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Gestational diabetes mellitus in women born small or preterm: Systematic review and meta-analysis

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Abstract

Purpose

There is some evidence that women born preterm or with low birth weight (LBW) have an increased future risk of gestational diabetes mellitus (GDM) during pregnancy; however, a quantitative summary of evidence is lacking. In this systematic review and meta-analysis, we examined the published data to investigate whether being born preterm, with LBW or small for gestational age (SGA) are associated with GDM risk.

Methods

We searched the MEDLINE, Embase, and CINAHL databases and study registries, including ClinicalTrials.gov and ICTRP, from launch until 29 October 2020. Observational studies examining the association between birth weight or gestational age and GDM were eligible. We pooled the odds ratios and 95% confidence intervals using the DerSimonian and Laird random-effects model.

Results

Eighteen studies were included (N = 827,382). The meta-analysis showed that being born preterm, with LBW or SGA was associated with increased risk of GDM (pooled odds ratio = 1.84; 95% confidence interval: 1.54–2.20; I2 = 78.3%; τ2 = 0.07). Given a GDM prevalence of 2.0, 10, and 20%, the absolute risk differences were 1.6%, 7.0%, and 11.5%, respectively. The certainty of the evidence was low due to serious concerns of risk of bias and publication bias.

Conclusions

Women born prematurely, with LBW or SGA status, may be at increased risk for GDM. However, whether this should be considered in clinical decision-making depends on the prevalence of GDM.

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Data availability

Data are available upon reasonable request.

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References

  1. T.A. Buchanan, A.H. **ang, K.A. Page, Gestational diabetes mellitus: Risks and management during and after pregnancy. Nat. Rev. Endocrinol. 8(11), 639–649 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. International Association of D, Pregnancy Study Groups Consensus P, B.E. Metzger, S.G. Gabbe, B. Persson, T.A. Buchanan et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care 33(3), 676–682 (2010)

    Article  Google Scholar 

  3. American Diabetes A, 2. Classification and diagnosis of diabetes. Diabetes Care 40(Suppl 1), S11–S24 (2017)

    Article  Google Scholar 

  4. American Diabetes Association, 14. Management of diabetes in pregnancy: Standards of medical care in diabetes—2019. Diabetes Care 42(Supplement 1), S165–S172 (2019)

    Article  Google Scholar 

  5. C. Kim, K.M. Newton, R.H. Knopp, Gestational diabetes and the incidence of type 2 diabetes: A systematic review. Diabetes Care 25(10), 1862–1868 (2002)

    Article  PubMed  Google Scholar 

  6. L. Bellamy, J.-P. Casas, A.D. Hingorani, D. Williams, Type 2 diabetes mellitus after gestational diabetes: A systematic review and meta-analysis. Lancet 373(9677), 1773–1779 (2009)

    Article  CAS  PubMed  Google Scholar 

  7. S. Chawanpaiboon, J.P. Vogel, A.-B. Moller, P. Lumbiganon, M. Petzold, D. Hogan et al. Global, regional, and national estimates of levels of preterm birth in 2014: A systematic review and modelling analysis. Lancet Glob. Health 7(1), e37–e46 (2019)

    Article  PubMed  Google Scholar 

  8. United Nations Children’s Fund (UNICEF) WHO. UNICEF-WHO Low birthweight estimates: Levels and trends 2000–2015. (World Health Organization, Geneva),(2019)

    Google Scholar 

  9. J. Katz, A.C. Lee, N. Kozuki, J.E. Lawn, S. Cousens, H. Blencowe et al. Mortality risk in preterm and small-for-gestational-age infants in low-income and middle-income countries: a pooled country analysis. Lancet 382(9890), 417–425 (2013)

    Article  PubMed  PubMed Central  Google Scholar 

  10. J.M. Piper, E.M. Xenakis, M. McFarland, B.D. Elliott, M.D. Berkus, O. Langer, Do growth-retarded premature infants have different rates of perinatal morbidity and mortality than appropriately grown premature infants? Obstet. Gynecol. 87(2), 169–174 (1996)

    Article  CAS  PubMed  Google Scholar 

  11. L. Belbasis, M.D. Savvidou, C. Kanu, E. Evangelou, I. Tzoulaki, Birth weight in relation to health and disease in later life: An umbrella review of systematic reviews and meta-analyses. BMC Med 14(1), 147 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  12. D.J. Barker, The fetal and infant origins of adult disease. Bmj. 301(6761), 1111 (1990)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. D.J. Pettitt, L. Jovanovic, Low birth weight as a risk factor for gestational diabetes, diabetes, and impaired glucose tolerance during pregnancy. Diabetes Care 30(Supplement 2), S147–S149 (2007)

