Prevalence of self-reported pain, joint complaints and knee or hip complaints in adults aged \(\geq\) 40 years
Bibliographic record
Abstract
\(\textit {Background:}\) Pain and musculoskeletal complaints are among the most common symptoms in the general population. Despite their epidemiological, clinical and health economic importance, prevalence data on pain and musculoskeletal complaints for Germany are scarce. \(\textit {Methods:}\) A cross-sectional survey of a random sample of citizens of Herne, Germany, aged \(\geq\) 40 years was performed. A detailed self-complete postal questionnaire was used, followed by a short reminder questionnaire and telephone contacts for those not responding. The questionnaire contained 66 items, mainly addressing pain of any site, musculoskeletal complaints of any site and of knee and hip, pain intensities, the Western Ontario MacMaster Universities (WOMAC) index, medication, health care utilization, comorbidities, and quality of life. \(\textit {Results:}\) The response rate was 57.8% (4,527 of 7,828 individuals). Survey participants were on average 1.3 years older, and the proportion of women among responders tended to be greater than in the population sample. There was no age difference between the population sample and 2,221 participants filling out the detailed questionnaire. The following standardized prevalences were assessed: current pain: 59.7%, pain within the past four weeks: 74.5%, current joint complaints: 49.3%, joint complaints within the past four weeks and twelve month: 62.8% and 67.4%, respectively, knee as the site predominantly affected: 30.9%, knee bilateral: 9.7%, hip: 15.2%, hip bilateral: 3.5%, knee and hip: 5.5%. Pain and musculoskeletal complaints were significantly more often reported by women. A typical relationship of pain and joint complaints to age could be found, i.e. increasing prevalences with increasing age categories, with a drop in the highest age groups. In general, pain and joint pain were associated with comorbidity and body mass index as well as quality of life. \(\textit {Conclusions:}\) Our data confirm findings of other recent national as well as European surveys. The high site specific prevalences of knee and hip complaints underline the necessity to further investigate characteristics and consequences of pain and symptomatic osteoarthritis of these joints in adults in Germany.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".