Patterns of multimorbidity among immigrants to Canada: an analysis of the CCHS-IMDB
Bibliographic record
Abstract
Background: Multimorbidity is a growing public health concern and is associated with reduced quality of life and adverse health outcomes, yet investigation of multimorbidity among the immigrant population is limited in the Canadian context.\nObjectives: To assess the prevalence and correlates of multimorbidity among immigrants to Canada 18 years of age or older.\nMethods: Data from the 2007 to 2014 Canadian Community Health Survey linked to the Longitudinal Immigration Database were used. Statistical analysis included descriptive statistics and multivariable regressions.\nResults: Among immigrants, 3.5% had multimorbidity. Immigration factors such as recency of immigration, birth region, immigration category as well as age, marital status, income, employment, physical activity and smoking status were associated with multimorbidity.\nConclusion: Immigration related factors are important considerations when studying multimorbidity among immigrants. Although significant correlates were identified, additional research is required to better understand the nature of the relationship between these factors and multimorbidity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".