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Record W3040179572 · doi:10.1371/journal.pmed.1003172

Associations of substance use, psychosis, and mortality among people living in precarious housing or homelessness: A longitudinal, community-based study in Vancouver, Canada

2020· article· en· W3040179572 on OpenAlexafffundabout
Andrea A. Jones, Kristina M. Gicas, Sam Seyedin, Taylor S. Willi, Olga Leonova, Fidel Vila‐Rodriguez, Ric M. Procyshyn, Geoffrey N. Smith, Toby Schmitt, Alexandra T. Vertinsky, Tari Buchanan, Alex Rauscher, Donna J. Lang, G. William MacEwan, Viviane D. Lima, Julio Montaner, William J. Panenka, Alasdair M. Barr, Allen E. Thornton, William G. Honer

Bibliographic record

VenuePLoS Medicine · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
FundersH. Lundbeck A/SVancouver Coastal Health Research InstituteUniversity of British ColumbiaGovernment of CanadaMichael Smith Health Research BCViiV HealthcarePfizerFondation Brain CanadaCanadian Institutes of Health ResearchSunovionJanssen PharmaceuticalsGilead SciencesSimon Fraser UniversityAstraZenecaEli Lilly and Company
KeywordsCannabisMedicineInterquartile rangeOdds ratioPsychiatryConfidence intervalLongitudinal studyDemographyAlcohol use disorderPoison controlEnvironmental healthInternal medicineAlcohol

Abstract

fetched live from OpenAlex

BACKGROUND: The "trimorbidity" of substance use disorder and mental and physical illness is associated with living in precarious housing or homelessness. The extent to which substance use increases risk of psychosis and both contribute to mortality needs investigation in longitudinal studies. METHODS AND FINDINGS: A community-based sample of 437 adults (330 men, mean [SD] age 40.6 [11.2] years) living in Vancouver, Canada, completed baseline assessments between November 2008 and October 2015. Follow-up was monthly for a median 6.3 years (interquartile range 3.1-8.6). Use of tobacco, alcohol, cannabis, cocaine, methamphetamine, and opioids was assessed by interview and urine drug screen; severity of psychosis was also assessed. Mortality (up to November 15, 2018) was assessed from coroner's reports and hospital records. Using data from monthly visits (mean 9.8, SD 3.6) over the first year after study entry, mixed-effects logistic regression analysis examined relationships between risk factors and psychotic features. A past history of psychotic disorder was common (60.9%). Nonprescribed substance use included tobacco (89.0%), alcohol (77.5%), cocaine (73.2%), cannabis (72.8%), opioids (51.0%), and methamphetamine (46.5%). During the same year, 79.3% of participants reported psychotic features at least once. Greater risk was associated with number of days using methamphetamine (adjusted odds ratio [aOR] 1.14, 95% confidence interval [CI] 1.05-1.24, p = 0.001), alcohol (aOR 1.09, 95% CI 1.01-1.18, p = 0.04), and cannabis (aOR 1.08, 95% CI 1.02-1.14, p = 0.008), adjusted for demographic factors and history of past psychotic disorder. Greater exposure to concurrent month trauma was associated with increased odds of psychosis (adjusted model aOR 1.54, 95% CI 1.19-2.00, p = 0.001). There was no evidence for interactions or reverse associations between psychotic features and time-varying risk factors. During 2,481 total person years of observation, 79 participants died (18.1%). Causes of death were physical illness (40.5%), accidental overdose (35.4%), trauma (5.1%), suicide (1.3%), and unknown (17.7%). A multivariable Cox proportional hazard model indicated baseline alcohol dependence (adjusted hazard ratio [aHR] 1.83, 95% CI 1.09-3.07, p = 0.02), and evidence of hepatic fibrosis (aHR 1.81, 95% CI 1.08-3.03, p = 0.02) were risk factors for mortality. Among those under age 55 years, a history of a psychotic disorder was a risk factor for mortality (aHR 2.38, 95% CI 1.03-5.51, p = 0.04, adjusted for alcohol dependence at baseline, human immunodeficiency virus [HIV], and hepatic fibrosis). The primary study limitation concerns generalizability: conclusions from a community-based, diagnostically heterogeneous sample may not apply to specific diagnostic groups in a clinical setting. Because one-third of participants grew up in foster care or were adopted, useful family history information was not obtainable. CONCLUSIONS: In this study, we found methamphetamine, alcohol, and cannabis use were associated with higher risk for psychotic features, as were a past history of psychotic disorder, and experiencing traumatic events. We found that alcohol dependence, hepatic fibrosis, and, only among participants <55 years of age, history of a psychotic disorder were associated with greater risk for mortality. Modifiable risk factors in people living in precarious housing or homelessness can be a focus for interventions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.059
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.163
GPT teacher head0.398
Teacher spread0.235 · 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 teacher head, 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

Citations50
Published2020
Admission routes3
Has abstractyes

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