Health Status among Black Canadians: Results from a National Survey
Bibliographic record
Abstract
This study obtained nationally representative estimates of health-related indicators among native-born Black Canadians, and compared these estimates with those of native-born White Canadians. Data came from the Canadian Community Health Survey (2003-2008). Outcomes included smoking status, general health status, body mass index, and chronic conditions (i.e., asthma, hypertension, diabetes, heart disease, cancer). Descriptive statistics and logistic regression models were used to obtain unadjusted and adjusted period prevalence estimates for Black and White survey participants, and to determine the magnitude of health inequalities between racial groups. Estimates were adjusted for various socio-demographic factors to account for potential confounding. After adjustment, Blacks had about 50% lower odds of being current or former smokers (p < 0.0001 for both), 60% lower odds of having cancer (p < 0.01), and 70% lower odds of having heart disease (p < 0.0001), relative to Whites. There were no statistically significant differences across the two racial groups for the remaining health status indicators. Native-born Black Canadians report comparable or better health status relative to their White counterparts. Pour cette étude, nous avons obtenu des estimations représentatives au niveau national d'indicateurs liés à la santé parmi les Canadiens de naissance noirs, et nous les avons comparées à celles de leurs homologues blancs. Les données proviennent de l'Enquête sur la santé des communautés canadiennes 2003-2008. Les résultats incluaient le fait d'être ou non fumeur, la santé en général, l'index de masse corporelle et les conditions chroniques (par exemple : l'asthme, l'hypertension, le diabète, les maladies cardiaques et le cancer). Des statistiques descriptives et des modèles de régression logistiques ont permis d'obtenir des estimations de prévalence sur un certain temps, corrigées et non corrigées, pour les Noirs et les Blancs ayant fait partie de l'enquête, et de déterminer la magnitude des inégalités en matière de santé entre les deux groupes. Ces estimations ont été corrigées en fonction de facteurs socio-démographiques variés pour tenir compte de confusion potentielle. Après ajustement, les Noirs avaient à environ 50% moins de risques que les Blancs d'être des fumeurs actuels ou passés (p<0,0001 pour les deux), à 60% d'avoir le cancer (p<0,01) et à 70% d'avoir une maladie cardiaque. Il n'y avait pas de différences statistiquement significatives entre les deux groupes en ce qui concerne les autres indicateurs de santé. Les Canadiens de naissance noirs présentaient une santé comparable ou meilleure à celle de leurs homologues blancs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".