UPDATE –
News from the
LS User Group
ISSN 1465-8828
Issue no. 24
April 2000
__________________________________________________________________
Contents
1
Page
Diary
LS Workshop
2
2
Using the LS for International Research
Report on the 1999 LS User Group meeting
3
2
Technical Issues
Migration between counties among LS members born in the 1930s
4
5
8
LS Publications
LS Working Paper on teenage fertility in England and Wales
14
LS Working Paper on identifying area effects
14
Staff Changes at CLS
14
This newsletter is designed to provide information on the ONS Longitudinal Study (LS) and a forum for
the exchange of users' views and comments. It is produced by the LS User Support Programme at the
Centre for Longitudinal Studies (CLS), Institute of Education. All comments and contributions should be
sent to Rosemary Creeser, LS User Support Programme, Centre for Longitudinal Studies, Institute of
Education, 20 Bedford Way, London WC1H 0AL (tel: 020 7612 6877 email: rc@cls.ioe.ac.uk)
1
1 Diary
This section highlights forthcoming events of interest to LS Users.
If you are arranging an event and wish to publicise it in Update please send details to
Dina Maher, the LS Administrator at CLS.
LS Workshop
On Wednesday 27 th/Thursday 28th September 2000 the LS User Support Programme will be holding a
2-day LS workshop. LS workshops provide detailed information on the ONS Longitudinal Study, and
the methods of analysis and software available to LS researchers. They are also an ideal opportunity to
meet members of the LS Support Team and to discuss the suitability of the LS for exploring specific
research questions. As part of the hands-on element of the workshop participants are able to specify an
analysis of their choice using a small sub-set of variables from the LS.
While LS workshops are open to all, places are limited to ensure that participants get sufficient
individual attention and hands-on experience. A non-refundable fee of £50 (£20 for students) is charged
to cover documentation, lunch and refreshments. For further details and to reserve a place please
contact LS Administrator Dina Maher (tel: 020 7612 6875, email: dm@cls.ioe.ac.uk).
2 Using the LS for international research
Report on the 1999 LS User Group Meeting
On 9th November the Institute of Education hosted the 1999 LS User Group meeting. While countries
around the world were commemorating the tenth anniversary of the end of the Berlin Wall a group of
researchers from Cyprus, Finland, Germany, Norway, Sweden, the United States and the UK were
meeting to consider how the LS may be used for cross-national work. Some of the main points of the
meeting are summarised below.
Copies of several of the papers given at the meeting are also available in .PDF (Portable Document
Format) from the CLS website – http://www.cls.ioe.ac.uk/Ls/user.htm
Introduction to using the LS for international research: Rosemary Creeser, LS User
Support Team, CLS
This session highlighted the opportunities that exist for using the LS for international comparative
research. In addition to national studies based on linked census and mortality data, some countries like
Austria and Israel have data based on one-off census link exercises, while others like Italy have studies
that bring together data for a particular region (e.g. the municipality of Turin).
While many countries in Europe and Scandinavia maintain studies similar to the LS it is important to
remember that national studies have not necessarily been designed to facilitate international
comparative research. Table 1 summarises some of the advantages of the LS for this type of work. One of
the distinctive features of the LS is that data are available in their raw, uncoded form. Consequently,
they are easier to recode to classifications developed to facilitate international comparisons, than data
that have been aggregated or “top coded”.
2
Table 1: Advantages of the LS for international comparative research
“Safe setting”
Data maintained in raw, disaggregated form.
Harmonised variables
Variables derived as part of previous research,
such as work on the “English and French family
in historical perspective” available for future
research.
Data Expertise
Staff at LS User Support Programme (CLS,
Institute of Education) and LS Unit (ONS) are
able to share data expertise and facilitate
access to the LS.
Unfortunately, one of the real obstacles to international comparative research is that few of the countries
with similar datasets are able to offer the high level of user support and access offered by the LS. LS
researchers are able to draw on the CLS and ONS teams’ experience of analysing this complex dataset
and to obtain expert advice on a large number of variables specially derived for international research.
The relationship between fertility and longevity in England and Wales and Austria:
Gabriele Doblhammer, Max Planck Institute for Demographic Research Rostock,
Germany
Gabriele Doblhammer's presentation focused on work she has undertaken using the LS and a linked
dataset based on the 1981 Census returns of 1.3 million Austrian women, between the ages of 40 and 59,
and the death records of 32,234 who died in the following year.
