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Residential green and blue space associated with better mental health: a pilot follow-up study in university students Cover

Residential green and blue space associated with better mental health: a pilot follow-up study in university students

Open Access
|Jan 2019

Abstract

Previous research has suggested that natural urban environment (green space and blue space) benefit mental health, but only a few longitudinal studies have explored the underlying mechanisms. In this pilot study we aimed to examine mechanisms/variables mediating associations between residential green/blue space and symptoms of anxiety/depression in 109 Bulgarian students from Plovdiv university. The students were followed from the beginning to the end of the school year (October 2017 to May 2018). Residential green space was defined as the mean of the normalised difference vegetation index (NDVI) in circular buffers of 100, 300, and 500 m around their residences. Blue space was assessed based on its presence in the same buffers. Levels of anxiety/depression were assessed using the 12-item General Health Questionnaire. The investigated mediator variables included residential noise (LAeq) and air pollution (NO2), environmental annoyance, perceived restorative quality of the neighbourhood, neighbourhood social cohesion, physical activity, and sleep disturbance. Cross-sectional data (obtained at baseline) showed that higher NDVI correlated with better mental health only indirectly through higher physical activity and restorative quality. Longitudinal (follow-up) data showed improved mental health but no significant effect of mediator variables. Similarly, blue space correlated with better mental health in all models, but physical activity and restorative quality were significant mediator variables only in the cross-sectional analysis. Our findings support that green space and blue space are psychologically restorative features in urban environment. Future research should replicate these findings in the general population and employ longitudinal modelling tailored to the specific mechanisms under study.

DOI: https://doi.org/10.2478/aiht-2018-69-3166 | Journal eISSN: 1848-6312 | Journal ISSN: 0004-1254
Language: English, Croatian, Slovenian
Page range: 340 - 349
Submitted on: Jul 1, 2018
Accepted on: Nov 1, 2018
Published on: Jan 11, 2019
Published by: Institute for Medical Research and Occupational Health
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Angel M. Dzhambov, published by Institute for Medical Research and Occupational Health
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.