Spatial patterns in sociodemographic factors explain to a large extent the prevalence of hypertension and diabetes in Aragon (Spain)

Introduction: The global burden of multi-morbidity has become a major public health challenge due to the multi stakeholder action required to its prevention and control. The Social Determinants of Health approach is the basis for the establishment of health as a cross-cutting element of public policies toward enhanced and more efficient decision making for prevention and management. Objective: To identify spatially varying relationships between the multi-morbidity of hypertension and diabetes and the sociodemographic settings (2015–2019) in Aragon (a mediterranean region of Northeastern Spain) from an ecological perspective. Materials and methods: First, we compiled data on the prevalence of hypertension, diabetes, and sociodemographic variables to build a spatial geodatabase. Then, a Principal Component Analysis (PCA) was performed to derive regression variables, i.e., aggregating prevalence rates into a multi-morbidity component (stratified by sex) and sociodemographic covariate into a reduced but meaningful number of factors. Finally, we applied Geographically Weighted Regression (GWR) and cartographic design techniques to investigate the spatial variability of the relationships between multi-morbidity and sociodemographic variables. Results: The GWR models revealed spatial explicit relationships with large heterogeneity. The sociodemographic environment participates in the explanation of the spatial behavior of multi-morbidity, reaching maximum local explained variance (R2) of 0.76 in men and 0.91 in women. The spatial gradient in the strength of the observed relationships was sharper in models addressing men’s prevalence, while women’s models attained more consistent and higher explanatory performance. Conclusion: Modeling the prevalence of chronic diseases using GWR enables to identify specific areas in which the sociodemographic environment is explicitly manifested as a driving factor of multi-morbidity. This is step forward in supporting decision making as it highlights multi-scale contexts of vulnerability, hence allowing specific action suitable to the setting to be taken

Impact of Dynamic Capabilities on Customer Satisfaction through Digital Transformation in the Automotive Sector

Technology has impacted businesses in different areas, and, consequently, many companies have found it necessary to make changes in their structures and business models to improve customer satisfaction. The objective was to quantify the effect of dynamic capabilities on customer satisfaction, through digital transformation within the automotive sector. A random sample of 42 questionnaires on 127 surveyed industries was collected during the period 2019–2020 in a pre-COVID-19 context. A structural equation model (SEM) in two stages was applied. In the first stage, two reflective models were built. In a second stage, a structural equation model was evaluated. The results obtained in this study showed that the capabilities of sensing, seizing and innovation were suitably grouped in a construct called “Dynamic Capabilities”. A positive influence of Dynamic Capabilities on customer satisfaction was found. Therefore, the companies in this industry should focus on developing dynamic capabilities to improve customer satisfaction. Once the opportunities have been identified, managers take advantage of their potential (seizing) to transform and exploit knowledge in the creation, innovation, process improvement, and definition of strategies to combine new knowledge with that already existing. The digital transformation has contributed to identify the real needs for customers, to contact them and solve their problems, as well as offering products and services by anticipating their needs

Análisis espacial de la prevalencia de obesidad infantil en Aragón bajo el enfoque de los determinantes de la salud

El presente Trabajo Fin de Grado (TFG) analiza una selección de determinantes sociales de la prevalencia de obesidad infantil (menores de 14 años) apoyándose en técnicas y herramientas de análisis espacial y representación cartográfica; presentado una reflexión sobre la necesidad de que los determinantes de la salud sean incorporados al análisis geográfico, médico y social de la malnutrición. Específicamente, se realiza un estudio epidemiológico para identificar las relaciones que puedan establecerse entre la distribución espacial de la prevalencia de obesidad infantil en Aragón y algunos determinantes de la salud, derivado de un proyecto de investigación aprobado por el Comité de Ética de la Investigación de la Comunidad Autónoma de Aragón (CEICA) en 2017 dirigido por la pediatra Rosa Mª Macipe Costa. Para ello se construye una base de datos que incluye el índice de prevalencia en obesidad infantil en Aragón en el año 2015 (variable dependiente) y diversos determinantes de la salud potencialmente relacionados (variables independientes). El estudio se ha realizado a nivel de Zona Básica de Salud, la unidad espacial de referencia de la información sanitaria en España, que incluye múltiples escalas. La estimación de la asociación entre las variables se apoya en técnicas de estadística espacial como la Geographically Weighted Logistic Regression (GWLR). Se trata de un conjunto de técnicas que, al incorporar la dimensión espacial de los fenómenos estudiados, permiten estimar variaciones locales en la asociación entre una variable dependiente y las variables explicativas. Los resultados se han analizado poniendo especial atención en la obtención de productos cartográficos como vía sintética y eficiente para la interpretación de los resultados

