Combined impact of concomitant arthritis and back problems on health status: Results from a nationally representative health survey
Bibliographic record
Abstract
OBJECTIVE: To investigate whether people who report both arthritis and back problems report poorer health outcomes than those who have either condition alone. METHODS: We performed an analysis of the 2005 Canadian Community Health Survey (n = 126,049, age ≥15 years). Respondents were asked about long-term chronic health conditions diagnosed by a health professional and lasting 6 months or more. The risks of reporting 4 health outcomes (activity limitation, fair/poor self-rated overall health, fair/poor self-rated mental health, and ≥4 doctor consultations in the previous 12 months) were estimated using log Poisson regression analysis adjusting for sociodemographic and lifestyle factors for 5 analytic groups (arthritis and back problems, arthritis only, back problems only, any other chronic condition, and no chronic condition). RESULTS: Arthritis and back problems were reported by 6% of the population (10.5% arthritis only and 13% back problems only). The arthritis and back problems and arthritis only groups had a higher prevalence in women, those of older age, and those who were overweight or obese. For all health outcomes, prevalence ratios showed higher risks of poor outcome for the arthritis and back problem group than for arthritis only or back problems only groups, which had similar risk. Risks were lowest for the any other chronic conditions group and the no chronic conditions group. CONCLUSION: Chronic back problems were reported by one-third of people with arthritis, who had increased risks of activity limitation, poorer self-rated overall and mental health, and higher health care use. The findings suggest that concomitant back problems are a major contributor to a range of health outcomes in arthritis.
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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".