This work seeks to address whether a woman's reproductive history influences her life span. A leading
biological theory of the evolution of ageing suggests that resources have to be directed either towards
maintenance and repair or reproduction.
Issues of comparability and data quality
In international cross-national work it is important to achieve comparability. One of the main variables
investigated in Gabriele's work - the woman's parity - was relatively simple to compare. The recording
of parity in both datasets would have been affected by similar problems - e.g. women may omit to
include children born outside marriage or still-births etc.
By comparison, Gabriele experienced some problems finding comparable data on education - one of the
explanatory variables she considered. While the Austrian dataset included good measures of education,
currently the educational data a vailable in the LS focus exclusively on the "higher" educational
qualifications obtained by less than twenty per cent of the population. (As mentioned in issue 22 of
Update , new proposals for the 2001 Census include collecting information on all of the educational and
vocational qualifications achieved, including GCSE (General Certificate of Secondary Education) and
NVQ (National Vocational Qualifications).)
The Austrian data were linked using date of birth and the municipality code of the last residential
address of the deceased. While 92 per cent of death records were linked, there were some sub-national
differences. The higher linkage rate for rural areas, such as Burgenland (94 per cent), compared with
Vienna (88 per cent) reflect differences in the likelihood of individuals moving into residential care in
the last few years of life. (Those living in rural areas are more likely to be living with their adult children
at both time points.)
3
Results/discussion
This work shows that there is a significant relationship between parity and mortality later in life in both
populations. Childless women and women with higher parities (3+) experience higher mortality risks
than women with one or two children (see Table 2). The Austrian data reveal that women experience
significant excess mortality from the fourth child on.
Table 3 shows that having a teenage birth some years before significantly increases the risk of mortality
later in life in both populations. While the proportion of English/Welsh women who gave birth before
age 20 is only half that of Austrian women, the excess mortality observed in the LS is nearly three times
as high (26 per cent) as in the Austrian dataset (9 per cent). One possible explanation may be that the
negative social circumstances that may have been related to giving birth comparatively early in life were
more severe in England and Wales than in Austria, where the phenomenon is more widespread.
The study also shows a positive relationship between giving birth after age 40 and longevity, which is
consistent with the findings of previous studies (Perls et al, 1997). An examination of the Austrian data
suggest that the longevity advantage of late mothers results from a reduction in the risk from circulatory
diseases, although their risk of breast cancer is significantly increased. One possible explanation may be
that a late birth is a biological marker that these women have aged at a slower rate and that their
menopause occurred comparatively late.
References:
Doblhammer, G. (1999) Reproductive history and mortality later in life: a comparative study of England and
Wales and Austria, Max Planck Institute for Demographic Research Working Paper WP 1999-004 (April
1999), Rostock: Max Planck Institute for Demographic Research
Perls, T. T ., Alpert, L. and Fretts, R.C. (1997) “Middle aged mothers live longer”, Nature, 389, page 133
4
Table 2: Relative mortality risks (RMR) by parity: Austria ages 50-94, England
and Wales ages 50-85
England and Wales1
Austria 2
Parity
RMR
Parity
RMR
0
1.15***
0
1.15***
1+2 (RG)
1.00
1
1.01
3+
1.07***
2 (RG)
1.00
3
1.02
4
1.06**
5+
1.10***
Education
Education
High (RG)
1.00
High (RG)
1.00
Medium
1.36***
Medium
1.16***
Basic
1.71***
Basic
1.38***
Family Status
Married (RG)
1.00
Widowed
1.27***
Divorced
1.39***
*** significant at the 99 per cent level; ** significant at the 95 per cent level
RG: Reference group
Source: Doblhammer (1999)
Table 3: Relative mortality risks (RMR) by parity, age at first birth and birth
after 40: Austria ages 50-94, England and Wales ages 50-85
England and Wales1 Austria
Parity
RMR
Parity
RMR
1+2 (RG)
1.00
1
1.01
3+
1.06***
2 (RG)
1.00
3
1.02
4+
1.06***
Age at first birth
Age at first birth
<20
<20
20+ (RG)
20+ (RG)
Birth above age 40
No (RG)
Yes
Birth above age 40
No (RG)
Yes
4th birth < 40, age at birth
5+ unknown
Education
Education
High (RG)
1.00
High (RG)
Medium
1.39***
Medium
Low
1.74***
Low
Family Status
Married (RG)
Widowed
Divorced
*** significant at the 99 per cent level; ** significant at the 95 per cent level;
* significant at the 90 per cent level. RG: Reference group
Source: Doblhammer (1999)
1
2
1.00
0.95*
1.00
0.95**
1.09
1.00
1.22***
1.43***
1.00
1.24***
1.36***
The LS data cover deaths occurring in the period 1971-96 to women enumerated at the 1971 Census.
