{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/393561"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/393561","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"How Urban Nature Shapes Health: Unravelling the Spatial Complexity of Nature-Health Systems","abstract":"Urban nature is recognised as a key Determinant of Health, yet existing research often relies on linear, aspatial approaches that overlook how Health Outcomes emerge from complex, interdependent processes, whose effects vary across space. This thesis adopts a spatial complexity lens and a multimethod design to overcome these limitations and advance a more nuanced understanding of how urban nature shapes Health Outcomes, combining conceptual, methodological, and applied perspectives. A scoping review of urban health policies mapping environmental, behavioural, and socioeconomic Determinants of Health reveals that policy agendas, although policy agendas broadly align with research evidence, they often oversimplify complex interdependencies among determinants and at the local level remain siloed in sectoral framings that limit integrative approaches. A bibliometric analysis of over 5,000 publications maps the fragmented conceptual landscape of nature–health research and advances an integrative framework that positions nature exposure as operating through interconnected pathways and contingently shaped by diverse social, ecological, and spatial contexts. Building on these insights, a high-resolution spatial dataset for Greater London (350m grid; 232 indicators) is developed to operationalise spatial complexity analysis. Using this dataset and applying Generalised Propensity Score weighting within Spatial Generalised Additive Models augmented by spatial-lag terms, the thesis estimates non-linear, spatially explicit dose–response functions between nature exposure and 20 chronic health outcomes. Results demonstrate that distance, size, and ecological quality interact across space to shape health benefits in a context-dependent manner. Together, these findings advance a spatial complexity paradigm for nature–health research, showing that accounting for non-linearity, spatial dependence, and context-specific variation yields a more nuanced understanding of how urban nature influences health. Beyond systematising fragmented policy and conceptual debates, the thesis makes three core contributions. Conceptually, it reframes urban nature as a systemic Determinant of Health that interacts dynamically with other determinants and with space, challenging reductionist perspectives. Methodologically, it introduces a replicable framework that integrates high-resolution spatial data, geostatistical exploration, and confounding-adjustment strategies to operationalise spatial complexity in practice. Empirically, the analysis demonstrates that health benefits of urban nature follow diminishing returns and threshold patterns, are moderated by ecological quality, and vary across space. These insights provide an evidence base for more context-sensitive interventions and highlight the need for spatially explicit, systems-informed, and cross-sectoral urban health policies.","abstract_html":"Urban nature is recognised as a key Determinant of Health, yet existing research often relies on linear, aspatial approaches that overlook how Health Outcomes emerge from complex, interdependent processes, whose effects vary across space. This thesis adopts a spatial complexity lens and a multimethod design to overcome these limitations and advance a more nuanced understanding of how urban nature shapes Health Outcomes, combining conceptual, methodological, and applied perspectives. A scoping review of urban health policies mapping environmental, behavioural, and socioeconomic Determinants of Health reveals that policy agendas, although policy agendas broadly align with research evidence, they often oversimplify complex interdependencies among determinants and at the local level remain siloed in sectoral framings that limit integrative approaches. A bibliometric analysis of over 5,000 publications maps the fragmented conceptual landscape of nature–health research and advances an integrative framework that positions nature exposure as operating through interconnected pathways and contingently shaped by diverse social, ecological, and spatial contexts. Building on these insights, a high-resolution spatial dataset for Greater London (350m grid; 232 indicators) is developed to operationalise spatial complexity analysis. Using this dataset and applying Generalised Propensity Score weighting within Spatial Generalised Additive Models augmented by spatial-lag terms, the thesis estimates non-linear, spatially explicit dose–response functions between nature exposure and 20 chronic health outcomes. Results demonstrate that distance, size, and ecological quality interact across space to shape health benefits in a context-dependent manner. Together, these findings advance a spatial complexity paradigm for nature–health research, showing that accounting for non-linearity, spatial dependence, and context-specific variation yields a more nuanced understanding of how urban nature influences health. Beyond systematising fragmented policy and conceptual debates, the thesis makes three core contributions. Conceptually, it reframes urban nature as a systemic Determinant of Health that interacts dynamically with other determinants and with space, challenging reductionist perspectives. Methodologically, it introduces a replicable framework that integrates high-resolution spatial data, geostatistical exploration, and confounding-adjustment strategies to operationalise spatial complexity in practice. Empirically, the analysis demonstrates that health benefits of urban nature follow diminishing returns and threshold patterns, are moderated by ecological quality, and vary across space. These insights provide an evidence base for more context-sensitive interventions and highlight the need for spatially explicit, systems-informed, and cross-sectoral urban health policies.","abstract_has_math":false,"creators":["A C Costalonga Seraphim, Ana Paula"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["A Silva, Elisabete"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-08-09","date_published":"2025-08-09","updated_at":"2026-07-22T22:24:00Z","subjects":["Urban Health","Urban Natural Spaces","Determinants of Health","Spatial Econometrics","Spatial Analysis","Spatial Complexity"],"languages":["eng"],"rights":[],"rights_urls":["https://www.repository.cam.ac.uk/bitstreams/c0418778-9da8-477f-af79-904240d574db/download","http://purl.org/NET/rdflicense/allrightsreserved"],"identifier_entries":[{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000000169702949"],"render_values":[{"text":"0000-0001-6970-2949","href":"https://orcid.org/0000-0001-6970-2949","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.123853","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["A Silva, Elisabete"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["Horizon 2020 eMotional Cities Project (grant agreement No 945307)"]},{"key":"dc:creator","label":"Author","values":["A C Costalonga Seraphim, Ana Paula"]},{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000000169702949"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2025-08-09"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/393561"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Urban Health","Urban Natural Spaces","Determinants of Health","Spatial Econometrics","Spatial Analysis","Spatial Complexity"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://www.repository.cam.ac.uk/bitstreams/c0418778-9da8-477f-af79-904240d574db/download","http://purl.org/NET/rdflicense/allrightsreserved"]},{"key":"dc:rights.embargodate","label":"Dc Rights Embargodate","values":["2026-12-08"]},{"key":"dc:rights.embargotype","label":"Dc Rights Embargotype","values":["embargo"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.17863/CAM.123853"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://www.repository.cam.ac.uk/bitstreams/0aeafa74-0b99-4b10-9a27-b7f22d2a453c/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Urban nature is recognised as a key Determinant of Health, yet existing research often relies on linear, aspatial approaches that overlook how Health Outcomes emerge from complex, interdependent processes, whose effects vary across space. 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