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Record W2166233113 · doi:10.1177/0022034512455062

Socio-economic Inequalities and Oral Health in Canada and the United States

2012· article· en· W2166233113 on OpenAlexafffundabout
Hawazin W. Elani, Sam Harper, Paul Allison, Christophe Bedos, Jay S. Kaufman

Bibliographic record

VenueJournal of Dental Research · 2012
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsMcGill University
FundersHealth CanadaCenters for Disease Control and PreventionUniversity of TorontoCanada Research ChairsMcGill University
KeywordsEdentulismNational Health and Nutrition Examination SurveyInequalityDemographyOral healthTooth lossMedicinePopulationSurvey data collectionGerontologyEnvironmental healthDentistrySociology

Abstract

fetched live from OpenAlex

This paper describes and compares the magnitude of socio-economic inequalities in oral health among adults in Canada and the US over the past 35 years. We analyzed data from nationally representative examination surveys in Canada and the US: Nutrition Canada National Survey (1970-1972, N = 11,546), Canadian Health Measures Survey (2007-2009, N = 3,508), The First National Health and Nutrition Examination Survey (1971-1974, N = 13,131), and National Health and Nutrition Examination Survey (2007-2008, N = 5,707). Oral health outcomes examined were prevalence of edentulism, proportion of individuals having at least 1 untreated decayed tooth, and proportion of individuals having at least 1 filled tooth. Sociodemographic indicators included in our analysis were place of birth, education, and income. Data were age-adjusted, and survey weights were used to account for the complex survey design in making population inferences. Our findings demonstrate that oral health outcomes have improved for adults in both countries. In the 1970s, Canada had a higher prevalence of edentulism and dental decay and lower prevalence of filled teeth. This was also combined with a more pronounced social inequality gradient among place of birth, education, and income groups. Over time, both countries demonstrated a decline in absolute socio-economic inequalities in oral health.

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)0.003
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 score0.074
Threshold uncertainty score0.221

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.096
GPT teacher head0.433
Teacher spread0.337 · 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

Citations88
Published2012
Admission routes3
Has abstractyes

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