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Greater Neighborhood Disadvantage Is Associated with Alterations in Fetal Functional Brain Network Structure
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“Specifically, affected fetuses exhibit less integrated functional brain networks, 24 along with larger brain volumes earlier in gestation but smaller volumes approaching term with region-specific and sex-dependent vulnerabilities. 25”
From Environmental roots of neonatal health: how social and structural exposures shape early-life outcomes (2026) · cites this paper as [24]
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Socioeconomic Status and Academic Achievement: A Meta-Analytic Review of Research
Sirin, S. R. (2005) · Review of Educational Research · doi:10.3102/00346543075003417 · Cited by 4,687
Reiss, F. (2013) · Social Science & Medicine · doi:10.1016/j.socscimed.2013.04.026 · Cited by 2,062
U.S. Disparities in Health: Descriptions, Causes, and Mechanisms
Adler, N. E., & Rehkopf, D. H. (2008) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.29.020907.090852 · Cited by 1,212
Neighborhoods, obesity, and diabetes—a randomized social experiment.
Ludwig, J., Sanbonmatsu, L., Gennetian, L., Adam, E., Duncan, G. J., Katz, L. F., Kessler, R. C., Kling, J. R., Lindau, S. T., Whitaker, R. C., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmsa1103216 · Cited by 964
Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults
Ludwig, J., Duncan, G. J., Gennetian, L. A., Katz, L. F., Kessler, R. C., Kling, J. R., & Sanbonmatsu, L. (2012) · Science · doi:10.1126/science.1224648 · Cited by 747
Functional Connectome of the Fetal Brain
Turk, E., van den Heuvel, M. I., Benders, M. J., de Heus, R., Franx, A., Manning, J. H., Hect, J. L., Hernandez-Andrade, E., Hassan, S. S., Romero, R., et al. (2019) · The Journal of Neuroscience · doi:10.1523/jneurosci.2891-18.2019 · Cited by 176
Intrinsic Functional Brain Architecture Derived from Graph Theoretical Analysis in the Human Fetus
Thomason, M. E., Brown, J. A., Dassanayake, M. T., Shastri, R., Marusak, H. A., Hernandez-Andrade, E., Yeo, L., Mody, S., Berman, S., Hassan, S. S., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0094423 · Cited by 130
Sex differences in functional connectivity during fetal brain development
Wheelock, M. D., Hect, J. L., Hernandez-Andrade, E., Hassan, S. S., Romero, R., Eggebrecht, A. T., & Thomason, M. E. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100632 · Cited by 126
Hubs in the human fetal brain network
van den Heuvel, M. I., Turk, E., Manning, J. H., Hect, J., Hernandez-Andrade, E., Hassan, S. S., Romero, R., van den Heuvel, M. P., & Thomason, M. E. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.02.001 · Cited by 108
Association of Prenatal Maternal Anxiety With Fetal Regional Brain Connectivity
De Asis-Cruz, J., Krishnamurthy, D., Zhao, L., Kapse, K., Vezina, G., Andescavage, N., Quistorff, J., Lopez, C., & Limperopoulos, C. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.22349 · Cited by 81
Self-citation
Research works printed but not linked: 72
- Liberatos, 1988, The measurement of social class in epidemiology, Epidemiol Rev, 10, 87, 10.1093/oxfordjournals.epirev.a036030 · DOI
- Bradley, 2002, Socioeconomic status and child development, Annu Rev Psychol, 53, 371, 10.1146/annurev.psych.53.100901.135233 · DOI · Paper page
- Luo, 2005, The impact of childhood and adult SES on physical, mental, and cognitive well-being in later life, J Gerontol: Series B, 60, S93, 10.1093/geronb/60.2.S93 · DOI · Paper page
- Mielck, 2014, Health-related quality of life and socioeconomic status: inequalities among adults with a chronic disease, Health Qual Life Outcomes, 12, 58, 10.1186/1477-7525-12-58 · DOI
- Last, 2018, Childhood socioeconomic status and executive function in childhood and beyond, PLoS One, 13, 10.1371/journal.pone.0202964 · DOI
