Evidence of Increased Age and Sex Standardized Death Rates Among Individuals Who Accessed Opioid Agonist Treatment Before the Era of Synthetic Opioids in Ontario, Canada
Bibliographic record
Abstract
Objective The objective of this study was to evaluate age-sex standardized death rates (ASDR) from all causes from 2011 to 2015 among people who have accessed opioid agonist treatment (OAT) and compare rates living in the Northern and Southern areas of Ontario. Methods Routinely collected administrative health data was used to calculate crude death rates and age-sex standardized death rates (ASDRs) per 1,000,000 population of individuals who accessed OAT and compared the rates geographically from 2011 to 2015. The weighted ASDRs for each year were calculated by using the mid-year population of these regions. The rate ratios were calculated considering the base year as 2011. Results A total of 55,924 adults who accessed OAT were included between January 1, 2011, and December 31, 2015. The majority of patients in the cohort - 52.3% - were between 15 and 34 years old, 32.5% were female, 11.3% were in the lowest income group, 71.1% lived in Southern areas. Overall, the ASDR steadily increased during the study period and spiked in 2015. We found that among individuals who had accessed OAT, living in Southern Ontario was associated with a lower risk of all-cause mortality than those living in Northern Ontario. ASDR for Northern Ontario was 20.0 (95% confidence interval (CI)= 10.2-34.2) in 2011, and 103.5(95%CI=78.5-133.5) in 2015, which was a five-fold increase from 2011. Whereas in Southern Ontario, ASDR in 2011 was 13.8 (95% CI= 11.5-16.5), and in 2015 ASDR was 60.8 (95%CI=55.8-66.1), which was only a 4-fold increase from 2011 Conclusion Our findings demonstrate evidence of a steadily increasing ASDR among individuals who accessed OAT with higher rates in Northern areas of the province before the era of synthetic opioids in Ontario, 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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".