The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Prenatal exposure to maternal social disadvantage and psychosocial stress and neonatal white matter connectivity at birth
Published version of a preprint
Abstract
Early life adversity (social disadvantage and psychosocial stressors) is associated with altered microstructure in fronto-limbic pathways important for socioemotional development. Understanding when these associations begin to emerge may inform the timing and design of preventative interventions. In this longitudinal study, 399 mothers were oversampled for low income and completed social background measures during pregnancy. Measures were analyzed with structural equation analysis resulting in two latent factors: social disadvantage (education, insurance status, income-to-needs ratio [INR], neighborhood deprivation, and nutrition) and psychosocial stress (depression, stress, life events, and racial discrimination). At birth, 289 healthy term-born neonates underwent a diffusion MRI (dMRI) scan. Mean diffusivity (MD) and fractional anisotropy (FA) were measured for the dorsal and inferior cingulum bundle (CB), uncinate, and fornix using probabilistic tractography in FSL. Social disadvantage and psychosocial stress were fitted to dMRI parameters using regression models adjusted for infant postmenstrual age at scan and sex. Social disadvantage, but not psychosocial stress, was independently associated with lower MD in the bilateral inferior CB and left uncinate, right fornix, and lower MD and higher FA in the right dorsal CB. Results persisted after accounting for maternal medical morbidities and prenatal drug exposure. In moderation analysis, psychosocial stress was associated with lower MD in the left inferior CB among the lower-to-higher socioeconomic status (SES) (INR ≥ 200%) group, but not the extremely low SES (INR < 200%) group. Increasing access to social welfare programs that reduce the burden of social disadvantage and related psychosocial stressors may be an important target to protect fetal brain development in fronto-limbic pathways.
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.
Integrity signals
Registry
Cites
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.
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?
In the citing paper
“and a follow-up analysis indicated that the effects of psychosocial stress were moderated by family income-to-needs, such that the relationship between maternal stress and mean diffusivity in the left inferior cingulum was stronger in a group with lower-to-higher income compared to an extremely low-income group (e.g., income <200% of national poverty line).”
From Prenatal Social Determinants of Health: Narrative review of maternal environments and neonatal brain development (2024) · cites this paper as [45]
In the citing paper
“Prenatal social disadvantage was associated with lower mean diffusivity in the bilateral cingulum, bilateral uncinate, and right fornix, with similar effects in radial and axial diffusivity.45”
From Prenatal Social Determinants of Health: Narrative review of maternal environments and neonatal brain development (2024) · cites this paper as [45]
In the citing paper
“These effects survived correction for maternal psychosocial stress”
From Prenatal Social Determinants of Health: Narrative review of maternal environments and neonatal brain development (2024) · cites this paper as [45]
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
Racial Differences in Physical and Mental Health: Socio-economic Status, Stress and Discrimination
Williams, D. R., Yu, Y., Jackson, J. S., & Anderson, N. B. (1997) · Journal of Health Psychology · doi:10.1177/135910539700200305 · Cited by 4,786
Making Neighborhood-Disadvantage Metrics Accessible — The Neighborhood Atlas
Kind, A. J. H., & Buckingham, W. R. (2018) · New England Journal of Medicine · doi:10.1056/nejmp1802313 · Cited by 3,310
Stress Effects on Neuronal Structure: Hippocampus, Amygdala, and Prefrontal Cortex
McEwen, B. S., Nasca, C., & Gray, J. D. (2016) · Neuropsychopharmacology · doi:10.1038/npp.2015.171 · Cited by 1,574
Levis, B., Negeri, Z., Sun, Y., Benedetti, A., & Thombs, B. D. (2020) · BMJ · doi:10.1136/bmj.m4022 · Cited by 922
The cingulum bundle: Anatomy, function, and dysfunction
Bubb, E. J., Metzler-Baddeley, C., & Aggleton, J. P. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.05.008 · Cited by 740 · cited 3×
“making the underlying dMRI tensors appear more directional (20, 23).”
BackgroundLuby, J., Belden, A., Botteron, K., Marrus, N., Harms, M. P., Babb, C., Nishino, T., & Barch, D. (2013) · JAMA Pediatrics · doi:10.1001/jamapediatrics.2013.3139 · Cited by 733
Self-citationBack, S. A., Gan, X., Li, Y., Rosenberg, P. A., & Volpe, J. J. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-16-06241.1998 · Cited by 586
Environmental influences on the pace of brain development
Tooley, U. A., Bassett, D. S., & Mackey, A. P. (2021) · Nature reviews. Neuroscience · doi:10.1038/s41583-021-00457-5 · Cited by 488
Family Poverty Affects the Rate of Human Infant Brain Growth
Hanson, J. L., Hair, N., Shen, D. G., Shi, F., Gilmore, J. H., Wolfe, B. L., & Pollak, S. D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0080954 · Cited by 430
Slavich, G. M., & Shields, G. S. (2018) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000534 · Cited by 268 · cited 3×
“Stressful/traumatic life events (count and severity) were assessed with the Stress and Adversity Inventory for Adults (STRAIN) (50), collected at the neonatal MRI scan ( n = 183) or at the 1-y follow-up ( n = 86).”