Austrian data cover all deaths in the year after the 1981 Census.
5
Using the LS for monitoring health inequalities in the EU, Anton Kunst, Department of
Public Health, Erasmus University, Rotterdam
Anton Kunst focused on the practicalities of doing international research, such as getting data from
different countries and the problems of achieving comparability. His presentation draws upon over ten
year’s experience of using LS data to study socio-economic inequalities in health. Figure 1 summarises
the three different ways in which access to data may be negotiated. This shows, for example, that data
from the National Centre for Health Statistics (NCHS) are available in public-use files. By comparison,
data from Statistics Finland are accessed via a research team based in the Sociology Department of the
University of Helsinki.
Figure 1: Three forms of access to data in a specific country
Erasmus
University
University
of Helsinki,
Finland
NCHS
(USA)
Statis tics
Finland
ONS
Anton mentioned that comparability problems crop up at different stages of the research project. A good
example is the range of different socio-economic classifications: different patterns may apply according
to the scheme that is used. Table 4 shows the different patterns that appear when two different
conversion algorithms were used.
Table 4: Mortality of skilled and unskilled workers: estimates based on two conversion algorithms
Sweden, 1980-1986, men ages 45-59 in 1980
SMRs estimated by EGP 3 algorithm
Skilled workers
Cause of death
All causes
Lung cancer
Ischemic heart disease
Cerebrovascular disease
Respiratory disease
Gastrointestinal disease
External causes of death
3
4
Unskilled
workers
121
135
121
120
138
133
133
105
111
106
92
104
96
110
SMRs estimated by GLT 4 algorithm
Skilled
workers
111
118
111
103
127
103
124
EGP=Erikson, Goldthorpe and Portocarero. See Erikson, Goldthorpe and Portocarero (1983)
GLP=Ganzeboom-Luijkx-Treiman. See Ganzeboom and Treiman, Donald (1996)
6
Unskilled workers
116
134
117
112
115
131
117
Using the EGP (Erikson, Goldthorpe and Portocarero) algorithm the mortality of unskilled workers is
consistently higher than that of skilled workers. However, using the GLT (Ganzeboom-Luijkx-Treiman)
algorithm for some causes of death skilled workers appear to have higher mortality than unskilled
workers. This variation occurs as some occupations are allocated to different groups under the two
classification schemes.
Anton considered why researchers would want to undertake international comparative research. He
came up with four explanations, which are particularly relevant to the international health inequalities
work he is involved in.
Figure 2: Why compare countries with respect to health inequalities?
1. Judgement: comparative work provides a yardstick to judge the health inequalities in your own
country.
2. Explanation: identifies factors that are associated with larger or smaller health inequalities
– e.g. smoking, diet, alcohol intake etc.
3. Policy: to study other countries as “natural experiments” in reducing health inequalities.
4. Exchange: to assess whether research findings from one country can be extrapolated to other
countries.
In the discussion that followed this presentation a member of the audience raised the issue of accessing
data from countries in Southern Europe, such as Portugal and Spain. Anton confirmed that the Erasmus
University research team used published data from these countries statistical offices, comparable to the
England and Wales decennial supplements. They also used data from sub-national census-link studies
– such as the study based on the Turin municipality.
