[Analysis on factors associated with life quality of HIV-infected individuals in antiretroviral therapy in Wuxi based on three models].

Objective

To analyze factors associated with life quality of HIV-infected individuals receiving antiretroviral therapy by using three models and compare the prediction performance of different models in Wuxi.

Methods

Using a cross-sectional study design, a questionnaire survey was conducted in HIV-infected individuals receiving antiretroviral therapy recruited through convenience sampling in Wuxi from June to September 2025 with a sample size of 346. The Chinese version of the World Health Organization Quality of Life Questionnaire for HIV was used to evaluate the life quality of HIV-infected individuals. The logistic regression model, decision tree model and random forest model were used to analyze factors associated with the life quality of HIV-infected individuals. The prediction performance of different models was compared by using confusion matrix and the area under receiver operating characteristic curve.

Results

A total of 460 HIV-infected individuals were involved, with a total life quality score (79.49±8.46) lower than that in general population of national norm (80.28±17.46)(t=-2.01, P=0.045). The logistic regression analysis showed that risk factors associated with the life quality of HIV-infected individuals included informing no others of HIV infection status (aOR=1.72, 95%CI: 1.04-2.85), anxiety (aOR=2.23, 95%CI: 1.26-4.00), and depression (aOR=4.05, 95%CI: 2.42-6.87), while protective factor was better social support (aOR=0.60, 95%CI: 0.37-0.97). The decision tree model showed that depression, social support, and education level were factors associated with life quality of HIV-infected individuals. The random forest model indicated that main factors associated with life quality of HIV-infected individuals were depression and anxiety, followed by other chronic diseases, education level, and marital status. The accuracy rates of logistic regression, decision tree, and random forest models for the prediction of the life quality of HIV-infected individuals were 0.723, 0.715, and 0.752, respectively.

Conclusions

The overall life quality of HIV-infected individuals was lower than that of general population, which was mainly associated with factors, such as depression, social support and education level. All the three models exhibited good accuracy in prediction of the life quality of HIV-infected individuals, but random forest model showed the better overall prediction performance.