Influential
Research works printed but not linked: 37
- B. Kolb, R. Gibb, Brain plasticity and behaviour in the developing brain. J. Can. Acad. Child Adolesc. Psychiatry 20, 265–276 (2011).
- 10.1016/j.neubiorev.2021.08.027 · DOI
- 10.1002/hbm.25031 · DOI
- 10.3389/fnhum.2017.00547 · DOI
- 10.1016/j.neuroimage.2018.04.031 · DOI · Paper page
- 10.1523/JNEUROSCI.21-04-01302.2001 · DOI
- 10.1016/j.neuroscience.2013.12.044 · DOI · Paper page
- 10.1016/j.psyneuen.2016.04.011 · DOI
- 10.1159/000430861 · DOI
- P. Yang , Changes in proinflammatory cytokines and white matter in chronically stressed rats. Neuropsychiatr. Dis. Treat. 11, 597–607 (2015).
- 10.1002/jnr.22139 · DOI · Paper page
- 10.1038/s41390-020-01264-x · DOI
- 10.1016/j.biopsych.2019.08.010 · DOI · Paper page
- 10.1016/j.jaac.2015.01.013 · DOI · Paper page
- 10.3174/ajnr.A6759 · DOI · Paper page
- J. L. Luby Modeling prenatal adversity/advantage: Effects on birth weight. medRxiv [Preprint] (2021) https://www.medrxiv.org/content/10.1101/2021.12.16.21267938v1. Accessed 17 December 2021. · DOI
- 10.1093/brain/awt094 · DOI · Paper page
- 10.1016/j.biopsych.2020.06.015 · DOI
- 10.1176/appi.ajp.2011.11091447 · DOI · Paper page
- Bendheim-Thoman Center for Research on Child Wellbeing, Disadvantaged Children who are Beating the Odds: Family, School, Neighborhood and City Contexts that Predict Academic Success among Socio-economically Disadvantaged Children (Princeton University, 2019).
- 10.3389/fnhum.2020.578822 · DOI
- 10.1001/jamapediatrics.2015.1475 · DOI
- T. Halle , Disparities in Early Learning and Development: Lessons from the Early Childhood Longitudinal Study - Birth Cohort (ECLS-B) (Child Trends, 2009).
- 10.1186/1471-2458-12-611 · DOI
- 10.1016/j.yhbeh.2016.04.010 · DOI
- 10.1038/s41380-019-0493-2 · DOI
- 10.1016/j.neuroscience.2018.05.020 · DOI
- N. Tottenham, M. A. Sheridan, A review of adversity, the amygdala and the hippocampus: A consideration of developmental timing. Front. Hum. Neurosci. 3, 68 (2010).
- 10.1196/annals.1425.016 · DOI
- 10.1038/s41598-021-97635-3 · DOI
- 10.1016/j.tins.2020.02.003 · DOI
- 10.1523/JNEUROSCI.4080-05.2006 · DOI · Paper page
- 10.1097/01.AOG.0000183597.31630.db · DOI · Paper page
- 10.1007/s00737-018-0821-6 · DOI
- 10.1016/j.jand.2018.05.021 · DOI · Paper page
- 10.1192/bjp.150.6.782 · DOI · Paper page
- 10.2307/2136404 · DOI · Paper page
Cited by
Herzberg, M. P., & Smyser, C. D. (2024) · Pediatric Research · doi:10.1038/s41390-024-03345-7 · Cited by 22
Self-citation
Metadata
- Authors
- Lean, R. E., Smyser, C. D., Brady, R. G., Triplett, R. L., Kaplan, S., Kenley, J. K., Shimony, J. S., Smyser, T. A., Miller, J. P., Barch, D. M., Luby, J. L., Warner, B. B., & Rogers, C. E.
- Affiliations
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO 63110
- Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110
- Department of Biostatistics, Institute for Informatics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2022-10-11
- Volume
- 119
- Issue
- 42
- ISSN
- 0027-8424
- 1091-6490
- Cited by
- 59
- References
- 14
- Language
- en
- Funders
- HHS | NIH | National Institute of Mental Health (K01 MH122735, F30 HD104313, T32 MH100019, R01 MH113883)
- Brain and Behavior Research Foundation (NARSAD Young Investigator Grant (28521))
- HHS | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50 HD103525)
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
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.