Abstract
BACKGROUND: Noise pollution, primarily caused by intense traffic activity, is a significant environmental stressor in cities such as Chandigarh, India. Prolonged exposure to environmental noise can trigger various psychological and physiological health disturbances. This study aims to identify the direct and indirect factors contributing to noise annoyance (NA) and associated health problems using Structural Equation Modeling. METHODS: A socioacoustic survey was conducted at 25 locations across Chandigarh from January 2, 2024 to June 1, 2024. A total of 562 participants provided responses on demographic details, perceived noise levels, noise sensitivity, NA, and health complaints, including sleeping disorders, blood pressure (BP) issues, anxiety, and headache. SmartPLS software (Version 3.0, SmartPLS GmbH, Boenningstedt, Germany) was used to develop and validate the Partial Least Squares Structural Equation Modeling (PLS-SEM). Reliability, convergent validity, and discriminant validity were confirmed through measurement model assessment. RESULTS: The PLS-SEM demonstrated that noise sources, noise sensitivity, and demographic characteristics significantly predicted NA. Noise sources emerged as the strongest predictor (β = 0.41, t = 7.05, P < 0.001), followed by noise sensitivity (β = 0.35, t = 6.15, P < 0.001) and demographics (β = 0.21, t = 6.75, P < 0.001). The structural model showed substantial predictive accuracy for NA with R2 = 0.78. NA further exhibited significant effects on health-related outcomes, including sleeping disorder (β = 0.50, t = 11.79, P < 0.001), BP (β = 0.77, t = 13.01, P < 0.001), anxiety (β = 0.62, t = 9.21, P < 0.001), and headache (β = 0.52, t = 8.29, P < 0.001). Overall, the model confirmed that NA acts as the dominant pathway linking acoustic and non-acoustic factors with perceived health disturbances. CONCLUSION: This study provides a comprehensive model explaining how environmental noise contributes to annoyance and psychological health problems. The findings can inform evidence-based urban planning and public health policies to mitigate the harmful effects of environmental noise.