Revisiting arthritis prevalence projections--it's more than just the aging of the population.
Bibliographic record
Abstract
OBJECTIVE: Data for successive population surveys show there is a sustained increase in the prevalence of arthritis, surpassing projected estimates. We examined whether the often-made assumption of stability in age/sex-specific arthritis point-prevalence estimates when estimating future burden is upheld; we used nearly a decade of survey data, and computed new projections for arthritis prevalence in Canada, taking into account past changes in age/sex-specific prevalence estimates and anticipated changes in the age/sex structure of the population. The prevalence from 1994 to 2003, overall and by age and sex, was documented. METHODS: Analyses were based on persons aged 15+ years from 3 cycles of the National Population Health Survey (1994-99; n > 14,000) and 2 cycles of the Canadian Community Health Survey (2000-03; n > 130,000). Two projection scenarios were adopted to estimate future burden. RESULTS: Stability in age/sex point-prevalence estimates was not observed. From 1994 to 2003, absolute and relative increases were greatest in the older age groups (55+ yrs) and younger age groups (25-54 yrs), respectively. By 2021, we anticipate the prevalence of arthritis in Canada will have increased to between 21% and 26%. Overall, the prevalence increased from 13.4% to 17.6% from 1994 to 2003, an increase of nearly 50% in the number of Canadians reporting arthritis. CONCLUSION: The assumption of stable age/sex prevalence estimates over time does not hold in Canada. Past projections have underestimated future burden; past trends need to be considered.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".