Exploring the Gender-based Variability in Terms of Body Mass Index, Eating Preference, and Sleep Pattern among School-going Adolescents of Periurban Settings of Karachi, Pakistan – A School-based Cross-sectional Study
Bibliographic record
Abstract
Background: Childhood obesity is a global problem; identifying its cause is crucial for formulating effective preventative and treatment measures. Objectives: This study assesses variability in body mass index (BMI), sleeping patterns, and eating habits among adolescents in the periurban area of Karachi, Pakistan. Methodology: This school-based cross-sectional survey was conducted from March to April 2023. Responders between 11 and 18 were chosen as research participants – a self-designed, structured, pretested questionnaire was used, and the association was checked through the Chi-square using STATA version 17. Results: Overall, 689 participants, 523 (74.9%) belonged to the 15–18 years of age group, in which 309 (44.8%) were female and 214 (31.9%) were male among them. Most male individuals, 213 (30.9%), were underweight. Of 368 (53.4%) participants, males and females prefer eating twice daily. Twenty-seven percent of male participants chose to sleep for <7.5 h compared to female participants, 211 (30.6%). Conclusion: Sleep and eating preferences significantly affect BMI among both genders. The research discussed here suggests that chronic partial sleep deprivation may increase the risk of obesity and underweight issues through a number of pathways, including having a negative impact on glucose regulation parameters, a dysregulation of the neuroendocrine control of appetite that results in excessive or undereating, and decreased energy expenditure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".