Awoke Seyoum Tegegne
Background: The use of structural equation modeling and latent variables remains unusual in epidemiology despite its potential usefulness and assessment of causal relations. Measuring the direct and indirect effect of latent variables helps with proper intervention and for the ART program to be effective. The main objective of the current investigation was to assess causal inference of assessment of the 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 the ART section at Felege Hiwot teaching and specialized hospital, AMOS software was used for parameter estimation. The study was conducted on 792 randomly selected HIV positive adults. The data were collected by the health staff after a brief orientation of the variables under study.
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 powerful effect of observed variables with latent variables was lower as compared to those without latent variables. The direct effect of latent variables on the response variable was a little bit greater than the indirect effect.
Conclusion: The power of the effects of observed variables was stronger than their effects with latent variables. Hence, the latent variables had significant contributions to the progress of CD4 cell count change. Health related education about the direct and indirect effects of latent variables should be given to patients under HAART. Knowledge of direct and indirect effects on the variable of interest is important for proper intervention in ART programs.
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