The rise in gestational diabetes (GDM), defined as first onset or diagnosis of diabetes in pregnancy, is a global problem. GDM is often associated with unhealthy diet and is a major contributor to adverse outcomes maternal and fetal outcomes. Manipulation of nutrition has the potential to prevent GDM.
We assessed the effects of nutritional manipulation in pregnancy on GDM and relevant maternal and fetal outcomes by a systematic review of the literature. We searched MEDLINE, EMBASE, and Cochrane Database from inception to March 2014 without any language restrictions. Randomised controlled trials (RCT) of nutritional manipulation to prevent GDM were included. We summarised dichotomous data as relative risk (RR) and continuous data as standardised mean difference (SMD) with 95% confidence interval (CI).
From 1761 citations, 20 RCTs (6,444 women) met the inclusion criteria. We identified the following interventions: diet-based (n = 6), mixed approach (diet and lifestyle) interventions (n = 13), and nutritional supplements (myo-inositol n = 1, diet with probiotics n = 1). Diet based interventions reduced the risk of GDM by 33% (RR 0.67; 95% CI 0.39, 1.15). Mixed approach interventions based on diet and lifestyle had no effect on GDM (RR 0.95; 95% CI 0.89, 1.22). Nutritional supplements probiotics combined with diet (RR 0.40; 95% CI 0.20, 0.78) and myo-inositol (RR 0.40; 95% CI 0.16, 0.99) were assessed in one trial each and showed a beneficial effect. We observed a significant interaction between the groups based on BMI for diet-based intervention. The risk of GDM was reduced in obese and overweight pregnant women for GDM (RR 0.40, 95% CI 0.18, 0.86).
Citation: Rogozińska E, Chamillard M, Hitman GA, Khan KS, Thangaratinam S (2015) Nutritional Manipulation for the Primary Prevention of Gestational Diabetes Mellitus: A Meta-Analysis of Randomised Studies. PLoS ONE 10(2): e0115526. https://doi.org/10.1371/journal.pone.0115526
Academic Editor: Antonio Gonzalez-Bulnes, INIA, SPAIN
Received: July 8, 2014; Accepted: November 25, 2014; Published: February 26, 2015
Copyright: © 2015 Rogozińska 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: All relevant data are within the paper.
Funding: The authors received funding from the European Union made available to the EBM-CONNECT Collaboration through its Seventh Framework Programme, Marie Curie Actions, International Staff Exchange Scheme (proposal no. 101377; grant agreement no. 247613). None of the funding providers played a role in the planning and execution of this work, or in drafting of the article.
Competing interests: The authors have declared that no competing interests exist.
Gestational diabetes mellitus (GDM), defined as carbohydrate intolerance first diagnosed in pregnancy, is on the rise worldwide.  An increase in the number of mothers entering pregnancy as obese and with advancing maternal age has contributed to this escalation in rates of GDM. Women with GDM and their children are at risk of adverse outcomes in pregnancy and in the long term.  About half of mothers with GDM are expected to develop Type 2 diabetes within five years after pregnancy.  In the offspring it is a major contributor to obesity and Type 2 diabetes in later life.  There is a need for safe, simple, effective and acceptable interventions that prevent the development of GDM. Such an approach has the potential to improve maternal and child health, with significant savings to the health care system.
Interventions that prevent Type 2 diabetes might reduce the risk of GDM. Nutritional manipulation based on diet and lifestyle is known to significantly lower the rates of Type 2 diabetes in non-pregnant individuals.  This beneficial effect could be attributed either to the reduction in the calorie intake, or to the effect of individual components of diet such as yoghurt and cereals that are rich in probiotics, fibre and vitamins. [7,8] Currently no such interventions are offered to mothers as part of routine antenatal care to reduce GDM. Systematic reviews to-date, are based on limited number of studies, and have not provided conclusive evidence on the benefits of nutritional interventions in preventing GDM. [9–11] Furthermore, individual studies are underpowered to reliably estimate reductions in the rates of GDM. 
There is a need to collate the accruing evidence on nutritional manipulation. We systematically reviewed the effectiveness of nutritional manipulation in pregnancy with mainly diet-based interventions; mixed approach with diet and lifestyle; and nutritional supplements in preventing GDM.
This project is secondary research only so requires no ethical approval.
