Family income, parental education and brain structure in children and adolescents
Socioeconomic status is associated with cognitive development, but the extent to which this reflects neuroanatomical differences is unclear. In 1,099 children and adolescents, family income was nonlinearly associated with brain surface area, and this association was greatest among disadvantaged chil...
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| Vydané v: | Nature neuroscience Ročník 18; číslo 5; s. 773 - 778 |
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| Hlavní autori: | , , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
New York
Nature Publishing Group US
01.05.2015
Nature Publishing Group |
| Predmet: | |
| ISSN: | 1097-6256, 1546-1726, 1546-1726 |
| On-line prístup: | Získať plný text |
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| Abstract | Socioeconomic status is associated with cognitive development, but the extent to which this reflects neuroanatomical differences is unclear. In 1,099 children and adolescents, family income was nonlinearly associated with brain surface area, and this association was greatest among disadvantaged children. Further, surface area mediated links between income and executive functioning.
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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| AbstractList | 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. Socioeconomic status is associated with cognitive development, but the extent to which this reflects neuroanatomical differences is unclear. In 1,099 children and adolescents, family income was nonlinearly associated with brain surface area, and this association was greatest among disadvantaged children. Further, surface area mediated links between income and executive functioning. 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. 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.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. Socioeconomic disparities are associated with differences in cognitive development. The extent to which this translates to disparities in brain structure is unclear. Here, we investigated relationships between socioeconomic factors and brain morphometry, independently of genetic ancestry, among a cohort of 1099 typically developing individuals between 3 and 20 years. Income was logarithmically associated with brain surface area. Specifically, 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 indicate that income relates most strongly to brain structure among the most disadvantaged children. Potential implications are discussed. |
| Audience | Academic |
| Author | Kenet, Tal Kennedy, David N Jernigan, Terry L Houston, Suzanne M Libiger, Ondrej Noble, Kimberly G Sowell, Elizabeth R Amaral, David G Akshoomoff, Natacha Kan, Eric Brito, Natalie H Bloss, Cinnamon S Murray, Sarah S Kuperman, Joshua M Chang, Linda Dale, Anders M Mostofsky, Stewart Ernst, Thomas M Van Zijl, Peter Casey, B J Bartsch, Hauke Schork, Nicholas J Frazier, Jean A Gruen, Jeffrey R Kaufmann, Walter E |
| AuthorAffiliation | 6 Robert Wood Johnson Health and Society Scholar Program, Columbia University 5 Department of Pediatrics of the Keck School of Medicine, University of Southern California, Los Angeles, CA 12 University of Massachusetts Medical School, Boston, MA 2 Teachers College, Columbia University, New York, NY 17 Harvard Medical School 13 Departments of Pediatrics, Genetics, and Investigative Medicine, Yale University School of Medicine, New Haven, CT 7 University of California at San Diego 15 Kennedy Krieger Institute 19 Center for Translational Imaging and Personalized Medicine, University of California 9 MD Revolution, Inc 16 Boston Children’s Hospital 1 College of Physicians & Surgeons, Columbia University, New York, NY 10 Weill Medical College of Cornell University, New York, NY 8 The MIND Institute, University of California at Davis 4 The Saban Research Institute of Children’s Hospital, Los Angeles, CA 11 University of Hawaii at Manoa, Honolulu, HI 14 Johns Hopkins University 18 Massachusetts General Hospita |
| AuthorAffiliation_xml | – name: 17 Harvard Medical School – name: 7 University of California at San Diego – name: 13 Departments of Pediatrics, Genetics, and Investigative Medicine, Yale University School of Medicine, New Haven, CT – name: 16 Boston Children’s Hospital – name: 19 Center for Translational Imaging and Personalized Medicine, University of California – name: 3 Department of Psychology, University of Southern California, Los Angeles, CA – name: 1 College of Physicians & Surgeons, Columbia University, New York, NY – name: 8 The MIND Institute, University of California at Davis – name: 10 Weill Medical College of Cornell University, New York, NY – name: 14 Johns Hopkins University – name: 6 Robert Wood Johnson Health and Society Scholar Program, Columbia University – name: 2 Teachers College, Columbia University, New York, NY – name: 18 Massachusetts General Hospital – name: 15 Kennedy Krieger Institute – name: 4 The Saban Research Institute of Children’s Hospital, Los Angeles, CA – name: 9 MD Revolution, Inc – name: 5 Department of Pediatrics of the Keck School of Medicine, University of Southern California, Los Angeles, CA – name: 11 University of Hawaii at Manoa, Honolulu, HI – name: 12 University of Massachusetts Medical School, Boston, MA |
