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Record W2617081894 · doi:10.15171/ijoem.2017.992

Impact of Diabetes Mellitus on Occupational Health Outcomes in Canada

2017· article· en· W2617081894 on OpenAlexaffabout
Anson Li, Behdin Nowrouzi‐Kia

Bibliographic record

VenueThe International Journal of Occupational and Environmental Medicine · 2017
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsLaurentian UniversityUniversity of Toronto
Fundersnot available
KeywordsContext (archaeology)MedicineDiabetes mellitusOccupational safety and healthCommunity healthProductivityGerontologyDemographyEnvironmental healthNursingPublic healthGeographyEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Research suggests that diabetes mellitus (DM) has a negative impact on employment and workplace injury, but there is little data within the Canadian context. OBJECTIVE: To determine if DM has an impact on various occupational health outcomes using the Canadian Community Health Survey (CCHS). METHODS: CCHS data between 2001 and 2014 were used to assess the relationships between DM and various occupational health outcomes. The final sample size for the 14-year study period was 505 606, which represented 159 432 239 employed Canadians aged 15-75 years during this period. RESULTS: We found significant associations between people with diabetes and their type of occupation (business, finance, administration: 2009, p=0.002; 2010, p=0.002; trades, transportation, equipment: 2008, p=0.025; 2011, p=0.002; primary industry, processing, manufacturing, utility: 2013, p=0.018), reasons for missing work (looking for work: 2001, p=0.024; school or education: 2003, p=0.04; family responsibilities: 2014, p=0.015; other reasons: 2001, p<0.001; 2003, p<0.001; 2010, p=0.015), the number of work days missed (2010, 3 days, p=0.033; 4 days, p=0.038; 11 days, p<0.001; 24 days, p<0.001), and work-related injuries (traveling to and from work: 2014, p=0.003; working at a job or business: 2009, p=0.021; 2014, p=0.001). CONCLUSION: DM is associated with various occupational health outcomes, including work-related injury, work loss productivity, and occupation type. This allows stakeholders to assess the impact of DM on health outcomes in workplace.

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)0.000
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 score0.130
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.040
GPT teacher head0.411
Teacher spread0.371 · 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

Citations12
Published2017
Admission routes2
Has abstractyes

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