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Background The relationship between predictors and the variable of interest was estimated using a structural equation model which is used to predict latent variables. The main advantage of the SEM is the ability to estimate the direct and indirect pathways of the effect of the primary independent variable on the outcome, given sufficient sample sizes. Despite not directly modeling the mediated pathways, GLMMs excluding mediating variables performed well with respect to power, bias and coverage probability in modeling the total effect of the primary independent variables on the outcome. In longitudinal studies, data are collected from subjects at several time points. The main purpose of longitudinal analysis is to detecting the trends or trajectories of the variables of interest. Methods A longitudinal study was conducted on 792 adults living with HIV/AIDS who commenced HAART. Structural equation modeling was used to construct a model to detecting predictors of CD4 cell count change. The procedure was illustrated by applying it to longitudinal health-related quality-of-life data on HIV/AIDS patients, collected from September 2008 to August 2012 monthly for the first six months and quarterly for remaining study period. Results The result of current investigation indicates that CD4 cell count change was highly influenced by certain socio-demographic and clinical variables. Out of all the participants, 141 (82%) have been considered 100% adherent to antiretroviral therapy. Structural equation modeling has confirmed the direct effect that personality (decision-making and tolerance of frustration) has on motives to behave, or act accordingly, which was in turn directly related to medication adherence behaviors. In addition, these behaviors have had a direct and significant effect on viral load, as well as an indirect effect on CD4 cell count. The final model demonstrates the congruence between theory and data (x2/df. = 1.480, goodness of fit index = 0.97, adjusted goodness of fit index = 0.94, comparative fit index = 0.98, root mean square error of approximation = 0.05), accounting for 55.7% of the variance. Conclusions The results of this study support our theoretical model as a conceptual framework for the prediction of medication adherence behaviors in persons living with HIV/AIDS. Implications for designing, implementing, and evaluating intervention programs based on the model are to be discussed.

Background: The use of structural equation modelling and latent variables remains unusual in epidemiology despite its potential usefulness and assessment of casual relations. Measuring direct and indirect effect of latent variables helps for proper intervention and for the ART program to be effective. The main objective of current investigation was to assess casual relations, direct and indirect effect of latent covariates on CD4 cell count change for HIV positive adults under HAART. Methods: Based on the repeated measures of CD4 cell count change data obtained in ART section at Felege Hiwot Teaching and Specialized hospital, AMOS software was employed parameter estimation. The data was conducted on 792 randomly selected HIV positive adults. The data was collected by the health staff for sake of delivering medication adherence. Results: CD4 cell count change was directly and indirectly affected by the latent variables. The powers of effects of observed variables with and without latent variables were a little bit different from each other. Hence, the power effect of observed variables with latent variables was lower as compared to without latent variables. The direct effect of latent variables on the response variable was a little bit greater than indirect effect. Conclusion: The power of effects of observed variables were stronger than their effects with latent variables. Hence, the latent variables had significant contributions for progress of CD4 cell count change. Health related education about the direct and indirect effect of latent variables should be given for patients under HAART.

Background: The rate of prevalence of HIV among adults has been increasing in Sub-Sahara African countries over the last decade. Currently, an estimated number of 722, 248 people are living with HIV, 23, 000 people are newly infected with HIV and 11,000 people are died because of AIDS related illness. The objective of this study was to identify the most significant variables associated with the variation of CD4 cell count and body mass index (BMI) of HIV positive adults who initiated HAART at Felege Hiwot Teaching and Specialized Hospital, North-West Ethiopia. This study also aimed to compared the precision of parameter estimates conducted by separate and joint models.Methods: To analyze the long-term CD4 cells count and body mass index of HIV infected adults, a cohort longitudinal study of 792 HIV-infected patients was performed. A joint model was employed to identify the variables associated with the variation of CD4 cell count and body mass index of adults receiving treatment at Felege Hiwot Teaching and specialized Hospital. A random of 792 samples was taken among patients using individual charts in the hospital.Results: Among the main effects, Socio-demographic variables (Level of education, level of disclosure of the disease to persons living together and Marital status ), individuals factors(age, weight and gender), economic factors (ownership of cell phone, level of income), clinical factors (baseline CD4 cell count) retention (food and medication adherence, follow-up time/visit) significantly affected the variables of interests. Similarly, the interaction effects of follow-up times/visits * cell phone ownership, follow-up times/visits * gender, age * gender of patients significantly affected both response variables in current investigation.Conclusion: Socio-demographic, individual and Clinical variables had significant effect on CD4 cell count and BMI in HAART medication program. Follow-up time/visit in the HAART program had also direct and significant effect on the variables of interest. Older HIV patients should be targeted by appropriate public health actions, such as opportunistic screening and easier access to healthcare service. The patients should be advised to disclose the disease to get support from communities around them.

The rate of prevalence of HIV among adults has been increasing in Sub-Sahara African countries over the last decade. The objective of this study was to identify the most significant variables associated with the variation of CD4 cell count and body mass index (BMI) of HIV positive adults who initiated HAART at Felege Hiwot Teaching and Specialized Hospital, North-West Ethiopia. This study also aimed to compare the precision of parameter estimates conducted by separate and joint models.A cohort longitudinal study of 792 HIV-infected patients was performed. A joint model was employed to identify predictor variables. A random of 792 samples was taken among patients using individual charts in the hospital. Among the main effects, Socio-demographic variables (Level of education, level of disclosure of the disease to persons living together and Marital status), individuals factors(age, weight and gender), economic factors (ownership of cell phone, level of income), clinical factors (baseline CD4 cell count) retention (food and medication adherence, follow-up time/visit) significantly affected the variables of interests. Similarly, the interaction effects of follow-up times/visits * cell phone ownership, follow-up times/visits * gender, age * gender of patients significantly affected both response variables in current investigation. Socio-demographic, individual and Clinical variables had significant effect on CD4 cell count and BMI in HAART medication program. Follow-up time/visit in the HAART program had also direct and significant effect on the variables of interest. The patients should be advised to disclose the disease to get support from communities around them.

In clinical trials and practices, failure of adherence to medications is a common challenge among patients with chronic diseases. Many factors are associated with this failure. Reports of previous studies about predictors of adherence to Highly Active Antiretroviral Therapy (HAART) were not consistent. The main objective of this study was to identify predictors of long-term adherence to HAART, considering lag variables as additional predictors. Transitional modeling was used to determine the predictors of long-term adherence to HAART. A retrospective transitional study design was conducted on 792 randomly selected adult patients at Felege-Hiwot Teaching and Specialized Hospital, Bahir Dar, Ethiopia. Results revealed that the first two lag-variables ( ) were significantly associated with performance of current adherence to HAART. The increase in CD4 cell count change was significantly associated with current adherence, if patients made transition from adherent level at lag2 to non-adherent level at lag1 ( ). As a conclusion, for patients who were transferred from adherent level at lag2 to non-adherent level at lag1, their CD4 cell count changes were positively correlated with current adherence level. Due attention should thus be given to address the specific needs of each group of patients. Non-adherence to HAART in this long-term treatment program was at risk and should receive interventional action. Educational therapy during follow-ups should also be given to non-adherent patients to strengthen the era of long-term treatment.