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Diabetologia

, Volume 62, Issue 9, pp 1561–1574 | Cite as

Neurocognitive and behavioural outcomes in offspring exposed to maternal pre-existing diabetes: a systematic review and meta-analysis

  • Jennifer M. YamamotoEmail author
  • Jamie L. Benham
  • Deborah Dewey
  • J. Johanna Sanchez
  • Helen R. Murphy
  • Denice S. Feig
  • Lois E. Donovan
Article

Abstract

Aims/hypothesis

We performed a systematic review and meta-analysis to determine whether exposure to maternal pre-existing diabetes in pregnancy is associated with neurocognitive or behavioural outcomes in offspring.

Methods

We searched MEDLINE, EMBASE, PsychINFO, the Cochrane Database of Systematic Reviews and Scopus for studies that examined any neurocognitive or behavioural outcomes in offspring of mothers with pre-existing diabetes in pregnancy in accordance with a published protocol (PROSPERO CRD42018109038). Title and abstract review, full-text review and data extraction were performed independently and in duplicate. Risk of bias was assessed using the Newcastle–Ottawa scale. Meta-analyses of summary measures were performed using random-effects models.

Results

Nineteen articles including at least 18,681 exposed and 2,856,688 control participants were identified for inclusion. Exposure to maternal pre-existing diabetes in pregnancy was associated with a lower pooled intelligence quotient in the offspring (pooled weighted mean difference −3.07 [95% CI −4.59, −1.55]; I2 = 0%) and an increased risk of autism spectrum disorders (effect estimate 1.98 [95% CI 1.46, 2.68]; I2 = 0%). There was also an increased risk of attention deficit/hyperactivity disorder (pooled HR 1.36 [95% CI 1.19, 1.55]; I2 = 0%), though this was based on only two studies. Although most studies were found to be high quality in terms of participant selection, in many studies, comparability of cohorts and adequacy of follow-up were sources of bias.

Conclusions/interpretation

There is evidence to suggest that in utero exposure to maternal pre-existing diabetes is associated with some adverse neurocognitive and behavioural outcomes. It remains unclear what the role of perinatal factors is and the degree to which other environmental factors contribute to these findings.

Keywords

ADHD ASD Autism Behaviour Childhood Diabetes IQ Meta-analysis Neurocognitive Offspring Pregnancy Systematic review 

Abbreviations

ADHD

Attention deficit/hyperactivity disorder

ASD

Autism spectrum disorder

GCSE

General Certificate of Secondary Education

IQ

Intelligence quotient

RR

Risk ratio

Notes

Acknowledgements

The authors would like to thank H. L. Robertson (University of Calgary, Calgary, Canada) for her expert advice in developing our search strategy. We also thank L. Lau (University of Calgary, Calgary, Canada) for her contribution to data extraction.

Contribution statement

JMY, JLB, LED, DSF, HRM, JJS and DD conceived and designed the study. JMY and JLB performed the search, data extraction and data analysis. JMY wrote the initial manuscript draft. JMY, JLB, LED, DSF, HRM, JJS and DD all participated in the critical revision of the manuscript for important intellectual content and approved the final version. JMY is the guarantor of this work, had full access to all of the study data and takes responsibility for the integrity of the data.

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

Supplementary material

125_2019_4923_MOESM1_ESM.pdf (170 kb)
ESM (PDF 170 kb)

