Prevalence of Obesity and Associated Risk Factors amongst Teaching Staff of Juba University, South Sudan
Notice bibliographique
Résumé
Obesity is a significant contributing factor in the development of various chronic diseases such as cardiovascular disease, hypertension, type 2 diabetes mellitus, stroke, osteoarthritis and certain cancer accounting for 2.8 million worldwide deaths annually. Recent global figures indicate that the prevalence of obesity is not just a problem of the developed countries but is also on the increase in the developing world, with over 115 million people suffering from obesity-related problems (WHO). In Africa, 8% of adults above 20 years are obese and 27% overweight (Steyn & Mchiza, 2014), Lack of empirical data remains an obstacle in monitoring the magnitude of current and future trends of overweight and obesity in sub Saharan Africa including South Sudan. This study investigated the prevalence of obesity and associated risk factors among teaching staff; a case at University of Juba in South Sudan (Rep). A cross-sectional study design was used. A total of 196 study participants drawn from various Colleges and faculties of Juba University using multi-stage systematic random sampling of 1st selecting the College, department and 2nd stage was the selection of participants using the exiting staff list obtained from the University administration. Key variables collected includes weight/kg, height, age, sex, physical activities, feeding habits and income of the study participants, which was used to determine the prevalence of obesity and associated risk factors. STATA version 12 was used to data analyze. Chi-square statistics were used to compare equality of distribution of obesity. Out of the 196 participants, 18.4% were males (160/196) and 81.6% were females (36/196). The mean age of the participant was estimated at 37 ± 8.5 years. Prevalence of Obesity (BMI> or=30) and Overweight (BMI >25 to <=30) among teaching staff was 4.1% and 10.2%, respectively. Of those found overweight/or obese, 20% were females (4/20) and 80% were males (16/20). While the age specific prevalence indicates obesity is highest among 35-44yrs (50%), followed by 45-55 yrs+ (37.5%) and 12.5% among 25-34yrs age groups. Age was found to be associated with obesity (P-value=0.0337, p<0.05)).Meal frequency was noted to be twice a day. Walking is the main physical activities for both males and females (97.5%) and nearly half of the participants (44.9%) had incomes 7500 South Sudan Pounds (SSP) an equivalent of $1000. Income levels was associated with BMI levels (P-value=0.0222; p<0.05). However, low prevalence of obesity among teaching staff at the University of Juba is not yet of an immediate public health concern, however, earlier preventive and control measures is required as most of the staff leads sedentary lifestyle. This study recommends public awareness intervention on dietary intake and physical exercises among others in schools and institutions at all levels to curtail an otherwise gradual rise in obesity and overweight in the near future.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 | 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 | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».