Prevalence of Back Pain in the Community. A COPCORD-Based Study in the Mexican Population
Bibliographic record
Abstract
OBJECTIVE: Back pain (BP) is frequent in the community; its prevalence in México is 6%. Our objective was to determine the prevalence of BP in Mexican communities and determine its most important characteristics. METHODS: A cross-sectional study of individuals aged > 18 years was conducted in Mexico City and in urban communities in the state of Nuevo León. Sampling in Mexico City was based on community census and in Nuevo León, on stratified, balanced, and random sampling. Procedures included a door-to-door survey, using the Community Oriented Program for the Control of Rheumatic Diseases, to identify individuals with BP > 1 on a visual analog scale in the last 7 days. General practitioners/rheumatology fellows confirmed and characterized BP symptoms. RESULTS: In all, 8159 individuals (mean age 43.7 yrs, two-thirds female) were surveyed and 1219 had BP. The prevalence of nontraumatic BP in the last 7 days was 8.0% (95% CI 7.5-8.7). The mean age of these individuals was 42.7 years, and 61.9% were female. Thirty-seven percent had inflammatory BP [prevalence of 3.0% (95% CI 2.7-3.4)]. Compared with the state of Nuevo Léon, the characteristics and consequences of BP in Mexico City were more severe. In logistic regression analysis, living in Mexico City, having a paid job, any kind of musculoskeletal pain, high pain intensity, and obesity among other variables were associated with BP. CONCLUSION: The prevalence of nontraumatic BP in the last 7 days in urban communities in México is 8.0%. However, clinical features and consequences differed among the communities studied, suggesting a role for local factors in BP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".