Evaluación del modelo cronourbanista de la “Ciudad de los 15 minutos” en Zaragoza.

Desde mediados del siglo anterior, el proceso de urbanización ha crecido considerablemente en todo el mundo. El desarrollo de muchas ciudades se ha guiado bajo las líneas del urbanismo del petróleo, aquel que ha creado urbes para el vehículo rodado, olvidando al principal sujeto que la habita, el humano. La actual crisis climática y sanitaria a la que se enfrenta este siglo XXI pone en entredicho el sistema urbano prestablecido. Por ello, al igual que en otras épocas en las que se han diseñado nuevas ideas de planificación urbana, en la actualidad existen programas internaciones como los ODS o la Nueva Agenda Urbana con los que se fijan metas e iniciativas para alcanzarlas.En este contexto, nace en París el concepto de “Ciudad de 15 minutos”, postulada como modelo urbano con el que resolver las problemáticas económicas, ambientales y sociales de nuestro tiempo. El presente trabajo estudia la situación de Zaragoza respecto a este modelocronourbanista, analizando tres de sus principios fundamentales: la ciudad debe ser compacta al mismo tiempo que presenta una complejidad elevada y ser accesible haciendo uso de la movilidad activa; además de valorar iniciativas de participación ciudadana. La creación de un nuevo índice que asocia estos tres indicadores urbanos junto con la representación cartográfica de los resultados, permite identificar la distribución espacial de este modelo urbano en Zaragoza. Dando a conocer el hecho de que no se trata de una ciudad de 15 minutos en su totalidad, si bien presenta zonas donde sí que se aprecia este modelo. Por tanto, resulta necesario analizar nuestras ciudades para identificar las líneas de acción que debe seguir el urbanismo táctico integral del futuro.<br /

Morphological Variations of Wild Populations of Brycon dentex (Characidae, Teleostei) in the Guayas Hydrographic Basin (Ecuador). The Impact of Fishing Policies and Environmental Conditions

The Guayas, located in Ecuador, is the largest basin in the Pacific Ocean and has an inventory of 123 native freshwater species. Most of these are endemic species that are threatened or at-risk due to anthropogenic activity and the modification, fragmentation, and destruction of habitats. The aim of this study was to determine the morphometric variation in three wild populations of Brycon dentex in the Guayas basin rivers and their connections to fishing management and environmental conditions. A total of 200 mature fish were captured, and 26 morphometric parameters were measured. The fishing policies (Hypothesis 1) and environmental conditions (Hypothesis 2) were considered fixed factors and were validated by t-tests. The morphological variation among the three populations (Hypothesis 3) was validated through a discriminant analysis. Fishing policies and resource management were found to generate morphological differences associated with body development. In addition, the environmental conditions were found to influence the size and structure of Brycon dentex populations. The analyzed populations were discriminated by the generated morphometric models, which differentiated Cluster 1 (Quevedo and Mocache rivers) with high fishing pressure from Cluster 2 (Pintado river) with medium–low fishing pressure. Morphometric differentiation by discriminant analysis is a direct and economic methodology that can be applied as an indicator of diversity maintenance

Spatial patterns in sociodemographic factors explain to a large extent the prevalence of hypertension and diabetes in Aragon (Spain)

