Do adversities in the intrauterine and neonatal periods interfere with intelligence?

Authors

DOI:

https://doi.org/10.11606/s1518-8787.2025059006206

Keywords:

Fetal Growth Retardation, Socioeconomic Factors, Intelligence

Abstract

Objective: Investigate the effects of intrauterine growth restriction and socioeconomic status at birth on intellectual development. 
Methods: Study conducted with 313 participants from a birth cohort from São Luís, in the state of Maranhão, assessed at birth and between 18 and 19 years of age. Variables at birth and early years of life (maternal age, maternal education, paternal education, occupation of the head of the household, family income, maternal gestational weight gain, intrauterine growth restriction, low birth weight, and breastfeeding duration), and education at 18 and 19 years were tested as determinants of intelligence quotient at 18 and 19 years using structural equation modeling. 
Results: Results: Intrauterine growth restriction did not have a total (p-value = 0.957), direct (p-value = 0.184), or indirect (p-value = 0.108) effect on the intelligence quotient at 18 and 19 years of age. Socioeconomic status at birth had a total positive effect of 0.406 standard deviations (p-value < 0.001) on its mean, corresponding to an increase of 4.54 points in the quotient for each increase in socioeconomic level at birth. This effect was not mediated by the other explanatory variables included in the model; however, a direct positive effect of 0.416 (p-value < 0.001) of socioeconomic status on education was identified, which showed a positive correlation (PC = 0.439; p-value < 0.001) with intelligence. Maternal age at birth also had a direct positive effect of 0.116 standard deviations (p-value = 0.042) on the mean intelligence quotient (QI) at 18 and 19 years, corresponding to an increase of 1.30 points for each 1-year increase in maternal age at birth. 
Conclusion: Higher socioeconomic levels at birth directly affected the participant’s intelligence and education positively, increasing the mean QI and education level at 18 and 19 years. A positive correlation was also identified between the two variables.

Downloads

Download data is not yet available.

References

1. Gottfredson LS. Intelligence and social inequality. In: Chamorro-Premuzik T, Stumm S von Furnham A, editors. The Handbook of Individual Differences. Hoboken: Wiley-Blackwell; 2010. p. 1-63.

2. Nakano T de C, Moraes IDT de, Oliveira AW de. Relação entre inteligência e competências socioemocionais em crianças e adolescentes. Rev Psicol. 2019;37(2):407-24. http://dx.doi.org/10.18800/psico.201902.002

3. Victora CG, Hartwig FP, Vidaletti LP, Martorell R, Osmond C, Richter LM, et al. Effects of early-life poverty on health and human capital in children and adolescents: analyses of national surveys and birth cohort studies in LMICs. The Lancet. 2022;399(10336):1741-52. https://doi.org/10.1016/S0140-6736(21)02716-1

4. Plomin R, von Stumm S. The new genetics of intelligence. Nat Rev Genet. 2018;19(3):148-59. https://doi.org/10.1038/nrg.2017.104

5. Koenis MMG, Brouwer RM, Swagerman SC, van Soelen ILC, Boomsma DI, Hulshoff Pol HE. Association between structural brain network efficiency and intelligence increases during adolescence. Hum Brain Mapp. 2018;39(2):822-36. https://doi.org/10.1002/hbm.23885

6. Takeuchi H, Taki Y, Asano K, Asano M, Sassa Y, Yokota S, et al. Childhood socioeconomic status is associated with psychometric intelligence and microstructural brain development. Commun Biol. 2021;4(470). https://doi.org/10.1038/s42003-021-01974-w

7. McDermott CL, Seidlitz J, Nadig A, Liu S, Clasen LS, Blumenthal JD et al. Longitudinally mapping childhood socioeconomic status associations with cortical and subcortical morphology. J Neurosc. 2019;39(8):1365-73. http://doi.org/10.1523/JNEUROSCI.1808-18.2018

8. Bick J, Nelson CA. Early adverse experiences and the developing brain. Neuropsychopharmacol. 2016;41(1):177-96. http://doi.org/10.1038/npp.2015.252

9. Chen Y, Baram TZ. Toward understanding how early-life stress reprograms cognitive and emotional brain networks. Neuropsychopharmacol. 2015;41:197-206. http://doi.org/10.1038/npp.2015.181

10. Jensen RB, Juul A, Larsen T, Mortensen EL, Greisen G. Cognitive ability in adolescents born small for gestational age: Associations with fetal growth velocity, head circumference and postnatal growth. Early Hum Dev. 2015;91(12):755-60. http://doi.org/10.1016/j.earlhumdev.2015.08.014

11. Luby JL, Belden AC, Whalen D, Harms MP, Barch DM. Breastfeeding and Childhood IQ: The Mediating Role of Gray Matter Volume. J Am Acad Child Adolesc Psychiatry. 2016;55(5):367-75. https://doi.org/10.1016/j.jaac.2016.02.009