References

  1. 1.
    Tennant PW, Glinianaia SV, Bilous RW, Rankin J, Bell R (2014) Pre-existing diabetes, maternal glycated haemoglobin, and the risks of fetal and infant death: a population-based study. Diabetologia 57(2):285–294.  https://doi.org/10.1007/s00125-013-3108-5 CrossRefPubMedGoogle Scholar
  2. 2.
    Murphy HR, Bell R, Cartwright C et al (2017) Improved pregnancy outcomes in women with type 1 and type 2 diabetes but substantial clinic-to-clinic variations: a prospective nationwide study. Diabetologia 60(9):1668–1677.  https://doi.org/10.1007/s00125-017-4314-3 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Feig DS, Donovan LE, Corcoy R et al (2017) Continuous glucose monitoring in pregnant women with type 1 diabetes (CONCEPTT): a multicentre international randomised controlled trial. Lancet 390(10110):2347–2359.  https://doi.org/10.1016/S0140-6736(17)32400-5 CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Evers IM, de Valk HW, Visser GH (2004) Risk of complications of pregnancy in women with type 1 diabetes: nationwide prospective study in the Netherlands. BMJ 328(7445):915.  https://doi.org/10.1136/bmj.38043.583160.EE CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Macintosh MC, Fleming KM, Bailey JA et al (2006) Perinatal mortality and congenital anomalies in babies of women with type 1 or type 2 diabetes in England, Wales, and Northern Ireland: population based study. BMJ 333(7560):177.  https://doi.org/10.1136/bmj.38856.692986.AE CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Mackin ST, Nelson SM, Kerssens JJ et al (2018) Diabetes and pregnancy: national trends over a 15 year period. Diabetologia 61(5):1081–1088.  https://doi.org/10.1007/s00125-017-4529-3 CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Clausen TD, Mortensen EL, Schmidt L et al (2011) Cognitive function in adult offspring of women with type 1 diabetes. Diabet Med 28(7):838–844.  https://doi.org/10.1111/j.1464-5491.2011.03300.x CrossRefPubMedGoogle Scholar
  8. 8.
    Temple RC, Hardiman M, Pellegrini M, Horrocks L, Martinez-Cengotitabengoa MT (2011) Cognitive function in 6- to 12-year-old offspring of women with type 1 diabetes. Diabet Med 28(7):845–848.  https://doi.org/10.1111/j.1464-5491.2011.03285.x CrossRefPubMedGoogle Scholar
  9. 9.
    Fraser A, Nelson SM, Macdonald-Wallis C, Lawlor DA (2012) Associations of existing diabetes, gestational diabetes, and glycosuria with offspring IQ and educational attainment: the Avon Longitudinal Study of Parents and Children. Exp Diabetes Res 2012:963735CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Xiang AH, Wang X, Martinez MP, Page K, Buchanan TA, Feldman RK (2018) Maternal type 1 diabetes and risk of autism in offspring. JAMA 320(1):89–91.  https://doi.org/10.1001/jama.2018.7614 CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Adane AA, Mishra GD, Tooth LR (2016) Diabetes in pregnancy and childhood cognitive development: a systematic review. Pediatrics 137(5):e20154234.  https://doi.org/10.1542/peds.2015-4234 CrossRefPubMedGoogle Scholar
  12. 12.
    Camprubi Robles M, Campoy C, Garcia Fernandez L, Lopez-Pedrosa JM, Rueda R, Martin MJ (2015) Maternal diabetes and cognitive performance in the offspring: a systematic review and meta-analysis. PLoS One 10(11):e0142583.  https://doi.org/10.1371/journal.pone.0142583 CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Stroup DF, Berlin JA, Morton SC et al (2000) 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.  https://doi.org/10.1001/jama.283.15.2008 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Wells G, Shae B, O’Connell D et al. (2013) The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Available from http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 22 Aug 2018
  15. 15.
    Zhang J, Yu KF (1998) What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 280(19):1690–1691.  https://doi.org/10.1001/jama.280.19.1690 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Burstyn I, Sithole F, Zwaigenbaum L (2010) Autism spectrum disorders, maternal characteristics and obstetric complications among singletons born in Alberta, Canada. Chronic Dis Can 30(4):125–134PubMedGoogle Scholar
  17. 17.
    Bytoft B, Knorr S, Vlachova Z et al (2016) Long-term cognitive implications of intrauterine hyperglycemia in adolescent offspring of women with type 1 diabetes (the EPICOM study). Diabetes Care 39(8):1356–1363.  https://doi.org/10.2337/dc16-0168 CrossRefPubMedGoogle Scholar
  18. 18.
    Bytoft B, Knorr S, Vlachova Z et al (2017) Assessment of attention deficits in adolescent offspring exposed to maternal type 1 diabetes. PLoS One 12(1):e0169308.  https://doi.org/10.1371/journal.pone.0169308 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Dodds L, Fell DB, Shea S, Armson BA, Allen AC, Bryson S (2011) The role of prenatal, obstetric and neonatal factors in the development of autism. J Autism Dev Disord 41(7):891–902.  https://doi.org/10.1007/s10803-010-1114-8 CrossRefPubMedGoogle Scholar
  20. 20.
    Hod M, Levy-Shiff R, Lerman M, Schindel B, Ben-Rafael Z, Bar J (1999) Developmental outcome of offspring of pregestational diabetic mothers. J Pediatr Endocrinol Metab 12(6):867–872CrossRefPubMedGoogle Scholar
