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Trends and Regional Variation in Prevalence of Cardiovascular Risk Factors and Association With Socioeconomic Status in Canada, 2005-2016

2021· article· en· W3194001663 on OpenAlexaffabout
Haijiang Dai, Arwa Younis, Jude Dzevela Kong, Nicola Luigi Bragazzi

Bibliographic record

VenueJAMA Network Open · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsYork University
Fundersnot available
KeywordsSocioeconomic statusMedicineObesityDemographyDiabetes mellitusBody mass indexCross-sectional studyEnvironmental healthGerontologyPopulationInternal medicine

Abstract

fetched live from OpenAlex

Importance: Cardiovascular disease remains the second leading cause of death in Canada. Monitoring and tracking the trends and disparities in major cardiovascular risk factors could provide benchmarks for future cardiovascular health strategies. Objective: To investigate the temporal trends, regional variations, and socioeconomic disparities in major cardiovascular risk factors in Canada from 2005 to 2016. Design, Setting, and Participants: This repeated cross-sectional survey study included adults aged 20 years and older from 6 Canadian Community Health Survey cycles between 2005 and 2016. Cardiovascular risk factors included hypertension, diabetes, obesity, and current smoking. Socioeconomic status was measured using equivalized household income. Data analysis was performed from September 2019 to April 2020. Exposures: A total of 112 health regions and socioeconomic status. Main Outcomes and Measures: Age- and sex-adjusted prevalence of hypertension, diabetes, obesity, and current smoking by year; health regions; and socioeconomic status. Absolute numbers were rounded to base 100 for confidentiality purposes, and percentages were based on weighted numbers. Slope index of inequality (SII) and relative index of inequality (RII) were calculated to assess absolute and relative socioeconomic inequalities, respectively. Results: A total of 670 000 respondents (329 000 [49.1%] men; 341 000 [50.9%] women) aged 20 years and older from 6 survey cycles were enrolled for this study. The largest age group was those aged 40 to 59 years (eg, 2005 cycle: 40.2% [95% CI, 39.9%-40.6%]). In the 2015/2016 cycle, the overall age- and sex-adjusted prevalence rates of hypertension, diabetes, obesity, and current smoking were 20.7% (95% CI, 20.4%-21.1%), 7.2% (95% CI, 7.0%-7.5%), 20.1% (95% CI, 19.7%-20.6%), and 17.8% (95% CI, 17.4%-18.2%), respectively. From 2005 to 2016, there was a significant increase in the prevalence of hypertension, diabetes, and obesity (eg, prevalence of diabetes in both sexes, 2005: 5.8% [95% CI, 5.6%-6.0%]; 2015/2016: 7.2% [95% CI, 7.0%-7.5%]; P < .001) but a significant decrease in the prevalence of current smoking (both sexes, 2005: 22.1% [95% CI, 21.7%-22.5%]; 2015/2016: 17.8% [95% CI, 17.4%-18.2%]; P < .001). The prevalence of all the risk factors varied widely across health regions (eg, obesity, Vancouver Health Service Delivery Area: 6.7% [95% CI, 4.5%-9.0%]; Miramichi Area: 36.8% [95% CI, 27.3%-46.3%]). In addition to obesity among men, all risk factors tended to be more common among those with lower income (eg, prevalence of hypertension in both sexes, 2015/2016, lowest income group: 23.2% [95% CI, 22.4%-24.0%]; highest income group: 18.4% [95% CI, 17.7%-19.1%]). The SII and RII indicated consistent absolute and relative socioeconomic inequalities in hypertension, diabetes, and current smoking over time (eg, RII for hypertension in both sexes, 2005: 1.25; 95% CI, 1.18-1.33; 2015/2016: 1.34; 95% CI, 1.26-1.43). However, the phenomenon of absolute and relative socioeconomic inequalities in obesity was only observed among women (eg, RII for 2015/2016 for obesity in women; 1.74 (95% CI, 1.56-1.93); men: 1.09; 95% CI, 0.99-1.21). Conclusions and Relevance: During the study period, the prevalence of hypertension, diabetes, and obesity significantly increased, while the prevalence of current smoking significantly decreased. Geographic and socioeconomic gaps should be considered and addressed in future interventions and policies targeted at reducing these cardiovascular risk factors in Canada.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.007
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.230
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), 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".

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Citations34
Published2021
Admission routes2
Has abstractyes

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