Literature search and study selection
A comprehensive search of the relevant literature was performed in electronic databases (MEDLINE, EMBASE and the Cochrane Library) from inception to March 2014. The search strategy was designed by combining the search terms: “diet,” “vitamins,” “probiotics,” “gestational,” “diabetes” and “pregnancy” using their word variants and Boolean operators AND and OR as appropriate. No language restrictions were applied. We contacted the authors of primary studies to obtain any relevant unpublished data. Additionally, we searched the reference lists of the included studies for relevant literature.
Studies were selected in a two-stage process. We screened the titles and abstracts against the pre-specified inclusion criteria for relevant citations. This was followed by assessment of the full texts of the selected abstracts. We included randomised studies that evaluated the effect of nutritional interventions in pregnancy: diet based advice, mixed approach (combination of diet and lifestyle including physical activity) and nutritional supplements that have the potential to reduce the risk of GDM such as vitamin-D, myo-inositol and probiotics. We did not include studies that evaluated only physical activity. The comparator was standard antenatal care. Primary prevention of GDM was the outcome of interest. The secondary outcomes were maternal and fetal complications such as pre-eclampsia, mode of delivery, gestation at delivery, birth weight of the fetus, neonatal death and neonatal intensive care unit admissions. We included studies on low risk and high-risk women. Women were classified as high risk if they have at least one of the following characteristics: obesity, previous history of GDM or fetal macrosomia, advanced maternal age, and family history of diabetes.  Two independent reviewers (ER and MC) selected the studies. Any discrepancy between them was resolved by a third reviewer (ST).
Study quality assessment and data extraction
Two independent reviewers (ER and MC) assessed the study quality and extracted the data using pre-designed forms. We assessed the risk of bias  in the following domains: sequence generation, allocation concealment, blinding, incomplete outcome data and selective reporting. Data were extracted in 2x2 tables for dichotomous outcomes. For continuous outcomes we extracted data on mean and standard deviation for both the groups. When more than one definition was used for GDM in a study, we extracted data for outcomes using the most recent diagnostic criteria. Any discrepancies were resolved by discussion with the third reviewer (ST).
Data were summarised as risk ratio (RR) with 95% confidence interval (CI) for dichotomous outcomes, and standardised or weighted mean difference with 95% CI for continuous outcomes using the random effects model. We assessed statistical heterogeneity between trials by using the I2 statistic. We undertook subgroup analysis planned a priori to explore whether the effect on the outcome would vary according to the type of intervention, and Body Mass Index (BMI), and risk status of the participants for GDM. The subgroup difference was evaluated using Chi squared test. When more than one intervention was compared to standard care in a study, we chose the combined intervention over the individual diet or nutritional supplement for the pooled analysis. We used random effects model for meta-analysis. Sensitivity analysis was undertaken by substituting the individual intervention instead of the combined method to assess for any change in the summary estimates of effects. We used Harbord’s modified test to assess for publication bias  and potential small study effect. All analyses were performed with Review Manager (RevMan version 5.2) and Stata software (version 11).
Our initial search in electronic databases yielded 1761 citations. Further eight studies were identified from the reference lists of the selected studies. Twenty RCTs with 6,444 women were included in the review. [18–37] The process of study identification and study selection is provided in Fig. 1.
Characteristics of the included studies
The following nutrition based methods were evaluated: diet based interventions (5 RCTs; 1,309 women) [25,31,33,36,37], mixed (diet and lifestyle) approach (13 RCTs; 4,745 women) [18,20–24,27–30,32,34,35] and nutritional supplements: myo-inositol (1 RCT; 220 women)  and diet with probiotics (1 RCT; 170 women)  .
Of the 20 included studies, 13 RCTs were on women at risk of developing gestational diabetes [18,19,21,22,25,30–37] and seven included any risk women [20,23,24,26–29]. Twelve RCTs examined the effect of the intervention in either obese or/and overweight women [18,20,22,27,30–35,37] and eight included women of any BMI. [19,23–26,28,29,36]
The interventions varied in their composition, especially those based on diet. The diet based strategy included low glycaemic index diet  , and restricted energy intake according to the individual requirements.  The mixed approach group delivered a combination of diet and lifestyle including physical activity. The nutritional supplement myo-inositol was provided as a 2 g dose twice a day with 200 ug folic acid. The probiotics Lactobacillus Rhamnosus GG and Bifidobacterium lactis Bb12 in dose of 1010 colony forming units were taken every day in addition to intensive dietary counselling. 
