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Nature contact and general health: Testing multiple serial mediation pathways with data from adults in 18 countries

  • Lewis R. Elliott
  • , Tytti Pasanen
  • , Mathew P. White
  • , Benedict W. Wheeler
  • , James Grellier
  • , Marta Cirach
  • , Gregory N. Bratman
  • , Matilda van den Bosch
  • , Anne Roiko
  • , Ann Ojala
  • , Mark Nieuwenhuijsen
  • , Lora E. Fleming

Publications: Contribution to journalArticlePeer Reviewed

Abstract

The role of neighbourhood nature in promoting good health is increasingly recognised in policy and practice, but consistent evidence for the underlying mechanisms is lacking. Heterogeneity in exposure methods, outcome measures, and population characteristics, little exploration of recreational use or the role of different types of green or blue space, and multiple separate mediation models in previous studies have limited our ability to synthesise findings and draw clear conclusions. We examined multiple pathways linking different types of neighbourhood nature with general health using a harmonised international sample of adults. Using cross-sectional survey data from 18 countries (n = 15,917), we developed a multigroup path model to test theorised pathways, controlling for sociodemographic variables. We tested the possibility that neighbourhood nature (e.g. greenspace, inland bluespace, and coastal bluespace) would be associated with general health through lower air pollution exposure, greater physical activity attainment, more social contact, and higher subjective well-being. However, our central prediction was that associations between different types of neighbourhood nature and general health would largely be serially mediated by recent visit frequency to corresponding environment types, and, subsequently, physical activity, social contact, and subjective well-being associated with these frequencies. Several subsidiary analyses assessed the robustness of the results to alternative model specifications as well as effect modification by sociodemographics. Consistent with this prediction, there was statistical support for eight of nine potential serial mediation pathways via visit frequency which held for a range of alternative model specifications. Effect modification by financial strain, sex, age, and urbanicity altered some associations but did not necessarily support the idea that nature reduced health inequalities. The results demonstrate that across countries, theorised nature-health linkages operate primarily through recreational contact with natural environments. This provides arguments for greater efforts to support use of local green/blue spaces for health promotion and disease prevention.
Original languageEnglish
Article number108077
Number of pages18
JournalEnvironment International
Volume178
Early online date30 Jun 2023
DOIs
Publication statusPublished - Aug 2023

Funding

We thank Ben Butler, Gavin Ellison, and Tom Powell at YouGov for managing the data collection pertaining to this study. We thank Perry Hystad for providing advanced access to contemporary NO 2 maps. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 666773 (BlueHealth). Data collection in California was supported by the Center for Conservation Biology, Stanford University. Data collection in Canada was supported by the Faculty of Forestry, University of British Columbia. Data collection in Finland was supported by the Natural Resources Institute Finland (Luke). Data collection in Australia was supported by Griffith University and the University of the Sunshine Coast. Data collection in Portugal was supported by ISCTE—University Institute of Lisbon. Data collection in Ireland was supported by the Environmental Protection Agency, Ireland. Data collection in Hong Kong was supported by an internal University of Exeter—Chinese University of Hong Kong international collaboration fund. The funders had no role in the conceptualisation, design, analysis, decision to publish or preparation of the manuscript. A subset of the data used in this study can be downloaded from the UK Data Service (Elliott, LR, White, MP. 2022. BlueHealth International Survey Dataset, 2017-2018. [data collection]. UK Data Service. SN: 8874, doi: 10.5255/UKDA-SN-8874-2). We thank Ben Butler, Gavin Ellison, and Tom Powell at YouGov for managing the data collection pertaining to this study. We thank Perry Hystad for providing advanced access to contemporary NO2 maps. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 666773 (BlueHealth). Data collection in California was supported by the Center for Conservation Biology, Stanford University. Data collection in Canada was supported by the Faculty of Forestry, University of British Columbia. Data collection in Finland was supported by the Natural Resources Institute Finland (Luke). Data collection in Australia was supported by Griffith University and the University of the Sunshine Coast. Data collection in Portugal was supported by ISCTE—University Institute of Lisbon. Data collection in Ireland was supported by the Environmental Protection Agency, Ireland. Data collection in Hong Kong was supported by an internal University of Exeter—Chinese University of Hong Kong international collaboration fund. The funders had no role in the conceptualisation, design, analysis, decision to publish or preparation of the manuscript. A subset of the data used in this study can be downloaded from the UK Data Service (Elliott, LR, White, MP. 2022. BlueHealth International Survey Dataset, 2017-2018. [data collection]. UK Data Service. SN: 8874, doi: 10.5255/UKDA-SN-8874-2).

Austrian Fields of Science 2012

  • 501030 Cognitive science

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