TY - JOUR
T1 - Spatial Variability Analysis of Quality of Life and Its Determinants
T2 - A Case Study of Medellín, Colombia
AU - Sepúlveda Murillo, Fabio Humberto
AU - Chica Olmo, Jorge
AU - Soto Builes, Norely Margarita
PY - 2019/8/1
Y1 - 2019/8/1
N2 - According to the Gini indicator, Medellín—the capital of the Department of Antioquia, Colombia—has been considered the most unequal city in Colombia for several consecutive years with regard to inequity in its residents’ quality of life (QoL) level. Therefore, this research mainly aimed to explore the spatial variations in the QoL of households and the determinants that explain it, using some geographically weighted techniques. This analysis becomes substantial when it is intended to contribute to government policies and programs that seek the well-being of individuals. For this purpose, an indicator that integrated both objective and subjective variables to measure the QoL of households in Medellín was constructed. The local and global spatial autocorrelation indexes were used to visualize and analyze the geographic structure of the quality of life indicator. The global or conventional principal components analysis and the geographically weighted principal components analysis were used to identify spatial trends and explore the spatial variations of the determinants that explain the QoL, respectively. The results confirm that the QoL and the factors explaining it are highly spatially heterogeneous in Medellín, being extremely supportive of appropriate authorities for spatial planning and developing strategies that help to improve the living conditions of homes in the city.
AB - According to the Gini indicator, Medellín—the capital of the Department of Antioquia, Colombia—has been considered the most unequal city in Colombia for several consecutive years with regard to inequity in its residents’ quality of life (QoL) level. Therefore, this research mainly aimed to explore the spatial variations in the QoL of households and the determinants that explain it, using some geographically weighted techniques. This analysis becomes substantial when it is intended to contribute to government policies and programs that seek the well-being of individuals. For this purpose, an indicator that integrated both objective and subjective variables to measure the QoL of households in Medellín was constructed. The local and global spatial autocorrelation indexes were used to visualize and analyze the geographic structure of the quality of life indicator. The global or conventional principal components analysis and the geographically weighted principal components analysis were used to identify spatial trends and explore the spatial variations of the determinants that explain the QoL, respectively. The results confirm that the QoL and the factors explaining it are highly spatially heterogeneous in Medellín, being extremely supportive of appropriate authorities for spatial planning and developing strategies that help to improve the living conditions of homes in the city.
KW - Geographically weighted principal components analysis
KW - Principal components analysis
KW - Quality of life
KW - Spatial autocorrelation
KW - Spatial non-stationarity
UR - http://www.scopus.com/inward/record.url?scp=85068740468&partnerID=8YFLogxK
U2 - 10.1007/s11205-019-02088-x
DO - 10.1007/s11205-019-02088-x
M3 - Artículo
AN - SCOPUS:85068740468
VL - 144
SP - 1233
EP - 1256
JO - Social Indicators Research
JF - Social Indicators Research
SN - 0303-8300
IS - 3
ER -