Using geo-demographic
segmentation tools to help
inform health insight
planning
Simon Orange, Public Health
Information Analyst
Yorkshire and Humber Public Health
Observatory, spo500@york.ac.uk
01904 328225
Segmentation
• A process of looking at the audience or
‘market’ and seeking to identify distinct subgroups (segments) that may have similar
needs, attitudes or behaviours.
• The aim of any segmentation should be to
define a small number of groups so that:
– all members of a particular group are as similar to
each other as possible
– they are as different from the other groups as
possible
“Promoting and delivering public health intelligence”
Types of Segmentation
Demographic -
Divides people into groups based on
variables such as age, gender, race.
Geographic -
Divides people into groups based on
different geographical units such as
regions.
Geo-demographic -
Combines demographics and geography
into a segmentation. Identify groups of
small geographic areas that have similar
demographic profiles.
Behavioural -
Divides people into groups based on the
way they respond to, use, or know of a
product or service.
“Promoting and delivering public health intelligence”
Geodemographics
• Geodemographics has been defined as the
‘analysis of people by where they live’.
• Use of geography to help us draw general
conclusions about the characteristics and
behaviours of the people who live in them.
• Similar people live in similar places, do
similar things and have similar lifestyles ‘birds
of a feather flock together’.
“Promoting and delivering public health intelligence”
Geodemographic Segmentation
Charles Booth’s 1898-99 Poverty
Map of London
Webber and Craig (1976 & 78)
• Office of Population Censuses and Surveys
(OPCS) commissioned three classifications based
on the 1971 census.
• Key variables used included unemployment,
students, two car households, industry sector,
social class, age, migration, tenure, overseas
immigration, overcrowding and household
amenities
• Commercial sector saw potential benefits of area
classification. The British Market Research Bureau
(BMRB) restructured Webbers classification and
renamed it ‘A Classification of Residential
Neighbourhoods’ (ACORN).
http://booth.lse.ac.uk/
http://www.geog.leeds.ac.uk/people/old/d.vickers/d.vick
ers_thesis_c2.pdf
“Promoting and delivering public health intelligence”
Tool Creation
% of variance explained
V1
Variables
are chosen
and refined
100%
Data is
standardised
Clusters are
created
80%
60%
40%
20%
Clusters
are
are Number of
0% Clusters
named and
clusters are
named and profiled
25 30 35
profiled 5 10 15 20
chosen
Cluster numbers V2
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Tools Available
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Segmentation Profiles
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Example of Profiling cervical screening for
Yorkshire and the Humber:
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Example of Profiling cervical screening for Bradford:
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Segmentation Profiles
All Leeds Deliveries
Under 18 Leeds Deliveries
Baseline
Target Profile
Profile
Struggling
families
Struggling
families
Secure
Families
Burdened
Singles
Source: HES data
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Mapping
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Health Intelligence Practice Profiles
Logarithmic Scale - % Population within Categories
Health ACORN
1.1
4.6
100%
Top Category: 4.6
1.2
4.5
4.4
10%
0%
0.1%
31% of the practice population.
Affluent towns and villages with
excellent health and diet
1.4
4.3
1%
0.1%
1.3
1.5
4.2
1.6
4.1
1.7
2nd Category: 4.4
3.6
1.8
3.5
16.4% of the practice population.
Towns and villages with average
health and diet
2.1
1%
3.4
2.2
10%
3.3
100%
2.3
3.2
3.1
B84004
B84004
B84004Hebden
Hebden
HebdenBridge
Bridge
BridgeGroup
Group
GroupPractice
Practice
Practice
2.5
2.4
Calderdale
Calderdale
Calderdale
England
England
England
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Source: CACI Ltd 2007
www.caci.co.uk
Identifying areas with excess
expected prevalence/incidence
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Comparison
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How do they add value?
•
Population health profiling:
–
–
•
•
Targeting health interventions by identifying areas with
excess expected prevalence/incidence etc.
Measurement of health inequalities by:
–
–
•
•
•
Understanding the characteristics of small geographical areas.
Mapping and visualisation.
Explaining variation in health determinants, outcomes or services.
Providing a more granular measure of health inequality.
Social marketing and communications
Support data linkage, and non-disclosable data sharing.
As a base for generating additional insight - on top of the
off-the-shelf descriptions.
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What geodemographics can not tell us.
•
Birds of a feather may not always flock together
•
Census 2001 data dependent
•
Analysis of the profiles is usually based on probabilities, rather
than hard data.
•
Not really intended to be used as a trend monitoring tool.
Cannot quickly detect change
•
Geodemographics in themselves do not provide the answer.
They are simply one of a range of tools and approaches that
can be used to generate insight and health intelligence to
support social marketing decisions.
“Promoting and delivering public health intelligence”
Simon Orange, Public Health
Information Analyst
Yorkshire and Humber Public Health
Observatory, spo500@york.ac.uk
01904 328225