soins d'interconception avec des soins standard ou d'autres formes de soins d'interconception pour les femmes ayant des antécédents de DSG lors d'une grossesse précédente sur leur santé et celles des nourrissons.

Recueil et analyse des données

Deux auteurs de la revue ont évalué, de façon indépendante, l'éligibilité des études. Dans les futures mises à jour de cette étude, au moins deux auteurs de la revue procèderont à l'extraction des données et évalueront le risque de biais des études incluses.

Résultats principaux

Un essai en cours a été identifié. Aucun essai complet éligible n'a été identifié.

Conclusions des auteurs

Le rôle des soins d'interconception pour les femmes ayant des antécédents de diabète gestationnel demeure incertain. Il faut réaliser des essais contrôlés randomisés évaluant l'effet de différentes formes et de différents protocoles de soins d'interconception pour ces femmes sur leur santé et celle des nourrissons dans la période périnatale et à long terme, l'acceptabilité de ces interventions et leur rapport coût-efficacité.

Plain language summary

Interconception care for women with a history of gestational diabetes for improving maternal and infant outcomes

Gestational diabetes mellitus (GDM) is a condition in which high blood sugar (hyperglycaemia) occurs, or is first recognised, during pregnancy. GDM is associated with complications for the mother and her baby both during and after pregnancy. Women with GDM are at an increased risk of developing pre-eclampsia (high blood pressure and protein in the urine during pregnancy), having a caesarean birth, and developing type 2 diabetes in the future. Babies of women with GDM are at an increased risk of macrosomia (birthweight greater than 4000 g), birth trauma because of their size, respiratory distress syndrome, and other health complications. They are also at risk of future obesity and type 2 diabetes. GDM typically resolves after birth, but women with GDM are at risk of developing GDM again in future pregnancies. It is possible that women may benefit from interventions such as education, dietary and lifestyle advice, or drug treatment in the interconception period (the time between the end of one pregnancy and the beginning of the next one), to improve their health outcomes in future pregnancies.

This review found that there is not yet enough evidence to determine whether interconception (between pregnancy) care for women with a history of GDM can help to improve the health of mothers and their babies. We identified only one trial that is currently ongoing. More high-quality studies are needed, and these studies should evaluate different forms of care for these women, and should assess both short-term and long-term health outcomes for women and their babies.

Résumé simplifié

Soins d'interconception pour les femmes ayant des antécédents de diabète gestationnel pour améliorer les critères d'évaluation pour la mère et le nourrisson

Le diabète sucré gestationnel (DSG) est une maladie au cours de laquelle un taux élevé de sucre (hyperglycémie) apparaît ou est établi pour la première fois pendant la grossesse. Le DSG est associé à des complications pour la mère et son bébé à la fois pendant et après la grossesse. Les femmes souffrant de DSG présentent un risque accru de développer une pré-éclampsie (hypertension artérielle et présence de protéines dans l'urine pendant la grossesse), de subir un accouchement par césarienne et de développer un diabète de type 2 dans le futur. Les bébés nés de femmes atteintes de DSG ont un risque accru de macrosomie (poids de naissance supérieur à 4 000 g), de traumatisme à la naissance en raison de leur taille, de syndrome de détresse respiratoire et d'autres complications. Ils présentent également un risque d'obésité et de diabète de type 2 dans le futur. Le DSG disparaît généralement après l'accouchement, mais les femmes atteintes de DSG ont un risque de nouveau développement d'un DSG lors des grossesses suivantes. Il est possible que les femmes puissent tirer un bénéfice d'interventions telles que l'éducation, les conseils relatifs à l'alimentation et au mode de vie ou le traitement médicamenteux pendant la période d'interconception (le temps entre la fin d'une grossesse et le début de la suivante) pour améliorer leur santé lors des grossesses ultérieures.

Cette revue a découvert qu'il n'existait pas encore suffisamment de preuves pour déterminer si les soins d'interconception (entre les grossesses) pour les femmes ayant des antécédents de DSG pouvaient améliorer la santé des mères et de leurs bébés. Nous n'avons identifié qu'un seul essai qui est actuellement en cours. D'autres études de grande qualité sont nécessaires et ces études doivent évaluer différentes formes de soins pour ces femmes et évaluer à la fois les critères de santé à court et à long terme pour les femmes et leurs bébés.

