The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Association Between Socioeconomic Status and In Utero Fetal 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.
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
“Parental education has been positively linked to fetal white matter, deep gray matter, and brain stem volumes, though the opposite was true for gray matter and cortical gyrification.90”
From Prenatal Social Determinants of Health: Narrative review of maternal environments and neonatal brain development (2024) · cites this paper as [90]
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
Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.015 · Cited by 8,868 · cited 1×
“The median (range) maternal and paternal SES scores were both 51 (11-55), and the maternal and paternal SES scores were not significantly different (rank sum test statistic, 20 841; P = .”
BackgroundFamily income, parental education and brain structure in children and adolescents
Noble, K. G., Houston, S. M., Brito, N. H., Bartsch, H., Kan, E., Kuperman, J. M., Akshoomoff, N., Amaral, D. G., Bloss, C. S., Libiger, O., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.3983 · Cited by 1,423
Socioeconomic status and the brain: mechanistic insights from human and animal research
Hackman, D. A., Farah, M. J., & Meaney, M. J. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2897 · Cited by 1,409
Luby, 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
Effects of childhood poverty and chronic stress on emotion regulatory brain function in adulthood
Kim, P., Evans, G. W., Angstadt, M., Ho, S. S., Sripada, C. S., Swain, J. E., Liberzon, I., & Phan, K. L. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1308240110 · Cited by 610
Neural correlates of socioeconomic status in the developing human brain
Noble, K. G., Houston, S. M., Kan, E., & Sowell, E. R. (2012) · Developmental Science · doi:10.1111/j.1467-7687.2012.01147.x · Cited by 542
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
Wu, Y., Lu, Y.-C., Jacobs, M., Pradhan, S., Kapse, K., Zhao, L., Niforatos-Andescavage, N., Vezina, G., du Plessis, A. J., & Limperopoulos, C. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.19940 · Cited by 218
Self-citationQuantitative in vivo MRI measurement of cortical development in the fetus
Clouchoux, C., Kudelski, D., Gholipour, A., Warfield, S. K., Viseur, S., Bouyssi-Kobar, M., Mari, J.-L., Evans, A. C., du Plessis, A. J., & Limperopoulos, C. (2012) · Brain Structure and Function · doi:10.1007/s00429-011-0325-x · Cited by 164
Self-citation
Research works printed but not linked: 68
- Hurt, 2016, Effect of socioeconomic status disparity on child language and neural outcome: how early is early?, Pediatr Res, 79, 148, 10.1038/pr.2015.202 · DOI
- Raizada, 2008, Socioeconomic status predicts hemispheric specialisation of the left inferior frontal gyrus in young children., Neuroimage, 40, 1392, 10.1016/j.neuroimage.2008.01.021 · DOI · Paper page
- Bradley, 2002, Socioeconomic status and child development., Annu Rev Psychol, 53, 371, 10.1146/annurev.psych.53.100901.135233 · DOI · Paper page
- McLoyd, 1998, Socioeconomic disadvantage and child development., Am Psychol, 53, 185, 10.1037/0003-066X.53.2.185 · DOI · Paper page
- Eckert, 2001, Planar asymmetry tips the phonological playground and environment raises the bar., Child Dev, 72, 988, 10.1111/cdev.2001.72.issue-4 · DOI
- 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
- Jednoróg, 2012, The influence of socioeconomic status on children’s brain structure., PLoS One, 7, 10.1371/journal.pone.0042486 · DOI
- Hanson, 2011, Association between income and the hippocampus., PLoS One, 6, 10.1371/journal.pone.0018712 · DOI
- Lange, 2010, Associations between IQ, total and regional brain volumes, and demography in a large normative sample of healthy children and adolescents., Dev Neuropsychol, 35, 296, 10.1080/87565641003696833 · DOI
