Characterisation of the natural environment: quantitative indicators across Europe

BACKGROUND: The World Health Organization recognises the importance of natural environments for human health. Evidence for natural environment-health associations comes largely from single countries or regions, with varied approaches to measuring natural environment exposure. We present a standardised approach to measuring neighbourhood natural environment exposure in cities in different regions of Europe. METHODS: The Positive Health Effects of the Natural Outdoor environment in TYPical populations of different regions in Europe (PHENOTYPE) study aimed to explore the mechanisms linking natural environment exposure and health in four European cities (Barcelona, Spain; Doetinchem, the Netherlands; Kaunas, Lithuania; and Stoke-on-Trent, UK). Common GIS protocols were used to develop a hierarchy of natural environment measures, from simple measures (e.g., NDVI, Urban Atlas) using Europe-wide data sources, to detailed measures derived from local data that were specific to mechanisms thought to underpin natural environment-health associations (physical activity, social interaction, stress reduction/restoration). Indicators were created around residential addresses for a range of straight line and network buffers (100 m-1 km). RESULTS: For simple indicators derived from Europe-wide data, we observed differences between cities, which varied with different indicators (e.g., Kaunas and Doetinchem had equal highest mean NDVI within 100 m buffer, but mean distance to nearest natural environment in Kaunas was more twice that in Doetinchem). Mean distance to nearest natural environment for all cities suggested that most participants lived close to some kind of natural environments (64 +/- 58-363 +/- 281 m; mean 180 +/- 204 m). The detailed classification highlighted marked between-city differences in terms of prominent types of natural environment. Indicators specific to mechanisms derived from this classification also captured more variation than the simple indicators. Distance to nearest and count indicators showed clear differences between cities, and those specific to the mechanisms showed within-city differences for Barcelona and Doetinchem. CONCLUSIONS: This paper demonstrates the feasibility and challenges of creating comparable GIS-derived natural environment exposure indicators across diverse European cities. Mechanism-specific indicators showed within- and between-city variability that supports their utility for ecological studies, which could inform more specific policy recommendations than the traditional proxies for natural environment access

Does the Health Impact of Exposure to Neighbourhood Green Space Differ between Population Groups? An Explorative Study in Four European Cities

It has been suggested that certain residents, such as those with a low socioeconomic status, the elderly, and women, may benefit more from the presence of neighbourhood green space than others. We tested this hypothesis for age, gender, educational level, and employment status in four European cities. Data were collected in Barcelona (Spain; n = 1002), Kaunas (Lithuania; n = 989), Doetinchem (The Netherlands; n = 847), and Stoke-on-Trent (UK; n = 933) as part of the EU-funded PHENOTYPE project. Surveys were used to measure mental and general health, individual characteristics, and perceived neighbourhood green space. Additionally, we used audit data about neighbourhood green space. In Barcelona, there were positive associations between neighbourhood green space and general health among low-educated residents. In the other cities and for the other population groups, there was little evidence that the association between health and neighbourhood green space differed between population groups. Overall, our study does not support the assumption that the elderly, women, and residents who are not employed full-time benefit more from neighbourhood green space than others. Only in the highly urbanised city of Barcelona did the low-educated group benefit from neighbourhood green spaces. Perhaps neighbourhood green spaces are more important for the health of low-educated residents in particularly highly urbanised areas

Characterisation of the natural environment: quantitative indicators across Europe

Background: The World Health Organization recognises the importance of natural environments for human health. Evidence for natural environment-health associations comes largely from single countries or regions, with varied approaches to measuring natural environment exposure. We present a standardised approach to measuring neighbourhood natural environment exposure in cities in different regions of Europe. Methods: The Positive health effects on the natural outdoor environment in typical populations of different regions in Europe (PHENOTYPE) study aimed to explore the mechanisms linking natural environment exposure and health in four European cities (Barcelona, Spain; Doetinchem, the Netherlands; Kaunas, Lithuania; and Stoke-on-Trent, UK). Common GIS protocols were used to develop a hierarchy of natural environment measures, from simple measures (e.g., NDVI, Urban Atlas) using Europe-wide data sources, to detailed measures derived from local data that were specific to mechanisms thought to underpin natural environment-health associations (physical activity, social interaction, stress reduction/restoration). Indicators were created around residential addresses for a range of straight line and network buffers (100m to 1km). Results: For simple indicators derived from Europe-wide data, we observed differences between cities, which varied with different indicators (e.g., Kaunas and Doetinchem had equal highest mean NDVI within 100m buffer, but mean distance to nearest natural environment in Kaunas was more twice that in Doetinchem). Mean distance to nearest natural environment for all cities suggested that most participants lived close to some kind of natural environments (64±58 to 363±281m; mean 180±204m). The detailed classification highlighted marked between-city differences in terms of prominent types of natural environment. Indicators specific to mechanisms derived from this classification also captured more variation than the simple indicators. Distance to nearest and count indicators showed clear differences between cities, and the those specific to the mechanisms showed within-city differences for Barcelona and Doetinchem. Conclusions: This paper demonstrates the feasibility and challenges of creating comparable GIS-derived natural environment exposure indicators across diverse European cities. Mechanism-specific indicators showed within- and between-city variability that suggests their utility for ecological studies, which could inform more specific policy recommendations than the traditional proxies for natural environment access