    Article  PubMed  Google Scholar 

  14. L.A. Plante, Low birth weight may not predict diabetes in pregnancy. Diabetes Care 27(7), 1759–1760 (2004)

    Article  PubMed  Google Scholar 

  15. Y.T. Lagerros, S. Cnattingius, F. Granath, U. Hanson, A.-K. Wikström, From infancy to pregnancy: Birth weight, body mass index, and the risk of gestational diabetes. Eur. J. Epidemiol. 27(10), 799–805 (2012)

    Article  PubMed  Google Scholar 

  16. J. Ogonowski, T. Miazgowski, K. Engel, Z. Celewicz, Birth weight predicts the risk of gestational diabetes mellitus and pregravid obesity. Nutr. (Burbank, Los Angeles Cty., Calif.) 30(1), 39–43 (2014)

    Article  Google Scholar 

  17. P.H. Andraweera, G. Dekker, S. Leemaqz, L. McCowan, J. Myers, L. Kenny et al. Effect of birth weight and early pregnancy bmi on risk for pregnancy complications. Obesity 27(2), 237–244 (2019)

    Article  PubMed  Google Scholar 

  18. Higgins J.P.T., Thomas J., Chandler J., Cumpston M., Li T., Page M.J., et al. Cochrane Handbook for Systematic Reviews of Interventions version 6.0: Cochrane; 2019 [updated July 2019]. Available from: www.training.cochrane.org/handbook

  19. A. Boivin, Z.-C. Luo, F. Audibert, B. Mâsse, F. Lefebvre, R. Tessier et al. Pregnancy complications among women born preterm. CMAJ 184(16), 1777–1784 (2012)

    Article  PubMed  PubMed Central  Google Scholar 

  20. R. Chawla, K.M. Rankin, J.W. Collins Jr., The relation of a woman’s impaired in utero growth and association of diabetes during pregnancy. Matern. Child Health J. 18(8), 2013–2019 (2014)

    Article  PubMed  Google Scholar 

  21. R. a Rogvi, J.L. Forman, P. Damm, G. Greisen, Women born preterm or with inappropriate weight for gestational age are at risk of subsequent gestational diabetes and pre-eclampsia. PloS One 7(3), e34001 (2012)

    Article  PubMed  PubMed Central  Google Scholar 

  22. C.L. De Mola, G.V.A. De França, L. de Avila Quevedo, B.L. Horta, Low birth weight, preterm birth and small for gestational age association with adult depression: Systematic review and meta-analysis. Br. J. Psychiatry 205(5), 340–347 (2014)

    Article  Google Scholar 

  23. A.M. Sonnenschein-van der Voort, L.R. Arends, J.C. de Jongste, I. Annesi-Maesano, S.H. Arshad, H. Barros et al. Preterm birth, infant weight gain, and childhood asthma risk: A meta-analysis of 147,000 European children. J. Allergy Clin. Immunol. 133(5), 1317–1329 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  24. P. Christian, S.E. Lee, M. Donahue Angel, L.S. Adair, S.E. Arifeen, P. Ashorn et al. Risk of childhood undernutrition related to small-for-gestational age and preterm birth in low- and middle-income countries. Int J. Epidemiol. 42(5), 1340–1355 (2013)

    Article  PubMed  PubMed Central  Google Scholar 

  25. D.F. Stroup, J.A. Berlin, S.C. Morton, I. Olkin, G.D. Williamson, D. Rennie et al. Meta-analysis of observational studies in epidemiology: A proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. Jama 283(15), 2008–2012 (2000)

    Article  CAS  PubMed  Google Scholar 

  26. F. Foroutan, G. Guyatt, V. Zuk, P.O. Vandvik, A.C. Alba, R. Mustafa et al. GRADE Guidelines 28: Use of GRADE for the assessment of evidence about prognostic factors: rating certainty in identification of groups of patients with different absolute risks. J. Clin. Epidemiol. 121, 62–70 (2020)

    Article  PubMed  Google Scholar 

  27. Sinha S.K. Essential neonatal medicine / Sunil Sinha, Lawrence Miall, Luke Jardine. Jardine L, Levene MIEnm, Miall L, editors. Chichester, West Sussex; Hoboken, NJ: Wiley-Blackwell; 2012

  28. ACOG Committee Opinion No 579, Definition of term pregnancy. Obstet. Gynecol. 122(5), 1139–1140 (2013)

    Article  Google Scholar 

  29. World Health Organization. ICD-11: International statistical classification of diseases and related health problems: eleventh revision Geneva: World Health Organization; 2019 [updated 2019]. Available from: https://icd.who.int/browse11/l-m/en