- Greenfield, 2019, Childhood socioeconomic status and later life Cognition: evidence from the Wisconsin longitudinal study, J Aging Health, 31, 1589, 10.1177/0898264318783489 · DOI
- van Zwieten, 2021, Socioeconomic status during childhood and Academic Achievement in secondary School, Acad Pediatr, 21, 838, 10.1016/j.acap.2020.10.013 · DOI
- Ribeiro, 2020, Socioeconomic disadvantage and health in early childhood: a population-based birth cohort study from Portugal, Pediatr Res, 88, 503, 10.1038/s41390-020-0786-9 · DOI
- Browning, 2002, Neighborhood structural disadvantage, collective efficacy, and self-rated physical health in an urban setting, J Health Soc Behav, 43, 383, 10.2307/3090233 · DOI · Paper page
- Graham, 2020, Does context matter? A multilevel analysis of neighborhood disadvantage and children’s sleep health, Sleep Health: J National Sleep Foundation, 6, 578, 10.1016/j.sleh.2020.05.002 · DOI
- 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
- Kind, 2014, Neighborhood socioeconomic disadvantage and 30-Day Rehospitalization, Ann Intern Med, 161, 765, 10.7326/M13-2946 · DOI · Paper page
- Singh, 2012, Impact of neighborhood social conditions and household socioeconomic status on behavioral problems among US children, Matern Child Health J, 16, S158, 10.1007/s10995-012-1005-z · DOI
- Gao, 2015, Functional network development during the first Year: relative sequence and socioeconomic correlations, Cereb Cortex, 25, 2919, 10.1093/cercor/bhu088 · DOI · Paper page
- Gianaros, 2013, Inflammatory pathways link socioeconomic inequalities to white matter architecture, Cereb Cortex, 23, 2058, 10.1093/cercor/bhs191 · DOI
- Lu, 2021, Association between socioeconomic status and in utero fetal brain development, JAMA Netw Open, 4, 10.1001/jamanetworkopen.2021.3526 · DOI · Paper page
- Ramphal, 2020, Associations between Amygdala-Prefrontal functional connectivity and age Depend on neighborhood socioeconomic status, Cereb Cortex Commun, 1
- Gellci, 2019, Community and household-level socioeconomic disadvantage and functional organization of the salience and emotion network in children and adolescents, Neuroimage, 184, 729, 10.1016/j.neuroimage.2018.09.077 · DOI
- Tooley, 2020, Associations between neighborhood SES and functional brain network development, Cereb Cortex, 30, 1, 10.1093/cercor/bhz066 · DOI
- Jeong, 2024, Early life stress and functional network topology in children, Dev Cogn Neurosci, 66, 10.1016/j.dcn.2024.101367 · DOI
- 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
- Lean, 2022, Prenatal exposure to maternal social disadvantage and psychosocial stress and neonatal white matter connectivity at birth, Proc Natl Acad Sci USA, 119, 10.1073/pnas.2204135119 · DOI · Paper page
- Keunen, 2017, The emergence of functional architecture during early brain development, Neuroimage, 160, 2, 10.1016/j.neuroimage.2017.01.047 · DOI
- Andescavage, 2017, Complex Trajectories of brain development in the healthy human fetus, Cereb Cortex, 27, 5274
- Flanagan, 2011, A social vulnerability index for disaster management, J Homel Secur Emerg Manag, 8
- De Asis-Cruz, 2021, Global network organization of the fetal functional connectome, Cereb Cortex, 31, 3034, 10.1093/cercor/bhaa410 · DOI · Paper page
- Gholipour, 2014, Construction of a deformable spatiotemporal MRI atlas of the fetal brain: evaluation of similarity metrics and deformation models, Med Image Comput Comput Assist Interv, 17, 292
- Tustison, 2010, N4ITK: improved N3 bias correction, IEEE Trans Med Imaging, 29, 1310, 10.1109/TMI.2010.2046908 · DOI
- Joshi, 2011, Unified framework for development, deployment and robust testing of neuroimaging algorithms, Neuroinformatics, 9, 69, 10.1007/s12021-010-9092-8 · DOI
- Scheinost, 2018, A fetal fMRI specific motion correction algorithm using 2 nd order edge features, IEEE, 1288