The interventions were delivered in groups or as a one-to-one contact session, and often in more than one step. The nutritional advice was accompanied by psychological input in some studies. [23,31] Participants were provided with food diaries to record their food intake and the dieticians tailored the intervention according to the caloric requirements. Most of the interventions from the mixed approach category were based on the national recommendations on healthy eating in pregnancy, with additional input provided by trained healthcare personnel. The mixed approach category aggregates studies with complex interventions targeting weight gain from different angles; ranging from change in a type of consumed foods and daily physical activity pattern [23,27] , behavioural change [18,22] to weight gain monitoring only  . All the interventions were commenced before 28 weeks at varied time points in the first or second trimester.
The definition of GDM varied between the studies (Table 1). The following maternal outcomes were evaluated: preterm delivery, caesarean section, induction of labour, pre-eclampsia and pregnancy induced hypertension. The fetal outcomes included birth weight, shoulder dystocia and admission to neonatal intensive care unit (NICU). The follow up period varied from 6 weeks after delivery to the end of exclusive breastfeeding.
Quality of the included studies
All studies with diet based interventions had low risk of bias for adequate randomisation and attrition [25,26,31,33,36,37] ; half of them (3/6) had low risk for allocation concealment [26,31,36] . Only one study reported adequate blinding of researchers and participants  and 33% were considered as high risk in this domain (2/6) [25,36] . The blinding of outcomes assessors was adequate in one diet study  and inadequate in one  . The risk of bias due to selective reporting was low in 33% of the included diet based studies (2/6) [26,31] and inadequate in other two trials [25,36] .
Twelve trials on mixed (diet and lifestyle) approach had a low risk of bias for adequate randomisation (92%, 12/13). [18,20–24,27,28,30,32,34,35] Allocation concealment was well described in six [20,22,27,28,30,32] out of 13 mixed approach interventions studies. Blinding of staff and participants was adequate in one trial  and inadequate in two; and blinding of outcomes assessment was correct in 31% of included trials (4/13) [20,22,28,34]. Attrition bias was low for majority of studies except one study that was at high risk . Selective reporting bias was low in 54% of mixed approach trials [18,20,22–24,28,29] and was considered to be high in four trials (31%) [21,27,32,35].
Of the two trials on nutritional supplements, the trial on myo-inositol supplementation  was assessed to have low risk of bias for adequate randomisation, attrition and selective reporting and high risk for blinding of staff and participants. The trial on probiotics had low risk of bias for all domains except for detection bias.  Fig. 2 provides the quality assessment of the included studies for diet based and mixed approach groups.
Effect of nutritional manipulation on GDM
Interventions that were mainly based on diet reduced the rates of GDM by 33% (RR 0.67; 95% CI 0.39, 1.15I2 = 52%) (Fig. 3a). There were no differences between the two groups for mixed (diet and lifestyle) approach (RR 0.95; 95% CI 0.89, 1.22; I2 = 23%) (Fig. 3b). The risk of GDM was reduced by 60% for probiotics (with diet) in comparison to standard care (RR 0.40; 95% CI 0.20, 0.78; p<0.01). A similar reduction was observed for the nutritional supplement myo-inositol (RR 0.40; 95% CI 0.16, 0.99; p = 0.05) (Fig. 3c).
Small study effect
Due to insufficient number of studies for myo-inositol and diet with probiotic supplementation we examined funnel plot asymmetry only for diet based and mixed approach groups. For both groups Harbord’s statistical tests for small study effect was insignificant (p = 0.87 and p = 0.21, respectively),
Subgroup comparison was possible to conduct only for two intervention categories: diet based and mixed approach. There was no subgroup differences based on maternal risk for GDM for both intervention groups and for BMI category comparison for the mixed approach group (Table 2). There was a significant difference according to the BMI for diet based intervention (p = 0.04). A significant reduction in GDM was observed in the subgroup comprised of obese and overweight women (RR 0.40; 95% CI 0.18, 0.86, I2 = 29%).
