Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.


Maternal prepregnancy body mass index and offspring white matter microstructure: results from three birth cohorts


Background and aims

Prepregnancy maternal obesity is a global health problem and has been associated with offspring metabolic and mental ill-health. However, there is a knowledge gap in understanding potential neurobiological factors related to these associations. This study explored the relation between maternal prepregnancy body mass index (BMI) and offspring brain white matter microstructure at the age of 6, 10, and 26 years in three independent cohorts.

Subjects and methods

The study used data from three European birth cohorts (n = 116 children aged 6 years, n = 2466 children aged 10 years, and n = 437 young adults aged 26 years). Information on maternal prepregnancy BMI was obtained before or during pregnancy and offspring brain white matter microstructure was measured at age 6, 10, or 26 years. We used magnetic resonance imaging-derived fractional anisotropy (FA) and mean diffusivity (MD) as measures of white matter microstructure in the brainstem, callosal, limbic, association, and projection tracts. Linear regressions were fitted to examine the association of maternal BMI and offspring white matter microstructure, adjusting for several socioeconomic and lifestyle-related confounders, including education, smoking, and alcohol use.


Maternal BMI was associated with higher FA and lower MD in multiple brain tracts, for example, association and projection fibers, in offspring aged 10 and 26 years, but not at 6 years. In each cohort maternal BMI was related to different white matter tract and thus no common associations across the cohorts were found.


Maternal BMI was associated with higher FA and lower MD in multiple brain tracts in offspring aged 10 and 26 years, but not at 6 years of age. Future studies should examine whether our observations can be replicated and explore the potential causal nature of the findings.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1
Fig. 2


  1. 1.

    Whitaker RC. Predicting preschooler obesity at birth: the role of maternal obesity in early pregnancy. Pediatrics. 2004;114:e29–e36.

    Article  Google Scholar 

  2. 2.

    Chu SY, Callaghan WM, Kim SY, Schmid CH, Lau J, England LJ, et al. Maternal obesity and risk of gestational diabetes mellitus. Diabetes Care. 2007;30:2070–6.

    Article  Google Scholar 

  3. 3.

    Reynolds RM, Allan KM, Raja EA, Bhattacharya S, McNeill G, Hannaford PC, et al. Maternal obesity during pregnancy and premature mortality from cardiovascular event in adult offspring: follow-up of 1 323 275 person years. BMJ. 2013;347:f4539.

    Article  Google Scholar 

  4. 4.

    Basatemur E, Gardiner J, Williams C, Melhuish E, Barnes J, Sutcliffe A. Maternal prepregnancy BMI and child cognition: a longitudinal cohort study. Pediatrics. 2013;131:56–63.

    Article  Google Scholar 

  5. 5.

    Bliddal M, Olsen J, Støvring H, Eriksen H-LF, Kesmodel US, TIA Sørensen, et al. Maternal pre-pregnancy BMI and intelligence quotient (IQ) in 5-year-old children: a cohort based study. PLoS ONE. 2014;9:e94498.

    Article  Google Scholar 

  6. 6.

    Heikura U, Taanila A, Hartikainen A-L, Olsén P, Linna S-L, Wendt Lvon, et al. Variations in prenatal sociodemographic factors associated with intellectual disability: a study of the 20-year interval between two birth cohorts in Northern Finland. Am J Epidemiol. 2008;167:169–77.

    Article  Google Scholar 

  7. 7.

    Hinkle SN, Schieve LA, Stein AD, Swan DW, Ramakrishnan U, Sharma AJ. Associations between maternal prepregnancy body mass index and child neurodevelopment at 2 years of age. Int J Obes. 2012;36:1312–9.

    CAS  Article  Google Scholar 

  8. 8.

    Huang L, Yu X, Keim S, Li L, Zhang L, Zhang J. Maternal prepregnancy obesity and child neurodevelopment in the Collaborative Perinatal Project. Int J Epidemiol. 2014;43:783–92.

    Article  Google Scholar 

  9. 9.

