Application of the structural equation modeling-partial least square method to analyze factors affecting the quality of life of hypertension patients

Hypertension is a serious health issue in Pidie Regency, Indonesia. This research utilizes Structural Equation Modeling - Partial Least Squares (SEM-PLS) method to analyze the factors contributing to hypertension in Pidie Regency. Primary data were was gathered via surveys and discussions held with inhabitants from the area. One of the multivariate statistical methods that can be used to explain these complex relationships is SEM-PLS. The direct effects of SEM-PLS analysis indicate the hidden demographic factors notably diminish the concealed variable of quality of life. The concealed indicators of medication adherence showcase a positive impact but lack statistical significance on the hidden variable of quality of life. Additionally, the latent activity variable has a positive and significant effect on quality of life. The research findings revealed an R 2 value of 0.234, signifying that 23.4% of the variance in the latent quality of life variable can be explained by latent demographic, medication adherence, and activity variables.