Background: There is a growing body of literature supporting positive associations between natural environments and better health. The type, quality and quantity of green and blue space (‘green-space’) in proximity to the home might be particularly important for less mobile populations, such as for some older people. However, considerations of measurement and definition of green-space, beyond single aggregated metrics, are rare. This constitutes a major source of uncertainty in current understanding of public health benefits derived from natural environments. We aimed to improve our understanding of how such benefits are conferred to different demographic groups through a comprehensive evaluation of the physical and spatial characteristics of urban green infrastructure. Methods: We employed a green infrastructure (GI) approach combining a high-resolution spatial dataset of land-cover and function with area-level demographic and socio-economic data. This allowed for a comprehensive characterization of a densely populated, polycentric city-region. We produced multiple GI attributes including, for example, urban vegetation health. We used a series of step-wise multi-level regression analyses to test associations between population chronic morbidity and the functional, physical and spatial components of GI across an urban socio-demographic gradient. Results: GI attributes demonstrated associations with health in all socio-demographic contexts even where associations between health and overall green cover were non-significant. Associations varied by urban socio-demographic group. For areas characterised by having higher proportions of older people (‘older neighbourhoods’), associations with better health were exhibited by land-cover diversity, informal greenery and patch size in high income areas and by proximity to public parks and recreation land in low income areas. Quality of GI was a significant predictor of good health in areas of low income and low GI cover. Proximity of publicly accessible GI was also significant. Conclusions: The influence of urban GI on population health is mediated by green-space form, quantity, accessibility, and vegetation health. People in urban neighbourhoods that are characterised by lower income and older age populations are disproportionately healthy if their neighbourhoods contain accessible, good quality public green-space. This has implications for strategies to decrease health inequalities and inform international initiatives, such as the World Health Organisation’s Age-Friendly Cities programme.

Common approaches to mapping green infrastructure in urbanised landscapes invariably focus on measures of land use or land cover and associated functional or physical traits. However, such one-dimensional perspectives do not accurately capture the character and complexity of the landscapes in which urban inhabitants live. The new approach presented in this paper demonstrates how open-source, high spatial and temporal resolution data with global coverage can be used to measure and represent the landscape qualities of urban environments. Through going beyond simple metrics of quantity, such as percentage green and blue cover, it is now possible to explore the extent to which landscape quality helps to unpick the mixed evidence presented in the literature on the benefits of urban nature to human well-being. Here we present a landscape approach, employing remote sensing, GIS and data reduction techniques to map urban green infrastructure elements in a large U.K. city region. Comparison with existing urban datasets demonstrates considerable improvement in terms of coverage and thematic detail. The characterisation of landscapes, using census tracts as spatial units, and subsequent exploration of associations with social–ecological attributes highlights the further detail that can be uncovered by the approach. For example, eight urban landscape types identified for the case study city exhibited associations with distinct socioeconomic conditions accountable not only to quantities but also qualities of green and blue space. The identification of individual landscape features through simultaneous measures of land use and land cover demonstrated unique and significant associations between the former and indicators of human health and ecological condition. The approach may therefore provide a promising basis for developing further insight into processes and characteristics that affect human health and well-being in urban areas, both in the United Kingdom and beyond.

This article provides a perspective on nature-based solutions. First, the argument is developed that nature-based solutions integrate social and ecological systems. Then, theoretical considerations relating to relational values, multifunctionality, transdisciplinarity, and polycentric governance are briefly outlined. Finally, a conceptual model of the social–ecological system of nature-based solutions is synthesised and presented. This conceptual model comprehensively defines the social and ecological external and internal systems that make up nature-based solutions, and identifies theoretical considerations that need to be addressed at different stages of their planning and implementation The model bridges the normative gaps of existing nature-based solution frameworks and could be used for consistent, comprehensive, and transferable comparisons internationally. The theoretical considerations addressed in this article inform practitioners, policymakers, and researchers about the essential components of nature-based solutions. The conceptual model can facilitate the identification of social and ecological interconnections within nature-based solutions and the range of stakeholders and disciplines involved.

Background: There are few robust natural experimental studies of improving urban green spaces on physical activity and wellbeing. The aim of this controlled natural experimental study was to examine the impact of green space improvements along an urban canal on canal usage, physical activity and two other wellbeing behaviours (social interactions and taking notice of the environment) among adults in Greater Manchester, UK. The intervention included resurfaced footpaths, removal of encroaching vegetation, improved entrances, new benches and signage. Methods: Two comparison sites were matched to the intervention site using a systematic five-step process, based on eight correlates of physical activity at the neighbourhood (e.g. population density) and site (e.g. lighting) levels. Outcomes were assessed using systematic observations at baseline, and 7, 12 and 24 months post-baseline. The primary outcome was the change in the number of people using the canal path from baseline to 12 months. Other outcomes were changes in physical activity levels (Sedentary, Walking, Vigorous), Connect and Take Notice behaviours. Data were analysed using multilevel mixed-effects negative binomial regression models, comparing outcomes in the intervention group with the matched comparison group, controlling for day, time of day and precipitation. A process evaluation assessed potential displacement of activity from a separate existing canal path using intercept surveys and observations. Results: The total number of people observed using the canal path at the intervention site increased more than the comparison group at 12 months post-baseline (IRR 2.10, 95% CI 1.79–2.48); there were similar observed increases at 7 and 24 months post-baseline. There was some evidence that the intervention brought about increases in walking and vigorous physical activity, social interactions, and people taking notice of the environment. The process evaluation suggested that there was some displacement of activity, but the intervention also encouraged existing users to use the canal more often. Conclusions: Urban canals are promising settings for interventions to encourage green space usage and potentially increase physical activity and other wellbeing behaviours. Interventions that improve access to green corridors along canals and provide separate routes for different types of physical activities may be particularly effective and warrant further research. Study protocol: Study protocol published in Open Science Framework in July 2018 before the first follow-up data collection finished (https://osf.io/zcm7v). Date of registration: 28 June 2018.