Obesity and Associated Factors Among Students of Different Medical Colleges in Cumilla During COVID-19 Pandemic
Notice bibliographique
Résumé
Background: The COVID-19 pandemic has led to special situations and changes to daily life due to the worldwide measures that were brought into effect such as lockdowns. Obesity is a major public health concern among medical students which are undesirable health condition and its frequency is high in this Covid -19 pandemic situation. The aim of the study was to assess the state of obesity and associated factors among students of three medical colleges located in Cumilla district during COVID-19 pandemic situation. Methods: This study was a cross-sectional study; Purposive sampling technique was used to select 325 students from three different medical colleges of Cumilla. Data were collected from participants through face-to-face interview using a semi-structured questionnaire after taking informed written consent. Data were analyzed by SPSS software. Results: Among the respondents 52.3% were low, 24.3% were moderate, 24.3%, 12% were high and 11.4% were no physical activity. About 1.8% took one time 12.9% took two times 55.7% took three times 29.5% took their meal more than three times per day. Majority of respondents 54.2% drunk 4 to 6 glasses water daily. Among the 325 participants 12.6% were obese, 21.2% were pre- obesity. Normal BMI was 44.9% and 21.2% was underweight. Obesity was associated with sex; as female medical students were observed to have significantly higher BMI compare to those with male respondents (P<0.000). Family type of the students from joint family were observed more obese than nuclear family, (P<0.05), Dietary pattern. as the BMI of the respondents increased with the increase of frequency of monthly fast food consumption of the respondents (P<0.04). Female medical students were significantly higher biscuits consumption (P<0.03) but male respondent inversely significantly higher in cold drink consumption (P<0.00). Conclusion: The study findings may contribute to developing awareness about weight gain and its long term health consequence and devising interventions to prevent COVID-19 related weight gain among medical students. JOPSOM 2024; 43(2): 53-60
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».