Assessment and prediction of noise pollution–induced health impacts in urban environment: a structural equation modeling (SEM)–based approach

Abstract

In recent years, the problem of noise pollution in urban areas has gained significant attention due to its detrimental impact on the health of residents. The present study aims to determine the current noise pollution scenario and direct and indirect association between the influencing factors on health issues of residents in an urban environment. The study utilized a partial least square-structural equation modeling (PLS-SEM) approach to examine the hypotheses related to how individuals perceive noise pollution and its impact on their health. The research findings reveal that noise annoyance and noise sensitivity have a direct impact on noise induced health issues, while demographic characteristics and traffic noise have an indirect influence. Additionally, noise level monitoring was conducted during morning, afternoon, and evening hours to evaluate ambient noise levels and prepare noise maps. Analysis of the prepared noise maps revealed that many sampling locations show noise levels higher than, or close to, 70 dBA. The study aims to develop a decision-support tool that utilizes data on noise pollution levels and associated health issues to inform policy interventions for managing and controlling noise pollution in urban settings.