References:
Erikson, R, Goldthorpe, J.H. and Portocarero (1983) “Intergenerational mobility and the convergence
thesis”, British Journal of Sociology, 34 , pp 303-340
Ganzeboom, H.B.G, Treiman, D.J. (1996). "Internationally comparable measures of occupational status
for the 1988 International Standard Classification of Occupations". Social Science Research , (25) ,
pp 201-239
One-person households and migration in France and England and Wales: some
comparative evidence from censuses and longitudinal sources: Ray Hall and Philip
Ogden, Department of Geography, Queen Mary and Westfield College, University of
London
Ray Hall and Philip Ogden’s presentation focused on work they have undertaken on the impact of
migration and living alone. Their research uses migration histories for adults under retirement age – the
group that has shown the greatest increase in the number of people living alone – and draws upon data
from the LS, the Echantillon Démographique Permanent (EDP) and specially commissioned tables from
the French census. This type of demographic comparison is useful for highlighting differences and
similarities and also gives perspective on the patterns seen in England and Wales. For this particular
project the researchers were more interested in identifying trends in the two countries – rather than
making direct comparisons.
Ray Hall highlighted that, compared with the LS, arrangements for accessing the EDP are less
comprehensive. For this project Philip Ogden carried out the French analyses from the offices of INSEE
(Institut National de la Statistique et des Etudes Economiques) in Paris. By comparison, the LS receives
funding from both the Economic and Social Research Council (ESRC) and the Office for National
7
Statistics (ONS). This facilitates a number of access arrangements – including the option of obtaining
small sub-sets of data in machine-readable form.
Ray confirmed that despite the fact that the EDP is less well resourced than the LS it can be successively
used for international comparative work. However, LS researchers need to be aware of the differences
between the two studies (for example, the LS migration data they used is based on a comparison of EDcentroids whereas the French migration data draws on questions asked at the census) and to make
appropriate adjustments to the LS data.
Possible uses of the LS and EDP on fertility: Michael Rendall, Population Research
Institute, Penn State University, USA
Michael Rendall’s presentation considered some of the similarities and differences of the LS and the
EDP (Echantillon Démographique Permanent) or French demographic panel, with particular reference
to fertility studies. The EDP has much in common with the LS – both in the type of data that are recorded
and the period covered. Currently, the EDP includes census data from 1968 to 1990 and data from birth
registration up to 1995. (Since 1982 birth registration data have only been linked into the EDP for half of
the women in the study.) Overall linkage rates are correspondingly high (around 85%) in both countries
for the periods since the last census.
While LS data are maintained as a hierarchical multi-file database, the French data are held in a flat file.
While this makes the EDP easier to use, compared with the LS, the French data allow for little
description of the census household. Also there is no French equivalent to the data on fertility history,
recorded at the 1971 Census, which has proved useful for studies of inter-generational effects.
Michael’s research on comparisons of teenage fertility focuses on the birth records of two cohorts (LS
members born between 1972-78 and members of the EDP born 1969-1975). Preliminary results show that
in both countries teenage girls are 2 to 2.5 times more likely to give birth if their mother was a teen
mother. However, by comparison with England and Wales where the rates haven’t changed much, in
France levels of teen childbearing in the 1990s are three times lower than in Britain. Work is currently
underway to build a projection model of inter-generational teen and non -teen childbearing in both
countries. It is hoped that this will highlight the importance of repetition of teen childbearing across
generations of mothers and daughters for explaining the divergence in teen childbearing in the two
countries.
3 Technical Issues
Migration between counties among LS members born in the 1930s:
a study of three time points (1939, 1971 and 1991)
David Strachan, Department of Public Health Sciences, St George's Hospital Medical
School, Brian Dodgeon, LS User Support Programme, Centre for Longitudinal
Studies, Institute of Education
An earlier contribution to Update (Dodgeon, 1998) described how the alphabetic stem of the National
Health Service number has been used to determine where LS members were enumerated in the wartime
National Register compiled on 29 September 1939. This article uses these areas of enumeration to
examine patterns of migration between 1939 and 1991.
The LS variable POBPOB provides a mapping of 1939 areas of enumeration onto post-1974 counties. We
examined this in relation to the areas of residence at census in 1971 and 1991, also classified by the
8
post-1974 boundaries. The analysis was limited to 39,409 LS members who were born 1 January 1930 to
29 September 1939, resident in England and Wales at the 1971 and 1991 censuses, and have POBPOB
codes indicating a county of England or Wales at National Registration. This group is 70 per cent of all
56,580 LS members born 1 January 1930 to 29 September 1939.
Over half of the cohort (22,085 individuals or 56 per cent) of the cohort were coded to the same county in
1939, 1971 and 1991. Although these may have migrated within the county, or moved out of the county
transiently within each time interval, they are considered for the purposes of this analysis as "nonmigrants". The pattern of movement among the remainder (the "migrants") was as follows:
•
•
•
•
10,711 (27 per cent of 39,409) changed county between 1939 and 1971, but not from 1971 to
1991.
