Lifestyle Habits and Obesity Risk Among Adolescent Medical Students
Bibliographic record
Abstract
Introduction. Obesity is a significant public health issue and a prevalent preventable nutritional disor- der. It can result from hereditary factors, prenatal conditions, environmental influences, metabolism, and lifestyle choices. This condition leads to an accu- mulation of adipose tissue and increased body mass.Aim. This study aimed to identify participants’ life- style habits, determine their nutritional status, and assess potential predictors of obesity.Methods. The cross-sectional study included 354 students from the Sarajevo High School of Medicine, of whom 236 (approximately 70%) were female. Par- ticipants were aged 14 to 18 years, with a mean age of 16.32 ± 1.74 years. The study involved collecting anthropometric data from physical education class records and administering a structured questionnaire (socio-demographic characteristics and assessment of life habits) designed for this study.Results. It was found that approximately one quarter of the subjects were overweight/obese. Unhealthy eating habits were prevalent, with around 50% of re- spondents consuming fruits and vegetables every day, 80% consuming sugar-sweetened beverages, snacks and fast food. The Pearson correlation test and linear regression determined that inappropriate eating hab- its, lack of physical activity and pronounced sedentary habits significantly affect the occurrence of excessive body mass/obesity in the subjects.Conclusion. Research shows many adolescents have unhealthy habits and obesity, which pose serious health risks. Early screening and prevention are crucial to reduce these risks and promote long-term health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".