Obesity burden by socioeconomic measures between 2000 and 2018 among women in sub‐Saharan Africa: A cross‐sectional analysis of demographic and health surveys
Notice bibliographique
Résumé
Background: The increasing global burden of obesity especially in low-and-middle-income countries (LMICs) accentuates the need for critical action. In the absence of evidence-based approaches to mitigate recent obesity trends, the likelihood of reaching global obesity targets will be almost zero. Objective: This study examined the obesity prevalence in Sub-Sahara Africa and observed transitions on the burden of obesity prevalence over time. Methods: Data from the Demographic and Health Survey which is based on cross sessional design was used. Most recent surveys carried out in 16 sub-Saharan Africa (SSA) between 2000 and 2018 were included in the analysis. Equiplot by the International Centre for Equity was used to display the inequities by the following socioeconomic measures: wealth index, education, and place of residence. Age-standardized prevalence was measured across these socioeconomic measures using the WHO standard population age distribution, examined changing trends and finally assessed transition in obesity prevalence by percentage point difference of highest and lowest prevalence within each of the three socioeconomic measures. Results: A total of 496,482 women were included in the analysis. Obesity prevalence among women varied substantially, from 2% in Chad to 27% in Lesotho. Variation in obesity prevalence was observed across countries and by socioeconomic status measures. Among women in all the countries except Comoros, the burden was concentrated among the wealthiest. Out of the 16 countries included, the prevalence of obesity was concentrated among women with no education in eight countries (Benin, Burundi, Chad, Cote d'Ivoire, Guinea, Mali, Niger, Comoros) while it was concentrated in those with primary education in Congo and Lesotho and among those with secondary school education in DR Congo, Gabon, Namibia, Nigeria, and Zimbabwe. The burden of obesity was more concentrated in the urban across the 16 countries except in Comoros and Lesotho where they were higher in the rural (8.9 [7.2, 11.1] and 15.1 [13.0, 17.5] respectively) than in urban (6.6 [5.0, 8.8] and 6.8 [5.2, 8.8] respectively). Finally, the trend analysis with five countries indicated that the prevalence and gap in obesity among women increased between previous and most recent surveys except in Zimbabwe where it reduces across the three socioeconomic measures between 2011 and 2018. Conclusions: This study examined transition in obesity prevalence among women across three socioeconomic measures in selected sub-Saharan African countries. Increasing prevalence of obesity was found in SSA but transition to women in lower socioeconomic status is already taking place in some countries.
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 | 0,002 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».