Evidence map›Paper›PMID 40885227›Full record

ArticlePhysiology & behavior2025

Predicting sugar-sweetened beverage intake from the brain and known risk factors in adolescents.

Muzayyana Akhmadjonova, Grace E Shearrer

Abstract read
In one paragraph

Article in Physiology & behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Muzayyana AkhmadjonovaGraduate program in Neuroscience, University of Wyoming, United States; Department of Family and Consumer Sciences, University of Wyoming, United States.
Grace E ShearrerGraduate program in Neuroscience, University of Wyoming, United States; Department of Family and Consumer Sciences, University of Wyoming, United States; School of Computing, University of Wyoming, United States. Electronic address: gshearre@uwyo.edu.

Funding

Wyoming INBRE Phase 4- Equipment Supplement for x-ray diffractometer for Center for Advanced Scientific InstrumentationP20GM103432 · NIGMS · UNIVERSITY OF WYOMING · PI Nicolas A. Blouin · 2012 to 2026
$56.8M
NIGMS NIH HHS P20 GM103432
6 · The paper itself

Abstract

backgroundLow socio-economic status, male sex, and body mass index (BMI) are known risk factors for high sugar sweetened beverage (SSB) consumption in adolescents. The present analysis aimed to predict SSB intake based on known risk factors and resting-state functional magnetic resonance (rsfMRI) connectivity from the Adolescent Brain Cognitive Development study.

methodsUsing the year-2 follow up visit Block Kids Food Screener data, participants were categorized as low SSB consumers (<8 floz/day) or high SSB consumers (>16 floz/day). The high and low groups were matched on baseline age, BMI percentile (BMI%) and combined household income (CHI; n/SSBgroup = 841). We used a grid search linear support vector classifier (SVC) to select baseline features from BMI%, sex, age, CHI, and resting state functional connectivity associated with SSB intake. With the selected features we used a binary logistic model to predict high SSB consumption at year-2.

resultsThe SVC identified sex and 58 functional connections as relevant features and predicted SSB intake at year-2 with 57 % accuracy. Logistic regression revealed visual-right caudate connectivity (predicted probability [PP]: 0.71, pFDR = 0.02) and sex (PP

conclusionThe average correlation between visual cortex and right caudate is significantly related to high SSB consumption in adolescents. Participants from low CHI families are at higher risk of exclusion due to excessive motion.

Indexed as

BrainSugar-Sweetened BeveragesAdolescentBody Mass IndexFemaleHumansMagnetic Resonance ImagingMaleRisk FactorsAdolescentsFunctional magnetic resonance imagingResting-state functional connectivitySocio-economic statusSugar-sweetened beverages

Identifiers

PMID40885227
PMCPMC13292796

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.