Evidence map›Paper›PMID 23564371›Full record

ArticleBrain imaging and behavior2013

Impact of body mass index on neuronal fiber bundle lengths among healthy older adults.

Jacob D Bolzenius, David H Laidlaw, Ryan P Cabeen, Thomas E Conturo, Amanda R McMichael, Elizabeth M Lane, Jodi M Heaps, Lauren E Salminen, Laurie M Baker, John Gunstad and 1 more

Abstract read
In one paragraph

Article in Brain imaging and behavior, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.5field-weighted citation impact, top 6% of its field
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

25 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Independent and Differential Effects of Obesity and Hypertension on Cognitive and Functional Abilities.Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists · 2018
    Article
  11. Review
  12. Differential associations between systemic markers of disease and white matter tissue health in middle-aged and older adults.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2017
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

11 authors at 5 institutions in 1 country.

Jacob D BolzeniusUniversity of Missouri-Saint Louis, One University Boulevard, Stadler Hall 443, Saint Louis, MO, 63121, USA, jdbdgf@umsl.edu.
David H Laidlaw
Ryan P Cabeen
Thomas E Conturo
Amanda R McMichael
Elizabeth M Lane
Jodi M Heaps
Lauren E Salminen
Laurie M Baker
John Gunstad
Robert H Paul
University of Missouri–St. Louis · USBrown University · USWashington University in St. Louis · USKent State University · USVanderbilt University Medical Center · US

Funding

Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Neuromarkers of age-related cognitive declineR01NS052470 · NINDS · UNIVERSITY OF MISSOURI-ST. LOUIS · PI PAUL, ROBERT HARRIS · 2007 to 2011
$2.7M
TRACKING NEURONAL FIBERS IN LIVING HUMAN BRAIN BY MRIR01NS039538 · NINDS · WASHINGTON UNIVERSITY · PI CONTURO, THOMAS EDWARD · 2001 to 2005
$2.1M
DEVELOPMENTAL CHARACTERISTICS OF MRI DIFFUSION TENSOR PATHWAY CHANGES IN AUTISMR21MH090494 · NIMH · WASHINGTON UNIVERSITY · PI CONTURO, THOMAS EDWARD · 2010 to 2011
$441k
BRAIN MICROSTRUCTURE & BEHAVIOR IN NEWLY-DIAGNOSED TODDLERS/PRESCHOOLERS WITH ASDR21MH105822 · NIMH · WASHINGTON UNIVERSITY · PI CONTURO, THOMAS EDWARD, STRAUSS, MARK · 2015 to 2016
$423k
NCATS NIH HHS UL1 TR000448NIMH NIH HHS R21 MH090494NIMH NIH HHS R21 MH105822NINDS NIH HHS R01 NS039538NINDS NIH HHS R01 NS052470
6 · The paper itself

Abstract

Increased body mass index (BMI) has been linked to various detrimental health outcomes, including cognitive dysfunction. Recent work investigating associations between obesity and the brain has revealed decreased white matter microstructural integrity in individuals with elevated BMI, independent of age or comorbid health conditions. However, the relationship between high BMI and white matter fiber bundle length (FBL), which represents a novel metric of microstructural brain integrity, remains unknown. The present study utilized quantitative tractography based on diffusion tensor imaging (DTI) to investigate the relationship between BMI and FBL in 72 otherwise healthy older adults (24 males, 48 females). All participants were between 51 and 85 years of age (M = 63.26, SD = 8.76). Results revealed that elevated BMI was associated with shorter FBL in the temporal lobe, independent of age (p < .01). In addition, increased age was associated with shorter frontal, temporal, and whole brain FBL (all p values < .01). These findings indicate that, while increased age is an important factor associated with reduced FBL, high BMI is uniquely associated with reduced FBL in the temporal lobe. These data offer evidence for additive adverse effects of high BMI on the brain, especially in areas already vulnerable to aging processes and age-related neurodegenerative diseases. Further research is necessary to determine the physiological mechanisms associated with the shortening of FBL in individuals with high BMI.

Indexed as

Body Mass IndexAgedAged, 80 and overAgingBrainDiffusion Tensor ImagingFemaleHumansMaleMiddle AgedNerve Fibers, MyelinatedReference ValuesStatistics as TopicTemporal Lobe

Identifiers

PMID23564371
PMCPMC3830712
OpenAlexW2077857224

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.