Effect of nutritional interventions on other maternal and neonatal outcomes
Eleven trials [19,20,22,24,27–29,32–34,36] evaluated the role of interventions in preventing preterm delivery before 37 weeks of gestation None of the interventions significantly reduced the rate of preterm deliveries; however, the risk reduction was the highest (51%) for diet based group (RR 0.49, 95% CI 0.19, 1.29).
Fourteen RCTs [18–20,23,24,26–29,32–36] reported the effect of interventions on the caesarean section rate and six studies [18,20,27,32,33,36] on the rate of the induction of labour. There was no significant effect of the intervention on the rates of evaluated outcomes (Table 3).
Ten studies reported on the effects of the intervention on gestational hypertension [18–20,24,27–29,32,33,37] and nine on pre-eclampsia [18,20,24,28,29,32,33,35,37]. The risk of gestational hypertension and pre-eclampsia was reduced by 84% and 34%, respectively, in diet-based group (Table 3). There was no noticeable effect of mixed approach on the occurrence of discussed outcomes.
Ten trials evaluated the effect of nutritional manipulation in pregnancy on the birth weight of the newborns. [18,19,23–25,27,28,31,33,34,36,37] The only significant difference in birth weight between the groups was recorded for myo-inositol (SMD-0.51, 95% CI-0.79, -0.22; p<0.01). Four trials [19,20,24,36] reported on shoulder dystocia, and showed no significant difference between the groups for any of three intervention groups (Table 3).
In two studies evaluating mixed approach (2,562 women) authors reported the rates of the admissions to Neonatal Intensive Care Unit. [20,35] There was no statistically significant difference in numbers of admissions between the intervention and the control group (RR 1.01, 95% CI 0.91, 1.13; I2 = 0%). Only one study  reported events of neonatal death and stillbirth. For both outcomes estimated risks were none significant (Table 3).
Nine of the 20 trials reported or evaluated the adverse effects of the interventions on the mother and offspring. [19,23,26,28,29,31,33,36,37] No significant adverse effects were observed for myo-inositol or probiotics in studies that exposed women to the intervention in the first trimester. One study , assessed the impact of the diet based intervention and reported a case of severe intrauterine growth restriction in each of the arms that resulted in preterm delivery.
Summary of findings
Nutritional manipulation based on diet or mixed approach does not appear to prevent GDM. There was a trend towards beneficial effect in women on mainly diet-based intervention, with a potential for significant reduction in GDM risk when limited to obese and overweight women. Nutritional supplements such as probiotics and myo-inositol show promising role in the strategy for primary prevention of GDM.
Relevance to current evidence
Until now, there has been no robust evidence to provide guidance on the primary prevention of GDM due to the small number of studies limited to few interventions in published reviews.  The number of eligible studies has doubled since our previous review that evaluated the effect of mixed approach (diet and lifestyle modification) on GDM.  By evaluating all the relevant interventions, our review is the first to systematically assess the effects of nutritional manipulation in pregnancy on GDM. We complied with current guidelines and used a comprehensive search strategy without any language restrictions. By including only randomised trials, we avoided some of the pitfalls encountered by earlier reviews that included quasi-randomised studies  and women with GDM .
Effects of interventions on GDM
Amongst evaluated interventions, diet based interventions appear to show potential for preventing GDM. This could be due to the following reasons: individual dietary and components; change in gestational weight gain and effect of nutritional supplements.
The interventions promoted the uptake of healthy components such as fibre, probiotics and food rich in vitamins such as myo-inositol that may have an additive effect in reducing the concentrations of maternal glucose. [19,26] The women in the intervention group had reduced total energy intake and glycaemic load compared to the controlled group. [30,36] Low glycaemic index diet attenuates the increase in insulin resistance observed in pregnancy, thereby reducing the risk of GDM.  The risk of GDM is known to be reduced by a quarter with each 10-g/day increment in total fibre intake.  The largest benefit with diet was observed where there was a multidisciplinary input into the intervention, with the use of food diaries  and feedback methods.
Diet based interventions have also shown the greatest reduction in gestational weight gain compared to other methods.  The reduction in gestational weight gain may have influenced the fall in the rates of GDM.  Serum leptin, a known factor associated with GDM , was lowered by 20% with reduced gestational weight gain.  Cord leptin concentrations were also increased in newborns born to mothers with diabetes. 
