Abstract P384: Gender Disparities in the Co-Existence of Hypertension and Diabetes in South Africa: Results From the Nationwide Demographic and Health Household Survey Data
Notice bibliographique
Résumé
Introduction: The rapidly growing public health burden of cardiovascular disease and diabetes in low- and middle-income countries threatens the progress expected by many countries’ effort to combat endemic infectious diseases and achieve good health and wellbeing (SDG3). Specifically, in South Africa the burden of hypertension and diabetes is a preventable but still neglected public health issue, causing a large number of premature deaths among men and women. There are very few population-based studies examining the distribution of risk factors and the combined burden of hypertension and diabetes prevalence in South Africa to inform an effective public health response. Objectives: This study investigates potential gender disparities in the co-existence of hypertension and diabetes prevalence and provincial variation in South Africa in 2016, adjusting for individual level demographic, behavioural and socio-economic variables, while allowing for spatial autocorrelation and adjusting simultaneously for the hierarchical data structure and risk factors. Methods: The study sample was based on participants aged ≥15 years from the 2016 South Africa DHS. Hypertension was defined as blood pressure ≥ 140/90 mmHg or self-reported health professional diagnosis or on antihypertensive medication and diabetes was defined as self-reported health professional diagnosis or on diabetic medication. Bayesian geo-additive regression modelling investigated the association of various socio-economic factors on the prevalence of both hypertension and diabetes across SA’s nine provinces while controlling for the latent effects of geographical location. Results: The prevalence of hypertension, diabetes, and combined hypertension and diabetes were 48.2% (4212 of 8679), 4.5% (458 of 10255) and 3.8% (314 of 8195) successively in the DHS in 2016. The prevalence of hypertension increased with age and was significantly higher in male, in people of coloured ethnic group, in overweight and obese, in people with high blood cholesterol and varied with geographical location. Diabetes prevalence increased with age and was significantly higher in male, in overweight and obese and in people with high blood cholesterol. The co-existence of the prevalence of both combined hypertension and diabetes was significantly higher in male, in overweight and obese and in people with high blood cholesterol, in people with heart attack/angina and increased with age. Conclusions: The findings can inform public health policy and decision making regarding the allocation of public resources to tackle the growing burden of hypertension and diabetes in South Africa, particularly in the most affected areas and subgroups of the population. Public health education aiming at the prevention of CVDs should target both ailments at the same time as cost-effective measure to achieve SDG3.
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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».