2,320 (6 per cent of 39,409) changed county between 1971 and 1991, but not from 1939 to 1971.
906 (2 per cent of 39,409) changed county between 1939 and 1971, but had returned to their
1939 county by 1991.
3,387 (9 per cent of 39,409) c hanged county in both time intervals, and were living in a different
county in 1991 from their county of enumeration in 1939.
Table 5 shows the pattern of inter-county migration during three time periods (1939 to 1971, 1971 to
1991, and 1939 to 1991) for groups defined by their county of enumeration in 1939. The proportion of
migrants during 1939 to 1971 tends to be highest in the "home counties" – e.g. Bedfordshire, Berkshire,
Buckinghamshire, Hertfordshire and Surrey. This may reflect in part the impact of evacuation of
children from London to surrounding rural areas during the first few weeks of the war. However, there
is also substantial mobility from other areas (including Greater London itself). Furthermore, cohort
members who were enumerated in the home counties in 1939 were also more mobile than average
during 1971 to 1991.
Tables 6 and 7 provide equivalent breakdowns, based on county of residence at the 1971 Census (Table
6) and 1991 Census (Table 7). The pattern of greater mobility in the south of England than in the north of
England and Wales is evident throughout.
These preliminary analyses provide an insight into the potential for research based on this "additional
time point" within the LS. The socio-economic characteristics of inter-regional migrants from 1939 to
1971 have been reported elsewhere (Leon and Strachan, 1993) but with a third time point and a finer
geographical breakdown by county, there is scope for a more detailed analysis.
Migrants are of particular interest in distinguishing critical periods of influence of environmental
factors on human development. We have published earlier the effects of interregional migration on
cardiovascular mortality among all LS members who were enumerated in 1939 (Strachan, Leon and
Dodgeon, 1995). In that analysis, 1939 area of enumeration related to different periods of life for different
birth cohorts of LS members. The advantage of concentrating on LS members born in the 1930s is that
area of enumeration is a marker for childhood environment, which is of special interest in the "life
course" approach to epidemiology (Kuh and Ben -Schlomo, 1997).
However, the specific disadvantage of the wartime register is that many children were evacuated from
major cities during the first week of September 1939 in anticipation of immediate bombing raids
(Holman, 1995; Inglis, 1989). Under official schemes, 826,959 unaccompanied schoolchildren and
536,670 children with mothers were evacuated during September 1939 (Holman, 1995). The proportion
of schoolchildren evacuated was highest in London (approximately 50 per cent), Manchester, Liverpool
and Newcastle (approximately 60 per cent) and the West Midlands (approximately 25 per cent), and
over half of these had not returned home by January 1940. Although a lower proportion of pre-school
children were evacuated, these massive population movements need to be considered when interpreting
the LS data for 1930-1939 birth cohorts.
9
Some insight can be obtained by comparing the distribution of Barker (Dodgeon, 1998) geographical
codes in the LS sample and the distribution of births (surviving to 1 year of age) across the same 229
local government areas during the 1930s.
In summary, the percentage distributions are:
% LS born 1930-39
Inner London boroughs
"Other city centres"*
Other county boroughs
Municipal & urban districts
Rural districts
% births 1930-38#
3.4%
5.9%
24.3%
42.2%
24.2%
9.7%
8.1%
26.1%
37.2%
19.0%
# Live births minus infant deaths by geographical area. No data published for 1939.
* Birmingham CB, Liverpool CB, Manchester CB and Newcastle CB.
The apparent deficit of LS members enumerated in the city centres is a manifestation of two influences:
slum clearance and surburban development, primarily in urban districts, throughout the 1930s; and
early wartime evacuation, primarily to rural districts. Although both will tend to reduce the differences
between urban and rural areas, this dilution effect is not overwhelming: for instance the population of
LS members enumerated in the rural districts is inflated by about one-quarter, relative to the distribution
of births. The equivalent excess in municipal and urban districts is about one-seventh.
Further work may be required to investigate local discrepancies between the distribution of births and
LS members enumerated in 1939. However, we conclude that the 1939 area codes can be used with
caution to investigate patterns of migration within the LS and the effect of early environment on
experiences later in life.
