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Record W1988388456 · doi:10.3402/ijch.v61i3.17460

Diabetes mellitus in the First Nations population of British Columbia, Canada. Part 3. Prevalence of diagnosed cases

2002· article· en· W1988388456 on OpenAlexaffabout
Suzanne Bennett Johnson, David Martín, Christopher Sarin

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsHealth Canada
Fundersnot available
KeywordsMedicineDiabetes mellitusPopulationDemographyEpidemiologyGestational diabetesGerontologyEnvironmental healthPregnancyInternal medicineGestation

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe the prevalence of diabetes mellitus in the on-reserve Status Indian population of British Columbia based on a survey conducted in 1997 and to compare these rates with previous surveys carried out in 1987, 1992 and 1995. STUDY DESIGN: Survey questionnaires were distributed to health centres, health stations and nursing stations providing health services to the 198 First Nations reserves in British Columbia. RESULTS: Data were received from 82 of 198 First Nations communities (41%) representing 24,407 (45%) of the on-reserve population of the province (53,893). A total of 636 cases of diabetes were identified. Seventy-seven percent of cases were age 35 plus. The overall prevalence in 1997 was 2.6% for all ages combined, more than doubled from 1.2% in 1987. First Nation's men and women 35 and older when compared to the general population by indirect age-standardization experienced a higher prevalence ratio-males 1.27, 95% CI 1.22, 1.40 and females 2.53, 95% CI: 2.77, 2.58. Among those with diabetes for > 20 years, 62.5% used insulin compared to 13% who had the disease < five years (622/636 reporting). Diabetic complications were reported in 48% of individuals. Diagnosed gestational diabetes was 28/1000 live births. CONCLUSIONS: General preventive initiatives must continue including Screening, nutrition and fitness education, and improved diabetic management directed at reduction in complications.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.205
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.283
Teacher spread0.266 · 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

Citations22
Published2002
Admission routes2
Has abstractyes

Explore more

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