Notes de traduction

Traduit par: French Cochrane Centre 16th July, 2013
Traduction financée par: Pour la France : Minist�re de la Sant�. Pour le Canada : Instituts de recherche en sant� du Canada, minist�re de la Sant� du Qu�bec, Fonds de recherche de Qu�bec-Sant� et Institut national d'excellence en sant� et en services sociaux.

Background

Description of the condition

Gestational diabetes mellitus (GDM) is defined as 'carbohydrate intolerance resulting in hyperglycaemia of variable severity with onset or first recognition during pregnancy' (WHO 1999). This definition includes women who first present with type 1 or type 2 diabetes during pregnancy, or where diabetes was previously undetected. Although GDM typically resolves following birth, it is associated with adverse outcomes for both mother and child, both in the perinatal period and in the long-term.

In subsequent pregnancies of women with a history of GDM, one of the main issues is recurrence of GDM and the associated outcomes. Irrespective of subsequent pregnancies, other long-term considerations for these women include the development of type 2 diabetes mellitus, metabolic syndrome and the risk of cardiovascular disease.

Epidemiology

The reported incidence of GDM varies between different populations and the method by which the diagnosis is made. Between 1% and 13% of pregnancies are affected by GDM (Hunt 2007). As with type 1 and type 2 diabetes, there is growing concern over the increasing incidence of GDM and its impact on health outcomes and health services (Dabelea 2005; Ferrara 2007; Hunt 2007; Lauenborg 2004; Metzger 2007). In women with a history of GDM, recurrence occurs in 30% to 84% of subsequent pregnancies (Kim 2007).

A number of risk factors have been linked to GDM, including a history of GDM or glucose intolerance, previous macrosomic infant, family history of diabetes, ethnic background (including African, Asian, Hispanic, Aboriginal, Middle Eastern and Polynesian), polycystic ovarian syndrome, increased weight gain in early adulthood, increased maternal age, currently smoking and maternal obesity (CDA 2002; Scott 2002).

Many of these risk factors are unmodifiable background characteristics of the women. It is therefore unsurprising that women with a history of GDM are at an increased risk of recurrent GDM. In addition to a history of GDM in a previous pregnancy, other risk factors for recurrence include ethnicity, maternal age, maternal prepregnancy obesity, weight gain between pregnancies, a short interpregnancy interval and the number of previous pregnancies affected by GDM (Gaudier 1992; Getahun 2010; Kwak 2008; Major 1998). Certain characteristics of the pregnancy affected by GDM have also been reported to increase the risk of recurrence, specifically, earlier diagnosis of GDM, insulin requirement for blood glucose control and higher infant birthweight (Gaudier 1992 ; Kwak 2008; MacNeill 2001; Major 1998).

Screening and diagnosis of gestational diabetes

There is little consensus on the most appropriate methods by which to screen and diagnose GDM. Screening methods include risk factor based screening, random or fasting blood glucose levels and an oral glucose challenge test. Diagnostic testing commonly involves either a 75 g or 100 g oral glucose tolerance test, with various diagnostic cut-offs used. These are addressed in the Cochrane reviews 'Screening and subsequent management for gestational diabetes for improving maternal and infant health' (Tieu 2010a) and 'Different strategies for diagnosing gestational diabetes to improve maternal and infant health (Farrar 2011).

Women with a history of GDM are acknowledged as being at high risk for both recurrent GDM and type 2 diabetes, and it is suggested that women with a history of GDM may require greater monitoring for glucose intolerance during subsequent pregnancies (NICE 2008). It is, however, unclear as to how this should occur.

Clinical features

Maternal

GDM is usually diagnosed before women experience symptoms, such as polyuria, polydipsia or fatigue. GDM is associated with increased rates of caesarean birth and pre-eclampsia (Dodd 2007). As mentioned above, women who develop GDM represent a subset of the population prone to developing subsequent type 2 diabetes mellitus, in addition to recurrent GDM in future pregnancies. Within 10 years of women developing GDM, approximately half develop type 2 diabetes mellitus (Kim 2002). Furthermore, there is increasing evidence that women with a history of GDM may also be at increased risk of cardiovascular disease and metabolic syndrome (Retnakaran 2009; Vohr 2008).