We did not observe the beneficial effect in the subgroup with mixed approach that combined diet and physical activity. This is consistent with previously published reviews that did not show beneficial effect of physical activity in pregnancy on pregnancy outcomes. [11,43] Rather than physical activity failing to have an expected impact on GDM, it is likely that women in the intervention group had poor compliance with the intervention. Objective assessments with methods such as accelerometry have shown no difference in the physical activity between the two groups.  The largest trial on mixed approach (diet and lifestyle) in pregnancy, the LIMIT study failed to show a benefit with the intervention for GDM and other maternal outcomes including gestational weight gain. Non-compliance with the intervention, with a quarter of women not attending the required two sessions with the dietician could have contributed to the lack of benefit.
Simple interventions based on nutritional supplements such as myo-inositol and probiotics appear to have significant potential in preventing GDM. Inositol is available in cereals, meat, fresh fruit and vegetables, corn and legumes. The average dietary intake contains 1g of inositol/day. Myo-inositol is known to increase the sensitivity to insulin,  a possible mechanism for the observed reduction in GDM.
Other supplements such as the probiotics, consisting of microorganisms of beneficial nature, appear to reduce the risk of GDM when combined with a dietary intervention.  By altering the gut microbiome, and by modifying the concentration of plasma lipopolysaccharides, probiotics alter the inflammatory pathways and sensitivity to insulin. It is possible that the benefit observed in the Luoto trial in reducing GDM  was due to a synergistic action between a diet rich in probiotics in addition to probiotics supplements.
Safety of the interventions
Any intervention evaluated in pregnancy needs to pass a rigorous evaluation of its safety to the mother and baby. Our previous detailed evaluation of diet and mixed interventions in pregnancy did not find adverse effects to the mother or baby, except in extreme conditions such as starvation.  Although theoretical concerns have been raised regarding the risk of preterm delivery with inositol, this was not observed in both randomised and observational studies on inositol in pregnancy. Inositol use in early pregnancy may in an additional beneficial role, by preventing the risk of neural tube defect in folate resistant mothers. 
Our findings were limited by differences in the inclusion criteria of the studies, variation in the components of the intervention such as duration, intensity and frequency, non-standardised care in the control group and non-uniform definitions of GDM. Furthermore, women in the intervention group had more than one intervention, such as diet and probiotics, making it difficult to delineate the beneficial effect of an individual intervention. It is possible that a different criterion for the diagnosis of gestational diabetes may have yielded changed estimates of effect.  Women in the control group may have accessed these interventions resulting in Hawthorne effect for the following reasons: interventions were easily accessible, including over the counter nutritional supplement; and absence of blinding of the women or health care provider, in any of the included studies. None of the studies evaluated GDM as a primary outcome. Hence it is possible that the different arms could have been treated differently, such as additional screening for GDM, and close follow-up in the intervention group, thereby influencing the outcome. Studies were limited in their reporting on proportion of women who complied with the intervention, which could have a major influence on the effect size observed.
Since women with GDM are mostly seen in the secondary care, with frequent follow ups including ultrasound assessment of fetal growth, any effective intervention that prevents GDM is likely to be cost effective in the long run. Dietary interventions are complex, and require a change in the behaviour of mothers, to have a positive impact on the outcomes. Furthermore, they require reinforcement and feedback with food diaries, and regular visits with healthcare professionals such as dieticians, midwives and clinicians. The diet based intervention may have a role in primary prevention of GDM, especially in obese and overweight pregnant women.
With a projected increase in the National Health Service (NHS) spend from £8.8 billion to £13 billion per year in the next 25 years on Type 2 diabetes and its complications,  primary prevention of GDM has significant societal and economic benefits. Interventions based on diet and nutritional supplements show potential to prevent GDM, with the possibility of promoting the health of subsequent generations, by reducing the risks of obesity and adult onset diabetes in children born to mothers with GDM.
The role of diet-based interventions in obese and overweight pregnant women, the population most likely to develop GDM, needs further evaluation. The beneficial effects of simple interventions such as probiotics and myo-inositol on GDM appear promising. There is a need to evaluate the effects of supplements by large multicentre randomised trials, involving wider group of individuals such as non-Caucasians and obese women. The optimal dose, frequency and type of inositol isomer need to be identified. Similarly the effects of different genera or strains of probiotics and their varied dose on GDM need to be identified. Given the considerable resources required to deliver the complex interventions based on diet, it is possible that nutritional supplements will also be cost effective. Furthermore, they are an attractive option as they are easily available as over the counter supplements.