12. Sacchi C, Marino C, Nosarti C, Vieno A, Visentin S, Simonelli A. Association of intrauterine growth restriction and small for gestational age status with childhood cognitive outcomes: A systematic review and meta-analysis. JAMA Pediatr. 2020;174(8):772-81. https://doi. org/10.1001/jamapediatrics.2020.1097

13. Cohen E, Baerts W, Van Bel F. Brain-Sparing in Intrauterine Growth Restriction: Considerations for the Neonatologist. Neonatol. 2015;108(4):269-76. https://doi.org/10.1159/000438451

14. McCowan LM, Figueras F, Anderson NH. Evidence-based national guidelines for the management of suspected fetal growth restriction: comparison, consensus, and controversy. Am J Obstet Gynecol. 2018;218(2):S855-S868. https://doi.org/10.1016/j.ajog.2017.12.004

15. Miller SL, Huppi PS, Mallard C. The consequences of fetal growth restriction on brain structure and neurodevelopmental outcome. J Physiol. 2016;594(4):807-23. https://doi.org/10.1113/jp271402

16. Cohen E, Baerts W, Van Bel F. Brain-Sparing in Intrauterine Growth Restriction: Considerations for the Neonatologist. Neonatol. 2015;108(4):269-76. https://doi.org/10.1159/000438451

17. Arthurs OJ, Rega A, Guimiot F, Berlabi N, Rosenblatt J, Biran V, et al. Diffusion-weighted magnetic resonance imaging of the fetal brain in intrauterine growth restriction. Ultrasound Obstet Gynecol. 2017;50(1):79-87. https://doi.org/10.1002/uog.17318

18. Ostgård HF, Løhaugen GCC, Bjuland KJ, Rimol LM, Brubakk A-M, Martinussen M et al. Brain morphometry and cognition in young adults born small for gestational age at term. J Pediatr. 2014;165(5):921-7.e1. https://doi.org/10.1016/j.jpeds.2014.07.045

19. Paz I, Laor A, Gale R, Harlap S, Stevenson DK, Seidman DS. Term infants with fetal growth restriction are not at increased risk for low intelligence scores at age 17 years. J Pediatr. 2001;138(1):87-91. https://doi.org/10.1067/mpd.2001.110131

20. Bergvall N, Iliadou A, Tuvemo T, Cnattingius S. Birth characteristics and risk of low intellectual performance in early adulthood: Are the associations confounded by socioeconomic factors in adolescence or familial effects? Pediatr. 2006;117(3):714-21. https://doi.org/10.1542/peds.2005-0735

21. Black MM, Walker SP, Fernald LCH, Andersen CT, DiGirolamo AM, Lu C, et al. Early childhood development coming of age: science through the life course. The Lancet. 2017;389(10064):77-90. https://doi.org/10.1016/S0140-6736(16)31389-7

22. Takeuchi H, Taki Y, Asano K, Asano M, Sassa Y, Yokota S, et al. Childhood socioeconomic status is associated with psychometric intelligence and microstructural brain development. Commun Biol. 2021;4(1). https://doi.org/10.1038/s42003-021-01974-w

23. McDermott CL, Seidlitz J, Nadig A, Liu S, Clasen LS, Blumenthal JD, et al. Longitudinally mapping childhood socioeconomic status associations with cortical and subcortical morphology. J Neurosc. 2019;39(8):1365-73. https://doi.org/10.1523/JNEUROSCI.1808-18.2018

24. Silva AAM, Coimbra LC, Silva RA, Britto e Alves MTSS de, Lamy Filho F, Lamy ZC, et al. Perinatal health and mother-child health care in the municipality of São Luís, Maranhão State, Brazil. Cad Saude Publica. 2001;17(6):1413-23. https://doi.org/10.1590/s0102-311x2001000600012

25. Silva AAM, Barbieri MA, Cardoso VC, Batista RF, Simões VM, Vianna EO et al. Prevalence of non-communicable diseases in Brazilian children: Follow-up at school age of two Brazilian birth cohorts of the 1990’s. BMC Public Health. 2011;11(486). https://doi.org/10.1186/1471-2458-11-486

26. Simões VMF, Batista RFL, Britto e Alves MTSS de, Ribeiro CCC, Thomaz EBAF, Carvalho CA de et al. Health of adolescents in the 1997/1998 birth cohort in São Luís, Maranhão State, Brazil. Cad Saude Publica. 2020;36(7). https://doi.org/10.1590/0102-311X00164519

27. Kramer MS. Socioeconomic determinants of intrauterine growth retardation. Eur J Clin Nutr. 1998;52(Suppl 1): S29-32. https://pubmed.ncbi.nlm.nih.gov/9511017/

28. Williams Rl, Creasy Rk, Cunningham G, Hawes We, Norris Fk, Tashiro M. Fetal growth and perinatal viability in California. Obstet Gynecol. 1982;59:624-32.

