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Record W3210750370 · doi:10.1101/2021.11.03.21265661

Differential age-associated brain atrophy and white matter changes among homeless and precariously housed individuals compared to the general population

2021· preprint· en· W3210750370 on OpenAlexafffund
Jacob L. Stubbs, Andrea A. Jones, Daniel Wolfman, Ryan C. Y. Chan, Alexandra T. Vertinsky, Manraj K.S. Heran, Wayne Su, Donna J. Lang, Thalia S. Field, Kristina M. Gicas, Melissa L. Woodward, Allen E. Thornton, Alasdair M. Barr, Olga Leonova, G. William MacEwan, Alexander Rauscher, William G. Honer, William J. Panenka

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsSimon Fraser UniversityYork UniversitySpinal Cord Injury BCBC Mental Health & Substance Use ServicesUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMedical Research CouncilDirectorate for Biological SciencesMichael Smith Health Research BCUniversity of CambridgeHeart and Stroke Foundation of Canada
KeywordsPopulationMedicineDemographyFractional anisotropyGerontologyWhite matterEnvironmental healthMagnetic resonance imaging

Abstract

fetched live from OpenAlex

ABSTRACT Importance Homeless or precariously housed individuals live with poor health and experience premature mortality compared to the general population. With an increasing average age among this demographic, syndromes associated with neurogenerative disease are also increasing. Quantitative MRI measures may help define the roles of age and risk factors for poor brain health among these individuals. Objective To evaluate whether MRI measures of brain structure are differentially associated with age and selected risk factors among individuals who are homeless or precariously housed compared to a general population sample. Design, setting, and participants Cross sectional comparison of baseline data from 312 community-based, precariously housed participants with a publicly available dataset of 382 participants recruited from the general population. Exposure(s) The primary exposure was housing status (precariously housed vs general population). Risk factors in the precariously housed sample included mental illness, substance dependence, intravenous drug use, HIV, and history of traumatic brain injury. Main outcome(s) and measure(s) The main outcomes were MRI measures of whole-brain tissue- to-intracranial volume ratio, fractional anisotropy, and mean diffusivity. Multiple linear regression and piecewise regression were used to evaluate differences in associations between MRI measures and age between the samples, and to explore associations with risk factors in the precariously housed sample. Results Compared to the general population sample, older age in the precariously housed sample was associated with more whole-brain atrophy ( β =-0.20, p=0.0029), lower whole-brain FA ( β =-0.32, p <0.0001), and higher whole-brain MD ( β =0.69, p <0.0001). Several MRI measures had non-linear associations with age, with further adverse changes after age 35-40 in the precariously housed sample. Frontal and temporal cortical thickness, corpus callosum volume, and diffusivity in the association tracts, corpus callosum, and thalamic radiations were the regions of interest most differentially affected. History of traumatic brain injury, stimulant dependence, and heroin dependence were associated with more atrophy or alterations in white matter diffusivity in the precariously housed sample. Conclusions and relevance Older age is associated with adverse MRI measures of brain structure among homeless and precariously housed individuals compared to the general population. Education, improvements in care provision and policy may help to reduce the health disparities experienced by these individuals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.349
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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