References:
Dodgeon, B. (1998) “Barker geographical codes”, Update - News from the LS User Group , Issue 2
(November 1998), page 3
Holman, B. (1995) The evacuation: a very British revolution, Oxford: Lion Publishing, pp 8-29
Inglis, R. (1989) The children's war: evacuation 1939-1945 . London: Collins
Kuh, D. and Ben-Shlomo, Y. (1997) (eds) Life course influences on adult disease. Oxford: OUP
Leon, D.A. and Strachan, D.P. (1993) “Socio-economic characteristics of inter-regional migrants in
England and Wales 1939-71”, Environment and Planning A, 25, pp 1441-1451
Strachan, D.A., Leon, D.A. and Dodgeon, B. (1995) “Mortality from cardiovascular disease among interregional migrants in England and Wales”, British Medical Journal , 310, pp 423-427
10
Table 5: Pattern of inter-county migration for LS members born 1930-39, by area of
enumeration in 1939 (classified to post-1974 county boundaries)
County in 1939
Total
Greater London
Greater Manchester
Merseyside
South Yorkshire
Tyne and Wear
West Midlands
West Yorkshire
Avon
Bedfordshire
Berkshire
Buckinghamshire
Cambridgeshire
Cheshire
Cleveland
Cornwall
Cumbria
Derbyshire
Devon
Dorset
Durham
East Sussex
Essex
Gloucestershire
Hampshire
Hereford and Worcs
Hertfordshire
Humberside
Isle of Wight
Kent
Lancashire
Leicestershire
Lincolnshire
Norfolk
Northamptonshire
Northumberland
North Yorkshire
Nottinghamshire
Oxfordshire
Shropshire
Somerset
Staffordshire
Suffolk
Surrey
Warwickshire
West Sussex
Wiltshire
Clwyd
Dyfed
Gwent
Gwynedd
Mid Glamorgan
Powys
South Glamorgan
West Glamorgan
All counties
4404
2178
1459
1371
1065
2243
1752
690
356
407
347
418
682
475
307
530
923
694
423
769
618
801
451
810
518
572
785
90
1043
1201
615
491
608
397
330
605
827
377
288
385
862
503
695
317
494
386
346
347
476
232
643
131
313
359
39409
Migrants 39-71
Migrants 71-91
Migrants 39-91
Number %total
Number %total
Number %total
2127
549
430
358
295
622
411
226
169
217
190
172
223
92
114
183
306
288
230
330
392
344
229
281
248
289
219
50
434
451
167
196
232
183
164
303
211
174
109
185
215
247
412
113
324
186
166
140
159
113
254
60
109
113
15004
48
25
29
26
28
28
23
33
47
53
55
41
33
19
37
35
33
42
54
43
63
43
51
35
48
51
28
56
42
38
27
40
38
46
50
50
26
46
38
48
25
49
59
36
66
48
48
40
33
49
40
46
35
31
38
11
1207
306
207
165
139
403
224
98
76
72
74
79
89
57
45
51
148
136
86
100
131
140
76
136
83
134
87
14
157
165
78
63
88
60
47
88
109
67
32
76
109
86
186
51
123
71
54
47
68
44
79
10
49
43
6613
27
14
14
12
13
18
13
14
21
18
21
19
13
12
15
10
16
20
20
13
21
17
17
17
16
23
11
16
15
14
13
13
14
15
14
15
13
18
11
20
13
17
27
16
25
18
16
14
14
19
12
8
16
12
17
2679
661
498
394
329
807
476
229
198
228
205
181
233
111
108
190
337
283
226
335
402
355
234
304
242
310
234
52
447
458
185
198
221
195
164
295
235
190
111
194
236
249
447
118
324
191
158
136
167
107
251
60
121
119
16418
61
30
34
29
31
36
27
33
56
56
59
43
34
23
35
36
37
41
53
44
65
44
52
38
47
54
30
58
43
38
30
40
36
49
50
49
28
50
39
50
27
50
64
37
66
49
46
39
35
46
39
46
39
33
42
Table 6: Pattern of inter-county migration for LS members born 1930-39, by area of residence
in 1971 (classified to post-1974 county boundaries)
County in 1971
Total
Greater London
Greater Manchester
Merseyside
South Yorkshire
Tyne and Wear
West Midlands
West Yorkshire
Avon
Bedfordshire
Berkshire
Buckinghamshire
Cambridgeshire
Cheshire
Cleveland
Cornwall
Cumbria
Derbyshire
Devon
Dorset
Durham
East Sussex
Essex
Gloucestershire
Hampshire
Hereford and Worcs
Hertfordshire
Humberside
Isle of Wight
Kent
Lancashire
