Sex-specific differences in the association between body mass index and brain aging in young adults: Findings from the human connectome project

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7 Scopus citations

Abstract

Background: This report evaluated sex-specific differences in the association between brain aging and body mass index (BMI) in young adults using the publicly available data from the Human Connectome Project (HCP). Methods: Participants of HCP with available structural imaging and BMI data were included [n = 1112; mean age = 28.80 (SD = 3.70); mean BMI = 26.53 (SD = 5.20); males n = 507, females n = 605]. Predicted brain age was generated using raw T1-weighted MRI scan and a Gaussian Processes regression model. The difference (Δ aging) between brain age predicted by structural imaging and chronological age was computed. A linear regression model was used with Δ aging as the dependent variable, and sex, BMI, and BMI-by-sex interaction as independent variables of interest, and race, ethnicity, income, and education as covariates. Results: There was a significant BMI-by-sex interaction for Δ aging (p = 0.041). Higher BMI was associated with greater brain aging in both sexes. However, this association was substantially stronger in males (β = 0.215; SE = 0.050; p < 0.0001) than in females (β = 0.122; SE = 0.035; p = 0.0005). Conclusion: We found evidence suggesting that higher BMI is associated with greater brain aging in adults. Furthermore, the association between higher BMI and greater brain aging was stronger in males than in females. Future studies are needed to explore the mechanistic pathways that link higher BMI to greater brain aging and whether weight-loss interventions, such as exercise, can reverse higher BMI-associated greater brain aging.

Original languageEnglish (US)
Article number105059
JournalPsychoneuroendocrinology
Volume124
DOIs
StatePublished - Feb 2021

Keywords

  • Body mass index
  • Brain age
  • Sex differences

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Endocrine and Autonomic Systems
  • Psychiatry and Mental health
  • Biological Psychiatry

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