The INHERIT Model: A Tool to Jointly Improve Health, Environmental Sustainability and Health Equity through Behavior and Lifestyle Change.

The need for analysis and action across the interrelated domains of human behaviors and lifestyles, environmental sustainability, health and inequality is increasingly apparent. Currently, these areas are often not considered in conjunction when developing policies or interventions, introducing the potential for suboptimal or conflicting outcomes. The INHERIT model has been developed within the EU-funded project INHERIT as a tool to guide thinking and intersectoral action towards changing the behaviors and lifestyles that play such an important role in today’s multidisciplinary challenges. The model integrates ecological public health and behavioral change models, emphasizing inequalities and those parts of the causal process that are influenced by human behaviors and lifestyles. The model was developed through web-based and live discussions with experts and policy stakeholders. To test the model’s usability, the model was applied to aspects of food consumption. This paper shows that the INHERIT model can serve as a tool to identify opportunities for change in important −food-related behaviors and lifestyles and to examine how they impact on health, health inequalities, and the environment in Europe and beyond. The INHERIT model helps clarify these interrelated domains, creating new opportunities to improve environmental health and health inequality, while taking our planetary boundaries into consideration

Neighbourhood green space, social environment and mental health: an examination in four European cities

Objectives This study examines the relationship between neighbourhood green space, the neighbourhood social environment (social cohesion, neighbourhood attachment, social contacts), and mental health in four European cities. Methods The PHENOTYPE study was carried out in 2013 in Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands), and Kaunas (Lithuania). 3771 adults living in 124 neighbourhoods answered questions on mental health, neighbourhood social environment, and amount and quality of green space. Additionally, audit data on neighbourhood green space were collected. Multilevel regression analyses examined the relation between neighbourhood green space and individual mental health and the influence of neighbourhood social environment. Results Mental health was only related to green (audit) in Barcelona. The amount and quality of neighbourhood green space (audit and perceived) were related to social cohesion in Doetinchem and Stoke-on-Trent and to neighbourhood attachment in Doetinchem. In all four cities, mental health was associated with social contacts. Conclusions Neighbourhood green was related to mental health only in Barcelona. Though neighbourhood green was related to social cohesion and attachment, the neighbourhood social environment seems not the underlying mechanism for this relationship

Does the Health Impact of Exposure to Neighbourhood Green Space Differ between Population Groups? An Explorative Study in Four European Cities

It has been suggested that certain residents, such as those with a low socioeconomic status, the elderly, and women, may benefit more from the presence of neighbourhood green space than others. We tested this hypothesis for age, gender, educational level, and employment status in four European cities. Data were collected in Barcelona (Spain; n = 1002), Kaunas (Lithuania; n = 989), Doetinchem (The Netherlands; n = 847), and Stoke-on-Trent (UK; n = 933) as part of the EU-funded PHENOTYPE project. Surveys were used to measure mental and general health, individual characteristics, and perceived neighbourhood green space. Additionally, we used audit data about neighbourhood green space. In Barcelona, there were positive associations between neighbourhood green space and general health among low-educated residents. In the other cities and for the other population groups, there was little evidence that the association between health and neighbourhood green space differed between population groups. Overall, our study does not support the assumption that the elderly, women, and residents who are not employed full-time benefit more from neighbourhood green space than others. Only in the highly urbanised city of Barcelona did the low-educated group benefit from neighbourhood green spaces. Perhaps neighbourhood green spaces are more important for the health of low-educated residents in particularly highly urbanised areas

The relationship between natural outdoor environments and cognitive functioning and its mediators

