Overweight, Obesity and its Associated Factors among Nurses at Tertiary Care Hospitals Karachi
Bibliographic record
Abstract
Overweight and obesity have been identified as considerable health risks worldwide. Objective: To identify the prevalence of overweight, and obesity and its association with demographic variables among nurses. Methods: A cross-sectional analytical study was conducted at Dr. Ruth KM Pfau Civil Hospital and Dow University Hospital Karachi over a period of six months of periods from March to August 2019. A total of 299 subjects of both genders were approached by the non-probability convenient sampling method. Chi-square test was applied to identify the associated factors. P-value ≤ 0.05 counted as significant. Results: Out of 299, half of the study nurses 149 (49.8%) were male. Among 299 participants, 75 (25.1%) of them were overweight or obese. While 13 (4.3%) were underweight and 211 (70.6%) were normal weight. Mean age, working experience, and BMI were found 29.52 ± 8.568, 7.35 ± 6.177, and 23.30 ± 3.148 respectively of the study nurses. Gender (p-value=0.003), educational status (p-value=0.002), and nature of the job (p-value=0.003) of the participants were found statistically significant with BMI. Conclusions: Present study concluded that the majority of study participants had normal BMI and a small number of study subjects were found obese. However, a quarter of nurses are recognized as overweight. Moreover, a significant association was established between BMI with gender, the nature of the job, and the education of nurses.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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".