@misc{13706,
  abstract     = {{Urban Nature-based Solutions (NBS) are hypothesized to play an important role in promoting health, but most of the evidence is cross-sectional. This study aims to examine the effects of an integrated urban intervention with NBS at its core, implemented in the Nantes Nord district on residents' physical activity, social activity, environmental quality of life and social network as well as self-rated health and mental health. Analysing 902 observations from 2 datasets, pre- and post-intervention, we categorized 802 participants within Nantes Nord as the treatment group and 100 from other districts as the control group. We used Propensity Score Matching to adjust for selection bias in the dataset and Difference-in-Differences analysis to evaluate changes in physical activity, socializing activities, social networks, environmental quality of life, as well as self-rated health and mental health outcomes. Our results indicate that the urban tranformation with NBS at its core was associated with a significant increase in physical activity levels and to some extent in social ties. However, no immediate improvements were noticeable in socializing activities, environmental quality of life, or health outcomes, suggesting a latency in the broader effects of such interventions. This study underscores the immediate effects of the integrated NBS intervention on physical activity as a precursor to potentially more significant health benefits, which should be followed up with a more mid-to-long-term evaluation of such NBS interventions. Our findings advocate for the integration of connected green space corridors in urban planning to facilitate active lifestyles as sustainable commitments by local authorities and stakeholders.}},
  author       = {{Cardinali, Marcel and Fleury-Bahi, Ghozlane and Sapin, Arnaud and Bodénan, Philippe and Bechet, Beatrice and Petrova, Milena Tasheva and Burov, Angel and Ferilli, Guido}},
  booktitle    = {{Quick And Easy Journal Title}},
  keywords     = {{NBS, green space, Health, urban transformation, Impact Assessment, Propensity, Score Matching}},
  pages        = {{In Press, Journal Pre--proof}},
  publisher    = {{Elsevier}},
  title        = {{{Evaluation of an Urban Nature-Based Solutions Intervention on Health-Related Indicators: A Propensity Score Matching and Difference-in- Differences Study in Nantes Nord}}},
  doi          = {{https://doi.org/10.1016/j.ufug.2026.129465}},
  year         = {{2026}},
}

@misc{11283,
  abstract     = {{Introduction: In recent decades, there has been a rise in mental illnesses. Community infrastructures are increasingly acknowledged as important for sustaining good mental health. Moreover, green spaces are anticipated to offer advantages for both mental health and social cohesion. However, the mediating pathway between green space, social cohesion and mental health and especially the proximity and characteristics of green spaces that trigger these potential effects remain of interest. Methods: We gathered data from 1365 individuals on self-reported social cohesion and mental health across four satellite districts in European cities: Nantes (France), Porto (Portugal), Sofia (Bulgaria), and Hoje-Taastrup (Denmark). Green space data from OpenStreetMap was manually adjusted using the PRIGSHARE guidelines. We used the AID-PRIGSHARE tool to generate 7 indicators about green space characteristics measured in distances from 100-1500 m, every 100 m. This resulted in 105 different green space variables that we tested in a single mediation model with structural equation modelling. Results: Accessible greenness (900-1400 m), accessible green spaces (900-1500 m), accessible green space corridors (300-800 m), accessible total green space (300-800), and mix of green space uses (700-1100 m) were significantly associated with social cohesion and indirectly with mental health. Green corridors also showed negative indirect and direct associations with mental health in larger distances. Surrounding greenness and the quantity of green space uses were not associated with social cohesion nor indirectly with mental health. We also observed no positive direct associations between any green space variable in any distance to mental health. Conclusions: Our results suggest that accessibility, connectivity, mix of use and proximity are key characteristics that drive the relationship between green spaces, social cohesion and mental health. This gives further guidance to urban planners and decision-makers on how to design urban green spaces to foster social cohesion and improve mental health.}},
  author       = {{Cardinali, Marcel and Beenackers, Mariëlle A. and Fleury-Bahi, Ghozlane and Bodénan, Philippe and Petrova, Milena Tasheva and van Timmeren, Arjan and Pottgiesser, Uta}},
  booktitle    = {{  Urban forestry & urban greening}},
  issn         = {{1610-8167}},
  keywords     = {{Soil Science, Ecology, Forestry, Green space, Mediation, Social cohesion, Well-being, Structural equation modelling}},
  publisher    = {{Elsevier BV}},
  title        = {{{Examining green space characteristics for social cohesion and mental health outcomes: A sensitivity analysis in four European cities}}},
  doi          = {{10.1016/j.ufug.2024.128230}},
  volume       = {{93}},
  year         = {{2024}},
}

