Estudio de prevalencia de asma en población general en España

Blanco-Aparicio, M.; García-Río, F.; González-Barcala, FJ.; Jiménez-Ruiz, CA.; Muñoz, X.; Plaza, V.; Soto-Campos, JG.; Urrutia-Landa, I.; Almonacid, C.; Peces-Barba, G.; Álvarez-Gutiérrez, FJ.

doi:10.1016/j.opresp.2023.100245

Cited by 1 publication

(2 citation statements)

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“…The prevalence of physician-diagnosed asthma in Aragon ranged from 3.1 to 9.7 cases per hundred, thus showing large differences over the study area. These differences were also observed in other studies in other geographical contexts (Antó et al, 1996;To et al, 2012;Blanco-Aparicio et al, 2023), supporting the existence of spatial differences in the impact of asthma and its underlying determinants. Spatially explicit analyses are therefore recommended, as we continue to demonstrate in this study.…”

Section: Discussionsupporting

confidence: 85%

“…The clinical asthma rates in adults aged 18-45 years vary between 1% (Vietnam), 1.4% (China and Bosnia-Herzegovina), 20.2% (Sweden), and 21.5% (Australia) (To et al, 2012). The adult prevalence in Spain varies between 1.5% and 16.7% (Plaza Moral et al, 2016), with a remarkable geographical variability, varying, depending on the territory surveyed from 1 (Huelva) to 4.7 percentage points (Albacete) (Antó et al, 1996;Blanco-Aparicio et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

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Spatial Patterns in the Association between the Prevalence of Asthma and Determinants of Health

Bentué‐Martínez,

Rodrigues,

Llorente González

et al. 2023

Geographical Analysis

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The World Health Organization endorses the study of diseases from the perspective of the Determinants of Health (DH), that is, the circumstances in which people are born and raised, the environment in which they grow up and age and their lifestyle. The aim of this study is to analyze the spatial behavior of the prevalence of asthma in Aragon, a Mediterranean region in Spain, under the DH approach. The methodological process entailed building a spatial database collating asthma prevalence as dependent variable, and lifestyle, socioeconomic, and climate indicators as explanatory factors, and then evaluating the spatial variability of the relationships by combining the Principal Component Analysis (PCA), Multiscale Geographically Weighted Regression (MGWR) models and cartographic design techniques. MGWR evidenced spatially varying relationships operating at different scales. Lifestyles seem closely tied to the prevalence of asthma in most of the study area while urban functionality and local climate patterns seem to boost prevalence rates in some specific enclaves. Consequently, the social and environmental conditions that characterize the study area translate into several DH scenarios modulating the spatial distribution of asthma. This differential DH behavior detected by local regression models is relevant to guiding and refining public health decision‐making.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%