Infant

Excess insulin due to maternal hyperglycaemia acts in two ways on the fetus. Firstly, insulin promotes fat deposition due to the state of nutrient excess (Pedersen 1954Whitelaw 1977). Insulin also acts as a growth factor, stimulating further growth of the infant in utero (Hunt 2007). Thus, fetal hyperinsulinaemia results in excessive growth of the fetus, leading to one of the major perinatal concerns in GDM, macrosomia (birthweight greater than 4000 g). Macrosomia may lead to birth trauma including shoulder dystocia, nerve palsies and fractures (Dodd 2007Metzger 1998). GDM is associated with respiratory distress syndrome, neonatal hypoglycaemia (low blood glucose), hyperbilirubinaemia (high bilirubin levels), polycythaemia (excess red blood cells), and hypocalcaemia (low calcium) (ADA 2003Metzger 1998). In utero exposure to hyperglycaemia has long-lasting effects on the infant, increasing their risk of future obesity and type 2 diabetes mellitus (Dabelea 2000; Lawlor 2011; Patel 2011; Pettitt 1985Silverman 1998).

While there is relatively little reported on the effects of recurrent GDM on infants, infants born to mothers with recurrent GDM are likely to be larger, as measured by birthweight, incidence of large-for-gestational age, or macrosomia compared with infants born to mothers without recurrent GDM in a subsequent pregnancy (Spong 1998).

Management of GDM

The importance of management for women with GDM has been evaluated by several Cochrane reviews (Alwan 2009; Boulvain 2001; Ceysens 2006) and evidence supports treatment of GDM (ADA 2003; Crowther 2005; Hoffman 1998; Landon 2009 ; Metzger 1998; NICE 2008; O'Sullivan 1966). Treatment focuses on reducing the hyperglycaemia that drives the complications of GDM and, in particular, mainly addresses: nutrition therapy, exercise, blood glucose monitoring, and insulin therapy.

Description of the intervention

Interconception care encompasses a variety of interventions, including education, dietary and lifestyle advice, pharmacological intervention and active surveillance for illness and complications. It includes care between the birth of one child to the next pregnancy.

Postpartum assessment for continuing glucose intolerance after six to 12 weeks is generally recommended, either by fasting blood glucose or oral glucose tolerance testing, with follow-up assessment every two to three years. It is further recommended that women are informed regarding future risks and dietary and lifestyle advice (ACOG 2009; CDA 2008; NICE 2008).

While often recommended, there is little evidence on what care women with a history of GDM should receive prior to a subsequent pregnancy. Consensus guidelines recommend that women be assessed preconceptually for a medical review and/or an oral glucose tolerance test, with early evaluation for glucose intolerance during pregnancy (ACOG 2001; Metzger 2007; NICE 2008). In addition to earlier identification and management of diabetes, interconception care after the postpartum period would ideally aim to target the modifiable risk factors for GDM, improving their metabolic profile.

How the intervention might work

In a survey of women with a history of GDM within the last five years, while 90% of those surveyed understood that previous GDM placed women at high risk of type 2 diabetes, only 16% believed that they themselves were at high risk of developing diabetes (Kim 2007). This was partially explained by women planning to improve their behaviour in the future, with the risk perception increasing to 39% if women considered their risk if they continued their current lifestyle. Importantly 85% of these women had plans for risk-reducing behaviour. Another survey comparing women with children and a history of GDM with women with children without a history of GDM, found that those with a history of GDM were more likely to smoke and less likely to meet fruit and vegetable consumption recommendations (Kieffer 2006).

The interconceptional period provides an opportunity to provide advice on potential risks and possible interventions to improve health. Moreover, it provides the opportunity to identify undiagnosed pre-existing diabetes. Since women with a history of GDM are at increased risk of diabetes, and pre-existing diabetes in pregnancy is linked to poor maternal and infant health outcomes, it is important to identify and manage accordingly in the preconceptual period.

Risk factor reduction is a potential area of focus for these women, targeting modifiable risk factors such as maternal obesity where dietary and lifestyle interventions could be implemented and potentially benefit women with a history of GDM. Reducing maternal obesity itself may also lead to better maternal and infant health outcomes outside of its potential effect in the prevention of GDM (Dodd 2011). Regardless of whether women subsequently become pregnant, such interventions would improve the health of these women.

