Ethnic and sex differences in the incidence of hospitalized acute myocardial infarction: British Columbia, Canada 1995-2002
Bibliographic record
Abstract
BACKGROUND: As populations in Western countries continue to change in their ethnic composition, there is a need for regular surveillance of diseases that have previously shown some health disparities. Earlier data have already demonstrated high rates of cardiovascular mortality among South Asians and relatively lower rates among people of Chinese descent. The aim of this study was to describe the differences in the incidence of hospitalized acute myocardial infarction (AMI) among the three largest ethnic groups in British Columbia (BC), Canada. METHODS: Using hospital administrative data, we identified all patients with incident AMI in BC between April 1, 1995, and March 31, 2002. Census data from 2001 provided the denominator for the entire BC population. Ethnicity was determined using validated surname analysis and applied to the census and hospital administrative datasets. Direct age standardization was used to compare incidence rates. RESULTS: A total of 34,848 AMI cases were identified. Among men, South Asians had the highest age standardized rate of AMI hospitalization at 4.97/1000 population/year, followed by Whites at 3.29, and then Chinese at 0.98. Young South Asian men, in particular, showed incidence rates that were double that of young Whites and ten times that of young Chinese men. South Asian women also had the highest age-standardized rate of AMI hospitalization at 2.35/1000 population/year, followed by White women (1.53) and Chinese women (0.49). CONCLUSIONS: South Asians continue to have a higher incidence of hospitalized AMI while incidence rates among Chinese remain low. Ethnic differences are most notable among younger men.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".