Geography and Geographical Analysis using the ONS Longitudinal Study

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Geography and Geographical Analysis using the ONS
Longitudinal Study
Christopher Marshall Julian Buxton CeLSIUS
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Aims of the Presentation

• What is the ONS LS and what data does it contain?
• What geographical information is in the LS and at
  what level?
• What does this allow us to do?
• The strengths and weaknesses of using
  geographical data in the LS.
• Examples of using geographical data in the LS.
• The Role of CeLSIUS (Centre for Longitudinal
  Study Information and User Support).

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The ONS Longitudinal Study

• Census data for individuals with one of four
  birthdates enumerated at the 1971 Census (c. 1
  of population)
• Maintained through addition of immigrants and new
  births with LS birth date
• Information from later censuses (1981, 91 2001)
  added and linked to that already there.
• Event data including deaths of LS members, cancer
  registrations, death of spouse, births to female
  members, and now, under test, the Claimant Count
  Cohort.

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Study Structure
1971 Original sample 530,000 selected from
1971 Census
1981 536,000 sample members found at 1981 Census
1991 543,000 sample members found at 1991 Census
2001 545,894 sample members found at 2001 Census
Plus members of household
Plus members of household
Plus members of household
Plus members of household
1. Census. High N. 2. Linking 3.
Non-members 4. Entrance Termination 5.
Events
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Geographical Location of LS Members From Census
Information

• Based on Address of Usual Residence on Census Day
• Visitors flagged prior to 2001 and usually
  excluded from studies
• Fully coded to the Administrative boundaries and
  also to Health boundaries (e.g. Regional Health
  Authority)

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Main Time Points Available

• 1970 from address 1 year ago in 1971
• Census day 1971 (25th/26th April)
• 1980 from address 1 year ago in 1981
• Census day 1981 (5th/6th April)
• 1990 from address 1 year ago in 1991
• Census day 1991 (21st/22nd April)
• 2000 from address 1 year ago in 2001
• Census day 2001 (29th/30th April)
• Also possible 1966 from address 5 years ago 1971
• 1939 (in theory)

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LS Geography (England Wales) 1971 - 2005
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What does this allow us to do?

• Migration
• Mobility Geographical Social Categories
• Use existing definitions
• Create new analytical definitions
• Attach and analyse ecological data
• Create new geographies
• Analyse specific areas

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Social and Geographical Mobility
1971 - Living in NE Social Class Skilled
Non-Manual Tenure Social Housing 2001 - Living
in SE Social Class Managerial Tenure Owner
Occupier
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Geographical Migration Patterns
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Use of existing definitions - Geographical

• Continuity for 30 years at 1974 geography despite
  changing boundaries.
• Standard Region / Government Office Region
• 2001 can be mapped to preceding years and look-up
  tables can bring earlier geographies forward to
  2001
• County and County Districts can be treated
  similarly.

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Use of existing definitions Geographical (2)

• Administrative boundaries
• Environmental boundaries
• Ecological Deprivation Indices
• Area Classifications (Urban / Rural)
• Population densities
• Small area statistics (Aggregate level variables)

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Create new definitions - Geographical

• Urban Rural
• Travel to Work
• Craig Webber
• Other valid divisions

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Create new definitions Socio-economic

• Social Class by Sex
• Social Class by Age Group
• Working Status Age Group
• Social Class by Tenure

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Attach ecological or social data
Any data can be attached to individual LS members
if it is produced in the form of a look-up table
with a valid geographical reference code (e.g.
Ward, County District) attached. Air pollution
indicators Average rainfall in 10
years Ecological Deprivation indices
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Create new geographies
It could be that for your specific purpose the
Geographies within the LS are inappropriate. Defin
e the geography you want based on LS wards or
county districts and this can be attached to LS
members and used for analysis. e.g. We have
regions but you want to divide each into two or
three separate areas not wholly based on counties.
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Look at specific areas
The purpose of your analysis is to look only at a
specific area of the country and compare it with
one or two others. Depending on parameters chosen
the analysis can run into disclosure control
restrictions keep the analysis simple with a
limited number of parameters. Analysis at Ward
level or below would require aggregation of
results, while at county district level, outputs
do not usually require aggregation.
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Strengths of geographical data in the LS

• Consistency over time 1971, 1981, 1991 all
  coded to same base (1974 geography). 2001 can be
  produced on the same base down to county district
  level with confidence fairly easily.
• If necessary earlier data can be brought forward
  to 2001 by the use of look-up tables.

