The Relationship between Noise Pollution and Depression and Implications for Healthy Ageing: A Spatial Analysis using Routinely Collected Primary Care Data

Abstract

AbstractEnvironmental noise is a significant public health concern, ranking among the top environmental risks to citizens’ health and quality of life. Despite various studies exploring the effects of atmospheric pollution on mental health, spatial investigations into the effects of noise pollution have been notably absent. This study addresses this gap by investigating the association between noise pollution (from road and rail networks) and depression for the first time in England and first explores localised patterns based on area deprivation. Depression prevalence, defined as the percentage of patients with a recorded depression diagnosis was calculated in small areas within Cheshire and Merseyside ICS using the Quality and Outcomes Framework Indicators dataset for 2019. Strategic noise mapping for rail and road noise (LDEN) was employed to quantify noise pollution, indicating a 24-hour annual average noise level with distinct weightings for evening and night periods. The English Index of Multiple Deprivation (IMD) was utilised to represent neighbourhood deprivation. Geographical Weighted Regression and Generalised Structural Equation Spatial Modelling (GSESM) were applied to estimate relationships between transportation noise, depression prevalence, and IMD at the Lower Super Output Area (LSOA) level. While transportation noise showed a low direct effect on depression levels in Cheshire and Merseyside ICS, it significantly mediated other factors linked to depression prevalence. Notably, GSESM revealed that health deprivation and disability was strongly associated (0.62) with depression through the indirect effect of environmental noise, particularly where transportation noise exceeds 55 dB on a 24-hour basis. Comprehending variations in noise exposure across different areas is paramount. This research not only provides valuable insights for informed decision-making but also lays the groundwork for implementing noise mitigation measures. These measures are aimed at addressing mental health inequalities, enhancing the quality of life for the exposed population and supporting a healthier ageing process in urban environments. The findings also carry crucial implications for public health, specifically in tailoring targeted interventions to mitigate noise-related health risks in areas where noise burdens exceed 55 dB, and residents may experience health deprivation and disability.