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Nat Neurosci. 2015 May;18(5):773-8. doi: 10.1038/nn.3983. Epub 2015 Mar 30.

Family income, parental education and brain structure in children and adolescents.

Author information

  • 11] College of Physicians and Surgeons, Columbia University, New York, New York, USA. [2] Teachers College, Columbia University, New York, New York, USA.
  • 21] Department of Psychology, University of Southern California, Los Angeles, California, USA. [2] The Saban Research Institute of Children's Hospital, Los Angeles, California, USA. [3] Department of Pediatrics of the Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
  • 3Robert Wood Johnson Health and Society Scholar Program, Columbia University, New York, New York, USA.
  • 4Stein Institute for Research on Aging, University of California, San Diego, La Jolla, California, USA.
  • 51] The Saban Research Institute of Children's Hospital, Los Angeles, California, USA. [2] Department of Pediatrics of the Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
  • 61] Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, California, USA. [2] Department of Radiology, University of California, San Diego, La Jolla, California, USA. [3] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA.
  • 71] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Center for Human Development, University of California, San Diego, La Jolla, California, USA. [3] Department of Psychiatry, University of California, San Diego, La Jolla, California, USA.
  • 81] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] The MIND Institute, University of California at Davis, Davis, California, USA.
  • 91] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] The Qualcomm Institute, University of California, San Diego, La Jolla, California, USA.
  • 10MD Revolution, Inc., La Jolla, California, USA.
  • 11Human Biology, J. Craig Venter Institute, University of California, San Diego, La Jolla, California, USA.
  • 121] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Pathology, University of California, San Diego, La Jolla, California, USA.
  • 131] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Weill Medical College of Cornell University, New York, New York, USA.
  • 141] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Medicine, John A. Burns School of Medicine, University of Hawaii and the Queen's Medical Center, Honolulu, Hawaii, USA.
  • 151] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] University of Massachusetts Medical School, Worcester, Massachusetts, USA.
  • 161] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA. [3] Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA. [4] Department of Investigative Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.
  • 171] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA. [3] Kennedy Krieger Institute, Baltimore, Maryland, USA.
  • 181] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Kennedy Krieger Institute, Baltimore, Maryland, USA.
  • 191] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, USA. [3] Harvard Medical School, Boston, Massachusetts, USA.
  • 201] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Harvard Medical School, Boston, Massachusetts, USA. [3] Department of Neurology, Massachusetts General Hospital, Massachusetts, USA.
  • 211] Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, California, USA. [2] Department of Radiology, University of California, San Diego, La Jolla, California, USA. [3] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [4] Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA. [5] Department of Neurology, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA. [6] Center for Translational Imaging and Personalized Medicine, University of California San Diego, La Jolla, California, USA.
  • 221] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Center for Human Development, University of California, San Diego, La Jolla, California, USA. [3] Department of Psychiatry, University of California, San Diego, La Jolla, California, USA. [4] Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA.
  • 231] The Saban Research Institute of Children's Hospital, Los Angeles, California, USA. [2] Department of Pediatrics of the Keck School of Medicine, University of Southern California, Los Angeles, California, USA. [3] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA.

Abstract

Socioeconomic disparities are associated with differences in cognitive development. The extent to which this translates to disparities in brain structure is unclear. We investigated relationships between socioeconomic factors and brain morphometry, independently of genetic ancestry, among a cohort of 1,099 typically developing individuals between 3 and 20 years of age. Income was logarithmically associated with brain surface area. Among children from lower income families, small differences in income were associated with relatively large differences in surface area, whereas, among children from higher income families, similar income increments were associated with smaller differences in surface area. These relationships were most prominent in regions supporting language, reading, executive functions and spatial skills; surface area mediated socioeconomic differences in certain neurocognitive abilities. These data imply that income relates most strongly to brain structure among the most disadvantaged children.

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PMID:
25821911
[PubMed - indexed for MEDLINE]
PMCID:
PMC4414816
Free PMC Article
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