Mixed approach interventions composed of diet and lifestyle modification do not appear to prevent GDM. Diet based interventions may be beneficial in obese and overweight pregnant women. Nutritional supplements such as probiotics and myo-inositol show benefit and need further evaluation in large randomised trials.
S1 Appendix. Search strategies for MEDLINE via Ovid.
S2 Appendix. Quality assessment of included studies.
S3 Appendix. Completed PRISMA Checklist.
We thank the EBM-CONNECT (Evidence-based medicine collaboration: network for systematic reviews and guideline development research and dissemination) Collaboration, in alphabetical order by country: L. Mignini, Centro Rosarino de Estudios Perinatales, Argentina; P. von Dadelszen, L. Magee and D. Sawchuck, University of British Columbia Canada; E. Gao, Shanghai Institute of Planned Parenthood Research, China; B.W. Mol and K. Oude Rengerink, Academic Medical Centre, the Netherlands; J. Zamora, Ramon y Cajal, Spain; C. Fox and J. Daniels, University of Birmingham, UK; K.S. Khan, S. Thangaratinam, and C. Meads, Barts and the London School of Medicine, Queen Mary University of London, UK.
Performed the experiments: ER MC. Analyzed the data: ER. Wrote the paper: ER ST. Provided critical input into the design and drafting of the manuscript: GAH KSK.
- 1. Ferrara A (2007) Increasing Prevalence of Gestational Diabetes Mellitus: A public health perspective. Diabetes Care 30(Supplement 2):S141–S146.
- 2. Jovanovic L, P DJ (2001) Gestational diabetes mellitus. JAMA 286(20):2516–8. pmid:11722247
- 3. Kim C, Newton KM, Knopp RH (2002) Gestational diabetes and the incidence of type 2 diabetes: a systematic review. Diabetes Care 25(10):1862–8. pmid:12351492
- 4. Buchanan TA, Xiang AH, Page KA (2012) Gestational diabetes mellitus: risks and management during and after pregnancy. Nat Rev Endocrinol 8(11):639–49. pmid:22751341
- 5. Coustan DR (2013) Can a dietary supplement prevent gestational diabetes mellitus? Diabetes Care 36(4):777–9. pmid:23520369
- 6. Gillies CL, Abrams KR, Lambert PC, Cooper NJ, Sutton AJ, et al. (2007) Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis. BMJ 334(7588):299. pmid:17237299
- 7. Kalergis M, Leung Yinko SS, Nedelcu R (2013) Dairy products and prevention of type 2 diabetes: implications for research and practice. Front Endocrinol (Lausanne) 4:90. pmid:23888154
- 8. Weickert MO, Pfeiffer AF (2008) Metabolic effects of dietary fiber consumption and prevention of diabetes. J Nutr 138(3):439–42. pmid:18287346
- 9. Oostdam N, van Poppel MN, Wouters MG, van MW (2011) Interventions for preventing gestational diabetes mellitus: a systematic review and meta-analysis. J Womens Health (Larchmt) 20(10):1551–63. pmid:21838525
- 10. Tieu J, Crowther CA, Middleton P (2008) Dietary advice in pregnancy for preventing gestational diabetes mellitus. Cochrane Database Syst Rev (2):CD006674. pmid:18425961
- 11. Thangaratinam S, Rogozinska E, Jolly K, Glinkowski S, Roseboom T, et al. (2012) Effects of interventions in pregnancy on maternal weight and obstetric outcomes: meta-analysis of randomised evidence. BMJ 344:e2088. pmid:22596383
- 12. Luoto R, Kinnunen TI, Aittasalo M, Kolu P, Raitanen J, et al. (2011) Primary prevention of gestational diabetes mellitus and large-for-gestational-age newborns by lifestyle counseling: a cluster-randomized controlled trial. PLoS Med 8(5):e1001036. pmid:21610860
- 13. Khan KS, ter Riet G, Glanville J, Sowden AJ, Kleijnen J (2001) Undertaking Systematic Reviews of Research on Effectiveness. CRD's Guidance for Carrying Out or Commissioning Reviews. NHS Centre for Reviews and Dissemination, University of York. Report No.: 4 (2nd edition).
