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The changing geography of clinical misery in England: lessons in spatio-temporal data analysis

In: Big Data Applications in Geography and Planning

Author

Listed:
  • Alexis Comber
  • Chris Brunsdon
  • Martin Charlton
  • John Cromby

Abstract

This chapter investigates the changing patterns of clinical Misery (depression, anxiety disorders), through patterns of Antidepressants and Anxiolytics (AD) prescribing rates (prescriptions per person). Misery measured in this way, has increased >40% nationally with greater increases in some areas. Rates were linked to individual deprivation domain scores (housing, crime, employment, etc), which in 2010 were evenly associated with AD prescribing rates. The impacts of austerity policies are evident in the increases in the association of Barriers to Housing and Services and Health, Deprivation and Disability deprivation scores with AD prescribing rates since 2015, and with Employment in 2019. The discussion describes a detailed research agenda for examining Misery, noting the need to shift narratives away from flimsy concepts of Well-being, and number of key rubrics for big data analysis are outlined. In these, the importance of data folding, investigation and visualizations are emphasized - 10km hexbins were used here to summarise annual prescribing rates. These form a key sequence in big data analysis of View -> Identify -> Refine -> Zoom.

Suggested Citation

  • Alexis Comber & Chris Brunsdon & Martin Charlton & John Cromby, 2021. "The changing geography of clinical misery in England: lessons in spatio-temporal data analysis," Chapters, in: Mark Birkin & Graham Clarke & Jonathan Corcoran & Robert Stimson (ed.), Big Data Applications in Geography and Planning, chapter 6, pages 64-78, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:19400_6
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