- Brain Development Cooperative Group, 2012, Total and regional brain volumes in a population-based normative sample from 4 to 18 years: the NIH MRI Study of Normal Brain Development., Cereb Cortex, 22, 1, 10.1093/cercor/bhr018 · DOI
- Lawson, 2013, Associations between children’s socioeconomic status and prefrontal cortical thickness., Dev Sci, 16, 641, 10.1111/desc.2013.16.issue-5 · DOI
- Noble, 2007, Socioeconomic gradients predict individual differences in neurocognitive abilities., Dev Sci, 10, 464, 10.1111/desc.2007.10.issue-4 · DOI
- Ritsher, 2001, Inter-generational longitudinal study of social class and depression: a test of social causation and social selection models., Br J Psychiatry Suppl, 40, s84, 10.1192/bjp.178.40.s84 · DOI
- Kainz, 2015, Fast volume reconstruction from motion corrupted stacks of 2D slices., IEEE Trans Med Imaging, 34, 1901, 10.1109/TMI.2015.2415453 · DOI · Paper page
- Makropoulos, 2014, Automatic whole brain MRI segmentation of the developing neonatal brain., IEEE Trans Med Imaging, 33, 1818, 10.1109/TMI.2014.2322280 · DOI
- Makropoulos, 2016, Regional growth and atlasing of the developing human brain., Neuroimage, 125, 456, 10.1016/j.neuroimage.2015.10.047 · DOI
- Shattuck, 2002, BrainSuite: an automated cortical surface identification tool., Med Image Anal, 6, 129, 10.1016/S1361-8415(02)00054-3 · DOI
- Shimony, 2016, Comparison of cortical folding measures for evaluation of developing human brain., Neuroimage, 125, 780, 10.1016/j.neuroimage.2015.11.001 · DOI
- Rodriguez-Carranza, 2008, A framework for in vivo quantification of regional brain folding in premature neonates., Neuroimage, 41, 462, 10.1016/j.neuroimage.2008.01.008 · DOI
- Mietchen, 2009, Computational morphometry for detecting changes in brain structure due to development, aging, learning, disease and evolution., Front Neuroinform, 3, 25, 10.3389/neuro.11.025.2009 · DOI
- Kochunov, 2012, A library of cortical morphology analysis tools to study development, aging and genetics of cerebral cortex., Neuroinformatics, 10, 81, 10.1007/s12021-011-9127-9 · DOI
- Engelhardt, 2015, Regional impairments of cortical folding in premature infants., Ann Neurol, 77, 154, 10.1002/ana.v77.1 · DOI
- Moeskops, 2015, Development of cortical morphology evaluated with longitudinal MR brain images of preterm infants., PLoS One, 10, 10.1371/journal.pone.0131552 · DOI
- Lefèvre, 2016, Are developmental trajectories of cortical folding comparable between cross-sectional datasets of fetuses and preterm newborns?, Cereb Cortex, 26, 3023, 10.1093/cercor/bhv123 · DOI · Paper page
- Leijser, 2018, Imaging evidence of the effect of socio-economic status on brain structure and development., Semin Pediatr Neurol, 27, 26, 10.1016/j.spen.2018.03.004 · DOI
- Dubois, 2008, Mapping the early cortical folding process in the preterm newborn brain., Cereb Cortex, 18, 1444, 10.1093/cercor/bhm180 · DOI
- Hill, 2010, A surface-based analysis of hemispheric asymmetries and folding of cerebral cortex in term-born human infants., J Neurosci, 30, 2268, 10.1523/JNEUROSCI.4682-09.2010 · DOI
- Van Essen, 2005, A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex., Neuroimage, 28, 635, 10.1016/j.neuroimage.2005.06.058 · DOI · Paper page
- Li, 2014, Mapping longitudinal development of local cortical gyrification in infants from birth to 2 years of age., J Neurosci, 34, 4228, 10.1523/JNEUROSCI.3976-13.2014 · DOI · Paper page
- Schaer, 2008, A surface-based approach to quantify local cortical gyrification., IEEE Trans Med Imaging, 27, 161, 10.1109/TMI.2007.903576 · DOI
- Tosun, 2015, Cortical thickness and sulcal depth: insights on development and psychopathology in paediatric epilepsy., BJPsych Open, 1, 129, 10.1192/bjpo.bp.115.001719 · DOI
- Pienaar, 2008, A methodology for analyzing curvature in the developing brain from preterm to adult., Int J Imaging Syst Technol, 18, 42, 10.1002/(ISSN)1098-1098 · DOI