@phdthesis{12863,
  abstract     = {{This doctoral thesis critically examines green space characteristics and their proximity to residents in their ability to help reduce the global disease burden of non-communicable diseases. By dissecting three pivotal pathways of theorized green space health effects through increased physical activity, increased social cohesion, and reduced air pollution, the thesis aims to provide new insights into which green space characteristics drive these relationships and in which distance they occur. To achieve these aims, this thesis develops reporting guidelines for the research field, a QGIS script for automatization of green space indicator development and uses two complementary sources for data collection. It builds on the self-reported data on physical activity, social cohesion, air pollution, health and mental health from the URBiNAT project and its case studies in the four European satellite neighbourhoods Nantes-Nord (France), Porto-Campanhã (Portugal), Sofia-Nadezhda (Bulgaria), and Høje-Taastrup (Denmark) and complements it with a rigorous spatial analysis. This enabled a rigorous sensitivity analysis based on up to 135 structural equation models per pathway. The results of this doctoral research revealed distinct green space characteristics and proximities that drive each pathway, including thresholds where these associations disappear or even change direction. It concludes that interconnected, multi-use green corridors are more beneficial than isolated patches for all space strategies to shift focus from mere ratios to green mobility infrastructures. Although rooted primarily in European contexts and of a cross-sectional nature, the doctoral research provides new evidence for urban planning and public health. It emphasizes the practical implications of how to design green spaces to address health concerns. The results not only resonate with the WHO's Urban Health Research Agenda but also provide tangible recommendations for a healthier human habitat.}},
  author       = {{Cardinali, Marcel}},
  isbn         = {{978-94-6366-849-1}},
  issn         = {{2212-3202}},
  keywords     = {{Health, Green Space, Green Infrastructure, Well-being, Structural Equation Modeling}},
  pages        = {{312}},
  publisher    = {{A+BE}},
  title        = {{{Green Health. Examining the role of green space characteristics and their proximity in green space health pathways}}},
  doi          = {{10.71690/ABE.2024.09}},
  volume       = {{9}},
  year         = {{2024}},
}

@misc{13014,
  abstract     = {{In the interdisciplinary field of green space health research, there is a demand to reduce the effort to assess green space, especially for non-spatial disciplines. To address this issue, we developed AID-PRIGSHARE, an open-source script that automates over 400 QGIS processes to substantially reduces the time-intensive task of generating green space indicators. AID-PRIGSHARE calculatesgreenness, green space amount, access to green infrastructure, and green space uses within distances of 100–1500 m around geolocations. This substantially reduces the effort for sensitivity analysis and may provide support for research that aims to understand the impact of green space indicators on health outcomes.}},
  author       = {{Cardinali, Marcel and Beenackers, Mariëlle A. and van Timmeren, Arjan and Pottgiesser, Uta}},
  booktitle    = {{Software Impacts}},
  issn         = {{2665-9638}},
  keywords     = {{Green space, Sensitivity analysis, Indicator, GIS, Script, Automatization}},
  publisher    = {{Elsevier BV}},
  title        = {{{AID-PRIGSHARE: Automatization of indicator development in green space health research in QGIS. Accompanying script to the PRIGSHARE reporting guidelines}}},
  doi          = {{10.1016/j.simpa.2023.100506}},
  volume       = {{16}},
  year         = {{2023}},
}