29. Wechsler D. WAIS-III: Escala de Inteligência Wechsler Para Adultos. São Paulo: Casa do Psicólogo; 2004.

30. Kline RB. Principles and Practice of Structural Equation Modeling. Nova York: The GuilfordPress; 2011.

31. Wang J, Wang X. Structural Equation Modeling: Applications Using Mplus. Uttar Pradesh: Thomson Digital; 2012.

32. Brasil. Resolução n0 466, de 12 de Dezembro de 2012. Brasília: Conselho Nacional de Saúde; 2012.

33. Arthurs OJ, Rega A, Guimiot F, Rosenblatt J, Biran V, Elmaleh M et al. Diffusion-weighted magnetic resonance imaging of the fetal brain in intrauterine growth restriction. Ultrasound Obstet Gynecol. 2017;50(1):79-87. https://doi.org/10.1002/uog.17318

34. Ostgård HF, Løhaugen GCC, Bjuland KJ, Rimol LM, Brubakk A-M, Martinussen M et al. Brain morphometry and cognition in young adults born small for gestational age at term. J Pediatr. 2014;165(5):921-7.E1. https:doi.org/10.1016/j.jpeds.2014.07.045

35. Sacchi C, Marino C, Nosarti C, Vieno A, Visentin S, Simonelli A. Association of intrauterine growth restriction and small for gestational age status with childhood cognitive outcomes: A systematic review and meta-analysis. JAMA Pediatr. 2020;174(8):772-81. https:doi.org/10.1001/jamapediatrics.2020.1097

36. Jensen RB, Juul A, Larsen T, Mortensen EL, Greisen G. Cognitive ability in adolescents born small for gestational age: Associations with fetal growth velocity, head circumference and postnatal growth. Early Hum Dev. 2015;91(12):755-60. https:doi.org/10.1016/j.earlhumdev.2015.08.014

37. Cave SN, Wright M, Von Stumm S. Change and stability in the association of parents’ education with children’s intelligence. Intelligence. 2022;90(2021 Nov):101597. https:doi.org/10.1016/j.intell.2021.101597

38. Rindermann H. Ceci SJ. Parents’ Education Is More Important Than Their Wealth in Shaping Their Children’ s Intelligence : Results of 19 Samples in Seven Countries at Different Developmental Levels. J Educ Gift. 2018;41(4):298-326. https://doi.org/10.1177/0162353218799481

39. Brito NH, Noble KG. Socioeconomic status and structural brain development. Front Neurosci. 2014;(8):1-12. https://doi.org/10.3389/fnins.2014.00276

40. Evans GW, Kim P. Childhood poverty and health: Cumulative risk exposure and stress dysregulation. Psychol Sci. 2007;18(11):953-7. https://doi.org/10.1111/j.1467-9280.2007.02008.x

41. Shonkoff JP, Garner AS, Siegel BS, Dobbins MI, Earls MF, McGuinn L et al. The lifelong effects of early childhood adversity and toxic stress. Pediatr. 2012;129(1):e232-e246. https://doi.org/10.1542/peds.2011-2663

42. Lemos GC, Almeida LS, Colom R. Intelligence of adolescents is related to their parents’ educational level but not to family income. Pers Individ Dif. 2011;50(7):1062-7. https://doi.org/10.1016/j.paid.2011.01.025

43. Rindermann H, Baumeister AEE. Parents’ SES vs. parental educational behavior and children’s development: A reanalysis of the Hart and Risley study. Learn Individ Differ. 2015;37:133-8. doi:https://doi.org/10.1016/j.lindif.2014.12.005

44. Jeong J, McCoy DC, Fink G. Paternal and maternal education, caregivers’ support for learning, and early child development in 44 low- and middle-income countries. Early Child Res Q. 2017;41:136-48. https://doi.org/10.1016/j.ecresq.2017.07.001

45. Kornrich S, Furstenberg F. Investing in Children: Changes in Parental Spending on Children, 1972-2007. Demogr. 2013;50(1):1-23.https://doi.org/10.1007/s13524-012-0146-4

46. Gould ED, Simhon A, Weinberg BA. Does Parental Quality Matter? Evidence on the Transmission of Human Capital Using Variation in Parental Influence from Death, Divorce, and Family Size. J Labor Econ. 2020;38(2):569-610. https://doi.org/10.1086/705904

47. Wan W, Zhu Y, Tian J, Cheng Y, Zeng L, Zhu Z. Associations of parental age at pregnancy with adolescent cognitive development and emotional and behavioural problems: a birth cohort in rural Western China. BMC Public Health. 2024;24:1-10. https://doi.org/10.1186/s12889-024-18309-z

Downloads

Published

2025-06-16

Issue

Vol. 59 (2025)

Section

Original Articles

How to Cite

Lima, J. F. de B., Batista, R. F. L., Aristizábal, L. Y. G., Almeida, C. C. C. R. de, Simões, V. M. F., & Silva, A. A. M. da. (2025). Do adversities in the intrauterine and neonatal periods interfere with intelligence?. Revista De Saúde Pública, 59, e15. https://doi.org/10.11606/s1518-8787.2025059006206

Funding data