Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 40

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Association of Preterm Birth and Socioeconomic Status With Neonatal Brain Structure

Mckinnon, Katie, Galdi, Paola, Blesa-Cábez, Manuel, Sullivan, Gemma, Vaher, Kadi, Corrigan, Amy, Hall, Jill, Jiménez-Sánchez, Lorena, Thrippleton, Michael, Bastin, Mark E., Quigley, Alan J., Valavani, Evdoxia, Tsanas, Athanasios, Richardson, Hilary, Boardman, James P.·2023·JAMA Network Open
DOI 10.1001/jamanetworkopen.2023.16067

Published version of a preprint

Open this paper in CoChat — free account

Abstract

Importance: Preterm birth and socioeconomic status (SES) are associated with brain structure in childhood, but the relative contributions of each during the neonatal period are unknown. Objective: To investigate associations of birth gestational age (GA) and SES with neonatal brain morphology by testing 3 hypotheses: GA and SES are associated with brain morphology; associations between SES and brain morphology vary with GA; and associations between SES and brain structure and morphology depend on how SES is operationalized. Design, Setting, and Participants: This cohort study recruited participants from November 2016 to September 2021 at a single center in the United Kingdom. Participants were 170 extremely and very preterm infants and 91 full-term or near-term infants. Exclusion criteria were major congenital malformation, chromosomal abnormality, congenital infection, cystic periventricular leukomalacia, hemorrhagic parenchymal infarction, and posthemorrhagic ventricular dilatation. Exposures: Birth GA and SES, operationalized at the neighborhood level (using the Scottish Index of Multiple Deprivation), the family level (using parental education and occupation), and subjectively (World Health Organization Quality of Life measure). Main Outcomes and Measures: Brain volume (85 parcels) and 5 whole-brain cortical morphology measures (gyrification index, thickness, sulcal depth, curvature, surface area) at term-equivalent age (median [range] age, 40 weeks, 5 days [36 weeks, 2 days to 45 weeks, 6 days] and 42 weeks [38 weeks, 2 days to 46 weeks, 1 day] for preterm and full-term infants, respectively). Results: Participants were 170 extremely and very preterm infants (95 [55.9%] male; 4 of 166 [2.4%] Asian, 145 of 166 [87.3%] White) and 91 full-term or near-term infants (50 [54.9%] male; 3 of 86 [3.5%] Asian, 78 of 86 [90.7%] White infants) with median (range) birth GAs of 30 weeks, 0 days (22 weeks, 1 day, to 32 weeks, 6 days) and 39 weeks, 4 days (36 weeks, 3 days, to 42 weeks, 1 day), respectively. In fully adjusted models, birth GA was associated with a higher proportion of brain volumes (27 of 85 parcels [31.8%]; β range, −0.20 to 0.24) than neighborhood-level SES (1 of 85 parcels [1.2%]; β = 0.17 [95% CI, −0.16 to 0.50]) or family-level SES (maternal education: 4 of 85 parcels [4.7%]; β range, 0.09 to 0.15; maternal occupation: 1 of 85 parcels [1.2%]; β = 0.06 [95% CI, 0.02 to 0.11] respectively). There were interactions between GA and both family-level and subjective SES measures on regional brain volumes. Birth GA was associated with cortical surface area (β = 0.10 [95% CI, 0.02 to 0.18]) and gyrification index (β = 0.16 [95% CI, 0.07 to 0.25]); no SES measure was associated with cortical measures. Conclusions and Relevance: In this cohort study of UK infants, birth GA and SES were associated with neonatal brain morphology, but low GA had more widely distributed associations with neonatal brain structure than SES. Further work is warranted to elucidate the mechanisms underlying the association of both GA and SES with early brain development.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jamanetworkopen.2023.16067

