Spatial modelling of psychosocial benefits of favourite places in Denmark: A tale of two cities

TY - JOUR

T1 - Spatial modelling of psychosocial benefits of favourite places in Denmark

T2 - A tale of two cities

AU - Amegbor, Prince M.

AU - Dalgaard, Rikke

AU - Nainggolan, Doan

AU - Jensen, Anne

AU - Sabel, Clive E.

AU - Panduro, Toke E.

AU - Jensen, Mira S.R.

AU - Dybdal, Amanda E.

AU - Puig, Marianne

N1 - Publisher Copyright: © The Author(s) 2024.

PY - 2025/1

Y1 - 2025/1

N2 - Living in urban areas is known to increase the risk of psychosocial disorders, including stress, depression, and anxiety. Existing studies suggest that experiential places, including places of interest or favourite places, can mitigate these negative effects on psychological and physical health often associated with urban living. This study aims to model the spatial patterns of the benefits derived from favourite locations in two cities in Denmark: an urban metropolitan area (the capital city) and a provincial commuter town. Additionally, it examines the influence of individual and household socioeconomic factors on the benefits derived from these favourite places. Employing an online Public Participatory Geographic Information System (PPGIS) approach, data on favourite locations, derived benefits, and socioeconomic characteristics of 1400 respondents were collected. Bayesian modelling with Stochastic Partial Differential Equations under the Integrated Nested Laplace Approximation framework (INLA-SPDE) was utilized to predict the spatial patterns of four types of benefits – restorative, physical activity, socializing, and cultural – associated with enjoying favourite places in the two municipalities. This geostatistical approach allows for the identification of specific locations within the cities with perceived benefits and areas lacking such benefits. The findings provide insights into potential inequalities in the spatial distribution of perceived benefits of favourite places in Copenhagen and Roskilde, thereby informing urban planning policies and programs aimed at addressing these disparities.

AB - Living in urban areas is known to increase the risk of psychosocial disorders, including stress, depression, and anxiety. Existing studies suggest that experiential places, including places of interest or favourite places, can mitigate these negative effects on psychological and physical health often associated with urban living. This study aims to model the spatial patterns of the benefits derived from favourite locations in two cities in Denmark: an urban metropolitan area (the capital city) and a provincial commuter town. Additionally, it examines the influence of individual and household socioeconomic factors on the benefits derived from these favourite places. Employing an online Public Participatory Geographic Information System (PPGIS) approach, data on favourite locations, derived benefits, and socioeconomic characteristics of 1400 respondents were collected. Bayesian modelling with Stochastic Partial Differential Equations under the Integrated Nested Laplace Approximation framework (INLA-SPDE) was utilized to predict the spatial patterns of four types of benefits – restorative, physical activity, socializing, and cultural – associated with enjoying favourite places in the two municipalities. This geostatistical approach allows for the identification of specific locations within the cities with perceived benefits and areas lacking such benefits. The findings provide insights into potential inequalities in the spatial distribution of perceived benefits of favourite places in Copenhagen and Roskilde, thereby informing urban planning policies and programs aimed at addressing these disparities.

KW - cities

KW - Favourite places

KW - participatory geographic information system

KW - socioeconomic factors

KW - urban well-being

UR - http://www.scopus.com/inward/record.url?scp=85195212334&partnerID=8YFLogxK

U2 - 10.1177/23998083241255984

DO - 10.1177/23998083241255984

M3 - Journal article

AN - SCOPUS:85195212334

SN - 2399-8083

VL - 52

SP - 186

EP - 213

JO - Environment and Planning B: Urban Analytics and City Science

JF - Environment and Planning B: Urban Analytics and City Science

IS - 1

ER -