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Record W4403636074 · doi:10.1371/journal.pone.0312117

Associations between people experiencing homelessness (PEH) and neurodegenerative disorders (NDDs): A systematic review and meta-analysis

2024· review· en· W4403636074 on OpenAlexafffundabout
Pengfei Fu, Vijay Mago, Rebecca Schiff, Bonnie Krysowaty

Bibliographic record

VenuePLoS ONE · 2024
Typereview
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of LethbridgeYork University
FundersCanada First Research Excellence FundYork University
KeywordsMeta-analysisDementiaWeb of scienceDiseaseMedicineGerontologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Homelessness represents a widespread social issue globally, yet the risk of neurodegenerative diseases (NDDs) associated with people experiencing homelessness (PEH) has not received sufficient attention. Therefore, this study aimed to explore the risk of NDDs among PEH and its variation across countries and regions through meta-analysis and systematic review. METHODS: Searching from databases such as PubMed and Web of Science, relevant research articles on PEH and NDDs were identified. After multiple screening, eight articles were selected for meta-analysis. Statistical methods and models were used to evaluate the association between PEH and NDDs, stratified by disease type and country. RESULTS: We found that PEH had a 51% higher risk of NDDs (OR = 1.51 (95% CI: 1.21, 1.89)) compared with those with stable housing. Specifically, PEH had a significantly higher risk of developing multiple sclerosis (OR = 4.64 (95% CI: 1.96, 10.98)). Alzheimer's disease and related dementias (ADRD) (OR = 1.93 (95% CI: 1.34, 2.77)), dementia (OR = 1.69 (95% CI: 1.26, 2.27)), and cognitive impairment (OR = 1.07 (95% CI: 0.98, 1.16)) were all at higher risk. Furthermore, country and regional differences were observed, with countries such as Iran (OR = 4.64 (95% CI: 1.96, 10.98)), the Netherlands (OR = 2.14 (95% CI: 1.23, 3.73)), the United States (OR = 1.66 (95% CI: 1.25, 2.22)), and Canada (OR = 1.06 (95% CI: 1.01, 1.10)) showing a higher risk of NDDs among the PEH. CONCLUSIONS: The study emphasizes the significant NDD risks among PEH, providing novel perspectives on this issue and shedding light on national disparities influenced by variations in healthcare systems and social environments. This will be beneficial for academia and government to prioritize the health of PEH with NDDs, aiming to mitigate disease incidence and economic burdens while preserving social stability and upholding basic human rights.

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)0.013
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.043
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.278
GPT teacher head0.440
Teacher spread0.162 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations4
Published2024
Admission routes3
Has abstractyes

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