Leicestershire
Lincolnshire
Norfolk
Northamptonshire
Northumberland
North Yorkshire
Nottinghamshire
Oxfordshire
Shropshire
Somerset
Staffordshire
Suffolk
Surrey
Warwickshire
West Sussex
Wiltshire
Clwyd
Dyfed
Gwent
Gwynedd
Mid Glamorgan
Powys
South Glamorgan
West Glamorgan
All counties
4414
2173
1343
1233
1055
2081
1682
721
403
509
447
455
841
542
305
424
830
647
374
572
409
1258
415
1132
464
839
766
76
1137
1107
653
461
537
361
240
533
875
409
300
352
974
445
839
427
508
444
280
277
407
180
501
109
311
332
39409
Migrants 39-71
Migrants 71-91
Migrants 39-91
Number %total
Number %total
Number %total
2137
544
314
220
285
460
341
257
216
319
290
209
382
159
112
77
213
241
181
133
183
801
193
603
194
556
200
36
528
357
205
166
161
147
74
231
259
206
121
152
327
189
556
223
338
244
100
70
90
61
112
38
107
86
15004
48
25
23
18
27
22
20
36
54
63
65
46
45
29
37
18
26
37
48
23
45
64
47
53
42
66
26
47
46
32
31
36
30
41
31
43
30
50
40
43
34
42
66
52
67
55
36
25
22
34
22
35
34
26
38
12
1319
282
174
111
102
359
174
91
113
132
145
93
141
64
43
24
108
85
52
58
82
224
67
245
71
217
75
14
170
117
94
67
54
60
32
70
103
105
44
57
144
61
244
83
106
93
24
25
37
22
47
10
47
32
6613
30
13
13
9
10
17
10
13
28
26
32
20
17
12
14
6
13
13
14
10
20
18
16
22
15
26
10
18
15
11
14
15
10
17
13
13
12
26
15
16
15
14
29
19
21
21
9
9
9
12
9
9
15
10
17
2648
663
384
265
321
646
418
268
241
315
295
211
378
172
107
91
238
253
186
153
205
817
192
614
198
580
216
37
542
379
222
159
161
157
80
223
284
209
124
157
343
188
588
220
340
242
97
70
104
61
117
36
116
87
16418
60
31
29
21
30
31
25
37
60
62
66
46
45
32
35
21
29
39
50
27
50
65
46
54
43
69
28
49
48
34
34
34
30
43
33
42
32
51
41
45
35
42
70
52
67
55
35
25
26
34
23
33
37
26
42
Table 7: Pattern of inter-county migration for LS members born 1930-39, by area of residence
in 1991 (classified to post-1974 county boundaries)
County in 1991
Total
Greater London
Greater Manchester
Merseyside
South Yorkshire
Tyne and Wear
West Midlands
West Yorkshire
Avon
Bedfordshire
Berkshire
Buckinghamshire
Cambridgeshire
Cheshire
Cleveland
Cornwall
Cumbria
Derbyshire
Devon
Dorset
Durham
East Sussex
Essex
Gloucestershire
Hampshire
Hereford and Worcs
Hertfordshire
Humberside
Isle of Wight
Kent
Lancashire
Leicestershire
Lincolnshire
Norfolk
Northamptonshire
Northumberland
North Yorkshire
Nottinghamshire
Oxfordshire
Shropshire
Somerset
Staffordshire
Suffolk
Surrey
Warwickshire
West Sussex
Wiltshire
Clwyd
Dyfed
Gwent
Gwynedd
Mid Glamorgan
Powys
South Glamorgan
West Glamorgan
All counties
3352
2037
1238
1191
1011
1815
1614
733
373
506
444
485
865
512
432
478
844
856
521
579
494
1291
439
1140
555
822
780
97
1207
1184
652
543
641
405
256
647
862
391
346
403
957
503
850
433
598
463
342
315
427
229
500
123
295
333
39409
Migrants 39-71
Migrants 71-91
Migrants 39-91
Number %total
Number %total
Number %total
1654
504
287
216
271
399
337
264
196
298
258
212
362
146
177
118
226
387
274
155
242
751
210
586
233
516
206
43
529
388
189
200
222
176
81
287
254
191
140
174
291
222
521
204
389
253
125
93
116
82
112
46
101
90
15004
49
25
23
18
27
22
21
36
53
59
58
44
42
29
41
25
27
45
53
27
49
58
48
51
42
63
26
44
44
33
29
37
35
43
32
44
29
49
40
43
30
44
61
47
65
55
37
30
27
36
22
37
34
27
38
13
257
146
69
69
58
93
106
103
83
129
142
123
165
34
170
78
122
294
199
65
167
257
91
253
162
200
89
35
240
194
93
149
158
104
48
184
90
87
90
108
127
119
255
89
196
112
86
63
57
71
46
24
31
33
6613
8
7
6
6
6
5
7
14
22
25
32
25
19
7
39
16
14
34
38
11
34
20
21
22
29
24
11
36
20
16
14
27
25
26
19
28
10
22
26
27
