A health data led approach for assessing potential health benefits of green and blue spaces: Lessons from an Irish case study

被引:5
作者
Arodudu, Oludunsin [1 ,2 ]
Foley, Ronan [2 ]
Taghikhah, Firouzeh [3 ]
Brennan, Michael [4 ]
Mills, Gerald [5 ]
Ningal, Tine [5 ]
机构
[1] SUNY Syracuse, Coll Environm Sci & Forestry, Dept Sustainable Resources Management, Syracuse, NY 13210 USA
[2] Natl Univ Ireland Maynooth, Dept Geog, Rhetor House, Maynooth, Kildare, Ireland
[3] Univ Sydney, Dicipline Business Analyt, Sydney, Australia
[4] Ballymun Civ Ctr, Eastern & Midland Reg Assembly, 3rd Floor North,Main St, Dublin, Ireland
[5] Univ Coll Dublin, Sch Psychol, Newman Bldg, Belfield, Ireland
关键词
Green space; Blue space; Human health; Data clustering techniques; Health data led approach; Environmental justice; ENVIRONMENTAL JUSTICE; SPATIAL ASSOCIATION; INEQUALITIES; INDICATORS; EXPOSURE; PLACES;
D O I
10.1016/j.jenvman.2023.118758
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Research producing evidence-based information on the health benefits of green and blue spaces often has within its design, the potential for inherent or implicit bias which can unconsciously orient the outcomes of such studies towards preconceived hypothesis. Many studies are situated in proximity to specific or generic green and blue spaces (hence, constituting a green or blue space led approach), others are conducted due to availability of green and blue space data (hence, applying a green or blue space data led approach), while other studies are shaped by particular interests in the association of particular health conditions with presence of, or engagements with green or blue spaces (hence, adopting a health or health status led approach). In order to tackle this bias and develop a more objective research design for studying associations between human health outcomes and green and blue spaces, this paper discussed the features of a methodological framework suitable for that purpose after an initial, year-long, exploratory Irish study. The innovative approach explored by this study (i.e., the health-data led approach) first identifies sample sites with good and poor health outcomes from available health data (using data clustering techniques) before examining the potential role of the presence of, or engagement with green and blue spaces in creating such health outcomes. By doing so, we argue that some of the bias associated with the other three listed methods can be reduced and even eliminated. Finally, we infer that the principles and paradigm adopted by the health data led approach can be applicable and effective in analyzing other sustainability problems beyond associations between human health outcomes and green and blue spaces (e.g., health, energy, food, income, environment and climate inequality and justice etc.). The possibility of this is also discussed within this paper.
引用
收藏
页数:16
相关论文
共 114 条
[1]  
Agrawal R., 1998, SIGMOD Record, V27, P94, DOI 10.1145/276305.276314
[2]   Automatic subspace clustering of high dimensional data [J].
Agrawal, R ;
Gehrke, J ;
Gunopulos, D ;
Raghavan, P .
DATA MINING AND KNOWLEDGE DISCOVERY, 2005, 11 (01) :5-33
[3]   The Application of Unsupervised Clustering Methods to Alzheimer's Disease [J].
Alashwal, Hany ;
El Halaby, Mohamed ;
Crouse, Jacob J. ;
Abdalla, Areeg ;
Moustafa, Ahmed A. .
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2019, 13
[4]   Age density patterns in patients medical conditions: A clustering approach [J].
Alhasoun, Fahad ;
Aleissa, Faisal ;
Alhazzani, May ;
Moyano, Luis G. ;
Pinhanez, Claudio ;
Gonzalez, Marta C. .
PLOS COMPUTATIONAL BIOLOGY, 2018, 14 (06)
[5]   Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling [J].
Alvioli, Massimiliano ;
Marchesini, Ivan ;
Reichenbach, Paola ;
Rossi, Mauro ;
Ardizzone, Francesca ;
Fiorucci, Federica ;
Guzzetti, Fausto .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2016, 9 (11) :3975-3991
[6]   Green and Blue Spaces and Behavioral Development in Barcelona Schoolchildren: The BREATHE Project [J].
Amoly, Elmira ;
Dadvand, Payam ;
Forns, Joan ;
Lopez-Vicente, Monica ;
Basagana, Xavier ;
Julvez, Jordi ;
Alvarez-Pedrerol, Mar ;
Nieuwenhuijsen, Mark J. ;
Sunyer, Jordi .
ENVIRONMENTAL HEALTH PERSPECTIVES, 2014, 122 (12) :1351-1358
[7]  
Ankerst M, 1999, SIGMOD RECORD, VOL 28, NO 2 - JUNE 1999, P49
[8]   LOCAL INDICATORS OF SPATIAL ASSOCIATION - LISA [J].
ANSELIN, L .
GEOGRAPHICAL ANALYSIS, 1995, 27 (02) :93-115
[9]  
Anselin L., 2005, Exploring spatial data with GeoDaTM: A workbook, P138
[10]  
Arodudu O.T., 2019, IALE INT ASS LANDSC