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Exploring the Joint Association of Road Traffic Noise and Air Quality with Hypertension Using QGIS

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Listed:
  • Wisdom K. Adza

    (School of Computing, Engineering & Physical Sciences, University of the West of Scotland, Paisley PA1 2BE, UK)

  • Andrew S. Hursthouse

    (School of Computing, Engineering & Physical Sciences, University of the West of Scotland, Paisley PA1 2BE, UK)

  • Jan Miller

    (School of Health & Life Sciences, University of the West of Scotland, Hamilton G72 0LH, UK)

  • Daniel Boakye

    (School of Health & Life Sciences, University of the West of Scotland, Hamilton G72 0LH, UK)

Abstract

There is growing evidence linking exposure to air pollution and traffic noise with hypertension. The aim of this study was to examine the associations of registered hypertension cases and hypertension rate with exposure to air pollution and road noise. In this cross-sectional study, we linked the information from the NHS Scotland database of 776,579 hypertension patients’ registrations and rates per 13.80 people at the Scottish NHS Board, HSCP, Cluster, and GP practice levels. Based on the geospatial attributes, the data on residential areas were added by modelling annual average air pollutant concentrations, including particulate matter (PM 10 and PM 2.5 ), nitrogen dioxide (NO 2 ), and road-traffic noise at different frequency components (Lden). The relationships between exposure to road noise, air pollution, and hypertension were examined using multiple regression and multivariate analysis. Traffic noise and air pollution at various frequency components positively and negatively predicted registered hypertension cases and hypertension rate. Based on the canonical loading technique, the variance explained by the canonical independent variable at a canonical correlation of 0.342 is 89%. There is a significant correlation between joint air pollution and noise at different frequency components and combined registered hypertension cases and hypertension rate. Exploring the combined effects of the two environmental exposures and the joint modelling of noise and air pollutants with hypertension in geospatial views provides an opportunity to integrate environmental and health data to support spatial assessment strategies in public and environmental health.

Suggested Citation

  • Wisdom K. Adza & Andrew S. Hursthouse & Jan Miller & Daniel Boakye, 2023. "Exploring the Joint Association of Road Traffic Noise and Air Quality with Hypertension Using QGIS," IJERPH, MDPI, vol. 20(3), pages 1-22, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:2238-:d:1047824
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    1. Wisdom K. Adza & Andrew S. Hursthouse & Jan Miller & Daniel Boakye, 2022. "Exploring the Combined Association between Road Traffic Noise and Air Quality Using QGIS," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
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