- 14. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, et al. (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med 6(7):e1000100. pmid:19621070
- 15. Walker JD (2008) NICE guidance on diabetes in pregnancy: management of diabetes and its complications from preconception to the postnatal period. NICE clinical guideline 63. London, March 2008. Diabet Med 25(9):1025–7. pmid:19183306
- 16. Higgins JPT, Green Se. Cochrane Reviewers Handbook 5.1.0. Available: http://handbook.cochrane.org/. 2011 Mar.
- 17. Harbord RM, Egger M, Sterne JA (2006) A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints. Stat Med 25(20):3443–57. pmid:16345038
- 18. Bogaerts A, Devlieger R, Nuyts E, Witters I, Gyselaers W, et al. (2013) Effects of lifestyle intervention in obese pregnant women on gestational weight gain and mental health: A randomized controlled trial. Int J Obes 37(6):814–21. pmid:23032404
- 19. D'Anna R, Scilipoti A, Giordano D, Caruso C, Cannata ML, et al. (2013) Myo-inositol supplementation and onset of gestational diabetes mellitus in pregnant women with a family history of type 2 diabetes: A prospective, randomized, placebo-controlled study. Diabetes Care 36(4):854–7. pmid:23340885
- 20. Dodd JM, Turnbull D, McPhee AJ, Deussen AR, Grivell RM, et al. (2014) Antenatal lifestyle advice for women who are overweight or obese: LIMIT randomised trial. BMJ 348:doi: http://dx.doi.org/10.1136/bmj.g1285.
- 21. Guelinckx I, Devlieger R, Mullie P, Vansant G (2010) Effect of lifestyle intervention on dietary habits, physical activity, and gestational weight gain in obese pregnant women: A randomized controlled trial. Am J Clin Nutr 91(2):373–80. pmid:19955397
- 22. Harrison CL, Lombard CB, Gibson-Helm M, Deeks A, Teede HJ (2011) Limiting excess weight gain in high-risk pregnancies: A randomized controlled trial. Endocr Rev 32(3). pmid:21441345
- 23. Hui A, Back L, Ludwig S, Gardiner P, Sevenhuysen G, et al. (2011) Lifestyle intervention on diet and exercise reduced excessive gestational weight gain in pregnant women under a randomised controlled trial. BJOG Int J Obstet Gynaecol 119(1):70–7.
- 24. Jeffries K, Shub A, Walker SP, Hiscock R, Permezel M (2009) Reducing excessive weight gain in pregnancy: a randomised controlled trial. Med J Aust 191(8):429–33. pmid:19835535
- 25. Korpi-Hyovalti E, Schwab U, Laaksonen DE, Linjama H, Heinonen S, et al. (2012) Effect of intensive counselling on the quality of dietary fats in pregnant women at high risk of gestational diabetes mellitus. Br J Nutr 108(5):910–7. pmid:22093485
- 26. Luoto R, Laitinen K, Nermes M, Isolauri E, Luoto R, et al. (2010) Impact of maternal probiotic-supplemented dietary counselling on pregnancy outcome and prenatal and postnatal growth: a double-blind, placebo-controlled study. Br J Nutr 103(12):1792–9. pmid:20128938
- 27. Petrella E, Malavolti M, Bertarini V, Pignatti L, Neri I, et al. (2013) Gestational weight gain in overweight and obese women enrolled in a healthy lifestyle and eating habits program. J Matern Fetal Neonatal Med Nov 25.
- 28. Phelan S, Phipps MG, Abrams B, Darroch F, Schaffner A, et al. (2011) Randomized trial of a behavioral intervention to prevent excessive gestational weight gain: the Fit for Delivery Study. Am J Clin Nutr 93(4):772–9. pmid:21310836
- 29. Polley BA, Wing RR, Sims CJ (2002) Randomized controlled trial to prevent excessive weight gain in pregnant women. Int J Obes Relat Metab Disord 26(11):1494–502. pmid:12439652
- 30. Poston L, Briley AL, Barr S, Bell R, Croker H, et al. (2013) Developing a complex intervention for diet and activity behaviour change in obese pregnant women (the UPBEAT trial); Assessment of behavioural change and process evaluation in a pilot randomised controlled trial. BMC Pregnancy Childbirth 13.