There is little information on the value of pharmacological agents such as oral anti-diabetics for women with a history of GDM in the preconceptual period. The use of oral anti-diabetic agents has been predominantly in the setting of polycystic ovarian syndrome or for prevention of type 2 diabetes in women with a history of GDM (Bottalico 2007; Glueck 2004; Ho 2007). In a trial of women with impaired glucose tolerance and a history of GDM randomised to intensive lifestyle intervention, metformin or placebo, both lifestyle intervention and metformin were found to be effective in delaying or preventing the development of diabetes mellitus (Ratner 2008). This topic will be the focus of the Cochrane review 'Interventions for the prevention of type 2 diabetes in women with previous gestational diabetes' (Wendland 2011).

Why it is important to do this review

Women with a history of GDM are recognised to be at high risk for recurrence in subsequent pregnancies, type 2 diabetes and cardiovascular disease, and therefore, for adverse maternal and infant health outcomes. While management of GDM is worthwhile, interconception care for these women also has the potential to improve maternal and infant health.

Interconception care may also allow for detection and appropriate management of asymptomatic pre-existing diabetes and provide an opportunity for risk factor reduction and, potentially, prevention of recurrent GDM and its sequelae.

Routine interconception care and interconception care for women with known diabetes mellitus are reviewed by the Cochrane reviews 'Routine pre-pregnancy health promotion for improving pregnancy outcomes' (Whitworth 2009) and 'Preconception care for diabetic women for improving maternal and infant health' (Tieu 2010).

Objectives

To investigate the effects of interconception care for women with a history of GDM on maternal and infant health outcomes.

Methods

Criteria for considering studies for this review

Types of studies

Randomised controlled trials (RCTs), including quasi-RCTs and cluster-RCTs. We planned to exclude cross-over trials. We planned to exclude trials presented only as abstracts where information on risk of bias and primary or secondary outcomes cannot be obtained; we plan to reconsider these trials for inclusion once the full publication is available.

Types of participants

Women who have been diagnosed with GDM in a previous pregnancy. Diagnosis of GDM made according to individual study criteria.

Types of interventions

Any protocol of care compared with no care and other forms of interconception care. Interventions may continue during pregnancy.

Types of outcome measures

Primary outcomes
Maternal
  • GDM (as defined by trialists)

  • Mode of birth (normal vaginal birth, operative vaginal birth, caesarean section)

Neonatal
  • Large-for-gestational age

  • Macrosomia

  • Perinatal mortality (stillbirth, neonatal or infant death)

Secondary outcomes
Maternal
  • Pregnancy

  • Positive screening for GDM

  • Glucose intolerance, not GDM by standard diagnostic criteria

  • HbA1c (preconception - before and after intervention commenced, antenatal, postnatal)

  • Blood glucose levels (preconception - before and after intervention commenced, antenatal, postnatal)

  • Fructosamine (preconception - before and after intervention commenced, antenatal, postnatal)

  • Body mass index (BMI) (preconception - before and after intervention commenced, antenatal, postnatal)

  • Weight (preconception - before and after intervention commenced, antenatal, postnatal)

  • Women’s sense of well-being and quality of life (preconception - before and after intervention commenced, antenatal, postnatal)

If pregnant:

  • spontaneous abortion/miscarriage/therapeutic abortion

  • induction of labour or augmentation of labour

  • pre-eclampsia

  • pregnancy-induced hypertension (as defined by trialists)

  • use of anti-hypertensive during pregnancy

  • subsequent type 2 diabetes mellitus development

  • postpartum haemorrhage

  • postnatal depression

If GDM:

  • use of oral anti-diabetic agent/insulin

  • HbA1c (preconception- before and after intervention, antenatal, postnatal)

  • blood glucose levels (preconception - before and after intervention, antenatal, postnatal)

Long-term:

  • HbA1c

  • blood glucose levels

  • BMI

  • subsequent recurrent GDM

  • subsequent type 2 diabetes mellitus

Infant

  • Birthweight

  • Birthweight centile

  • Respiratory distress syndrome

  • Neonatal hypoglycaemia (requiring treatment and/or not requiring treatment)

