Weight-loss strategies of South African female university students and comparison of weight management-related characteristics between dieters and non-dieters
Notice bibliographique
Résumé
BACKGROUND: Female university students are at risk for weight gain and use of inappropriate weight-loss strategies. By gaining a greater understanding of the weight-loss strategies used by and weight management related characteristics of these students, effective weight management interventions for this vulnerable group can be developed. METHODS: Two hundred and fifty female students from South Africa universities, aged 18-25 years, participated in this cross-sectional study; 162 attempted weight loss during the year preceding the study (dieters) and 88 were non-dieters. Weight and height were measured and BMI (kg/m(2)) computed. A self-administered questionnaire was used to record all other variables. Weight loss strategies were described for dieters and compared between BMI groups within the dieters group. Weight management related characteristics were compared between dieters and non-dieters. Statistical tests included Pearson Chi-square test, independent samples t-test or Mann-Whitney U test (depending on distribution of the data). Predictors for a higher BMI and being overweight/obese (BMI ≥25 kg/m(2)) were identified using regression models. RESULTS: Healthy weight-loss strategies included increased exercise and fruit/vegetable intake and decreased intake of sugar and fat containing items; unhealthy methods included eating little food and skipping meals; and extreme weight loss strategies included laxatives and vomiting. The most commonly used weight-loss product was Herbex. Dieters were characterized by a higher BMI, overestimation of their weight (especially normal weight students), dissatisfaction with weight and select body parts, higher intake of breakfast and healthy foods, lower intake of unhealthy foods, higher levels of vigorous physical activity, higher use of select informal weight-loss information sources and experiencing more pressure to lose weight from mothers, siblings and friends. Predictors of higher BMI and/or increased risk for BMI ≥25 included weight-loss attempt during the past year, race, dissatisfaction with waist, perception of currently being "chubby," and higher frequencies of intake of a snack and fatty foods. CONCLUSION: Attempting weight-loss is common among female students and predicts BMI. Healthy (mainly), unhealthy and extreme weight loss methods are used. Dieters are characterized by a less realistic body image, lower body satisfaction, higher pressure to lose weight, use of informal weight-management information and a healthier life-style.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».