- 31. Quinlivan J, Lam LT, Fisher J (2011) A randomised trial of a four-step multidisciplinary approach to the antenatal care of obese pregnant women. Australian & New Zealand Journal of Obstetrics & Gynaecology 51(2):141–6.
- 32. Renault KM, Norgaard K, Nilas L, Carlsen EM, Cortes D, et al. (2014) The Treatment of Obese Pregnant Women (TOP) study: a randomized controlled trial of the effect of physical activity intervention assessed by pedometer with or without dietary intervention in obese pregnant women. Am J Obstet Gynecol 210(2):134–9. pmid:24060449
- 33. Thornton YS, Smarkola C, Kopacz SM, Ishoof SB (2009) Perinatal outcomes in nutritionally monitored obese pregnant women: a randomized clinical trial. J Natl Med Assoc 101(6):569–77. pmid:19585925
- 34. Vesco K, Leo M, Gillman M, King J, McEvoy C, et al. (2013) Impact of a weight management intervention on pregnancy outcomes among obese women: The Healthy Moms Trial. Am J Obstet Gynecol 208(1):S352.
- 35. Vinter C, Jensen DM, Ovesen P, Beck-Nielsen H, Jorgensen JS (2011) The LiP (Lifestyle in Pregnancy) study: a randomized controlled trial of lifestyle intervention in 360 obese pregnant women. Diabetes Care 34(12):2502–7. pmid:21972411
- 36. Walsh J, McGowan CA, Mahony R, Foley ME, McAuliffe FM (2012) Low glycaemic index diet in pregnancy to prevent macrosomia (ROLO study): randomised control trial. BMJ 345:e5605. pmid:22936795
- 37. Wolff S, Legarth J, Vangsgaard K, Toubro S, Astrup A (2008) A randomized trial of the effects of dietary counseling on gestational weight gain and glucose metabolism in obese pregnant women. Int J Obes (Lond) 32(3):495–501. pmid:18227847
- 38. Barrett HL, Callaway LK, Nitert MD (2012) Probiotics: a potential role in the prevention of gestational diabetes? Acta Diabetol 49 Suppl 1:S1–13. pmid:23180045
- 39. Fraser RB, Ford FA, Lawrence GF (1988) Insulin sensitivity in third trimester pregnancy. A randomized study of dietary effects. Br J Obstet Gynaecol 95, 223–229. pmid:2835977
- 40. Zhang C, Liu S, Solomon CG, Hu FB (2006) Dietary fiber intake, dietary glycemic load, and the risk for gestational diabetes mellitus. Diabetes Care 29(10):2223–30. pmid:17003297
- 41. Qiu C, Williams MA, Vadachkoria S, Frederick IO, Luthy DA (2004) Increased maternal plasma leptin in early pregnancy and risk of gestational diabetes mellitus. Obstet Gynecol 103(3):519–25. pmid:14990416
- 42. Pirc LK, Owens JA, Crowther CA, Willson K, De Blasio MJ, et al. (2007) Mild gestational diabetes in pregnancy and the adipoinsular axis in babies born to mothers in the ACHOIS randomised controlled trial. BMC Pediatr 7:18. pmid:17430602
- 43. Han S, Middleton P, Crowther CA (2012) Exercise for pregnant women for preventing gestational diabetes mellitus. Cochrane Database Syst Rev 7:CD009021. pmid:22786521
- 44. Genazzani AD, Lanzoni C, Ricchieri F, Jasonni VM (2008) Myo-inositol administration positively affects hyperinsulinemia and hormonal parameters in overweight patients with polycystic ovary syndrome. Gynecol Endocrinol 24(3):139–44. pmid:18335328
- 45. Cogram P, Tesh S, Tesh J, Wade A, Allan G, et al. (2002) D-chiro-inositol is more effective than myo-inositol in preventing folate-resistant mouse neural tube defects. Hum Reprod 17(9):2451–8. pmid:12202440
- 46. Shang M, Lin L (2014) IADPSG criteria for diagnosing gestational diabetes mellitus and predicting adverse pregnancy outcomes. J Perinatol 34(2):100–4. pmid:24232664
- 47. Hex N, Bartlett C, Wright D, Taylor M, Varley D (2012) Estimating the current and future costs of Type 1 and Type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs. Diabet Med 29(7):855–62. pmid:22537247