Comparison of Prevalence of Metabolic Disorders of Urban and Rural Adults of Punjab, India
Bibliographic record
Abstract
SUMMARY: A study was conducted to determine the prevalence of metabolic syndrome (MetS) in urban and rural areas of Ludhiana district, Punjab. A total of 1000 subjects aged 25-65 years were selected for screening. The study found that both urban and rural areas had an average body mass index above 23.0 kg/m2, with rural populations having higher waist circumference, hip circumference, and waist-hip ratios. Abdominal obesity was more prevalent in women in both areas. Rural men and women had higher fasting blood glucose and systolic blood pressure/diastolic blood pressure levels. MetS prevalence in urban areas is lower among men (7%) and women (10%) compared to rural areas (34% and 26%). The timely detection of metabolic disorder risk factors and intervention can effectively address MetS in the Indian population, thereby improving the country's health statistics.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".