Cover Image

Geographically weighted regression for modelling the accessibility to the public hospital network in Concepción Metropolitan Area, Chile

Marcela Martínez Bascuñán, Carolina Rojas Quezada
  • Marcela Martínez Bascuñán
    Centre for Urban Sustainable Development, University of Concepción, Chile
  • Carolina Rojas Quezada
    Centre for Urban Sustainable Development, University of Concepción; Department of Geography, University of Concepción, Concepción, Chile | crojasq@udec.cl

Abstract

Accessibility models in transport geography based on geographic information systems have proven to be an effective method in determining spatial inequalities associated with public health. This work aims to model the spatial accessibility from populated areas within the Concepción metropolitan area (CMA), the second largest city in Chile. The city’s public hospital network is taken into consideration with special reference to socio-regional inequalities. The use of geographically weighted regression (GWR) and ordinary least squares (OLS) for modelling accessibility with socioeconomic and transport variables is proposed. The explanatory variables investigated are: illiterate population, rural housing, alternative housing, homes with a motorised vehicle, public transport routes, and connectivity. Our results identify that approximately 4.1% of the population have unfavourable or very unfavourable accessibility to public hospitals, which correspond to rural areas located south of CMA. Application of a local GWR model (0.87 R2 adjusted) helped to improve the settings over the use of traditional OLS methods (multiple regression) (0.67 R2 adjusted) and to find the spatial distribution of both coefficients of the explanatory variables, demonstrating the local significance of the model. Thus, accessibility studies have enormous potential to contribute to the development of public health and transport policies in turn to achieve equality in spatial accessibility to specialised health care.

Keywords

Accessibility; Spatial equity; Hospital facility; Geographically weighted regression; Chile

Full Text:

PDF
HTML
Submitted: 2016-01-13 15:30:56
Published: 2016-11-22 14:11:52
Search for citations in Google Scholar
Related articles: Google Scholar
Abstract views:
1285

Views:
PDF
502
HTML
1026

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM


Copyright (c) 2016 Marcela Loreto Martínez, Carolina Alejandra Rojas

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
 
© PAGEPress 2008-2017     -     PAGEPress is a registered trademark property of PAGEPress srl, Italy.     -     VAT: IT02125780185