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Record W2966802368 · doi:10.23889/ijpds.v4i1.1102

Population-based study of the association between food insecurity and preventable hospitalization among persons with diabetes using linked survey and administrative data

2019· article· en· W2966802368 on OpenAlex
Neeru Gupta, Zihao Sheng

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal for Population Data Science · 2019
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of New Brunswick
FundersCanadian Institutes of Health ResearchDiabetes CanadaFondation de la recherche en santé du Nouveau-BrunswickHeart and Stroke Foundation of CanadaDiabetes Action Research and Education Foundation
KeywordsMedicineSocioeconomic statusEnvironmental healthDiabetes mellitusLogistic regressionPopulationOddsOdds ratioDemographyGerontology

Abstract

fetched live from OpenAlex

BACKGROUND: Studies have found food insecurity to be more prevalent among persons with diabetes mellitus. Other research using areal-based measures of socioeconomic status have pointed to a social gradient in diabetes hospitalizations, but without accounting for individuals' health status. Linking person-level data from health surveys to population-based hospital records enables profiling of the role of food insecurity with hospital morbidity, focusing on the high-risk diabetic population. OBJECTIVE: This national study aims to assess the association between income-related household food insecurity and potentially avoidable hospital admissions among community-dwelling persons living with diagnosed diabetes. METHODS: We use three cycles of the Canadian Community Health Survey (2007, 2008, and 2011) linked to multiple years of hospital records from the Discharge Abstract Database (2005/06 to 2012/13), covering 12 of Canada's 13 provinces and territories. We apply multiple logistic regression for testing the association of household food insecurity with the risk of hospitalization for diabetes and common comorbid ambulatory care sensitive conditions among persons aged 12 and over living with diabetes. ANALYSIS: Data linkage allowed us to analyze inpatient hospital records among 10,260 survey respondents with diabetes; 590 respondents had been hospitalized at least once for diabetes or a common comorbid chronic physical or mental illness. The regression results indicated that the odds of experiencing a preventable hospital admission were significantly higher among persons with diabetes who were food insecure compared to their counterparts who were food secure (OR=1.66 [95%CI=1.24-2.23]), after controlling for age, sex and other characteristics. CONCLUSION: We found food insecurity to significantly increase the odds of hospital admission for ambulatory care sensitive conditions among Canadians living with diabetes. These results reinforce the need to consider food insecurity in public health and clinical strategies to reduce the hospital burden of diabetes and other nutrition-related chronic diseases, from primary prevention to post-discharge care.

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.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
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 head0.291
GPT teacher head0.490
Teacher spread0.200 · 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