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Record W4381309713 · doi:10.1111/jgs.18477

Sex‐based differences in the association between loneliness and polypharmacy among older adults in Ontario, Canada

2023· article· en· W4381309713 on OpenAlexafffundabout
James Im, Susan E. Bronskill, Rachel Strauss, Andrea Gruneir, Jun Guan, Alexa Boblitz, Mindy Lu, Paula A. Rochon, Rachel Savage

Bibliographic record

VenueJournal of the American Geriatrics Society · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of AlbertaInstitute for Clinical Evaluative SciencesWomen's College HospitalPublic Health OntarioUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineLonelinessPolypharmacyGerontologyAssociation (psychology)GeriatricsDemographyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Emerging evidence shows loneliness is associated with polypharmacy and high-risk medications in older adults. Despite notable sex-based differences in the prevalence in each of loneliness and polypharmacy, the role of sex in the relationship between loneliness and polypharmacy is unclear. We explored the relationship between loneliness and polypharmacy in older female and male respondents and described sex-related variations in prescribed medication subclasses. METHODS: We performed a cross-sectional analysis of representative data from the Canadian Community Health Survey-Healthy Aging cycle (2008/2009) linked to health administrative databases in Ontario respondents aged 66 years and older. Loneliness was measured using the Three-Item Loneliness Scale, with respondents classified as not lonely, moderately lonely, or severely lonely. Polypharmacy was defined as five or more concurrently-prescribed medications. Sex-stratified multivariable logistic regression models with survey weights were used to assess the relationship between loneliness and polypharmacy. Among those with polypharmacy, we examined the distribution of prescribed medication subclasses and potentially inappropriate medications. RESULTS: Of the 2348 individuals included in this study, 54.6% were female respondents. The prevalence of polypharmacy was highest in those with severe loneliness both in female (no loneliness, 32.4%; moderate loneliness, 36.5%; severe loneliness, 44.1%) and male respondents (32.5%, 32.2%, and 42.5%). Severe loneliness was significantly associated with greater adjusted odds of polypharmacy in female respondents (OR = 1.59; 95% CI: 1.01-2.50) but this association was attenuated after adjustment in male respondents (OR = 1.00; 95% CI: 0.56-1.80). Among those with polypharmacy, antidepressants were more commonly prescribed in female respondents with severe loneliness (38.7% [95% CI: 27.3-50.0]) compared to those who were moderately lonely (17.7% [95% CI: 9.3-26.2]). CONCLUSIONS: Severe loneliness was independently associated with polypharmacy in older female but not male respondents. Clinicians should consider loneliness as an important risk factor in medication reviews and deprescribing efforts to minimize medication-related harms, particularly in older women.

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)0.001
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 score0.014
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.020
GPT teacher head0.293
Teacher spread0.273 · 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

Citations9
Published2023
Admission routes3
Has abstractyes

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