Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach
Geographical accessibility is an important determinant for the utilisation of community pharmacies. The present study explored patterns of spatial accessibility with respect to pharmacies in Liguria, Italy, a region with particular geographical and demographic features. Municipal density of pharmaci...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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PAGEPress Publications
2016-11-01
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| Series: | Geospatial Health |
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| Online Access: | http://www.geospatialhealth.net/index.php/gh/article/view/457 |
| _version_ | 1811295313430839296 |
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| author | Alexander Domnich Lucia Arata Daniela Amicizia Alessio Signori Roberto Gasparini Donatella Panatto |
| author_facet | Alexander Domnich Lucia Arata Daniela Amicizia Alessio Signori Roberto Gasparini Donatella Panatto |
| author_sort | Alexander Domnich |
| collection | DOAJ |
| description | Geographical accessibility is an important determinant for the utilisation of community pharmacies. The present study explored patterns of spatial accessibility with respect to pharmacies in Liguria, Italy, a region with particular geographical and demographic features. Municipal density of pharmacies was proxied as the number of pharmacies per capita and per km2, and spatial autocorrelation analysis was performed to identify spatial clusters. Both non-spatial and spatial models were constructed to predict the study outcome. Spatial autocorrelation analysis showed a highly significant clustered pattern in the density of pharmacies per capita (<em>I</em>=0.082) and per km<sup>2</sup> (<em>I</em>=0.295). Potentially under-supplied areas were mostly located in the mountainous hinterland. Ordinary least-squares (OLS) regressions established a significant positive relationship between the density of pharmacies and income among municipalities located at high altitudes, while no such association was observed in lower-lying areas. However, residuals of the OLS models were spatially auto-correlated. The best-fitting mixed geographically weighted regression (GWR) models outperformed the corresponding OLS models. Pharmacies per capita were best predicted by two local predictors (altitude and proportion of immigrants) and two global ones (proportion of elderly residents and income), while the local terms <em>population</em>, <em>mean altitude</em> and <em>rural status</em> and the global term income functioned as independent variables predicting pharmacies per km<sup>2</sup>. The density of pharmacies in Liguria was found to be associated with both socio-economic and landscape factors. Mapping of mixed GWR results would be helpful to policy-makers. |
| first_indexed | 2024-04-13T05:30:28Z |
| format | Article |
| id | doaj.art-a88fd5b87cd34c1eba6659e54e19a96e |
| institution | Directory Open Access Journal |
| issn | 1827-1987 1970-7096 |
| language | English |
| last_indexed | 2024-04-13T05:30:28Z |
| publishDate | 2016-11-01 |
| publisher | PAGEPress Publications |
| record_format | Article |
| series | Geospatial Health |
| spelling | doaj.art-a88fd5b87cd34c1eba6659e54e19a96e2022-12-22T03:00:27ZengPAGEPress PublicationsGeospatial Health1827-19871970-70962016-11-0111310.4081/gh.2016.457387Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approachAlexander Domnich0Lucia Arata1Daniela Amicizia2Alessio Signori3Roberto Gasparini4Donatella Panatto5Department of Health Sciences, University of GenoaDepartment of Health Sciences, University of GenoaDepartment of Health Sciences, University of GenoaDepartment of Health Sciences, University of GenoaDepartment of Health Sciences, University of GenoaDepartment of Health Sciences, University of GenoaGeographical accessibility is an important determinant for the utilisation of community pharmacies. The present study explored patterns of spatial accessibility with respect to pharmacies in Liguria, Italy, a region with particular geographical and demographic features. Municipal density of pharmacies was proxied as the number of pharmacies per capita and per km2, and spatial autocorrelation analysis was performed to identify spatial clusters. Both non-spatial and spatial models were constructed to predict the study outcome. Spatial autocorrelation analysis showed a highly significant clustered pattern in the density of pharmacies per capita (<em>I</em>=0.082) and per km<sup>2</sup> (<em>I</em>=0.295). Potentially under-supplied areas were mostly located in the mountainous hinterland. Ordinary least-squares (OLS) regressions established a significant positive relationship between the density of pharmacies and income among municipalities located at high altitudes, while no such association was observed in lower-lying areas. However, residuals of the OLS models were spatially auto-correlated. The best-fitting mixed geographically weighted regression (GWR) models outperformed the corresponding OLS models. Pharmacies per capita were best predicted by two local predictors (altitude and proportion of immigrants) and two global ones (proportion of elderly residents and income), while the local terms <em>population</em>, <em>mean altitude</em> and <em>rural status</em> and the global term income functioned as independent variables predicting pharmacies per km<sup>2</sup>. The density of pharmacies in Liguria was found to be associated with both socio-economic and landscape factors. Mapping of mixed GWR results would be helpful to policy-makers.http://www.geospatialhealth.net/index.php/gh/article/view/457Community pharmaciesGeographical accessibilityAccess inequalitiesGeographically weighted regression |
| spellingShingle | Alexander Domnich Lucia Arata Daniela Amicizia Alessio Signori Roberto Gasparini Donatella Panatto Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach Geospatial Health Community pharmacies Geographical accessibility Access inequalities Geographically weighted regression |
| title | Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach |
| title_full | Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach |
| title_fullStr | Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach |
| title_full_unstemmed | Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach |
| title_short | Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach |
| title_sort | assessing spatial inequalities in accessing community pharmacies a mixed geographically weighted approach |
| topic | Community pharmacies Geographical accessibility Access inequalities Geographically weighted regression |
| url | http://www.geospatialhealth.net/index.php/gh/article/view/457 |
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