Lecture 10: Medical Cartography Spatial Analysis Overview

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Lecture 10 Medical Cartography / Spatial
AnalysisOverview

• DEGENERATIVE DISEASES
• Importance Of Degenerative Diseases
• Underlying Rationale Of Spatial Analysis
• MEDICAL CARTOGRAPHY
• SPATIAL ANALYTICAL METHODOLOGY
• Significance
• Indices
• Indicators of Significance
• EXAMPLES

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Degenerative Diseases

• Following the decline in infectious diseases, the
  three major degenerative diseases (heart disease,
  cancer and stroke) account for 2/3 of all deaths.
  Many of the remaining 1/3 are triggered by
  degenerative complaints.
• The key questions are
• Are the disparities between areas in disease
  rates simply due to chance or caused by
  something?
• If they are caused by something, can we identify
  what the something is?
• Having identified a cause, can we do anything to
  prevent it?
• The first question involves mapping diseases and
  testing for statistical significance.

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Medical Cartography (1)

• The basic principles can be demonstrated using
  historical examples of cholera maps from the
  mid-19th century.
• Augustus Peterman (1852). Dots are used to locate
  cases at national level. Main points are ports as
  points of entry and the importance of rivers.
• Rabert Baker (1833). One of earliest maps.
  Cholera areas in Leeds were shaded in,
  highlighting the north-east quadrant.
• Thomas Shapter (1849). Dots were used to identify
  cases. The southern quadrant close to the river
  is highlighted.

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Medical Cartography (2)

• Henry Wentworth Acland (1856). Dots were used to
  identify cases in Oxford. However, Acland also
  drew maps of other features, including altitude
  and undrained areas. The maps can be compared in
  much the same way as they would be in a modern
  GIS.
• John Snow (1855). Snows famous map showed the
  cluster of cases around the water pump in Broad
  Street in Soho which resulted in 500 deaths in 10
  days. Once the pump was disabled, the epidemic
  receded almost immediately demonstrating that
  cholera was somehow linked with the water supply.

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Spatial Analytical Methodology

• Meaning of significance. Unlikely to have
  occurred by chance, therefore something must be
  causing it.
• Indices. Crude death rates / crude morbidity
  rates can be very misleading. Need to calculate
  age specific or age standardised rates.
• Indications of spatial significance extreme
  variations between areas spatial autocorrelation
  (clustering) temporal consistency.
• Hypothesis testing. If the distributions of a
  disease is found to be significant, then the
  objective is to identify possible causes i.e.
  factors having a similar spatial distribution.

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Regional Variations (UK)

• There is a marked difference in mortality rates
  between the south-east (low) and the north and
  west (high).
• Mortality rates tend to reflect affluence.
• Urban areas have higher mortality than rural
  areas.
• These patterns have not changed much over the
  past 100 years.
• The death rates translate into a difference of
  approximately 4 years in life expectancy.

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Males
Females
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Life expectancies at birth
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Regional Variations In Ireland

• Mortality rates are higher in urban areas (and
  urbanised counties).
• The regional pattern in Ireland was unusual in
  the 1970s because the more deprived regions
  tended to have lower mortality rates.
• The regional anomalies appear to be breaking down
  in the 1990s.

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Intra-Urban Variations

• Comparatively little is known about intra-urban
  variations in Ireland.
• 1980s data suggest that mortality from heart
  disease, cancer and respiratory diseases tended
  to be highest in working class suburbs.
• Deaths from cerebrovascular disease tended to be
  highest in inner city areas.

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