| Author_xml | – sequence: 1 givenname: Kimberly G surname: Noble fullname: Noble, Kimberly G email: kgn2106@columbia.edu organization: College of Physicians and Surgeons, Columbia University, Teachers College, Columbia University – sequence: 2 givenname: Suzanne M surname: Houston fullname: Houston, Suzanne M organization: Department of Psychology, University of Southern California, The Saban Research Institute of Children's Hospital, Department of Pediatrics of the Keck School of Medicine, University of Southern California – sequence: 3 givenname: Natalie H surname: Brito fullname: Brito, Natalie H organization: Robert Wood Johnson Health and Society Scholar Program, Columbia University – sequence: 4 givenname: Hauke surname: Bartsch fullname: Bartsch, Hauke organization: Stein Institute for Research on Aging, University of California, San Diego, La Jolla, California, USA – sequence: 5 givenname: Eric surname: Kan fullname: Kan, Eric organization: The Saban Research Institute of Children's Hospital, Department of Pediatrics of the Keck School of Medicine, University of Southern California – sequence: 6 givenname: Joshua M surname: Kuperman fullname: Kuperman, Joshua M organization: Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, California, USA., Department of Radiology, University of California, San Diego, La Jolla, California, USA., The Pediatric Imaging, Neurocognition, and Genetics Study – sequence: 7 givenname: Natacha surname: Akshoomoff fullname: Akshoomoff, Natacha organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Center for Human Development, University of California, San Diego, La Jolla, California, USA., Department of Psychiatry, University of California, San Diego, La Jolla, California, USA – sequence: 8 givenname: David G surname: Amaral fullname: Amaral, David G organization: The Pediatric Imaging, Neurocognition, and Genetics Study, The MIND Institute, University of California at Davis – sequence: 9 givenname: Cinnamon S surname: Bloss fullname: Bloss, Cinnamon S organization: The Pediatric Imaging, Neurocognition, and Genetics Study, The Qualcomm Institute, University of California, San Diego, La Jolla, California, USA – sequence: 10 givenname: Ondrej surname: Libiger fullname: Libiger, Ondrej organization: MD Revolution, Inc – sequence: 11 givenname: Nicholas J surname: Schork fullname: Schork, Nicholas J organization: Human Biology, J. Craig Venter Institute, University of California, San Diego, La Jolla, California, USA – sequence: 12 givenname: Sarah S surname: Murray fullname: Murray, Sarah S organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Department of Pathology, University of California, San Diego, La Jolla, California, USA – sequence: 13 givenname: B J surname: Casey fullname: Casey, B J organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Weill Medical College of Cornell University – sequence: 14 givenname: Linda surname: Chang fullname: Chang, Linda organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Department of Medicine, John A. Burns School of Medicine, University of Hawaii and the Queen's Medical Center – sequence: 15 givenname: Thomas M surname: Ernst fullname: Ernst, Thomas M organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Department of Medicine, John A. Burns School of Medicine, University of Hawaii and the Queen's Medical Center – sequence: 16 givenname: Jean A surname: Frazier fullname: Frazier, Jean A organization: The Pediatric Imaging, Neurocognition, and Genetics Study, University of Massachusetts Medical School – sequence: 17 givenname: Jeffrey R surname: Gruen fullname: Gruen, Jeffrey R organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Department of Pediatrics, Yale University School of Medicine, Department of Genetics, Yale University School of Medicine, Department of Investigative Medicine, Yale University School of Medicine – sequence: 18 givenname: David N orcidid: 0000-0002-9377-0797 surname: Kennedy fullname: Kennedy, David N organization: The Pediatric Imaging, Neurocognition, and Genetics Study, University of Massachusetts Medical School – sequence: 19 givenname: Peter surname: Van Zijl fullname: Van Zijl, Peter organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Department of Radiology, Johns Hopkins University, Kennedy Krieger Institute – sequence: 20 givenname: Stewart surname: Mostofsky fullname: Mostofsky, Stewart organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Kennedy Krieger Institute – sequence: 21 givenname: Walter E surname: Kaufmann fullname: Kaufmann, Walter E organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Department of Neurology, Boston Children's Hospital, Harvard Medical School – sequence: 22 givenname: Tal orcidid: 0000-0003-3346-9027 surname: Kenet fullname: Kenet, Tal organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Harvard Medical School, Department of Neurology, Massachusetts General Hospital – sequence: 23 givenname: Anders M surname: Dale fullname: Dale, Anders M organization: Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, California, USA., Department of Radiology, University of California, San Diego, La Jolla, California, USA., The Pediatric Imaging, Neurocognition, and Genetics Study, Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA., Department of Neurology, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA., Center for Translational Imaging and Personalized Medicine, University of California San Diego – sequence: 24 givenname: Terry L surname: Jernigan fullname: Jernigan, Terry L organization: The Pediatric Imaging, Neurocognition, and Genetics Study, Center for Human Development, University of California, San Diego, La Jolla, California, USA., Department of Psychiatry, University of California, San Diego, La Jolla, California, USA., Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA – sequence: 25 givenname: Elizabeth R surname: Sowell fullname: Sowell, Elizabeth R email: esowell@chla.usc.edu organization: The Saban Research Institute of Children's Hospital, Department of Pediatrics of the Keck School of Medicine, University of Southern California, The Pediatric Imaging, Neurocognition, and Genetics Study |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25821911$$D View this record in MEDLINE/PubMed |
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| Title | Family income, parental education and brain structure in children and adolescents |
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