    Widen EM, Kahn LG, Cirillo P, Cohn B, Kezios KL, Factor-Litvak P. Prepregnancy overweight and obesity are associated with impaired child neurodevelopment. Matern Child Nutr. 2018;14:n/a–n/a.

    Article  Google Scholar 

  10. 10.

    Yeung EH, Sundaram R, Ghassabian A, Xie Y, Louis GB. Parental obesity and early childhood development. Pediatrics. 2017;139:e20161459.

    Article  Google Scholar 

  11. 11.

    Mina TH, Lahti M, Drake AJ, Denison FC, Räikkönen K, Norman JE, et al. Prenatal exposure to maternal very severe obesity is associated with impaired neurodevelopment and executive functioning in children. Pediatr Res. 2017;82:47–54.

    Article  Google Scholar 

  12. 12.

    Rodriguez A. Maternal pre-pregnancy obesity and risk for inattention and negative emotionality in children. J Child Psychol Psychiatry. 2010;51:134–43.

    Article  Google Scholar 

  13. 13.

    Deardorff J, Smith LH, Petito L, Kim H, Abrams BF. Maternal prepregnancy weight and children’s behavioral and emotional outcomes. Am J Prev Med. 2017;53:432–40.

    Article  Google Scholar 

  14. 14.

    Adane AA, Mishra GD, Tooth LR. Maternal pre-pregnancy obesity and childhood physical and cognitive development of children: a systematic review. Int J Obes. 2016;40:1608–18.

    CAS  Article  Google Scholar 

  15. 15.

    Li X, Andres A, Shankar K, Pivik RT, Glasier CM, Ramakrishnaiah RH, et al. Differences in brain functional connectivity at resting state in neonates born to healthy obese or normal-weight mothers. Int J Obes. 2016;40:1931–4.

    CAS  Article  Google Scholar 

  16. 16.

    Ou X, Thakali KM, Shankar K, Andres A, Badger TM. Maternal adiposity negatively influences infant brain white matter development. Obesity. 2015;23:1047–54.

    CAS  Article  Google Scholar 

  17. 17.

    Campoy C, Martín-Bautista E, García-Valdés L, Florido J, Agil A, Lorente JA, et al. Study of maternal nutrition and genetic on the foetal adiposity programming: The PREOBE study. Nutr Hosp. 2008;23:584–90.

    CAS  PubMed  Google Scholar 

  18. 18.

    Kooijman MN, Kruithof CJ, Duijn CM, van, Duijts L, Franco OH, van IJzendoorn MH. et al. The Generation R Study: design and cohort update 2017. Eur J Epidemiol. 2016;31:1243–64.

    Article  Google Scholar 

  19. 19.

    White T, Muetzel RL, Marroun HE, Blanken LME, Jansen P, Bolhuis K, et al. Paediatric population neuroimaging and the Generation R Study: the second wave. Eur J Epidemiol. 2018;33:99–125.

    Article  Google Scholar 

  20. 20.

    Riitta JM, Anna‐Liisa H‐S, Paula R. Labour induction policy in hospitals of different levels of specialisation. Int J Obstet Gynaecol. 2005;100:310–5.

    Google Scholar 

  21. 21.

    Björnholm L, Nikkinen J, Kiviniemi V, Nordström T, Niemelä S, Drakesmith M, et al. Structural properties of the human corpus callosum: multimodal assessment and sex differences. Neuroimage. 2017;152:108–18.

    Article  Google Scholar 

  22. 22.

    Olsén P, Läärä E, Rantakallio P, Järvelin M-R, Sarpola A, Hartikainen A-L. Epidemiology of preterm delivery in two birth cohorts with an interval of 20 years. Am J Epidemiol. 1995;142:1184–93.

    Article  Google Scholar 

  23. 23.

    Muetzel RL, Blanken LME, van der Ende J, El Marroun H, Shaw P, Sudre G. et al. Tracking brain evelopment and dimensional psychiatric symptoms in hildren: a longitudinal population-based neuroimaging study. AJP. 2017;175:54–62.

    Article  Google Scholar 

  24. 24.

    Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM. FSL. Neuroimage. 2012;62:782–90.