  • Neonatal hyperbilirubinaemia (requiring and/or not requiring phototherapy)

  • Small-for-gestational age

  • Gestational age at birth

  • Preterm birth

  • Admission to neonatal nursery

  • Length of hospital stay

  • Birth injury (nerve palsy, fracture, intracranial haemorrhage)

  • One-minute Apgar less than seven

  • Five-minute Apgar less than seven

  • Ponderal index

Long-term:

  • development of type 1 diabetes, type 2 diabetes or impaired glucose tolerance

  • obesity

  • BMI

  • anthropometry

Economic:

  • number of hospital visits

  • length of hospital stay

  • extra investigations

  • antenatal tests

  • acceptability of interventions

Search methods for identification of studies

Electronic searches

We contacted the Trials Search Co-ordinator to search the Cochrane Pregnancy and Childbirth Group’s Trials Register (31 January 2013). 

The Cochrane Pregnancy and Childbirth Group’s Trials Register is maintained by the Trials Search Co-ordinator and contains trials identified from:

  1. monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL);

  2. weekly searches of MEDLINE;

  3. weekly searches of EMBASE;

  4. handsearches of 30 journals and the proceedings of major conferences; and

  5. weekly current awareness alerts for a further 44 journals, plus monthly BioMed Central email alerts.

Details of the search strategies for CENTRAL and MEDLINE, the list of handsearched journals and conference proceedings, and the list of journals reviewed via the current awareness service can be found in the ‘Specialized Register’ section within the editorial information about the Cochrane Pregnancy and Childbirth Group.

Trials identified through the searching activities described above are each assigned to a review topic (or topics). The Trials Search Co-ordinator searches the register for each review using the topic list rather than keywords. 

We did not apply any language restrictions.

Data collection and analysis

See Appendix 1 Methods of data collection and analysis to be used in future updates of this review.

Results

Description of studies

See Characteristics of ongoing studies.

No completed studies that met the inclusion criteria of the review were found. One ongoing clinical trial was identified (NCT00924599); for more details, see Characteristics of ongoing studies.

Risk of bias in included studies

No randomised trials were found for inclusion in the review.

Effects of interventions

No randomised trials were found for inclusion in the review.

Discussion

Summary of main results

One ongoing trial (NCT00924599), aims to evaluate the effects of a dietary and behavioural intervention for obese women with a history of GDM planning a subsequent pregnancy, on recurrence of GDM. No other randomised controlled trials were identified evaluating the effects of interconception care on maternal and infant outcomes in women with a history of GDM.

Women with a history of GDM are at increased risk of recurrence of GDM in subsequent pregnancies, future impaired glucose tolerance and diabetes mellitus, cardiovascular disease and their sequelae. Given the potential poor outcomes identified in these women, they represent a group who could potentially benefit from an intervention aiming to prevent these outcomes. A number of interventions studied in women with a history of GDM after birth, most notably to increase follow-up testing for impaired glucose tolerance or diabetes mellitus (Clark 2003; Clark 2009), and interventions such as metformin/troglitazone and lifestyle modification to prevent type 2 diabetes mellitus have demonstrated benefit (Buchanan 2002; Ratner 2008). It remains uncertain how this may translate to interventions in the interconception period for the prevention of GDM recurrence.

In theory, the interconceptional period in these women represents a time in a younger, high-risk person's life: for identification and management of undiagnosed impaired glucose tolerance and type 2 diabetes mellitus; to initiate lifestyle interventions to potentially improve maternal and infant health outcomes; and to reinforce dietary and lifestyle behaviours for prevention of long-term adverse health outcomes. No randomised controlled trials have been completed evaluating the effects of interventions in this interconceptional period for women with a history of GDM for improving health outcomes for women and their children. Given the potential benefits, it remains important to evaluate the effects of such interventions and identify the ideal form of intervention for these women.

Authors' conclusions

Implications for practice

The role of interconception care for women with a history of GDM on maternal and infant health outcomes remains unclear.

Implications for research

Research should be conducted to investigate the effects of interconception care for women with a history of GDM on health outcomes for mother and infant. Although such trials are faced with difficulties in identifying women in this time period between pregnancies, women with a history of GDM do represent a population at risk for potentially reversible poor health outcomes.