  30. American Diabetes Association, 2. Classification and Diagnosis of Diabetes. Diabetes Care 39(Suppl 1), S13–S22 (2016)

    Article  Google Scholar 

  31. World Health Organization. Diagnostic criteria and classification of hyperglycaemia first detected in pregnancy. World Health Organization, 2013

  32. I. Blumer, E. Hadar, D.R. Hadden, L. Jovanovič, J.H. Mestman, M.H. Murad et al. Diabetes and pregnancy: an endocrine society clinical practice guideline. J. Clin. Endocrinol. Metab. 98(11), 4227–4249 (2013)

    Article  CAS  PubMed  Google Scholar 

  33. J.A. Hayden, D.A. van der Windt, J.L. Cartwright, P. Côté, C. Bombardier, Assessing bias in studies of prognostic factors. Ann. Intern Med. 158(4), 280–286 (2013)

    Article  PubMed  Google Scholar 

  34. J.L. Beauregard, C. Drews-Botsch, J.M. Sales, W.D. Flanders, M.R. Kramer, Does socioeconomic status modify the association between preterm birth and children’s early cognitive ability and kindergarten academic achievement in the United States? Am. J. Epidemiol. 187(8), 1704–1713 (2018)

    Article  PubMed  PubMed Central  Google Scholar 

  35. Gestational Hypertension and Preeclampsia, ACOG Practice Bulletin, Number 222. Obstet. Gynecol. 135(6), e237–e260 (2020)

    Article  Google Scholar 

  36. A. Laupacis, D.L. Sackett, R.S. Roberts, An assessment of clinically useful measures of the consequences of treatment. N. Engl. J. Med. 318(26), 1728–1733 (1988)

    Article  CAS  PubMed  Google Scholar 

  37. Y. Zhu, C. Zhang, Prevalence of gestational diabetes and risk of progression to type 2 diabetes: A global perspective. Curr. Diabetes Rep. 16(1), 7 (2016)

    Article  Google Scholar 

  38. M. Egger, G.D. Smith, M. Schneider, C. Minder, Bias in meta-analysis detected by a simple, graphical test. Bmj 315(7109), 629–634 (1997)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. C.G. Solomon, W.C. Willett, V.J. Carey, J. Rich-Edwards, D.J. Hunter, G.A. Colditz et al. A prospective study of pregravid determinants of gestational diabetes mellitus. Jama 278(13), 1078–1083 (1997)

    Article  CAS  PubMed  Google Scholar 

  40. National Collaborating Centre for Ws, Children’s H. National Institute for Health and Care Excellence: Clinical Guidelines. Diabetes in Pregnancy: Management of Diabetes and Its Complications from Preconception to the Postnatal Period. (National Institute for Health and Care Excellence (UK) Copyright © 2015 National Collaborating Centre for Women’s and Children’s Health, London), (2015)

    Google Scholar 

  41. N.S. Artzi, S. Shilo, E. Hadar, H. Rossman, S. Barbash-Hazan, A. Ben-Haroush et al. Prediction of gestational diabetes based on nationwide electronic health records. Nat. Med. 26(1), 71–76 (2020)

    Article  CAS  PubMed  Google Scholar 

  42. S. Boccia, K.J. Rothman, N. Panic, M.E. Flacco, A. Rosso, R. Pastorino et al. Registration practices for observational studies on ClinicalTrials.gov indicated low adherence. J. Clin. Epidemiol. 70, 176–182 (2016)

    Article  PubMed  Google Scholar 

  43. G. Rucker, G. Schwarzer, J.R. Carpenter, M. Schumacher, Undue reliance on I(2) in assessing heterogeneity may mislead. BMC Med. Res. Methodol. 8, 79 (2008)

    Article  PubMed  PubMed Central  Google Scholar 

  44. J.F. Plows, J.L. Stanley, P.N. Baker, C.M. Reynolds, M.H. Vickers, The Pathophysiology of Gestational Diabetes Mellitus. Int J. Mol. Sci. 19, 11 (2018)

    Article  Google Scholar 

  45. I.C. McMillen, J.S. Robinson, Developmental origins of the metabolic syndrome: prediction, plasticity, and programming. Physiol. Rev. 85(2), 571–633 (2005)

    Article  CAS  PubMed  Google Scholar 

  46. P.H. Whincup, S.J. Kaye, C.G. Owen, R. Huxley, D.G. Cook, S. Anazawa et al. Birth weight and risk of type 2 diabetes: a systematic review. Jama 300(24), 2886–2897 (2008)

