Comparison of the dietary intake of the urban black population in Cape Town in 1990 with 2009
Notice bibliographique
Résumé
Background: In 1990 the BRISK was undertaken in the black population in five townships in Cape Town, Langa, Gugulethu, Khayalitsha, Nyanga, and Crossroads.The prevalence of noncommunicable diseases (diabetes and heart disease) and their risk factors, including dietary intake were investigated.Aim: To determine the dietary intake of the urban black population (25-64 years) of Cape Town in 2009 and compare these findings with a similar sample examined in the same townships in 1990. Study design and sample:A cross-sectional survey including a representative sample of 392 males and 707 females (n=1099) was drawn from the same townships as in 1990.Methods: Socio-demographic data were collected by trained field workers.Weight, height, and waist and hip circumference were measured.Body mass index (BMI), and waist-hip ratio (WHR) were calculated.Dietary intake data (macro-and micronutrients, mean adequacy ratio (MAR), food groups and portion sizes) were calculated using the MRC FoodFinder program and compared with the dietary reference intakes.The MAR was calculated for each participant.Data analyses: Anthropometric and dietary data are presented as means and standard deviations by age, level education, type of housing, degree of urbanisation and asset index (proxy for socioeconomic status).Associations of dietary data with anthropometric and biochemistry data (TC, HDL-C, LDL-C, and glucose), blood pressure, asset index, and degree of urbanisation were assessed.A linear regression model was computed using MAR as the dependent variable and adding age, gender, urbanisation, asset index and other variables to the model.Correlations between the asset index and urbanisation duration were done with energy and nutrient intakes using Pearson's correlations.Regressions were done to test the significance of various variables.Results: Most of the adults had an education of at least 8-12 years, though 60% of the males and 58.3% of females were unemployed, and 13.8% were pensioners.Twenty-one per cent lived in formal houses, 35.4% in council houses or hostels, and 43.6% in shacks.Only 12.1% of adults had spent less than 20% of their life in an urban area.Thirty three per cent were classified as falling within the poorest tertile of the asset index.The percentage of adults with a BMI greater than 30 kg/m 2 was 63.3% in females and 12% in males.Males had a WC and WHR of 85.7 cm and 0.89 and females 97.5 cm and 0.85, respectively.Analysis of the 24-hour dietary recall data showed very low mean energy intakes [M 6516 (2929); F 5760 (2446) kJ].These results did not support the high prevalence of obesity, particularly in females, and also in four other studies among urban black populations.Hence the Goldberg equation was used to remove under-reporters.The remaining sample comprised 544 (214 males and 330 females) participants residing in Khayelitsha (42.4%),Langa (31.4%),Gugulethu (15.3%), and less than 10% in Crossroads and Nyanga.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».