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Family Poverty Affects the Rate of Human Infant Brain Growth

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Hanson, Jamie L., Hair, Nicole, Shen, Dinggang G., Shi, Feng, Gilmore, John H., Wolfe, Barbara L., Pollak, Seth D.·2013·PLoS ONE
DOI 10.1371/journal.pone.0080954PMC PMC3859472
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Abstract

Living in poverty places children at very high risk for problems across a variety of domains, including schooling, behavioral regulation, and health. Aspects of cognitive functioning, such as information processing, may underlie these kinds of problems. How might poverty affect the brain functions underlying these cognitive processes? Here, we address this question by observing and analyzing repeated measures of brain development of young children between five months and four years of age from economically diverse backgrounds (n = 77). In doing so, we have the opportunity to observe changes in brain growth as children begin to experience the effects of poverty. These children underwent MRI scanning, with subjects completing between 1 and 7 scans longitudinally. Two hundred and three MRI scans were divided into different tissue types using a novel image processing algorithm specifically designed to analyze brain data from young infants. Total gray, white, and cerebral (summation of total gray and white matter) volumes were examined along with volumes of the frontal, parietal, temporal, and occipital lobes. Infants from low-income families had lower volumes of gray matter, tissue critical for processing of information and execution of actions. These differences were found for both the frontal and parietal lobes. No differences were detected in white matter, temporal lobe volumes, or occipital lobe volumes. In addition, differences in brain growth were found to vary with socioeconomic status (SES), with children from lower-income households having slower trajectories of growth during infancy and early childhood. Volumetric differences were associated with the emergence of disruptive behavioral problems.

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Crossref · 10.1371/journal.pone.0080954

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Figure 1 This figure shows example axial slices from a typical subject scanned at birth (left column), 2 (middle column), and 4 years old (right column). T1 MRI, T2 MRI, and segmented gray matter (green) and white matter (red) are provided.
Figure 1 This figure shows example axial slices from a typical subject scanned at birth (left column), 2 (middle column), and 4 years old (right column). T1 MRI, T2 MRI, and segmented gray matter (green) and white matter (red) are provided.CC BY · PubMed Central
Figure 2 This figure shows total gray matter volume for group by age. Age in months is shown on the horizontal axis, spanning from 5 to 37 months. Total gray matter volume is shown on the vertical axis. The blue line shows children from Low SES households; children from Mid SES households are shown in red. The green line shows children from High SES households.
Figure 2 This figure shows total gray matter volume for group by age. Age in months is shown on the horizontal axis, spanning from 5 to 37 months. Total gray matter volume is shown on the vertical axis. The blue line shows children from Low SES households; children from Mid SES households are shown in red. The green line shows children from High SES households.CC BY · PubMed Central
Figure 3 This figure shows frontal lobe gray matter volumes for group by age. Age in months is shown on the horizontal axis, spanning from 5 to 37 months. Total gray matter volume is shown on the vertical axis. The blue line shows children from Low SES households; children from Mid SES households are shown in red. The green line shows children from High SES households.
Figure 3 This figure shows frontal lobe gray matter volumes for group by age. Age in months is shown on the horizontal axis, spanning from 5 to 37 months. Total gray matter volume is shown on the vertical axis. The blue line shows children from Low SES households; children from Mid SES households are shown in red. The green line shows children from High SES households.CC BY · PubMed Central
Figure 4 This figure shows parietal lobe gray matter volumes for group by age. Age in months is shown on the horizontal axis, spanning from 5 to 37 months. Total gray matter volume is shown on the vertical axis. The blue line shows children from Low SES households; children from Mid SES households are shown in red. The green line shows children from High SES households.
Figure 4 This figure shows parietal lobe gray matter volumes for group by age. Age in months is shown on the horizontal axis, spanning from 5 to 37 months. Total gray matter volume is shown on the vertical axis. The blue line shows children from Low SES households; children from Mid SES households are shown in red. The green line shows children from High SES households.CC BY · PubMed Central

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Metadata

Authors
Hanson, J. L., Hair, N., Shen, D. G., Shi, F., Gilmore, J. H., Wolfe, B. L., & Pollak, S. D.
Affiliations
  • University of Wisconsin–Madison (US)
  • University of North Carolina at Chapel Hill (US)
Corresponding author
Hanson, Jamie L.
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2013-12-11
Volume
8
Issue
12
Pages
e80954
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0080954
PMC
PMC3859472
OpenAlex
W2018329895
Cited by
430
References
76
Citations by year
2026: 18 · 2025: 16 · 2024: 25 · 2023: 29 · 2022: 31 · 2021: 43 · 2020: 65 · 2019: 34 · 2018: 38 · 2017: 44 · 2016: 39 · 2015: 30 · 2014: 17
FWCI
26.60
Type
journal article
Language
en
Update notices
correction (2015-12-30)
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • UNC Libraries
Funders
  • U.S. Department of Health and Human Services
  • Russell Sage Foundation
  • Sage Foundation
  • University of Wisconsin-Madison
  • McGill University
  • National Institutes of Health (n01hd23343-8-0-0, MH61285, MH100217)
  • National Institute on Aging (R01AG042599, R01AG041721, AG041721)
  • National Institute of Mental Health (MH100217, MH61285, T32MH018029, R01MH100217, N01-NS-9-2314, R01MH068858, N01-MH 90002, MH018029, MH 68858, R01MH061285)
  • National Institute on Drug Abuse (F31DA028087, N01-MH9-0002, DA028087)
  • National Institute of Neurological Disorders and Stroke (N01-NS-9-2317, N01-NS-92314, N01-HD02–3343, N01-MH9-0002, N01-NS-92319, N01-NS 92315, N01‐NS‐9‐2314, ‐2315, ‐2316, ‐2317, ‐2319 and ‐2320, N01-NS 92316, N01 NS-9-2320)
  • National Institute of Biomedical Imaging and Bioengineering (EB006733, EB009634, EB008374, R01EB008374, R01EB009634, R01EB006733)
  • National Institute of Child Health and Human Development (N01‐HD02‐3343)
  • U.S. Children's Bureau
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (P30HD003352, N01-HD023343)
Topics
  • Health Sciences › Nursing › Nutrition and Dietetics › Child Nutrition and Water Access
  • Social Sciences › Psychology › Clinical Psychology › Child Abuse and Trauma
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Food Security and Health in Diverse Populations
Keywords
household poverty, socioeconomic status, infant brain development, gray matter volume, white matter volume, frontal lobe, parietal lobe, low-income children, disruptive behavior problems, cognitive development, brain growth trajectories
MeSH terms
Adolescent, Brain, Child, Child, Preschool, Female, Frontal Lobe, Humans, Image Processing, Computer-Assisted, Infant, Infant, Newborn, Magnetic Resonance Imaging, Male, Occipital Lobe, Parietal Lobe, Poverty, Socioeconomic Factors, Temporal Lobe

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