    Article  CAS  PubMed  Google Scholar 

  47. T. Cundy, E. Ackermann, E.A. Ryan, Gestational diabetes: new criteria may triple the prevalence but effect on outcomes is unclear. Bmj 348, g1567 (2014)

    Article  PubMed  Google Scholar 

  48. T.A.O. Zhou, D. Sun, X. Li, Y. Heianza, H. Nisa, G. Hu et al. Prevalence and Trends in Gestational Diabetes Mellitus among Women in the United States, 2006–2016. Diabetes 67(Supplement 1), 121-OR (2018)

    Article  Google Scholar 

  49. J.J. Deeks, Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes. Stat. Med. 21(11), 1575–1600 (2002)

    Article  PubMed  Google Scholar 

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Acknowledgements

We wish to thank Anne Monique Nuyt, Ariane Boivin, Prabha H. Andraweera, and Shalem Leemaqz for kindly providing additional study data that were not included in the original reports. We are also grateful to Kyosuke Kamijo and Ayako Shibata for contributing a clinical perspective. We would like to thank Editage (www.editage.com) for English language editing.

Author contributions

YT is the guarantor of the review. YT had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: YT, YK, MB, ST, MK, and YY. Acquisition, analysis, or interpretation of data: All authors. Drafting of the paper: YT, YK, MB, and ST. Critical revision of the manuscript for important intellectual content: MK, YM, and YY. Statistical analysis: YT. Administrative, technical, or material support: YT, YK, MB, and ST. Study supervision: MK, YM, and YY.

Funding

The English editing fee was supported by the Systematic Review Peer Support Group (a not-for-profit organisation). The funders played no role in the design or conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the paper; or decision to submit the paper for publication.

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Authors and Affiliations

  1. Department of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine / School of Public Health, Yoshida Konoe cho, Sakyo-ku, Kyoto, Japan

    Yasushi Tsujimoto

  2. Department of Nephrology and Dialysis, Kyoritsu Hospital, Chuo-cho 16-5, Kawanishi, Hyogo, Japan

    Yasushi Tsujimoto

  3. Systematic Review Peer Support Group, Koraibashi, Chuo-ku, Osaka, Japan

    Yasushi Tsujimoto, Yuki Kataoka, Masahiro Banno & Shunsuke Taito

  4. Cochrane Japan, Akashi Cho 10-1, Chuo-ku, Tokyo, Japan

    Yasushi Tsujimoto, Yuko Masuzawa & Yoshiko Yamamoto

  5. Department of Healthcare Epidemiology, School of Public Health in the Graduate School of Medicine, Kyoto University, Yoshida Konoe cho, Sakyo-ku, Kyoto, Japan

    Yuki Kataoka & Masayo Kokubo

  6. Department of Internal Medicine, Kyoto Min-Iren Asukai Hospital, Tanaka Asukai-cho 89, Sakyo-ku, Kyoto, Japan

    Yuki Kataoka

  7. Section of Clinical Epidemiology, Department of Community Medicine, Kyoto University Graduate School of Medicine, Yoshida Konoe-cho, Sakyo-ku, Kyoto, Japan

    Yuki Kataoka

  8. Department of Psychiatry, Seichiryo Hospital, Tsurumai 4-16-27, Showa-ku, Nagoya, Aichi, Japan

    Masahiro Banno

  9. Department of Psychiatry, Nagoya University Graduate School of Medicine, Tsurumai-cho 65, Showa-ku, Nagoya, Aichi, Japan

    Masahiro Banno

  10. Division of Rehabilitation, Department of Clinical Practice and Support, Hiroshima University Hospital, Kasumi 1-2-3, Minami-ku, Hiroshima, Japan

    Shunsuke Taito

  11. Department of Neonatology, Nagano Children’s Hospital, Toyoshina 3100, Azumino, Nagano, Japan

    Masayo Kokubo

  12. Chiba Faculty of Nursing, Division of Nursing, Tokyo Healthcare University, Kai**chonishi 1-1042-2, Funabashi, Chiba, Japan

    Yuko Masuzawa

  13. Department of Health Policy, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, Japan

    Yoshiko Yamamoto

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  1. Yasushi Tsujimoto
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  2. Yuki Kataoka
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Correspondence to Yasushi Tsujimoto.

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Tsujimoto, Y., Kataoka, Y., Banno, M. et al. Gestational diabetes mellitus in women born small or preterm: Systematic review and meta-analysis. Endocrine 75, 40–47 (2022). https://doi.org/10.1007/s12020-021-02926-4

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