To Determine the Concern of Females of Karachi towards their Bone Health
Bibliographic record
Abstract
Background: Osteoporosis is a disease that thins and weakens the bones to the limit that they become fragile and break easily. It is usually thought that osteoporosis is an unavoidable part of aging but good lifestyle habits can help us protect our bones and decrease our chance of getting osteoporosis. Since women are at greater risk of developing osteoporosis than men because of multiple reasons, the study was conducted to assess prevalence of risk factors among studied groups which can help guide early intervention. Aim: The aim of the study is to evaluate the concern of bone health among females of Karachi and to analyze their dietary habits. Through this research, our principal outcome was to specify the forces which ultimately leads to the disrupt bone matters, determination of outcomes regarding female health and reduce burden of risks among them. Method: For this purpose a survey with questionnaire was scrutinized including a total sample size of 150, grouped into premenopausal and postmenopausal females. Interviews were conducted regarding their dietary pattern, drug history and Bone Mineral Density test (BMD) histories. Results: The datashowed that 86% of the participants were not even aware of BMD test and its significance while only 14% of participants were aware of BMD test but none of them had it done in their whole life. Results also showed that frequency of taking calcium supplements, milk or other dairy products is very low among studied groups whereas soft drink, caffeinated products and chocolate are consumed as their routine diet. Conclusion: It is concluded that the females of Karachi mostly are not concerned about their bone health and bone related issues.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".