Socioeconomic inequalities in uptake of HIV testing during antenatal care: evidence from Sub-Saharan Africa
Notice bibliographique
Résumé
BACKGROUND: Measuring socioeconomic inequalities in healthcare usage represents a critical step towards promoting health equity, in alignment with the principles of universal health coverage and the United Nations' Sustainable Development Goals. In this study, we assessed the socioeconomic inequalities in HIV testing during antenatal care (ANC) in sub-Saharan Africa. METHODS: Sub-Saharan Africa was the focus of this study. Benin, Burundi, Cameroon, Ethiopia, Gambia, Guinea, Liberia, Malawi, Mali, Mauritania, Mozambique, Rwanda, Sierra Leone, Uganda, Zambia, and Zimbabwe were the countries included in the study. This study used current Demographic and Health Surveys data spanning from 2015 to 2022. A total of 70,028 women who tested for HIV as part of antenatal contacts formed the sample for analysis. We utilized the standard concentration index and curve to understand the socioeconomic inequalities in HIV testing during antenatal care among women. Additionally, a decomposition analysis of the concentration index was ran to ascertain the contributions of each factor to the inequality. RESULTS: Overall, 73.9% of women in sub-Saharan Africa tested for HIV during ANC. The countries with the highest proportions were Malawi, Rwanda, Zambia, and Zimbabwe. Mali Benin, Guinea, Mali, and Mauritania were the countries with the lowest proportions of HIV testing. Being among the richer [AOR 1.10, 95% CI: 1.02,1.18] and richest [AOR 1.41, 95% CI:1.30, 1.54] wealth quintiles increased the odds of HIV testing during ANC. The concentration value of 0.03 and the curve show that HIV testing is more concentrated among women in the highest wealth quintile. Hence, wealthy women are advantaged in terms of HIV testing. As the model's residual value is negative (-0.057), the model overestimates the level of inequality in the outcome variable (HIV during ANC), which means that the model's explanatory factors can account for higher concentration than is the case. CONCLUSION: We found that there is substantial wealth index-related inequalities in HIV testing, with women of the poorest wealth index disadvantaged in relation to the HIV testing. This emphasizes the necessity for sub-Saharan Africa public health programs to think about concentrating their limited resources on focused initiatives to grasp women from these socioeconomic circumstances. To increase women's access to HIV testing, maternal and child health programs in sub-Saharan Africa should attempt to minimize female illiteracy and poverty. Consequently, health education may be required to provide women with comprehensive HIV knowledge and decrease the number of lost opportunities for women to get tested for HIV. Given the link between knowledge of HIV and HIV testing, it is important to focus on community education and sensitization about HIV and the need to know one's status.
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 | 0,004 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».