Abstract

England has some of the largest spatial inequalities in health in Europe – greater, for example, than those that currently exist between the former East and West of Germany (Bambra et al., 2014). People in the North of England are consistently found to be less healthy than those in the South – across all social classes and amongst both men and women (Dorling, 2010). The reasons for this are both compositional and contextual (Macintyre et al., 2002), reflecting uneven economic and social geographies (Dorling, 2010). It is also a long-standing health gap dating back to at least the 19th century (Bambra et al., 2014). It is popular to map these health inequalities using thematic choropleth, cartogram, or topological techniques. Our graphics expand on the latter by visualising the health divide between the North and South of England using some familiar national train journeys. It uses average life expectancy at birth for both women (Figure 1) and men (Figure 2) (data from Public Health England, 2015; reproduced under the Open Government Licence) along the West Coast Mainline (WCM, 300 miles, London Euston to Carlisle), the East Coast Mainline (ECM, 335 miles, London Kings Cross to Berwick), and the Great Western Mainline (GWM, 300 miles, London Paddington to Penzance). The data are georeferenced to each of the main stations along the routes using the relevant Local Authority (e.g. the data for Newark is for Nottinghamshire). Differently sized and coloured circles represent values above (large, green), around (medium, amber), or below (small, red) the English average of 79.4 years for men and 83.1 years for women. The visualisations show very clearly the health divides within a comparatively small country, particularly between the North East and South East regions which have the lowest and highest life expectancies respectively for both men and women. There are gaps of four years for men and five years for women between the best Southern and worst Northern areas. They also demonstrate a socio-spatial gradient with average life expectancy

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