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Record W2758960953

Race, Ethnicity and Cardiovascular Risk: A Population-based Study in Ontario, Canada

2012· dissertation· en· W2758960953 on OpenAlexaboutno aff
Maria S. Chiu

Bibliographic record

VenueTSpace · 2012
Typedissertation
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsnot available
Fundersnot available
KeywordsRace (biology)Ethnic groupPopulationDemographyMedicineGeographyGerontologyPolitical scienceEnvironmental healthGender studiesSociology
DOInot available

Abstract

fetched live from OpenAlex

Background: Ethnic and immigrant groups represent a large and growing segment of the Canadian population, however, little is known about how these groups differ in their cardiovascular risk factor profiles when compared to the White population. This thesis describes three large, population-based studies examining cardiovascular risk among people of White, South Asian, Chinese and Black ethnicity living in Ontario. It was hypothesized that ethnic groups would differ significantly in their cardiovascular risk factor profiles.\n\nMethods: The study population included 154 653 White, 3364 South Asian, 3038 Chinese, and 2742 Black subjects derived from Statistics Canada’s National Population Health Survey and Canadian Community Health Surveys. In Project 1, the age- and sex-standardized prevalence of cardiovascular risk factors, heart disease, and stroke were compared across the four ethnic groups. In Project 2, the degree to which cardiovascular risk factor profiles differed between recent immigrants and long-term residents was compared across ethnic groups. In Project 3, a subsample of the study population was used to compare the ethnic-specific incidence and age at diagnosis of diabetes. We also derived ethnically appropriate body-mass index (BMI) cutoff values for obesity for assessing diabetes risk. \n\nResults: Ethnic groups living in Ontario differ strikingly in their cardiovascular risk profiles. The Chinese group had the most favourable cardiovascular risk factor profile, with 4.3% of the population reporting ≥2 major cardiovascular risk factors (i.e., smoking, obesity, diabetes, hypertension), followed by the South Asian (7.9%), White (10.1%) and Black (11.1%) groups. For all ethnic groups, cardiovascular risk factor profiles were worse among those with longer duration of residency in Canada. Nonwhite subjects developed diabetes at a higher rate, at an earlier age, and at lower ranges of BMI than White subjects. For the equivalent incidence rate of diabetes at a BMI of 30 in White subjects, the BMI cutoff value was 24, 25, and 26 in South Asian, Chinese, and Black subjects, respectively.\n\nInterpretation: These findings highlight the need for designing ethnically tailored cardiovascular disease prevention strategies and for lowering current targets for ideal body weight for nonwhite populations.

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)0.001
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 score0.033
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.006
Science and technology studies0.0060.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.037
GPT teacher head0.370
Teacher spread0.333 · 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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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