Trials should consider the role of different forms of intervention including dietary, lifestyle and pharmacological therapies, in addition to the duration of such interventions. Such trials should not only evaluate the effects on maternal and infant health outcomes, but also the acceptability and cost effectiveness, to enable translation to clinical practice. Furthermore, future research should focus on long-term follow-up, evaluating the effects of such interventions on the long-term health outcomes associated with gestational diabetes on both the mother and infant.

Acknowledgements

Thanks to staff in the editorial office of the Cochrane Collaboration Pregnancy and Childbirth Group for their help in preparing the protocol and to the editor and referees for their helpful comments.

As part of the pre-publication editorial process, this review has been commented on by four peers (an editor and three referees who are external to the editorial team) and the Group's Statistical Adviser.

The National Institute for Health Research (NIHR) is the largest single funder of the Cochrane Pregnancy and Childbirth Group.  The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health.

Data and analyses

Download statistical data

This review has no analyses.

Appendices

Appendix 1. Methods of data collection and analysis to be used in future updates of this review

Selection of studies  

Two review authors will independently assess for inclusion all the potential studies we identify as a result of the search strategy. We will resolve any disagreement through discussion or, if required, we will consult the third author.

Data extraction and management  

We will design a form to extract data. For eligible studies, two review authors will extract the data using the agreed form. We will resolve discrepancies through discussion or, if required, we will consult the third author. We will enter data into Review Manager software (RevMan 2012) and check the data for accuracy.

When information regarding any of the above is unclear, we will attempt to contact authors of the original reports to provide further details.

Assessment of risk of bias in included studies  

Two review authors will independently assess risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will resolve any disagreement by discussion or by involving a third assessor.

(1) Random sequence generation (checking for possible selection bias)

We will describe for each included study the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups.

We will assess the method as:

  • low risk of bias (any truly random process, e.g. random number table; computer random number generator);

  • high risk of bias (any non-random process, e.g. odd or even date of birth; hospital or clinic record number); or

  • unclear risk of bias.

(2) Allocation concealment (checking for possible selection bias)

We will describe for each included study the method used to conceal allocation to interventions prior to assignment and will assess whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment.

We will assess the methods as:

  • low risk of bias (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes);

  • high risk of bias (open random allocation; unsealed or non-opaque envelopes, alternation; date of birth); or

  • unclear risk of bias.

(3.1) Blinding of participants and personnel (checking for possible performance bias)

We will describe for each included study the methods used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. We will consider that studies are at low risk of bias if they were blinded, or if we judge that the lack of blinding would be unlikely to affect results. We will assess blinding separately for different outcomes or classes of outcomes.

We will assess the methods as:

  • low, high or unclear risk of bias for participants; and

  • low, high or unclear risk of bias for personnel.

(3.2) Blinding of outcome assessment (checking for possible detection bias)

We will describe for each included study the methods used, if any, to blind outcome assessors from knowledge of which intervention a participant received. We will assess blinding separately for different outcomes or classes of outcomes.

We will assess methods used to blind outcome assessment as:

  • low, high or unclear risk of bias.

(4) Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data)

We will describe for each included study, and for each outcome or class of outcomes, the completeness of data including attrition and exclusions from the analysis. We will state whether attrition and exclusions were reported and the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information is reported, or can be supplied by the trial authors, we will re-include missing data in the analyses which we undertake.

We will assess methods as:

  • low risk of bias (e.g. no missing outcome data; missing outcome data balanced across groups);

  • high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups; ‘as treated’ analysis done with substantial departure of intervention received from that assigned at randomisation); or

  • unclear risk of bias.

(5) Selective reporting (checking for reporting bias)

We will describe for each included study how we investigated the possibility of selective outcome reporting bias and what we found.

We will assess the methods as:

  • low risk of bias (where it is clear that all of the study’s prespecified outcomes and all expected outcomes of interest to the review have been reported);

  • high risk of bias (where not all the study’s prespecified outcomes have been reported; one or more reported primary outcomes were not prespecified; outcomes of interest are reported incompletely and so cannot be used; study fails to include results of a key outcome that would have been expected to have been reported); or

  • unclear risk of bias.

