Prevalence and determinants of HIV testing-seeking behaviors among women of reproductive age in Tanzania: analysis of the 2022 Demographic and health survey
Notice bibliographique
Résumé
AIM: HIV remains one of the major epidemics and public health concerns within low and middle-income countries such as Tanzania. This study aimed to assess the prevalence and the factors associated with HIV testing-seeking behaviors among women of childbearing age in Tanzania. METHODS: This study used the 2022 Tanzania Demographic and Health Survey dataset. The study utilized individual recodes (IR) files where data was collected using the Women's Questionnaire to analyze factors influencing HIV testing behavior among women, Descriptive analysis, and bivariate and multivariate logistic regressions were performed and all the data were processed and analyzed using STATA version 17 at 95% CI and significance level P < 0.05. RESULTS: This study included 2531 women with 90.0% having ever tested for HIV while 7.0% had never tested for HIV. Not employed [AOR:0.35, CI (0.20-0.61)] has lower odds of HIV testing than All-year employed status. Rural residents have reduced odds of HIV testing [AOR:0.43, CI (0.21-0.88)] compared to women living in urban areas. Those able to ask their partner to use a condom are more likely to have been tested with increased odds [AOR: 3.52, CI (2.31-5.37)]. Participants with a history of genital discharge [AOR:4.30, CI (1.28-14.46)] and those who don't know their genital discharge history have [AOR: 0.20, CI (0.07-0.55)] are significant for HIV testing. Women who have heard about PrEP but are not uncertain about its approval [AOR: 36.07, CI (3.33-390.25)], respondents who have tested before with HIV testing kits [AOR:35.99, CI (4.00-324.13)] and women who are aware of HIV testing kids but never tested with them before [AOR: 2.80, CI (1.19-6.58)] are predictors of HIV testing seeking behaviors. CONCLUSION: The government and other concerned agencies should introduce mobile or community-based testing units and subsidize testing costs to reach economically disadvantaged or rural populations. Promote Open Communication on Sexual Health: Public health campaigns should encourage open discussions about sexual health within relationships, emphasizing condom negotiation and mutual health checks as preventive measures. Raise Awareness and Accessibility of HIV Prevention Tools: Expand education on PrEP and HIV self-test kits to improve familiarity and acceptance, which may empower individuals to proactively seek testing. Integrate Sexual Health Screening into Routine Healthcare: Health facilities should incorporate HIV testing when individuals present with symptoms like genital discharge to improve early detection and intervention.
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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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| 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 ».