  21. 21.
    Ji J, Chen T, Sundquist J, Sundquist K (2018) Type 1 diabetes in parents and risk of attention deficit/hyperactivity disorder in offspring: a population-based study in Sweden. Diabetes Care 41(4):770–774.  https://doi.org/10.2337/dc17-0592 CrossRefPubMedGoogle Scholar
  22. 22.
    Knorr S, Clausen TD, Vlachova Z et al (2015) Academic achievement in primary school in offspring born to mothers with type 1 diabetes (the EPICOM study): a register-based prospective cohort study. Diabetes Care 38(7):1238–1244.  https://doi.org/10.2337/dc15-0223 CrossRefPubMedGoogle Scholar
  23. 23.
    Kong L, Norstedt G, Schalling M, Gissler M, Lavebratt C (2018) The risk of offspring psychiatric disorders in the setting of maternal obesity and diabetes. Pediatrics 142(3):e20180776.  https://doi.org/10.1542/peds.2018-0776 CrossRefPubMedGoogle Scholar
  24. 24.
    Kowalczyk M, Ircha G, Zawodniak-Szalapska M, Cypryk K, Wilczynski J (2002) Psychomotor development in the children of mothers with type 1 diabetes mellitus or gestational diabetes mellitus. J Pediatr Endocrinol Metab 15(3):277–281CrossRefPubMedGoogle Scholar
  25. 25.
    Li M, Fallin MD, Riley A et al (2016) The association of maternal obesity and diabetes with autism and other developmental disabilities. Pediatrics 137(2):e20152206.  https://doi.org/10.1542/peds.2015-2206 CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Mann JR, Pan C, Rao GA, McDermott S, Hardin JW (2013) Children born to diabetic mothers may be more likely to have intellectual disability. Matern Child Health J 17(5):928–932.  https://doi.org/10.1007/s10995-012-1072-1 CrossRefPubMedGoogle Scholar
  27. 27.
    Ornoy A, Ratzon N, Greenbaum C, Peretz E, Soriano D, Dulitzky M (1998) Neurobehaviour of school age children born to diabetic mothers. Arch Dis Child Fetal Neonatal Ed 79(2):F94–F99.  https://doi.org/10.1136/fn.79.2.F94 CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Persson B, Gentz J (1984) Follow-up of children of insulin-dependent and gestational diabetic mothers. Neuropsychological outcome. Acta Paediatr Scand 73(3):349–358.  https://doi.org/10.1111/j.1651-2227.1994.tb17747.x CrossRefPubMedGoogle Scholar
  29. 29.
    Rizzo T, Metzger BE, Burns WJ, Burns K (1991) Correlations between antepartum maternal metabolism and intelligence of offspring. N Engl J Med 325(13):911–916.  https://doi.org/10.1056/NEJM199109263251303 CrossRefPubMedGoogle Scholar
  30. 30.
    Sells CJ, Robinson NM, Brown Z, Knopp RH (1994) Long-term developmental follow-up of infants of diabetic mothers. J Pediatr 125(1):S9–S17.  https://doi.org/10.1016/S0022-3476(94)70170-9 CrossRefPubMedGoogle Scholar
  31. 31.
    Potharst ES, Houtzager BA, van Sonderen L et al (2012) Prediction of cognitive abilities at the age of 5 years using developmental follow-up assessments at the age of 2 and 3 years in very preterm children. Dev Med Child Neurol 54(3):240–246.  https://doi.org/10.1111/j.1469-8749.2011.04181.x CrossRefPubMedGoogle Scholar
  32. 32.
    Shah R, Harding J, Brown J, McKinlay C (2018) Neonatal glycaemia and neurodevelopmental outcomes: a systematic review and meta-analysis. Neonatology 115:116–126CrossRefPubMedGoogle Scholar
  33. 33.
    Xu G, Jing J, Bowers K, Liu B, Bao W (2014) Maternal diabetes and the risk of autism spectrum disorders in the offspring: a systematic review and meta-analysis. J Autism Dev Disord 44(4):766–775.  https://doi.org/10.1007/s10803-013-1928-2 CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Wan H, Zhang C, Li H, Luan S, Liu C (2018) Association of maternal diabetes with autism spectrum disorders in offspring: a systemic review and meta-analysis. Medicine 97(2):e9438.  https://doi.org/10.1097/MD.0000000000009438 CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Li YM, Ou JJ, Liu L, Zhang D, Zhao JP, Tang SY (2016) Association between maternal obesity and autism spectrum disorder in offspring: a meta-analysis. J Autism Dev Disord 46(1):95–102.  https://doi.org/10.1007/s10803-015-2549-8 CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Medicine, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
  2. 2.Department of Obstetrics and Gynecology, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
  3. 3.Alberta Children’s Hospital Research Institute, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
  4. 4.Department of Community Health Sciences, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
  5. 5.Department of Paediatrics, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
  6. 6.Owerko Centre at the Alberta Children’s Hospital Research Institute, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
  7. 7.Sunnybrook Research InstituteTorontoCanada
  8. 8.Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation TrustCambridgeUK
  9. 9.Women’s Health Academic Centre, Division of Women’s and Children’s HealthKing’s College LondonLondonUK
  10. 10.Norwich Medical SchoolUniversity of East AngliaNorwichUK
  11. 11.Mount Sinai HospitalTorontoCanada
  12. 12.Lunenfeld-Tanenbaum Research InstituteTorontoCanada
  13. 13.Department of MedicineUniversity of TorontoTorontoCanada

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