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 6 references

Research works printed but not linked: 66

  1. Chawanpaiboon, 2019, Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis., Lancet Glob Health, 7, e37, 10.1016/S2214-109X(18)30451-0 · DOI · Paper page
  2. Johnson, 2017, Early and long-term outcome of infants born extremely preterm., Arch Dis Child, 102, 97, 10.1136/archdischild-2015-309581 · DOI
  3. Agrawal, 2018, Prevalence of autism spectrum disorder in preterm infants: a meta-analysis., Pediatrics, 142, 1, 10.1542/peds.2018-0134 · DOI
  4. Twilhaar, 2018, Cognitive outcomes of children born extremely or very preterm since the 1990s and associated risk factors: a meta-analysis and meta-regression., JAMA Pediatr, 172, 361, 10.1001/jamapediatrics.2017.5323 · DOI
  5. Batalle, 2018, Annual research review: not just a small adult brain: understanding later neurodevelopment through imaging the neonatal brain., J Child Psychol Psychiatry, 59, 350, 10.1111/jcpp.2018.59.issue-4 · DOI
  6. Boardman, 2007, Early growth in brain volume is preserved in the majority of preterm infants., Ann Neurol, 62, 185, 10.1002/ana.21171 · DOI
  7. Romberg, 2022, MRI-based brain volumes of preterm infants at term: a systematic review and meta-analysis., Arch Dis Child Fetal Neonatal Ed, 107, 520, 10.1136/archdischild-2021-322846 · DOI
  8. Dimitrova, 2021, Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age., Neuroimage, 243, 10.1016/j.neuroimage.2021.118488 · DOI
  9. Thompson, 2020, Tracking regional brain growth up to age 13 in children born term and very preterm., Nat Commun, 11, 696, 10.1038/s41467-020-14334-9 · DOI
  10. Boardman, 2010, A common neonatal image phenotype predicts adverse neurodevelopmental outcome in children born preterm., Neuroimage, 52, 409, 10.1016/j.neuroimage.2010.04.261 · DOI
  11. Dubois, 2008, Primary cortical folding in the human newborn: an early marker of later functional development., Brain, 131, 2028, 10.1093/brain/awn137 · DOI
  12. Kapellou, 2006, Abnormal cortical development after premature birth shown by altered allometric scaling of brain growth., PLoS Med, 3, 10.1371/journal.pmed.0030265 · DOI
  13. Farah, 2017, The neuroscience of socioeconomic status: correlates, causes, and consequences., Neuron, 96, 56, 10.1016/j.neuron.2017.08.034 · DOI · Paper page
  14. von Stumm, 2015, Socioeconomic status and the growth of intelligence from infancy through adolescence., Intelligence, 48, 30, 10.1016/j.intell.2014.10.002 · DOI
  15. Noble, 2005, Neurocognitive correlates of socioeconomic status in kindergarten children., Dev Sci, 8, 74, 10.1111/desc.2005.8.issue-1 · DOI
  16. McLoyd, 1998, Socioeconomic disadvantage and child development., Am Psychol, 53, 185, 10.1037/0003-066X.53.2.185 · DOI · Paper page
  17. Duncan, 1998, How much does childhood poverty affect the life chances of children?, Am Sociol Rev, 63, 406, 10.2307/2657556 · DOI
  18. Pillas, 2014, Social inequalities in early childhood health and development: a European-wide systematic review., Pediatr Res, 76, 418, 10.1038/pr.2014.122 · DOI
  19. Noble, 2015, Socioeconomic disparities in neurocognitive development in the first two years of life., Dev Psychobiol, 57, 535, 10.1002/dev.v57.5 · DOI
  20. Mackey, 2015, Neuroanatomical correlates of the income-achievement gap., Psychol Sci, 26, 925, 10.1177/0956797615572233 · DOI · Paper page
  21. Hair, 2015, Association of child poverty, brain development, and academic achievement., JAMA Pediatr, 169, 822, 10.1001/jamapediatrics.2015.1475 · DOI
  22. Gur, 2019, Burden of environmental adversity associated with psychopathology, maturation, and brain behavior parameters in youths., JAMA Psychiatry, 76, 966, 10.1001/jamapsychiatry.2019.0943 · DOI · Paper page
  23. Boardman, 2020, Impact of preterm birth on brain development and long-term outcome: protocol for a cohort study in Scotland., BMJ Open, 10, 10.1136/bmjopen-2019-035854 · DOI
  24. Gale, 2018, Neonatal brain injuries in England: population-based incidence derived from routinely recorded clinical data held in the National Neonatal Research Database., Arch Dis Child Fetal Neonatal Ed, 103, F301, 10.1136/archdischild-2017-313707 · DOI
  25. Minh, 2017, A review of neighborhood effects and early child development: how, where, and for whom, do neighborhoods matter?, Health Place, 46, 155, 10.1016/j.healthplace.2017.04.012 · DOI
  26. Thompson, 2007, Perinatal risk factors altering regional brain structure in the preterm infant., Brain, 130, 667, 10.1093/brain/awl277 · DOI
  27. Selvanathan, 2022, Head circumference, total cerebral volume and neurodevelopment in preterm neonates., Arch Dis Child Fetal Neonatal Ed, 107, 181, 10.1136/archdischild-2020-321397 · DOI
  28. Lehtola, 2019, Associations of age and sex with brain volumes and asymmetry in 2-5-week-old infants., Brain Struct Funct, 224, 501, 10.1007/s00429-018-1787-x · DOI
  29. Roustaei, 2020, Associations between maternal age and socioeconomic status with smoking during the second and third trimesters of pregnancy: a register-based study of 932 671 women in Finland from 2000 to 2015., BMJ Open, 10, 10.1136/bmjopen-2019-034839 · DOI
  30. Ekblad, 2015, Smoking during pregnancy affects foetal brain development., Acta Paediatr, 104, 12, 10.1111/apa.12791 · DOI
  31. Blesa, 2019, Early breast milk exposure modifies brain connectivity in preterm infants., Neuroimage, 184, 431, 10.1016/j.neuroimage.2018.09.045 · DOI
  32. Sullivan, 2023, Breast milk exposure is associated with cortical maturation in preterm infants., Ann Neurol, 93, 591, 10.1002/ana.v93.3 · DOI
  33. Makropoulos, 2018, The developing human connectome project: a minimal processing pipeline for neonatal cortical surface reconstruction., Neuroimage, 173, 88, 10.1016/j.neuroimage.2018.01.054 · DOI