- Ojemann, 1997, Anatomic localization and quantitative analysis of gradient refocused echo-planar fMRI susceptibility artifacts, Neuroimage, 6, 156, 10.1006/nimg.1997.0289 · DOI
- Hallquist, 2013, The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity, Neuroimage, 82, 208, 10.1016/j.neuroimage.2013.05.116 · DOI · Paper page
- Behzadi, 2007, A component based noise correction method (CompCor) for BOLD and perfusion based fMRI, Neuroimage, 37, 90, 10.1016/j.neuroimage.2007.04.042 · DOI · Paper page
- Muschelli, 2014, Reduction of motion-related artifacts in resting state fMRI using aCompCor, Neuroimage, 96, 22, 10.1016/j.neuroimage.2014.03.028 · DOI
- Jo, 2010, Mapping sources of correlation in resting state FMRI, with artifact detection and removal, Neuroimage, 52, 571, 10.1016/j.neuroimage.2010.04.246 · DOI
- Worsley, 1996, A unified statistical approach for determining significant signals in images of cerebral activation, Hum Brain Mapp, 4, 58, 10.1002/(SICI)1097-0193(1996)4:1<58::AID-HBM4>3.0.CO;2-O · DOI
- Friston, 1996, Movement-related effects in fMRI time-series, Magn Reson Med, 35, 346, 10.1002/mrm.1910350312 · DOI · Paper page
- Thomason, 2019, Prenatal lead exposure impacts cross-hemispheric and long-range connectivity in the human fetal brain, Neuroimage, 191, 186, 10.1016/j.neuroimage.2019.02.017 · DOI · Paper page
- Norr, 2021, An examination of maternal prenatal BMI and human fetal brain development, J Child Psychol Psychiatry, 62, 458, 10.1111/jcpp.13301 · DOI
- Jakab, 2014, Fetal functional imaging portrays heterogeneous development of emerging human brain networks, Front Hum Neurosci, 8, 852, 10.3389/fnhum.2014.00852 · DOI · Paper page
- Craddock, 2012, A whole brain fMRI atlas generated via spatially constrained spectral clustering, Hum Brain Mapp, 33, 1914, 10.1002/hbm.21333 · 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
- Peer, 2016, Intensity-based masking: a tool to improve functional connectivity results of resting-state fMRI, Hum Brain Mapp, 37, 2407, 10.1002/hbm.23182 · DOI
- Rubinov, 2010, Complex network measures of brain connectivity: uses and interpretations, Neuroimage, 52, 1059, 10.1016/j.neuroimage.2009.10.003 · DOI · Paper page
- Bullmore, 2009, Complex brain networks: graph theoretical analysis of structural and functional systems, Nat Rev Neurosci, 10, 186, 10.1038/nrn2575 · DOI · Paper page
- Bouyssi-Kobar, 2019, Altered functional brain network integration, segregation, and Modularity in infants born very preterm at term-equivalent age, J Pediatr, 213, 13, 10.1016/j.jpeds.2019.06.030 · DOI
- Muldoon, 2016, Small-world propensity and weighted brain networks, Sci Rep, 6, 10.1038/srep22057 · DOI
- Benjamini, 1995, Controlling the false discovery rate: a practical and powerful approach to multiple testing, J R Stat Soc, 57, 289, 10.1111/j.2517-6161.1995.tb02031.x · DOI · Paper page
- Rakesh, 2021, Neighborhood disadvantage and longitudinal brain-predicted-age trajectory during adolescence, Dev Cogn Neurosci, 51, 10.1016/j.dcn.2021.101002 · DOI
- Karim, 2021, Aging faster: worry and rumination in late life are associated with greater brain age, Neurobiol Aging, 101, 13, 10.1016/j.neurobiolaging.2021.01.009 · DOI
- Lautarescu, 2020, Prenatal stress: effects on fetal and child brain development, Int Rev Neurobiol, 150, 17, 10.1016/bs.irn.2019.11.002 · DOI · Paper page
- Rakers, 2020, Transfer of maternal psychosocial stress to the fetus, Neurosci Biobehav Rev, 117, 185, 10.1016/j.neubiorev.2017.02.019 · DOI
- Negrón-Oyarzo, 2016, Impaired functional connectivity in the Prefrontal Cortex: a mechanism for chronic stress-Induced Neuropsychiatric disorders, Neural Plast, 2016, 10.1155/2016/7539065 · DOI
- Golkar, 2014, The influence of work-related chronic stress on the regulation of emotion and on functional connectivity in the brain, PLoS One, 9, 10.1371/journal.pone.0104550 · DOI
- Delpech, 2016, Early life stress perturbs the maturation of microglia in the developing hippocampus, Brain Behav Immun, 57, 79, 10.1016/j.bbi.2016.06.006 · DOI · Paper page