    Article  Google Scholar 

  25. 25.

    Haselgrove JC, Moore JR. Correction for distortion of echo-planar images used to calculate the apparent diffusion coefficient. Magn Reson Med. 1996;36:960–4.

    CAS  Article  Google Scholar 

  26. 26.

    Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17:143–55.

    Article  Google Scholar 

  27. 27.

    Groot M, de Ikram MA, Akoudad S, Krestin GP, Hofman A, Lugt Avander. et al. Tract-specific white matter degeneration in aging: The Rotterdam Study. Alzheimer’s Dement. 2015;11:321–30.

    Article  Google Scholar 

  28. 28.

    Gaillard R, Welten M, Oddy WH, Beilin LJ, Mori TA, Jaddoe VWV et al. Associations of maternal prepregnancy body mass index and gestational weight gain with cardio-metabolic risk factors in adolescent offspring: a prospective cohort study. BJOG 2016;123: 207–16.

  29. 29.

    Jharap VV, Santos S, Steegers EAP, Jaddoe VWV, Gaillard R. Associations of maternal obesity and excessive weight gain during pregnancy with subcutaneous fat mass in infancy. Early Hum Dev. 2017;108:23–28.

    Article  Google Scholar 

  30. 30.

    Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodol). 1995;57:289–300.

    Google Scholar 

  31. 31.

    R Core Team (2018). R: A language and environment for statistical computing. R foundation for Statistical Computing, Vienna, Austria. URL

  32. 32.

    Aubert-Broche B, Fonov V, Leppert I, Pike GB, Collins DL. Human brain myelination from birth to 4.5 years. Med Image Comput Comput Assist Interv. 2008;11:180–7.

    CAS  PubMed  Google Scholar 

  33. 33.

    Carnell S, Benson L, Chang K-Y (Virginia), Wang Z, Huo Y, Geliebter A. et al. Neural correlates of familial obesity risk and overweight in adolescence. Neuroimage. 2017;159:236–47.

    Article  Google Scholar 

  34. 34.

    Hayden BY, Platt ML. Neurons in anterior cingulate cortex multiplex information about reward and action. J Neurosci. 2010;30:3339–46.

    CAS  Article  Google Scholar 

  35. 35.

    LaMantia AS, Rakic P. Axon overproduction and elimination in the corpus callosum of the developing rhesus monkey. J Neurosci. 1990;10:2156–75.

    CAS  Article  Google Scholar 

  36. 36.

    LaMantia AS, Rakic P. Axon overproduction and elimination in the anterior commissure of the developing rhesus monkey. J Comp Neurol. 1994;340:328–36.

    CAS  Article  Google Scholar 

  37. 37.

    Paus T. Growth of white matter in the adolescent brain: myelin or axon? Brain Cogn. 2010;72:26–35.

    Article  Google Scholar 

  38. 38.

    Graf AE, Haines KM, Pierson CR, Bolon BN, Houston RH, Velten M, et al. Perinatal inflammation results in decreased oligodendrocyte numbers in adulthood. Life Sci. 2014;94:164–71.

    CAS  Article  Google Scholar 

  39. 39.

    Madan JC, Davis JM, Craig WY, Collins M, Allan W, Quinn R, et al. Maternal obesity and markers of inflammation in pregnancy. Cytokine. 2009;47:61–64.

    CAS  Article  Google Scholar 

  40. 40.

    Burg JW, van der, Sen S, Chomitz VR, Seidell JC, Leviton A, Dammann O. The role of systemic inflammation linking maternal BMI to neurodevelopment in children. Pediatr Res. 2015;79:3–12.

    Article  Google Scholar 

  41. 41.

    Graf AE, Lallier SW, Waidyaratne G, Thompson MD, Tipple TE, Hester ME, et al. Maternal high fat diet exposure is associated with increased hepcidin levels, decreased myelination, and neurobehavioral changes in male offspring. Brain Behav Immun. 2016;58:369–78.

    CAS  Article  Google Scholar 

  42. 42.