  34. Assari, 2021, Parental educational attainment, the superior temporal cortical surface area, and reading ability among American children: a test of marginalization-related diminished returns., Children (Basel), 8, 412, 10.3390/children8050412 · DOI
  35. Lu, 2021, Association between socioeconomic status and in utero fetal brain development., JAMA Netw Open, 4, 10.1001/jamanetworkopen.2021.3526 · DOI · Paper page
  36. Machlin, 2020, Brain structure mediates the association between socioeconomic status and attention-deficit/hyperactivity disorder., Dev Sci, 23, 10.1111/desc.v23.1 · DOI
  37. Jha, 2019, Environmental influences on infant cortical thickness and surface area., Cereb Cortex, 29, 1139, 10.1093/cercor/bhy020 · DOI
  38. Rakesh, 2021, Socioeconomic status and the developing brain: a systematic review of neuroimaging findings in youth., Neurosci Biobehav Rev, 130, 379, 10.1016/j.neubiorev.2021.08.027 · DOI
  39. Taylor, 2020, Assessment of neighborhood poverty, cognitive function, and prefrontal and hippocampal volumes in children., JAMA Netw Open, 3, 10.1001/jamanetworkopen.2020.23774 · DOI
  40. Jednoróg, 2012, The influence of socioeconomic status on children’s brain structure., PLoS One, 7, 10.1371/journal.pone.0042486 · DOI
  41. Benjamini, 1995, Controlling the false discovery rate: a practical and powerful approach to multiple testing., J R Stat Soc Ser A Stat Soc, 57, 289, 10.1111/rssb.1995.57.issue-1 · DOI
  42. Ene, 2019, Associations of socioeconomic deprivation and preterm birth with speech, language, and communication concerns among children aged 27 to 30 months., JAMA Netw Open, 2, 10.1001/jamanetworkopen.2019.11027 · DOI
  43. Noble, 2021, Baby’s first years: design of a randomized controlled trial of poverty reduction in the United States., Pediatrics, 148, 10.1542/peds.2020-049702 · DOI
  44. Benavente-Fernández, 2020, Socioeconomic status and brain injury in children born preterm: modifying neurodevelopmental outcome., Pediatr Res, 87, 391, 10.1038/s41390-019-0646-7 · DOI
  45. Stiver, 2015, Maternal postsecondary education associated with improved cerebellar growth after preterm birth., J Child Neurol, 30, 1633, 10.1177/0883073815576790 · DOI
  46. Knickmeyer, 2017, Impact of demographic and obstetric factors on infant brain volumes: a population neuroscience study., Cereb Cortex, 27, 5616, 10.1093/cercor/bhw331 · DOI · Paper page
  47. Gui, 2019, Longitudinal study of neonatal brain tissue volumes in preterm infants and their ability to predict neurodevelopmental outcome., Neuroimage, 185, 728, 10.1016/j.neuroimage.2018.06.034 · DOI
  48. Thompson, 2019, Early life predictors of brain development at term-equivalent age in infants born across the gestational age spectrum., Neuroimage, 185, 813, 10.1016/j.neuroimage.2018.04.031 · DOI · Paper page
  49. Makropoulos, 2016, Regional growth and atlasing of the developing human brain., Neuroimage, 125, 456, 10.1016/j.neuroimage.2015.10.047 · DOI
  50. Spann, 2020, Prenatal socioeconomic status and social support are associated with neonatal brain morphology, toddler language and psychiatric symptoms., Child Neuropsychol, 26, 170, 10.1080/09297049.2019.1648641 · DOI · Paper page
  51. Kersbergen, 2016, Relation between clinical risk factors, early cortical changes, and neurodevelopmental outcome in preterm infants., Neuroimage, 142, 301, 10.1016/j.neuroimage.2016.07.010 · DOI
  52. Betancourt, 2016, Effect of socioeconomic status (SES) disparity on neural development in female African-American infants at age 1 month., Dev Sci, 19, 947, 10.1111/desc.2016.19.issue-6 · DOI
  53. Triplett, 2022, Association of prenatal exposure to early-life adversity with neonatal brain volumes at birth., JAMA Netw Open, 5, 10.1001/jamanetworkopen.2022.7045 · DOI · Paper page
  54. Baron, 2015, Socio-demographic inequalities across a range of health status indicators and health behaviours among pregnant women in prenatal primary care: a cross-sectional study., BMC Pregnancy Childbirth, 15, 261, 10.1186/s12884-015-0676-z · DOI
  55. Dean, 2021, Eye-tracking for longitudinal assessment of social cognition in children born preterm., J Child Psychol Psychiatry, 62, 470, 10.1111/jcpp.v62.4 · DOI
  56. Ginnell, 2022, Emotion regulation and cortisol response to the still-face procedure in preterm and full-term infants., Psychoneuroendocrinology, 141, 10.1016/j.psyneuen.2022.105760 · DOI
  57. Blesa, 2021, Hierarchical complexity of the macro-scale neonatal brain., Cereb Cortex, 31, 2071, 10.1093/cercor/bhaa345 · DOI
  58. Galdi, 2020, Neonatal morphometric similarity mapping for predicting brain age and characterizing neuroanatomic variation associated with preterm birth., Neuroimage Clin, 25, 10.1016/j.nicl.2020.102195 · DOI
  59. Ou, 2016, Voxel-based morphometry and fMRI revealed differences in brain gray matter in breastfed and milk formula-fed children., AJNR Am J Neuroradiol, 37, 713, 10.3174/ajnr.A4593 · DOI
  60. Ng, 2020, Investigating altered brain development in infants with congenital heart disease using tensor-based morphometry., Sci Rep, 10, 14909, 10.1038/s41598-020-72009-3 · DOI
  61. Gard, 2021, Beyond family-level adversities: exploring the developmental timing of neighborhood disadvantage effects on the brain., Dev Sci, 24, 10.1111/desc.v24.1 · DOI
  62. Linsell, 2015, Prognostic factors for poor cognitive development in children born very preterm or with very low birth weight: a systematic review., JAMA Pediatr, 169, 1162, 10.1001/jamapediatrics.2015.2175 · DOI
  63. Cebula, 2021, Ethnicity, Poverty and the Data in Scotland
  64. Hastie, 2009, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 10.1007/978-0-387-84858-7 · DOI · Paper page
  65. Nieuwenhuys, 2008, The Human Central Nervous System, 10.1007/978-3-540-34686-9 · DOI · Paper page
  66. Mckinnon? K, Galdi? P, Blesa-Cábez? M, . The impact of preterm birth and socioeconomic status on neonatal brain morphology. OSF. 2022. Accessed April 25, 2023. https://osf.io/ftv2s · DOI