(6) Other bias (checking for bias due to problems not covered by (1) to (5) above)

We will describe for each included study any important concerns we have about other possible sources of bias.

(7) Overall risk of bias

We will make explicit judgements about whether studies are at high risk of bias, according to the criteria given in the Cochrane Handbook (Higgins 2011). With reference to (1) to (6) above, we will assess the likely magnitude and direction of the bias and whether we consider it is likely to impact on the findings. We will explore the impact of the level of bias through undertaking sensitivity analyses - see Sensitivity analysis.

Measures of treatment effect  

Dichotomous data

For dichotomous data, we will present results as summary risk ratios (RRs) with 95% confidence intervals (CIs). 

Continuous data

For continuous data, we will use the mean difference (MD) if outcomes are measured in the same way between trials. We will use the standardised mean difference (SMD) to combine trials that measure the same outcome, but use different methods.  

Unit of analysis issues  

Cluster-randomised trials

We will include cluster-randomised trials in the analyses along with individually-randomised trials. We will adjust their sample sizes or standard errors using the methods described in the Cochrane Handbook using an estimate of the intracluster correlation coefficient (ICC) derived from the trial (if possible), or from another source (Higgins 2011). If ICCs from other sources are used, we will report this and conduct sensitivity analyses to investigate the effect of variation in the ICC. If we identify both cluster-randomised trials and individually-randomised trials, we plan to synthesise the relevant information. We will consider it reasonable to combine the results from both if there is little heterogeneity between the study designs and the interaction between the effect of intervention and the choice of randomisation unit is considered to be unlikely.

We will also acknowledge heterogeneity in the randomisation unit and perform a separate meta-analysis.

Cross-over trials

We will exclude cross-over trials from this review.

Multi-armed trials

Where a multi-armed trial is included, we will record and include all outcome data in the review as two-arm comparisons. We will include the data for the different arms in independent two-arm comparisons in separate meta-analyses. In instances where we cannot include the data in separate comparisons, we will combine it to create a single pair-wise comparison (Higgins 2011). If the control group is shared by two or more study arms, we will divide the control group between relevant subgroup categories to avoid double-counting the participants (for dichotomous data we will divide the events and the total population, while for continuous data we will assume the same mean and standard deviation (SD) but will divide the total population). We will describe the details in the 'Characteristics of included studies' tables.

Dealing with missing data  

For included studies, we will note levels of attrition. We will explore the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.

We will carry out all outcomes' analyses, as far as possible, on an intention-to-treat basis i.e. we will attempt to include all participants randomised to each group in the analyses. The denominator for each outcome in each trial will be the number randomised minus any participants whose outcomes are known to be missing.

Assessment of heterogeneity  

We will assess statistical heterogeneity in each meta-analysis using the Tau², I² and Chi² statistics. We will regard heterogeneity as substantial if the I² is greater than 50% and either Tau² is greater than zero, or there is a low P value (less than 0.10) in the Chi² test for heterogeneity. If we identify substantial heterogeneity (above 50%), we will explore it by prespecified subgroup analysis. 

Assessment of reporting biases  

If there are 10 or more studies in the meta-analysis, we will investigate reporting biases (such as publication bias) using funnel plots. We will assess funnel plot asymmetry visually. If asymmetry is suggested by a visual assessment, we will perform exploratory analyses to investigate it.

Data synthesis  

We will carry out statistical analysis using the Review Manager software (RevMan 2012). We will use fixed-effect meta-analysis for combining data where it is reasonable to assume that studies are estimating the same underlying treatment effect, i.e. where trials are examining the same intervention, and the trials’ populations and methods are judged sufficiently similar. If there is clinical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if substantial statistical heterogeneity is detected, we will use random-effects meta-analysis to produce an overall summary if an average treatment effect across trials is considered clinically meaningful. The random-effects summary will be treated as the average of the range of possible treatment effects and we will discuss the clinical implications of treatment effects differing between trials. If the average treatment effect is not clinically meaningful, we will not combine trials. If we use random-effects analyses, we will present the results as the average treatment effect with 95% CIs, and the estimates of Tau² and I².

