Prevalence and the Risk Factors Associated with HIV-TB Co-Infection Among Clinic Attendees in Dots and Art Centres in Ibadan, Nigeria
Notice bibliographique
Résumé
Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) co-infection form a very serious public health menace in Nigeria. Among patients confirmed to have been infected with either of the disease, co-infection with the other is highly prevalent. However, comprehensive studies focusing on the distributions and correlates of TB/HIV co-infections among Patients attending TB clinics in Ibadan are lacking in the literature. The objective of this study was to determine the prevalence and correlates of TB/HIV co-infection among patients suspected to be TB positive at various health facilities offering TB/HIV Collaboration Service (THCS) in Ibadan. A descriptive cross-sectional study was carried out among 500 TB/ HIV clinic attendees in Ibadan, Nigeria. A simple random sampling method was used to select 8 TB clinics in Ibadan from the list of all clinics offering THCS in Ibadan. An interviewer administered questionnaire was used to elicit information on TB/HIV status, risk factors and knowledge of HIV and TB from all participants who consented to be interviewed. Descriptive statistics, Chi-square test and logistic regression were used for data analysis at 5% level of significant. Mean age of the patients was 33.98±13.15 years. The overall prevalence of TB/HIV co-infection among the participants was found to be (41.6%). Prevalence of TB/HIV co-infection were highest (11.2% and 14.8%) among participants in age group 20-29 years and 30-39 years respectively. More females (25.2%) than males (16.4%) had been infected with TB/HIV co- infection. While the prevalence of TB/HIV co-infection were respectively 2.0%, 6.6% 18.4% and 14.6% among participants with no formal education, Primary education, Secondary education and Tertiary education, the prevalence was 20.6% and 16.4% among the married and the unmarried respectively. Results of the Chi-square test show that TB/HIV co-infection was found to be associated with History of the use of TB and HIV drugs defaults, Multiple sex partners, Paid sex, Marital status and occupation of participants. Also, Multiple sex partners (OR = 6.0, 95% CI: 2.4-15.0), Extra-vaginal intercourse (OR= 0.3, 95% CI: 0.1- 0.8) and Paid sex (OR= 0.1, 95% CI: 0.5-0.7) were found to be associated with TB/HIV co-infection among the participants. The study revealed that a higher prevalence of co-infection was observed among 10-49 years age group. This implies that the productive age group bears the brunt of TB/HIV co-infection. It was also found that participants with multiple sex partner (OR=6.01) those whose partners are residing with them(OR=1.45) and those with formal education(OR=1.59) are more likely to have TB/HIV co-infection while those with History of anti-TB drug default(OR=0.54), History of anti-retroviral drug default(OR=0.49), those who practice Extra-vaginal intercourse(OR=0.346) and paid sex(OR=0.19) are less likely to be TB/HIV co-infected. TB/HIV control programs that educate people on the prevalence and focus on these subgroups are likely to decrease the joint burden of TB and HIV
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 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».