Matthew Dennis1, Penny A Cook2, Philip James3, C Philip Wheater4, Sarah J Lindley5. 1. Department of Geography, School of Environment Education and Development, University of Manchester, Arthur Lewis Building, Manchester, M13 9PL, UK. Matthew.Dennis@Manchester.ac.uk. 2. School of Health and Society, University of Salford, The Crescent, Allerton Building, Salford, M5 4WT, UK. 3. School of Science, Engineering and Environment, University of Salford, The Crescent, Peel Building, Salford, M5 4WT, UK. 4. School of Science and the Environment, Manchester Metropolitan University, Chester Street, John Dalton Building, Manchester, M1 5GD, UK. 5. Department of Geography, School of Environment Education and Development, University of Manchester, Arthur Lewis Building, Manchester, M13 9PL, UK.
Abstract
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.
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.
Authors: Linda Powers Tomasso; Jie Yin; Jose Guillermo Cedeño Laurent; Jarvis T Chen; Paul J Catalano; John D Spengler Journal: Int J Environ Res Public Health Date: 2021-02-05 Impact factor: 3.390
Authors: Elaine Ruth Carnegie; Greig Inglis; Annie Taylor; Anna Bak-Klimek; Ogochukwu Okoye Journal: Int J Environ Res Public Health Date: 2022-02-24 Impact factor: 3.390