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Strengths of geographical data in the LS

• 30 years of continuous follow-up of individuals
• 9 Time points (1966 2001)
• Consistency of geography through this time period.

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Strengths of geographical data in the LS

• Flexibility of study design
• Individual and Area data
• Can add data using geographical identifiers (e.g.
  Carstairs deciles)
• High level of detail available for later data.

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Weaknesses of geographical data in the LS

• While County and County District Codes have
  remained fairly consistent the Ward codes needed
  to attach additional data have changed
  significantly over time.
• Data are for England and Wales only
• Members who move to Scotland classed as
  embarkations (migrants)

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Weaknesses of geographical data in the LS

• Data codings and data detail not consistent.
• It is not possible to back transfer all
  geographies.
• Ward code history many changes and
  manipulations lay traps for the unwary.

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Scotland Members in 1971 found with a Scottish
NHS number were incorporated into the LS. Events
to LS members (e.g. deaths) that occur in
Scotland are traced and do get linked to LS
members. LS members who migrate to Scotland are
treated as Emigrants and this is recorded in the
LS. Earlier data remain within the LS.
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Disclosure Control Rules
Researchers should design their projects such
that it would never be possible to identify an
individual from the output data generated
(Population uniques). Output cell counts of 1 or
2 are considered potentially disclosive (although
most 2s will be released to users), and for
publication purposes some aggregation of data
would be required. Exposure times for single
events are a considered a risk and have to be
disguised.
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Disclosure Control Rules
Tables containing data with a mix of any of the
following types of variable will be examined more
scrupulously Occupation Country of
birth Industry Ethnicity Cause of Death Higher
education levels Sub regional geographical fields
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Examples of Using LS Geography within a project

• Do people move out of London when they retire?
• Have people moved from Urban to Rural areas
  between 1991 and 2001?

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Research Question
1. Do people move out of London when they retire?
Main Study Population LS members present at 1991
2001, Males 55-65 in 1991 Females 50-60 in
1991 All resident within Greater London in 1991
from county code 1991
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1. Do people move out of London when they retire?
GOR of residence in 2001 by Sex for those living
in London in 1991
Source ONS Longitudinal Study
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Research Question
2. Has the population distribution between Urban
and Rural areas changed between 1991 and 2001?
Main Study Population LS members present at
1991 2001 Age 16 - 55 in 1991 Report resident
in Urban / Rural Ward classification in 1991 and
in 2001 using 1974 boundaries.
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2. Distribution of Urban / Rural residency
between 1991 and 2001.
Area of residence 1991 v Area of residence 2001
Source ONS Longitudinal Study
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The Role of CeLSIUS (Centre for Longitudinal
Study Information and User Support)

• An interface between academics and the Office for
  National Statistics.
• Provide - through our Web site - information on
• The structure of the ONS LS.
• How to decide if it is for you.
• Training modules to assist your understanding of
  the data and how it can be manipulated.
• All the documents needed to apply for permission
  to use the ONS LS and access to the LS datasets.

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• The CeLSIUS training modules
• Socio-economic indicators
• LS Outputs
• Households and families
• Defining a study population
• Ethnicity
• Geography NEW just released

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www.celsius.lshtm.ac.uk
A Free service for UK academic users General
enquiries celsius_at_lshtm.ac.uk 020 7299
4634 Emily Grundy Andy Sloggett Lynda
Clarke Julian Buxton Christopher Marshall Jo
Tomlinson