Assessment of noise pollution and associated subjective health complaints and psychological symptoms: analysis through structure equation model.

Road traffic noise is affecting the exposed population through its detrimental effects. This study was conducted in urban zones of Peshawar, Khyber Pakhtunkhwa, Pakistan, to analyze causal relationship between noise and subjective health complaints with a special focus on psychological symptoms. A 12-h (LAeq) noise survey conducted at different locations (n = 57) indicated a noise range of 46.3-86.3 dB (A). A questionnaire survey was conducted from local residents (n = 500), students (n = 500), policemen (n = 500), shopkeepers (n = 500), and drivers (n = 500) exposed to road traffic noise and analyzed through structure equation modeling (SEM). Different models were prepared and a modified model obtained the acceptable model fit, i.e., chi-square 0.093, χ2/df 1.286, comparative fit index 0.986, goodness of fit index 0.966, normed fit index 0.943, Tucker-Lewis index 0.977, and root mean square error of approximation 0.034. The modified model gives not only the information about direct but also indirect effects of noise on the exposed population. Adding on, the model clearly indicates that sensitivity to noise has strong relationship with subjective health complaints (headache, exhaustion, and psychological symptoms such as annoyance, difficulty concentrating, ill temper, and anxiety) than profession, age, location, and gender. Duration of exposure to road traffic noise has an important role in increasing the frequency of subjective health issues. The model is important in depicting that sensitivity to noise may produce subjective health complaints (standardized parameter estimates of 0.12 and 0.29) but the mediator has much stronger positive path estimates (0.59). The modified model sought to discover and explicate the underlying mechanism of an observed relationship existing between the selected dependent and an independent variable through the identification of the mediator variables.