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Socio-Demographic and Clinical Predictor Variables on CD4 Cell Count Change among HIV Positive adults; a Structural Equations Modelling

Article scientifique 2020 Anglais

Résumé

Abstract Background: The prevalence of HIV/AIDS among adult individuals has been increasing in Sub-Sahara African countries over the last decade. In Ethiopia , the prevalence of HIV among adults was 1%. Hence, 23, 000 people were newly infected with HIV and 11,000 people were died because of AIDS related illness in 2018. The purpose of this study was to identify the most significant socio-demographic, economic, individual and clinical determinants of CD4 cell count change in HIV positive adults who initiated HAART at Felege Hiwot Teaching and Specialized Hospital, North-West Ethiopia. Methods: A secondary and retrospective study design was conducted on 792 HIV positive adults. A structural equation modeling was employed to identify the socio-demographic and clinical covariates that have a statistically significant effect on the status of CD4 cell count change. Results: Literate patients, patients living with partner, patients living in urban area, patients disclosed the disease to family members, high income , ownership of cell, age and sex (male) were statistically significant variables. Conclusion: There was direct relation between socio-demographic variables with retention of HIV positive individuals in HAART program. There was also a direct and significant effect of clinical variables on adherence competence and adherence on CD4 cell change. Retention of patients in the HAART program had direct and significant effect on CD4 cell count change. This finding will be important for policy makers, health officials and for patients to easier access to healthcare service. Keywords: Socio-demographic, clinical factors, individual characteristics, Structural equation, CD4count change

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Tegegne, A. S., Ndlovu, P., & Zewotire, T. Z. (2020). Socio-Demographic and Clinical Predictor Variables on CD4 Cell Count Change among HIV Positive adults; a Structural Equations Modelling. https://doi.org/10.21203/rs.2.20118/v1

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