    White CL, Pistell PJ, Purpera MN, Gupta S, Fernandez-Kim S-O, Hise TL, et al. Effects of high fat diet on Morris maze performance, oxidative stress, and inflammation in rats: contributions of maternal diet. Neurobiol Dis. 2009;35:3–13.

    CAS  Article  Google Scholar 

  43. 43.

    Bergmann S, Schlesier-Michel A, Wendt V, Grube M, Keitel-Korndörfer A, Gausche R et al. Maternal weight predicts children’s psychosocial development via parenting stress and emotional availability. Front Psychol. 2016; 7:1156.

  44. 44.

    Panagos PG, Vishwanathan R, Penfield-Cyr A, Matthan NR, Shivappa N, Wirth MD, et al. Breastmilk from obese mothers has pro-inflammatory properties and decreased neuroprotective factors. J Perinatol. 2016;36:284–90.

    CAS  Article  Google Scholar 

  45. 45.

    Edlow A, Hui L, Wick H, Fried I, Bianchi D. Assessing the fetal effects of maternal obesity via transcriptomic analysis of cord blood: a prospective case–control study. BJOG. 2016;123:180–9.

    CAS  Article  Google Scholar 

  46. 46.

    Lebel C, Gee M, Camicioli R, Wieler M, Martin W, Beaulieu C. Diffusion tensor imaging of white matter tract evolution over the lifespan. Neuroimage. 2012;60:340–52.

    CAS  Article  Google Scholar 

  47. 47.

    Keim SA, Branum AM, Klebanoff MA, Zemel BS. Maternal body mass index and daughters’ age at menarche. Epidemiology. 2009;20:677–81.

    Article  Google Scholar 

  48. 48.

    Birdsill AC, Oleson S, Kaur S, Pasha E, Ireton A, Tanaka H, et al. Abdominal obesity and white matter microstructure in midlife. Hum Brain Mapp. 2017;38:3337–44.

    PubMed  PubMed Central  Google Scholar 

  49. 49.

    Ong ZY, Muhlhausler BS. Maternal “junk-food” feeding of rat dams alters food choices and development of the mesolimbic reward pathway in the offspring. FASEB J. 2011;25:2167–79.

    CAS  Article  Google Scholar 

  50. 50.

    Stachowiak EK, Srinivasan M, Stachowiak MK, Patel MS. Maternal obesity induced by a high fat diet causes altered cellular development in fetal brains suggestive of a predisposition of offspring to neurological disorders in later life. Metab Brain Dis. 2013;28:721–5.

    CAS  Article  Google Scholar 

  51. 51.

    Williams L, Seki Y, Vuguin PM, Charron MJ. Animal models of in utero exposure to a high fat diet: a review. Biochim Biophys Acta. 2014;1842:507–19.

    CAS  Article  Google Scholar 

Download references


This work was supported by the European Union’s Horizon 2020 research and innovation program [grant agreement no. 633595 DynaHEALTH] and no. 733206 LifeCycle], the Netherlands Organization for Health Research and Development [ZONMW Vici project 016.VICI.170.200]. The PREOBE cohort was funded by Spanish Ministry of Innovation and Science. Junta de Andalucía: Excellence Projects (P06-CTS-02341) and Spanish Ministry of Economy and Competitiveness (BFU2012-40254-C03-01). The first phase of the Generation R Study is made possible by financial support from the Erasmus Medical Centre, the Erasmus University, and the Netherlands Organization for Health Research and Development (ZonMW, grant ZonMW Geestkracht 10.000.1003). The Northern Finland Birth Cohort 1986 is funded by University of Oulu, University Hospital of Oulu, Academy of Finland (EGEA), Sigrid Juselius Foundation, European Commission (EURO-BLCS, Framework 5 award QLG1-CT-2000-01643), NIH/NIMH (5R01MH63706:02)

Author information



Corresponding author

Correspondence to Hanan El Marroun.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Verdejo-Román, J., Björnholm, L., Muetzel, R.L. et al. Maternal prepregnancy body mass index and offspring white matter microstructure: results from three birth cohorts. Int J Obes 43, 1995–2006 (2019).

Download citation

Further reading


Quick links