IntroductionThe global burden of multi-morbidity has become a major public health challenge due to the multi stakeholder action required to its prevention and control. The Social Determinants of Health approach is the basis for the establishment of health as a cross-cutting element of public policies toward enhanced and more efficient decision making for prevention and management.ObjectiveTo identify spatially varying relationships between the multi-morbidity of hypertension and diabetes and the sociodemographic settings (2015–2019) in Aragon (a mediterranean region of Northeastern Spain) from an ecological perspective.Materials and methodsFirst, we compiled data on the prevalence of hypertension, diabetes, and sociodemographic variables to build a spatial geodatabase. Then, a Principal Component Analysis (PCA) was performed to derive regression variables, i.e., aggregating prevalence rates into a multi-morbidity component (stratified by sex) and sociodemographic covariate into a reduced but meaningful number of factors. Finally, we applied Geographically Weighted Regression (GWR) and cartographic design techniques to investigate the spatial variability of the relationships between multi-morbidity and sociodemographic variables.ResultsThe GWR models revealed spatial explicit relationships with large heterogeneity. The sociodemographic environment participates in the explanation of the spatial behavior of multi-morbidity, reaching maximum local explained variance (R2) of 0.76 in men and 0.91 in women. The spatial gradient in the strength of the observed relationships was sharper in models addressing men’s prevalence, while women’s models attained more consistent and higher explanatory performance.ConclusionModeling the prevalence of chronic diseases using GWR enables to identify specific areas in which the sociodemographic environment is explicitly manifested as a driving factor of multi-morbidity. This is step forward in supporting decision making as it highlights multi-scale contexts of vulnerability, hence allowing specific action suitable to the setting to be taken

Socio-Economic Development and Mental Health: Case Study of the Spanish Region of Aragon (2010–20)

IntroductionConsidering health as a cross-cutting element of all public policies leads to rethinking its interactions with the environment in which people live. The collection of large volumes of data by public administrations offers the opportunity to monitor and analyze the possible associations between health and territory. The increase in the incidence and prevalence of mental health diseases, particularly depression, justifies the need to develop studies that seek to identify links with the socioeconomic and environmental setting.ObjectiveThe objective of this study is to explain the behavior of the depression in a mediterranean region of Northeastern Spain from an ecological and diachronic perspective.MethodsWe conducted a correlation and multivariate logistic regression analysis to identify explanatory factors of the prevalence of depression in 2010 and 2020 and in the variation rate. Potential explanatory factors are related to the socioeconomic status and to the territorial development level.ResultsThe regression models retained both socioeconomic and territorial development variables as predictors of the prevalence in both years and in the variation rate. Rural areas seem to play a protective role against the prevalence.ConclusionIt is under the territorial prism that epidemiological studies could offer useful guidelines for proactive decision-making. The integration of data on diseases and territory must be considered when developing policies for the creation of healthier environments and for directing health services with more specific resources to where they may be needed

Usefulness of Discriminant Analysis in the Morphometric Differentiation of Six Native Freshwater Species from Ecuador

The aim of this research was to find out the morphometric differentiation of six native freshwater species in the Guayas Hydrographic Basin (Ecuador) by means of discriminant analysis. A total of 1355 mature fishes (Cichlasoma festae, Andinoacara rivulatus, Dormitator latifrons, Bryncon dentex, Hoplias microlepis and Leporinus ecuadorensis) were captured and 27 morphometric measurements and 20 landmarks were used. Two-way analysis of variance with species and sex as fixed factors and discriminant analysis were applied. The selection of the most discriminant variables was made applying the F of Snedecor, Wilks’-Lambda and the 1-Tolerance. While sex within species had no significant effect on the morphology, differences among species were significant. Twenty-seven morphological variables showed highly significant differences among six native freshwater species. Nine biometric variables with high discriminant power were selected. The six species analyzed were discriminated by the morphometric models generated, thus showing that discriminant analysis was useful for differentiating species. The morphometric differentiation by discriminant analysis is a direct, simple and economic methodology to be applied in situ in rural communities. It favors the implementation of a livestock development program and it could be used with other native freshwater species in the Guayas Hydrographic Basin