Developing Geographical
Information Systems In A Cohort
Study
Andy Boyd
ALSPAC, Social Medicine
University of Bristol
Geographical Data Matching
- the ALSPAC resource • Overview of our data, the issues involve and our plan for the
future
• Time for questions
• Time for discussion on how other studies have developed
their GIS data resource
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Defining GIS
GIS combine mapping and a record of
location with database technology. This
can be used in the storage, analysis,
management or presentation of data.
E.W.Gilbert‘s1955 version of John Snow’s 1855 Soho Cholera Outbreak Map
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Scope of this presentation
• Not about GIS tools
• Not about GIS analysis or techniques
• It is about the capture and storage of
data in an accessible manner to allow
future GIS analysis
• Uses ALSPAC as an example
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The ALSPAC GIS dataset
• Geographic identifiers collected directly from the cohort
• Data collected via external data sources
• Geographical data linkage
• Precision of geographic variables – accuracy
• Precision of geographic variables – ethics
• Providing the data as an integral part of the resource
• Current data availability
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ALSPAC administered data collection
Residential Address (~50000 address points)
• updated from cohort (self reported)
• team who tracks lost cases
• email
• second contacts
• database searches (osis, electoral roll)
School the young person attends / wishes to attend
• via questionnaire (ALSPAC questionnaires/assessments
administered in schools, primary to secondary transition questionnaire)
• clinic attendance interview
• collected from the school
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Linkage to external data sources
Validation / Cleaning
• Validation and cleaning of self reported data using data collected
via record linkage (NSTS – NHS Tracing, NPD – National Pupil
DB, Royal Mail/OS products)
Missing Data
• Enhancing the resource through record
linkage
Data collection via geographical identifiers
• Accessing existing data organised
around geographical IDs (census
data,neighbourhood data)
• Primary data collection (distance to
overhead power lines, air quality,
commuting, school selection)
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Data Collection through Record Linkage
• Office National Statistics (ONS) Tracing
• Health Authority
• Embarkation
• NSTS (NHS Strategic Tracing Service)
• Address registered with GP
• National Pupil Database (DCSF, DIUS*, UCAS*)
• School Address
• Pupil Residential Address
• DWP*
• Home Office*
* Linkage currently being investigated
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G.I.S – ALSPAC Resource
• ~50,000 ALSPAC residential address points, associated with a
date range which can then be linked to ALSPAC data collection
• Schools attendance data from NPD ~17000
• Schools attendance data from ALSPAC collection ~ 10000
The geographic relation between household
income and polluting factories – FoE 1999
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G.I.S Precision
• Spatial data held at many geographic levels
• Geographies range in scale from 0.1 meters to regional/national
data
• Tied together via address, postcode or grid reference as central
ID
• Key resources include:
– NSPD ( was All Fields Postcode Directory) - geo linking
database
– Deprivation & Socio Economic indices (IMD, Townsend,
Acorn)
– Census data
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G.I.S – How we link cases to data
•
•
•
•
Master file of Postcodes (NSPD)
Postcodes linked to grid reference
Grid references of various scales
PCs/GridRef mapped to:
– Electoral geographies
– Census geographies
• Ethics:
– We don’t generally identify
residence at PC or equivalent level
Ordinance Survey – The National Grid
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G.I.S – How we link geographies
Current Situation
• Use Postcode / postcode centroid grid reference as our highest
precision variable
• Link geographies using NSPD/AFPD appropriate to the measure
required
Proposed Method
• Use property reference number (UPRN) / property centroid grid
reference as highest precision variable
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G.I.S Problems
• Shifting geographies across time points
• Royal Mail change postcode areas (and therefore postcode
centroids)
• Postcodes are ‘recycled’
• Postcode not precise enough in some cases
• Postcode boundaries are not contiguous with other geographic
boundaries
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Accuracy issues with analysis at postcode
level
Address level
Postcode level
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Accuracy issues with analysis at postcode
level
Address level
Postcode level
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Accuracy issues with analysis at postcode
level
Address level
Postcode level
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Linkage problems with the cohort data
• Missing data
– Especially problematic for the cases who
didn’t enrol in the original recruitment
– Gaps in the address data
– Move date often date we were informed
not the actual move date
• However…
– ONS matched 99.7% mothers, so we have
their old & new NHS numbers and cleaned
data (original recruitment cases only)
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GIS Data Availability
• Collected as administrative resource
• Not yet cleaned, documented and
presented to usual ALSPAC standards
• Initiatives under way to validate and fill
gaps in record
• Schools GIS data in the main not
processed
• Aim to build into standard ALSPAC
resource
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GIS Ethics
• Postcode level or greater accuracy treated as
a personal identifier
• Research proposals to use these data need
ALSPAC Law & Ethics Approval
• Broader geographical data can be released in
normal manner
• A two-stage process is used to collect and
process precise data
• Data collected via linkage not available for all
cases due to ethical decisions
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GIS Data Access
Step 1 – Postcodes (or full address) provided to
researcher with unique collection ID with no
other data attached
Step 2 – Researcher attaches their data and
returns file to ALSPAC
Step 3 – ID converted to the appropriate
collaborator ID, postcode data removed
Step 4 – Requested ALSPAC data added to the
file and data sent to the researcher
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Andy Boyd
A.W.Boyd@Bristol.ac.uk