- Garcia, 2017, Statistical approaches to longitudinal data analysis in neurodegenerative diseases: Huntington’s disease as a model., Curr Neurol Neurosci Rep, 17, 14, 10.1007/s11910-017-0723-4 · DOI
- Daniels, 2003, Modelling the random effects covariance matrix in longitudinal data., Stat Med, 22, 1631, 10.1002/(ISSN)1097-0258 · DOI
- Andescavage, 2017, In vivo assessment of placental and brain volumes in growth-restricted fetuses with and without fetal Doppler changes using quantitative 3D MRI., J Perinatol, 37, 1278, 10.1038/jp.2017.129 · DOI
- Hair, 2015, Association of child poverty, brain development, and academic achievement., JAMA Pediatr, 169, 822, 10.1001/jamapediatrics.2015.1475 · DOI
- Farah, 2017, The neuroscience of socioeconomic status: correlates, causes, and consequences., Neuron, 96, 56, 10.1016/j.neuron.2017.08.034 · DOI · Paper page
- Yang, 2017, Individual and regional association between socioeconomic status and uncertainty stress, and life stress: a representative nationwide study of China., Int J Equity Health, 16, 118, 10.1186/s12939-017-0618-7 · DOI
- Sverke, 2002, No security: a meta-analysis and review of job insecurity and its consequences., J Occup Health Psychol, 7, 242, 10.1037/1076-8998.7.3.242 · DOI · Paper page
- Heaney, 1994, Chronic job insecurity among automobile workers: effects on job satisfaction and health., Soc Sci Med, 38, 1431, 10.1016/0277-9536(94)90281-X · DOI
- Wanberg, 2012, The individual experience of unemployment., Annu Rev Psychol, 63, 369, 10.1146/annurev-psych-120710-100500 · DOI
- Barbeau, 2004, Working class matters: socioeconomic disadvantage, race/ethnicity, gender, and smoking in NHIS 2000., Am J Public Health, 94, 269, 10.2105/AJPH.94.2.269 · DOI
- Sorensen, 2004, Reducing social disparities in tobacco use: a social-contextual model for reducing tobacco use among blue-collar workers., Am J Public Health, 94, 230, 10.2105/AJPH.94.2.230 · DOI
- Landsbergis, 2003, Lower socioeconomic status among men in relation to the association between job strain and blood pressure., Scand J Work Environ Health, 29, 206, 10.5271/sjweh.723 · DOI
- Ham, 2011, Occupation and workplace policies predict smoking behaviors: analysis of national data from the current population survey., J Occup Environ Med, 53, 1337, 10.1097/JOM.0b013e3182337778 · DOI
- Neiss, 2000, Parental education and child’s verbal IQ in adoptive and biological families in the National Longitudinal Study of Adolescent Health., Behav Genet, 30, 487, 10.1023/A:1010254918997 · DOI
- MacKinnon, 2007, Mediation analysis., Annu Rev Psychol, 58, 593, 10.1146/annurev.psych.58.110405.085542 · DOI · Paper page
- Li, 2020, Meta-analysis of cortical thickness abnormalities in medication-free patients with major depressive disorder., Neuropsychopharmacology, 45, 703, 10.1038/s41386-019-0563-9 · DOI
- Dowlati, 2010, A meta-analysis of cytokines in major depression., Biol Psychiatry, 67, 446, 10.1016/j.biopsych.2009.09.033 · DOI · Paper page
- Qiu, 2014, Regional increases of cortical thickness in untreated, first-episode major depressive disorder., Transl Psychiatry, 4, 10.1038/tp.2014.18 · DOI
- Abé, 2020, Longitudinal cortical thickness changes in bipolar disorder and the relationship to genetic risk, mania, and lithium use., Biol Psychiatry, 87, 271, 10.1016/j.biopsych.2019.08.015 · DOI
- Coussons-Read, 2007, Psychosocial stress increases inflammatory markers and alters cytokine production across pregnancy., Brain Behav Immun, 21, 343, 10.1016/j.bbi.2006.08.006 · DOI · Paper page
- Hantsoo, 2019, Inflammation: a proposed intermediary between maternal stress and offspring neuropsychiatric risk., Biol Psychiatry, 85, 97, 10.1016/j.biopsych.2018.08.018 · DOI · Paper page
- Entringer, 2008, Influence of prenatal psychosocial stress on cytokine production in adult women., Dev Psychobiol, 50, 579, 10.1002/(ISSN)1098-2302 · DOI
