Evidence map›Paper›PMID 37506551›Full record

ArticleNeurobiology of aging2023

Lower socioeconomic status is associated with premature brain aging.

Natalie Busby, Sarah Newman-Norlund, Sara Sayers, Roger Newman-Norlund, Janina Wilmskoetter, Chris Rorden, Samaneh Nemati, Sarah Wilson, Nicholas Riccardi, Rebecca Roth and 4 more

Abstract read
In one paragraph

Article in Neurobiology of aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Natalie BusbyDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA. Electronic address: hethern@mailbox.sc.edu.
Sarah Newman-NorlundDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Sara SayersDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Roger Newman-NorlundDepartment of Psychology, University of South Carolina, Columbia, SC, USA.
Janina WilmskoetterDepartment of Neurology, Medical University of South Carolina, Charleston, SC, USA.
Chris RordenDepartment of Psychology, University of South Carolina, Columbia, SC, USA.
Samaneh NematiDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Sarah WilsonDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Nicholas RiccardiDepartment of Psychology, University of South Carolina, Columbia, SC, USA.
Rebecca RothDepartment of Neurology, Emory University, Atlanta, GA, USA.
Lisa JohnsonDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Dirk B den OudenDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Julius FridrikssonDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Leonardo BonilhaDepartment of Neurology, Emory University, Atlanta, GA, USA.

Funding

Telerehab for Aphasia (TERRA)P50DC014664 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI BONILHA, LEONARDO F · 2016 to 2025
$25.0M
NIDCD NIH HHS P50 DC014664
6 · The paper itself

Abstract

backgroundPremature age-related brain changes may be influenced by physical health factors. Lower socioeconomic status (SES) is often associated with poorer physical health. In this study, we aimed to investigate the relationship between SES and premature brain aging.

methodsBrain age was estimated from T1-weighted images using BrainAgeR in 217 participants from the ABC@UofSC Repository. The difference between brain and chronological age (BrainGAP) was calculated. Multiple regression models were used to predict BrainGAP with age, SES, body mass index, diabetes, hypertension, sex, race, and education as predictors. SES was calculated from size-adjusted household income and the cost of living.

resultsFifty-five participants (25.35%) had greater brain age than chronological age (premature brain aging). Multiple regression models revealed that age, sex, and SES were significant predictors of BrainGAP with lower SES associated with greater BrainGAP (premature brain aging).

conclusionsThis study demonstrates that lower SES is an independent contributor to premature brain aging. This may provide additional insight into the mechanisms associated with brain health, cognition, and resilience to neurological injury.

Indexed as

Aging, PrematureHypertensionAgingBrainEducational StatusHumansSocial ClassSocioeconomic FactorsAgingBrain ageBrain HealthHealthSocioeconomic status

Identifiers

PMID37506551
PMCPMC13277732

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.