An Epidemiologic Analysis of Low Back Pain in Primary Care
Bibliographic record
Abstract
BACKGROUND: Low back pain is one of the most common conditions for which patients seek medical care. AIM: The aim of the study was to study the epidemiology of low back pain in primary care setting with emphasis on frequency, sociodemographic factors, and impact of low back pain on lifestyle habits. SUBJECTS AND METHODS: This is a cross-sectional study. A representative sample of 2742 patients was approached and 2180 subjects agreed to participate in this study (79.5%). The survey was conducted among primary health care visitors during the period from March to October 2012. The questionnaire collected the sociodemographic characteristics, lifestyle habits, and type of treatment taken for relief from recruited subjects. RESULTS: Of the subjects studied, 52.9% were males and 47.1% were females. The prevalence of low back pain in the study sample was 59.2%. Low back pain was more prevalent among women (67.7%) than among men (51.6%). The proportion of low back pain was highest in the age-group 45 to 55 years in both the genders (37.6% and 36.4%, respectively). Nearly half of the men (45.7%) and women (45.2%) with low back pain were overweight with a significant difference (P < .001). More than half of the women with low back pain were housewives (50.4%), whereas most of the men had clerical jobs (36.8%). There was a significant difference observed between men and women in terms of nationality (P < .001), body mass index (P < .001), and occupation (P < .001). Prolonged standing (41.2% vs 29.5%; P < .001) and use of sponge mattress (50.9% vs 45.8%; P .041) was significantly higher among male patients with low back pain compared with females. Coughing/sneezing/straining (9.7% vs 5.9%; P = .01) were more frequent triggering factors in male patients with low back pain as compared with females. CONCLUSION: The study findings revealed that the prevalence of low back pain was higher among women than among men. Low back pain was observed more frequently among older people and among those who were overweight.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".