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Record W2538596570 · doi:10.9778/cmajo.20150124

Trends in binge drinking in Canada from 1996 to 2013: a repeated cross-sectional analysis

2016· article· en· W2538596570 on OpenAlexaffvenueabout
Andrew GM Bulloch, Jeanne V.A. Williams, Dina H. Lavorato, Scott B. Patten

Bibliographic record

VenueCMAJ Open · 2016
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBinge drinkingMedicineCross-sectional studyDemographyConfidence intervalPopulationPublic healthEnvironmental healthPoison controlInjury prevention

Abstract

fetched live from OpenAlex

BACKGROUND: Heavy drinking is a major factor in morbidity and mortality worldwide. Little information is available on trends in Canada regarding alcohol abuse. We sought to estimate abstinence, binge drinking and alcohol intake exceeding low-risk drinking guidelines in the Canadian population from 1996 to 2013. METHODS: The data sources for this analysis were a series of cross-sectional national health surveys of the Canadian population carried out by Statistics Canada between 1996 and 2013. These were cross-sectional files from the National Population Health Surveys of 1996 and 1998, plus the Canadian Community Health Surveys from 2000 to 2013. Respondents were aged 18 years and older. RESULTS: The proportion of binge drinkers increased steadily from 13.7% (95% confidence interval [CI] 13.2%-14.2%) in 1996 to 19.7% (95% CI 19.1%-20.3%) in 2013. The corresponding proportions for men were 20.8% (95% CI 19.9%-21.7%) in 1996, and 25.7% (95% CI 24.7%-26.6%) in 2013; for women, these proportions were 6.9% (95% CI 6.4%-7.5%) in 1996, and 13.8% (95% CI 13.1%-14.5%) in 2013. No significant increases were seen in the proportion of people who exceeded low-risk drinking guidelines or of abstainers during the same period. INTERPRETATION: The rate of self-reported binge drinking in Canada has increased from 1996 to 2013, relatively more so among women than among men. No evidence of an increase in the proportion of people exceeding low-risk drinking guidelines or of abstainers was seen during the same period. These results suggest that binge drinking is of particular concern regarding intervention strategies aimed at improvement of public 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.327
Teacher spread0.285 · 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.

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

Citations18
Published2016
Admission routes3
Has abstractyes

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