A Space–Time Study for Mapping Quality of Life in Andalusia During the Crisis

Sánchez, Angeles; Chica-Olmo, Jorge; Jiménez-Aguilera, Juan de Dios

doi:10.1007/s11205-016-1497-9

Cited by 10 publications

(14 citation statements)

References 60 publications

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“…In Spain, a worsening of the QoL has also been observed during the crisis between 2007 and 2011 [ 39 ]. Spain was one of the European countries where the consequences of the global economic crisis were most devastating.…”

Section: Discussionmentioning

confidence: 99%

Influence of Active and Healthy Ageing on Quality of Life Changes: Insights from the Comparison of Three European Countries

Ayala

Rodríguez‐Blázquez

Calderón‐Larrañaga

et al. 2021

IJERPH

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This study aimed to analyze the determinants of quality of life (QoL) in older people in three European countries (Portugal, Spain and Sweden). A sample of 7589 participants in waves 4 (2011) and 6 (2015) of the Survey on Health, Aging, and Retirement in Europe (SHARE) project, aged 50 and over and living in Portugal, Spain and Sweden, was included. The CASP-12 scale was used to measure QoL. A principal component analysis was performed to group preselected variables related to active and healthy ageing into the dimensions of health, social participation, and lifelong learning. A linear regression model was built using the change in CASP-12 scores over the 4-year follow-up as the dependent variable, including the interactions between country and each independent variable in the model. After four years, the average QoL increased in Portugal (difference = 0.8, p < 0.001), decreased in Spain (−0.8, p < 0.001), and remained constant in Sweden (0.1, p = 0.408). A significant country-participation component interaction (p = 0.039) was found. In Spain, a higher participation (β = 0.031, p = 0.002) was related to a higher QoL improvement at 4 years, but not in Sweden or Portugal. Physical health and emotional components (β = 0.099, p < 0.001), functional ability (β = 0.044, p = 0.023), and cognitive and sensory ability (β = 0.021, p = 0.026) were associated with QoL changes over time in all countries. The country-specific associations between health, social participation and QoL should be taken into account when developing public health policies to promote QoL among European older people.

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Section: Discussionmentioning

confidence: 99%

Influence of Active and Healthy Ageing on Quality of Life Changes: Insights from the Comparison of Three European Countries

Ayala

Rodríguez‐Blázquez

Calderón‐Larrañaga

et al. 2021

IJERPH

View full text Add to dashboard Cite

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“…The use of the Internet is an increasingly crucial factor for competitiveness and economic security, as it determines the capacity of territories to compete in and benefit from the knowledge-based economy. Studies with a territorial approach have shown that the availability of high-speed networks is a key determinant of quality of life because it facilitates economic, educational and social connections (Sánchez et al, 2018 ). On the contrary, the lack of Internet could represent a digital divide that increases levels of economic and social inequality.…”

Section: Data and Variablesmentioning

confidence: 99%

European Union Cohesion Policy: Socio-Economic Vulnerability of the Regions and the COVID-19 Shock

Sánchez¹,

Fernández

2022

Applied Research Quality Life

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The European Union Cohesion Policy for the period 2021–2027 focuses on five goals to make the European Union smarter, greener, more connected, more social and closer to citizens. However, a macroeconomic index is proposed as the predominant criterion for allocating the Structural Funds among regions. In this paper, we hypothesise that it is possible to take into account new, complementary criteria that better reflect citizens’ quality of life. To that end, we build a composite index of socio-economic vulnerability for the 233 regions. The results show that following our multidimensional approach for allocating the Structural Funds, there are remarkable differences in the maps of priority regions. In addition, the COVID-19 pandemic represents a threat to well-being. Are all regions equally exposed to COVID-19 in terms of their socio-economic vulnerability? To address this issue, we estimate multilevel models which indicate that country characteristics interact with regions’ characteristics to alter patterns of vulnerability. More specifically, increases in government expenditures in education and an improvement in political stability would reduce the regional vulnerability or foster the capacity for resilience, whereas increases in poverty would be associated with greater vulnerability. Likewise, more vulnerable regions would be the most exposed to the negative socio-economic effects of COVID-19. However, it is remarkable that several regions of Sweden and Finland would be among the group of regions whose socio-economic vulnerability would be the most negatively affected.

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“…This allows governments to have a support and feedback tool to make decisions. Sánchez et al (2018) show in a region of Spain that the quality of life in a municipality is explained by the quality of life of the municipality in the previous period and the changes in the quality of life in neighboring municipalities in the past and nowadays. Therefore, public policies must take into account that time and space are important in terms of quality of life.…”

Section: Literature Reviewmentioning

confidence: 99%

“…On the other hand, we are interested in finding out whether spatial location has an influence on these indicators. Sánchez et al (2018) conclude that public policies must take into account that time and space are important in terms of quality of life. Our interest lies in seeking arguments for or against the role of localization of these indicators.…”

Section: Introductionmentioning

confidence: 99%

Synthetic Indicators of Quality of Subjective Life in the EU: Rural and Urban Areas

Sánchez-Sellero¹,

García-Carro²,

Sánchez‐Sellero³

2021

Prague Economic Papers

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The aim of this paper is to develop subjective synthetic indicators that quantify the quality of life in the different countries of the EU-28, with data from the 2016 European Quality of Life Survey (EQLS). We add other indicators to the general synthetic ones in order to quantify the different dimensions of quality life due to its multidimensional nature. The successive but unchained application of the principal component analysis and the Mazziota-Pareto analysis allows us to classify 5 dimensions of quality of life: subjective component of governance, public services, environment, general satisfaction with life, and socioeconomic issues. We verify that countries with the lowest or highest positions in the general index usually keep that position in most dimensions. The spatial perspective is fundamental to study of regional development. For this reason, the next objective is the analysis of differences by spatial location using the variance analysis. The general indicator shows significant differences between EU countries but it does not show differences in the quality of life of European citizens in urban and rural areas.

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A Space–Time Study for Mapping Quality of Life in Andalusia During the Crisis

Cited by 10 publications

References 60 publications

Influence of Active and Healthy Ageing on Quality of Life Changes: Insights from the Comparison of Three European Countries

Influence of Active and Healthy Ageing on Quality of Life Changes: Insights from the Comparison of Three European Countries

European Union Cohesion Policy: Socio-Economic Vulnerability of the Regions and the COVID-19 Shock

Synthetic Indicators of Quality of Subjective Life in the EU: Rural and Urban Areas

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