- Falkai, 2007, Disturbed frontal gyrification within families affected with schizophrenia., J Psychiatr Res, 41, 805, 10.1016/j.jpsychires.2006.07.018 · DOI
- Harris, 2004, Abnormal cortical folding in high-risk individuals: a predictor of the development of schizophrenia?, Biol Psychiatry, 56, 182, 10.1016/j.biopsych.2004.04.007 · DOI
- Harris, 2004, Gyrification in first-episode schizophrenia: a morphometric study., Biol Psychiatry, 55, 141, 10.1016/S0006-3223(03)00789-3 · DOI
- Stanfield, 2008, Increased right prefrontal cortical folding in adolescents at risk of schizophrenia for cognitive reasons., Biol Psychiatry, 63, 80, 10.1016/j.biopsych.2007.04.012 · DOI
- Sasaki, 2015, SPECT findings in autism spectrum disorders and medically refractory seizures., Epilepsy Behav, 47, 167, 10.1016/j.yebeh.2014.10.033 · DOI
- 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
- Benavente-Fernández, 2019, Association of socioeconomic status and brain injury with neurodevelopmental outcomes of very preterm children., JAMA Netw Open, 2, e192914, 10.1001/jamanetworkopen.2019.2914 · DOI
- Kishiyama, 2009, Socioeconomic disparities affect prefrontal function in children., J Cogn Neurosci, 21, 1106, 10.1162/jocn.2009.21101 · DOI
- Hendrickson, 2017, Cortical gyrification is abnormal in children with prenatal alcohol exposure., Neuroimage Clin, 15, 391, 10.1016/j.nicl.2017.05.015 · DOI
- Cao, 2017, Lifespan gyrification trajectories of human brain in healthy individuals and patients with major psychiatric disorders., Sci Rep, 7, 511, 10.1038/s41598-017-00582-1 · DOI
- DeCarli, 2008, Brain behavior relationships among African Americans, Whites, and Hispanics., Alzheimer Dis Assoc Disord, 22, 382, 10.1097/WAD.0b013e318185e7fe · DOI
- Choi, 2020, The aging slopes of brain structures vary by ethnicity and sex: evidence from a large magnetic resonance imaging dataset from a single scanner of cognitively healthy elderly people in Korea., Front Aging Neurosci, 12, 233, 10.3389/fnagi.2020.00233 · DOI
- Winter? B. A very basic tutorial for performing linear mixed effects analyses: tutorial 2. Quantitative Undergraduate Biology Education and Synthesis. Accessed February 18, 2021. doi:10.25334/Q4W716 · DOI
- Papini? C, Palaniyappan? L, Kroll? J, Froudist-Walsh? S, Murray? RM, Nosarti? C. Altered cortical gyrification in adults who were born very preterm and its associations with cognition and mental health.? bioRxiv. 2019. doi:10.1101/2019.12.13.871558 · DOI
Cited by
Fetal Brain Volume Predicts Neurodevelopment in Congenital Heart Disease
Sadhwani, A., Wypij, D., Rofeberg, V., Gholipour, A., Mittleman, M., Rohde, J., Velasco-Annis, C., Calderon, J., Friedman, K. G., Tworetzky, W., et al. (2022) · Circulation · doi:10.1161/circulationaha.121.056305 · Cited by 169
Wu, Y., Espinosa, K. M., Barnett, S. D., Kapse, A., Quistorff, J. L., Lopez, C., Andescavage, N., Pradhan, S., Lu, Y.-C., Kapse, K., et al. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.9244 · Cited by 113
Self-citationLu, Y.-C., Andescavage, N., Wu, Y., Kapse, K., Andersen, N. R., Quistorff, J., Saeed, H., Lopez, C., Henderson, D., Barnett, S. D., et al. (2022) · Communications Medicine · doi:10.1038/s43856-022-00111-w · Cited by 46
Self-citationHerzberg, M. P., & Smyser, C. D. (2024) · Pediatric Research · doi:10.1038/s41390-024-03345-7 · Cited by 22
Metadata
- Authors
- Lu, Y.-C., Kapse, K., Andersen, N., Quistorff, J., Lopez, C., Fry, A., Cheng, J., Andescavage, N., Wu, Y., Espinosa, K., Vezina, G., du Plessis, A., & Limperopoulos, C.
- Venue
- JAMA Network Open
- Publisher
- American Medical Association (AMA)
- Published
- 2021-03-29
- Volume
- 4
- Issue
- 3
- Pages
- e213526
- ISSN
- 2574-3805
- Cited by
- 63
- References
- 9
- 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
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.