- Tottenham, 2020, Early Adversity and the Neotenous human brain, Biol Psychiatry, 87, 350, 10.1016/j.biopsych.2019.06.018 · DOI
- Cook, 2023, Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm, Front Neurosci, 17, 10.3389/fnins.2023.1214080 · DOI
- Martenies, 2017, Disease and health inequalities Attributable to air pollutant exposure in Detroit, Michigan, Int J Environ Res Public Health, 14, 2843, 10.3390/ijerph14101243 · DOI
- Shao, 2020, Prenatal exposure to ambient air multi-pollutants significantly impairs intrauterine fetal development trajectory, Ecotoxicol Environ Saf, 201, 10.1016/j.ecoenv.2020.110726 · DOI
- Zhou, 2023, Individual and joint effect of indoor air pollution index and ambient particulate matter on fetal growth: a prospective cohort study, Int J Epidemiol, 52, 690, 10.1093/ije/dyad021 · DOI
- Scher, 2023, Interdisciplinary fetal-neonatal neurology training applies neural exposome perspectives to neurology principles and practice, Front Neurol, 14
- Tiffin, 2012, Inequalities in diet and nutrition, Proc Nutr Soc, 71, 105, 10.1017/S0029665111003284 · DOI
- Cusick, 2022, Nutrition and brain development, Curr Top Behav Neurosci, 53, 131, 10.1007/7854_2021_244 · DOI
- Lindsay, 2019, The interplay between nutrition and stress in pregnancy: implications for fetal programming of brain development, Biol Psychiatry, 85, 135, 10.1016/j.biopsych.2018.06.021 · DOI
- Sripada, 2014, Childhood poverty and stress reactivity are associated with aberrant functional connectivity in default mode network, Neuropsychopharmacology, 39, 2244, 10.1038/npp.2014.75 · DOI
- Chan, 2018, Socioeconomic status moderates age-related differences in the brain’s functional network organization and anatomy across the adult lifespan, Proc Natl Acad Sci USA, 115, E5144, 10.1073/pnas.1714021115 · DOI
- May, 2018, How Does the neighborhood “Come through the door?” Concentrated disadvantage, Residential Instability, and the home environment for Preschoolers, Am J Community Psychol, 61, 218, 10.1002/ajcp.12223 · DOI
- Richmond, 2022, Maternal warmth is associated with network segregation across late childhood: a longitudinal neuroimaging study, Front Psychol, 13, 10.3389/fpsyg.2022.917189 · DOI
- Whittle, 2017, Role of positive parenting in the association between neighborhood social disadvantage and brain development across adolescence, JAMA Psychiatr, 74, 824, 10.1001/jamapsychiatry.2017.1558 · DOI
- Pawar, 2023, Influence of neighborhood socioeconomic status on adverse outcomes in pregnancy, Matern Child Health J, 27, 1401, 10.1007/s10995-023-03701-9 · DOI
- Kim, 2018, Socioeconomic status can affect pregnancy outcomes and complications, even with a universal healthcare system, Int J Equity Health, 17, 2, 10.1186/s12939-017-0715-7 · DOI
- Keenan-Devlin, 2022, The intersection of race and socioeconomic status is associated with inflammation patterns during pregnancy and adverse pregnancy outcomes, Am J Reprod Immunol, 87, 10.1111/aji.13489 · DOI
Cited by
Nawaz, K., Babata, K., Scheid, L., Bitar, L., Ortiz, N. V., Kota, S., & Chalak, L. F. (2026) · Pediatric Research · doi:10.1038/s41390-026-05139-5 · Cited by 1
Metadata
- Authors
- Cook, K. M., De Asis-Cruz, J., Sitrin, C., Barnett, S. D., Krishnamurthy, D., & Limperopoulos, C.
- Venue
- The Journal of Pediatrics
- Publisher
- Elsevier BV
- Published
- 2024-11
- Volume
- 274
- Pages
- 114201
- ISSN
- 0022-3476
- Cited by
- 9
- References
- 12
- Language
- en
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 286 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Funders
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (T32-HD098066)
- Canadian Institutes of Health Research (MOP-81116)
- A James & Alice B Clark Foundation
- National Institutes of Health
- National Heart Lung and Blood Institute (R01-HL116585)
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