Cited by

See all 40

Metadata

Authors
Mckinnon, K., Galdi, P., Blesa-Cábez, M., Sullivan, G., Vaher, K., Corrigan, A., Hall, J., Jiménez-Sánchez, L., Thrippleton, M., Bastin, M. E., Quigley, A. J., Valavani, E., Tsanas, A., Richardson, H., & Boardman, J. P.
Venue
JAMA Network Open
Publisher
American Medical Association (AMA)
Published
2023-05-31
Volume
6
Issue
5
Pages
e2316067
ISSN
2574-3805
DOI
10.1001/jamanetworkopen.2023.16067
Cited by
40
References
6
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Association of Preterm Birth and Socioeconomic Status With Neonatal Brain Structure. https://app.cochat.ai/papers/10.1001/jamanetworkopen.2023.16067
The paper
Mckinnon, K., Galdi, P., Blesa-Cábez, M., Sullivan, G., Vaher, K., Corrigan, A., Hall, J., Jiménez-Sánchez, L., Thrippleton, M., Bastin, M. E., Quigley, A. J., Valavani, E., Tsanas, A., Richardson, H., & Boardman, J. P. (2023). Association of Preterm Birth and Socioeconomic Status With Neonatal Brain Structure. JAMA Network Open. https://doi.org/10.1001/jamanetworkopen.2023.16067

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.