ISSN 2456-0235

​​​​​​​International Journal of Modern Science and Technology, Vol. 2, No. 4, 2017, Pages 131-137. 


Evaluation of HIV/AIDS Treatment Adherence in Uasin Gishu County, Kenya

E. N. Kihumba¹, T. Kibua², A. Obala²
¹Department of Statistics and Actuarial Science, Kenyatta University, Kenya.
²Department of Medical Microbiology, Moi University, Kenya.  

*Corresponding author’s e-mail: elijahnk12@yahoo.com

Abstract
Ninety-five percent adherence to antiretroviral drugs regimen is often needed to achieve optimal rates of viral suppression in people living with HIV/AIDS. Thus cross sectional study evaluated ARVs drug adherence among people living with HIV/AIDS in Uasin Gishu County and the impact on their health. The ages of participants ranged between 18 years and 56 years with median age of 35 years with the 95% confidence interval (32.8668, 36.7028). The mean age of the females was higher (35.4872) than that of the males (34.1). The results show that ARVs adherence status in Uasin Gishu County is low. For instance, only 26.6% of PLWHIV adhere to ARVs drugs while 73.4% do not. More males (79.73%; no=177/222) failed to adhere to ARVs intake compared to females (67.54%; no=154/228). Within the last three months prior to the interview 40.5% of the participants were hospitalized for at least a day while 59.5% were not hospitalized. Chi-square test showed significant association between the adherence to ARV drugs and the health of PLWHIV. Mantel – Haensel common ratio test showed that, the odds ratio of ill health of PLWHIV on ARVs adhering to the ARVs drugs is significantly different from those not adhering to the ARVs treatment. The odds of ill health of PLWHIV on ARVs not adhering to the ARVs was 2.787 times more compared to the odds of ill health of PLWHIV on ARVs for those adhering to the ARVs. The 95% confidence interval is (0.901, 8.619). A logistic regression model of adherence to the ARVs was fitted with factors leading to non-adherence as the covariates to assess the relationship between the adherence to the ARVs and the factors leading to non-adherence. The results showed most predominant factors leading to non-adherence of ARVs are lack of family support (p=0.040), violence (p=0.032), lack of time (p=0.039), family conflict (p=0.017), stigma (p=0.019), poverty (p=0.018), waiting for new drug (p=0.043), other health complications (p=0.046) and many drugs (p=0.029).

​​Keywords: HIV/AIDS; Treatment Adherence; Evaluation; Uasin Gishu County.

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International Journal of Modern Science and Technology

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