Abstract

The issue of water pollution is rapidly becoming an international problem with wide consequences for human health, ecosystem sustainability, and community well-being. Since the problems of physical and ecological impacts have been precisely defined, the psychological impact on people living near polluted water bodies has not been well researched. This paper discusses the relationships between the severity of aquatic pollution and mental health using a mixed-methods approach. The 2,460 samples, which included chemical contaminant indicators and demographic and mental health indexes, were compiled into a simulation yet realistic dataset, constructed based on the WHO and CDC environmental health patterns. The study uses correlational analysis, regression modeling, random forest prediction, and structural equation modeling to establish statistically significant relationships between exposure to pollution and psychological distress. Results show that the stress, anxiety, and depressive symptoms levels are 3241 more in the group of residents in high-pollution areas (r = 0.67, p < 0.01). The Random Forest model was the most effective, with R2 = 0.83, RMSE = 4.11, and MAE = 2.87, indicating it is a good predictor. Other ablation experiments confirm the mediation findings: perceived environmental risk and the socioeconomic variables mediate the psychological outcomes and together account for 24 percent of the predictive power. The present study finds that the prevalence of aquatic pollution is not an environmental concern but rather a major psychosocial stressor that should be addressed through joint policy measures. The findings show that resolving the interrelation between pollution and psychological well-being requires holistic environmental governance, mental health support structures, and interdisciplinary research.

Keywords: Aquatic pollution, Psychological well-being, Environmental health, Risk perception, Mental health assessment, Pollution exposure modelling, Environmental psychology