13
24
30
21
33
24
25
20
13
31
9
20
11
10
17
1627
520
277
214
275
379
338
272
215
327
302
248
416
148
233
138
258
445
324
145
278
845
222
634
279
560
229
59
611
441
222
250
254
203
90
337
270
204
169
212
331
249
602
234
428
268
154
104
118
104
108
52
103
93
16418
49
26
22
18
27
21
21
37
58
65
68
51
48
29
54
29
31
52
62
25
56
65
51
56
50
68
29
61
51
37
34
46
40
50
35
52
31
52
49
53
35
50
71
54
72
58
45
33
28
45
22
42
35
28
42
4 LS publications
LS Working Paper 78: Teenage fertility in England and Wales: trends in
socio-economic circumstances between the 1971 and 1981 Censuses
Michael Rosato, Central Health Outcomes Unit, London School of Hygiene and Tropical
Medicine
This working paper explores trends in teenage fertility between two periods after the 1971 and 1981
Censuses. The role of social mobility in the generation of these trends is also examined. Gradients
associated with housing tenure became steeper between the two periods of interest, dominated by
increased relative risks associated with Local Authority tenure. Indicators of family structure (the age of
the LS teenager’s mother and the number of siblings) continue to show significant independent
associations with the risk of teenage pregnancy.
LS Working Paper 79: Identifying area effects: a comparison of single
and multi-level models
Simon Gleave, Richard Wiggins, Heather Joshi and Kevin Lynch, Centre for Longitudinal
Studies, Institute of Education and Sociology Department, City University
This paper explores whether multi-level models are more sensitive to a relationship between the
incidence of limiting long-term illness and area deprivation at ward level that was seen in the single
level analysis undertaken by Sloggett and Joshi using deprivation indicators for 1971 and 1981. The
present authors were also able to use a ward deprivation index for 1991. The single level method can
only reveal spatial effects associated with variables in the model but the multilevel approach also
reveals area variation in unmeasured heterogeneity. The broad conclusion that individual effects are
more important than area effects remains, but this paper has produced better estimates of the relatively
minor effects of area.
LS Working Papers are available from the LS User Support Programme (price £3). To obtain a copy of
these and other LS Working Papers contact LS Administrator Dina Maher (tel: 020 7612 6875, email:
dm@cls.ioe.ac.uk).
5 Staff Changes at CLS
Since the beginning of the year there have been a number of changes in the composition of the LS User
Support Team at CLS. At the end of March 2000 Simon Gleave, who has been working on the LS since
1991, left to take up a post in the Netherlands. We would like to thank Simon for his valuable
contribution to the team and to wish him the best of luck in his new career.
In January 2000 Sarah Jones joined the LS Team, closely followed by Angela Brassett-Grundy and
Andrew Cullis, who joined in March. Sarah, who has a degree in Statistics and French from Coventry
University is one of the key researchers on the ESRC-funded project “The Longitudinal Study after 2001:
preparing for continuity”. Angela, who has a B.Sc. (Hons) in Psychology, previously worked as a
Research Officer and IT Manager at the Association of Colleges. Before joining CLS Andrew, worked as
a Senior Lecturer in the School of Service Industries at Bournemouth University. Each of the new team
members will be providing research support/advice and helping to update and develop new LS
documentation.
14