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Record W3081563555 · doi:10.23889/ijpds.v5i1.1351

Individual and neighbourhood socioeconomic status increase risk of avoidable hospitalizations among Canadian adults: A retrospective cohort study of linked population health data

2020· article· en· W3081563555 on OpenAlexafffundabout
Lauren E. Wallar, Laura C. Rosella

Bibliographic record

VenueInternational Journal for Population Data Science · 2020
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity of TorontoUniversity of Guelph
KeywordsMedicineSocioeconomic statusPopulationNeighbourhood (mathematics)DemographyCohortHousehold incomeEnvironmental healthGerontologyGeography

Abstract

fetched live from OpenAlex

INTRODUCTION: Avoidable hospitalizations refer to acute care use for conditions that should normally be managed in primary care settings. Lower socioeconomic status that is often measured using area-based indicators (e.g. median household income) has been shown to increase risk of avoidable hospitalizations. However, both area- and individual-level socioeconomic status can contribute to hospitalization risk, but previous data limitations have prevented separate analyses. Further, the joint effect of individual and neighbourhood socioeconomic status has not been established in the Canadian population. To address this, this study links individual-level household income and neighbourhood-level material deprivation data within a population-based Canadian cohort. OBJECTIVES: To determine the individual and joint effect of individual-level household income and neighbourhood-level material deprivation on risk of hospitalization for a set of chronic ambulatory care sensitive conditions using linked health survey, hospital discharge, and census-derived data. METHODS: A pooled cohort was created by linking sociodemographic and health information from eight cycles of the Canadian Community Health Survey (2000/2001 - 2010) to hospital discharge records and Canadian Marginalization Indices (2001, 2006) (N = 354,595). The primary outcome variable was risk of index hospitalization with a primary diagnosis of angina, asthma, congestive heart failure, chronic obstructive pulmonary disease, diabetes, epilepsy, or hypertension. The primary exposure variable was joint individual-level national household income quintile and neighbourhood-level material deprivation quintile. Relative risk (RR) was estimated by constructing modified Poisson regression models with robust error variance. RESULTS: In fully adjusted models with income and deprivation considered separately, individuals in the lowest household income quintile and highest material deprivation quintile were at increased risk of hospitalization (Income RR: 1.82 (95% CI 1.56-2.13) Deprivation RR: 1.67 (1.44-1.95)). When income and deprivation were jointly considered, those with low individual income living in high deprivation neighbourhoods were at greatest risk of hospitalization (RR 1.83 (95% CI 1.63 - 2.05)). CONCLUSION: Both individual income and neighbourhood deprivation separately and jointly increase risk of avoidable hospitalizations. Additional research is needed to understand their mechanisms of action. However, both levels should be considered when designing effective policies and interventions to reduce avoidable hospitalizations.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.021
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.007
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
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 head0.059
GPT teacher head0.420
Teacher spread0.361 · 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

Citations15
Published2020
Admission routes3
Has abstractyes

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