Subgroup analysis and investigation of heterogeneity  

If we identify substantial heterogeneity, we will investigate it using subgroup analyses and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, use random-effects analysis to produce it.

We plan to carry out the following subgroup analyses.

  1. Periconceptual BMI (underweight; normal range; overweight; obese; morbidly obese).

  2. Polycystic ovarian syndrome versus no polycystic ovarian syndrome.

  3. Diagnostic criteria for GDM mellitus (75 g oral glucose tolerance test (OGTT) - e.g. WHO versus International association of diabetes and pregnancy study groups (IADPS); 100 g OGTT - e.g. Coustan and Carpenter versus National Diabetes Data Group (NDDG)) (Carpenter 1982; Metzger 2010; NDDG 1979; WHO 2006).

  4. Management of GDM in previous pregnancy (non-pharmacological measures, e.g. dietary and lifestyle advice; oral anti-diabetic agents; insulin).

  5. Ethnicity (Caucasian; Asian; Middle-Eastern; African).

  6. Pregnancy interval (estimated date of delivery less than one year from last birth; one year to five years from last birth; more than five years from last birth).

We will restrict subgroup analyses to the review's primary outcomes.

We will assess differences between subgroups by interaction tests available within RevMan (RevMan 2012). We will report the results of subgroup analyses quoting the χ2 statistic and P value, and the interaction test I² value.

Sensitivity analysis  

We plan to carry out sensitivity analysis on primary outcomes to explore the effect of trial quality where there is an overall high risk of bias associated with included trials or where quasi-randomised or cluster-randomised trials are included in the review. We will consider a study to be at overall high risk of bias if both concealment of allocation and attrition rates are assessed as being at high risk of bias. We plan to exclude studies of poor quality from the analysis (those rating as high risk in total overall risk of bias) or quasi-randomised or cluster-randomised trials in order to assess for any substantive difference in the overall result.

Contributions of authors

Joanna Tieu and Emily Bain wrote the review with regular input and feedback from Caroline Crowther and Philippa Middleton.

Declarations of interest

None known.

Sources of support

Internal sources

  • ARCH, Robinson Institute, Discipline of Obstetrics and Gynaecology, The University of Adelaide, Australia.

External sources

  • Department of Health and Ageing, Australia.

  • National Health and Medical Research Council, Australia.

  • National Institute for Health Research, UK.

    NIHR Programme of centrally-managed pregnancy and childbirth systematic reviews of priority to the NHS and users of the NHS:10/4001/02

Differences between protocol and review

None.

Characteristics of studies

Characteristics of ongoing studies [ordered by study ID]

NCT00924599

  1. a

    BMI: body mass index
    GDM: gestational diabetes mellitus

Trial name or title 
MethodsRandomised controlled trial.
Participants

Inclusion criteria

  • 18-40 year old women.

  • English or Spanish speaking.

  • GDM in last pregnancy.

  • BMI 30-40.

  • 1-5 years since last pregnancy.

  • Non-smoking.

  • Planning to have a baby but willing to use birth control during a 3- month weight loss program.

Exclusion criteria

  • 3 or more miscarriages.

  • History of infertility.

  • Type 1 or type 2 diabetes mellitus.

  • Any weight loss since last pregnancy (based on last pre-pregnancy weight).

  • History of major psychiatric illness, drug abuse, or unsafe dieting practices.

  • History of bariatric surgery, major medical conditions that prohibit physical activity or dietary intervention.

Interventions

Women are randomised to receive 1 of 2 interventions: weight loss and exercise intervention or lifestyle education.

Weight loss and exercise intervention

  • Participants attend sessions focused on healthy weight loss, healthy eating and exercise.

  • Weekly sessions for 12 weeks followed by monthly group meetings until conception.

  • Aim for loss of 7% of body weight and increased physical activity to 2.5 hours per week.

Lifestyle education

  • Education focusing on learning about healthy eating and healthy activity, stress reduction techniques, ways of increasing activity.

  • Once a month for 3 months, then once a month until conception.

OutcomesPrimary outcome: GDM not present in pregnancy.
Starting dateJune 2009 (estimated completion August 2013).
Contact informationSuzanne Phelan, Associate Professor, California Polytechnic State University-San Luis Obispo.
Notes 

Ancillary