Background Urban residents may experience cognitive fatigue and little opportunity for mental restoration due to a lack of access to nature. Natural outdoor environments (NOE) are thought to be beneficial for cognitive functioning, but underlying mechanisms are not clear. Objectives To investigate the long-term association between NOE and cognitive function, and its potential mediators. Methods This cross-sectional study was based on adult participants of the Positive Health Effects of the Natural Outdoor Environment in Typical Populations in Different Regions in Europe (PHENOTYPE) project. Data were collected in Barcelona, Spain; Doetinchem, the Netherlands; and Stoke-on-Trent, United Kingdom. We assessed residential distance to NOE, residential surrounding greenness, perceived amount of neighborhood NOE, and engagement with NOE. Cognitive function was assessed with the Color Trails Test (CTT). Mediation analysis was undertaken following Baron and Kenny. Results Each 100 m increase in residential distance to NOE was associated with a longer CTT completion time of 1.50% (95% CI 0.13, 2.89). No associations were found for other NOE indicators and cognitive function. Neighborhood social cohesion was (marginally) significantly associated with both residential distance to NOE and CTT completion time, but no evidence for mediation was found. Nor were there indications for mediation by physical activity, social interaction with neighbors, loneliness, mental health, air pollution worries, or noise annoyance. Conclusions Our findings provide some indication that proximity to nature may benefit cognitive function. We could not establish which mechanisms may explain this relationship

Development of the natural environment scoring tool (NEST)

Natural environments (green and blue space) are associated with a range of health benefits, but their use is likely to be influenced by the presence of features, facilities and amenities and the condition/maintenance, or the natural environment quality. Most 'quality' assessment tools have focused on green spaces and their support for physical activity. This limits their utility for assessment of other natural environment typologies and uses (e.g., social, relaxation). We aimed to develop a tool for feasible, in situ assessment of diverse natural environments that might support a variety of uses, and to explore associations between natural environment quality and objectively measured amount of natural environment and neighbourhood-level socio-economic status (SES). This work was conducted as part of the PHENOTYPE project. Data were collected in 124 neighbourhoods in four European cities (Barcelona, Doetinchem, Kaunas, Stoke-on-Trent). The Natural Environment Scoring Tool (NEST) was developed using existing tools, expert input and field-testing. The final tool comprised 47-items across eight domains: Accessibility, Recreation facilities, Amenities, Aesthetics- natural, Aesthetics- non-natural, Significant natural features, Incivilities and Usability; typology-specific Overall Scores were derived. In total, 174 natural environments, covering a range of typologies, were audited. Mean time to complete NEST was 16±28 min. There was good inter-rater agreement. Mean domain scores showed some expected patterns by typology (e.g., higher Recreation Facilities scores in urban parks and formal recreation areas; lower Amenities scores in natural/semi-natural areas). Highest mean Overall Scores were observed for areas of blue space and woodland, the types of area that often lack the recreational facilities or amenities that can be dominant in physical activity-focused audit tools. There was a trend towards lower natural environment quality in neighbourhoods of lower SES, with some inter-city variation. Correlations between NEST scores and amount of natural environment indicated higher natural environment in areas with worse access. We recommend further testing of NEST in other locations in relation to use and health outcomes

Use of the Natural Outdoor Environment in Different Populations in Europe in Relation to Access: Implications for Policy

This cross-cultural study explores the relationship of natural outdoor environment (NOE) use with NOE access. Most urban planning recommendations suggest optimal accessibility to be 300 m–500 m straight distance to spaces with vegetation of at least 1 hectare. Exploring this recommendation, we used data (n = 3947) from four European cities collected in the framework of the PHENOTYPE study: Barcelona (Spain), Doetinchem (The Netherlands), Kaunas (Lithuania) and Stoke-on-Trent (United Kingdom) to obtain residential access to NOE (straight or network distances, using 300 m and 150 m buffers, to NOE larger than 1 hectare or 0.5 hectare) and use of NOE (i.e., self-reported time spent in NOE). Poisson regression models were used to examine the associations between residential access and use of NOE. The models with the strongest association with time spent in NOE in the combined sample were for those living within 300 m straight line distance to either 0.5 ha or 1 ha NOE. Noting that the only indicator that was consistent across all individual cities was living with 150 m network buffer of NOE (of at least 1 ha), this warrants further exploration in reducing recommendations of 300 m straight-line distance to 150 m network distance to 1 ha of NOE for a general indicator for cities within Europe