Usage Information
Citation Information: JCI Insight. 2024;9(16):e181690. https://doi.org/10.1172/jci.insight.181690.
Abstract
Childhood obesity and its adverse health consequences have risen worldwide, with low socioeconomic status increasing the risk in high-income countries like the United States. Understanding the interplay between childhood obesity, cognition, socioeconomic factors, and the brain is crucial for prevention and treatment. Using data from the Adolescent Brain Cognitive Development (ABCD) study, we investigated how body mass index (BMI) relates to brain structural and functional connectivity metrics. Children with obesity or who are overweight (n = 2,356) were more likely to live in poverty and exhibited lower cognitive performance compared with children with a healthy weight (n = 4,754). Higher BMI was associated with multiple brain measures that were strongest for lower longitudinal diffusivity in corpus callosum; increased activity in cerebellum, insula, and somatomotor cortex; and decreased functional connectivity in multimodal brain areas, with effects more pronounced among children from low-income families. Notably, nearly 80% of the association of low income and 70% of the association of impaired cognition on BMI were mediated by higher brain activity in somatomotor areas. Increased resting activity in somatomotor areas and decreased structural and functional connectivity likely contribute to the higher risk of being overweight or having obesity among children from low-income families. Supporting low-income families and implementing educational interventions to improve cognition may promote healthy brain function and reduce the risk of obesity.
Authors
Dardo Tomasi, Nora D. Volkow
Usage data is cumulative from November 2024 through November 2025.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 2,427 | 358 |
| 238 | 130 | |
| Figure | 262 | 0 |
| Table | 49 | 0 |
| Supplemental data | 170 | 3 |
| Citation downloads | 128 | 0 |
| Totals | 3,274 | 491 |
| Total Views | 3,765 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
