Abstract
In their study, Astell-Burt and Feng1 address 2 important limitations of much of the research on contact with nearby nature and human health and well-being.2 The first one is its cross-sectional design, preventing the ability to draw firm conclusions regarding the causality of observed associations. The second one is that most studies do not distinguish between different types of green and/or blue space and consequently tell us little about which type of nature is most beneficial. In their study, they begin to address this gap by making efficient use of longitudinal health data already collected for other purposes and enriching these data with land-use data on the availability of green and blue space in the residential environment. Consequently, in addition to prevalence data, incidence data were available on high risk of psychological distress, physician-diagnosed anxiety and/or depression, and less than good self-rated health. Furthermore, they distinguished 3 types of vegetation: tree canopy, grass, and low-lying vegetation. They concluded that tree canopy may be more beneficial than the other 2 types.
Highlights
The study by Astell-Burt and Feng[1] is definitely a step in the right direction
The spatial resolution of the land-use data used to determine the amount of different types of green space is not mentioned
The authors mention that the level of biodiversity of the green space may be important based on a study conducted in 2007
Summary
The study by Astell-Burt and Feng[1] is definitely a step in the right direction. At the same time, it bears the markings of a journey in uncharted territory. The study’s information on which green spaces are included is limited. It remains unclear whether vegetation in agricultural areas within the 1.6-km buffer is included.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.