LS Working Paper 73
DEATH AND THE SALESWOMEN: AN INVESTIGATION OF
MORTALITY AND OCCUPATIONAL IMMOBILITY OF
WOMEN IN THE LONGITUDINAL STUDY OF ENGLAND AND WALES
by
Anne Harrop and Heather Joshi
Social Statistics Research Unit
The City University
Northampton Square
London EC 1V OHB
ACKNOWLEDGEMENTS
‘ l l i s study is part of an ESRC hnded programme, Health Ineaualities Amona Women and Their
Families (R000232797), undertaken at the Centre for Population Studies, London School of
Hygiene and Tropical Medicine, 99 Gower Street, London WC1E 6AZ. The permission of OPCS
to use the Longitudinal Study is also gratehlly acknowledged, as are helphl comments from
Rosamund Weatherall. The coding for occuaption in 1981 was supplied by Clare Ward.
May 1994
ABSTRACT
Occupational differences in the mortality of women in the Longitudinal Study of England and
Wales are explored. Occupations are classified into the expansion of Social Class originally
proposed for the Women and Employment Survey. This survey also provides direct evidence on
the likely history of occupational mobility leading up to the occupations in 1971, which are
followed up to 1989 in the mortality analysis. We find occupational mortality differentials which,
though modest, are greater than those reported earlier. When the analysis is confined to groups
least likely to have experienced occupational mobility before 1971 or between censuses, estimates
of mortality ratios become more diEerentiated though less well determined. For example, among
those who were in the same occupation at both censuses, and in hll-time employment in 1971,
estimated occupational mortality differentials appeared as wide as among men. Thus women's
occupational mobility may serve partly to obscure (and protect from) specific occupational
hazards. However, relatively poor health ofwomen in semi-skilled factory jobs is confirmed in this
study, especially for long-term incumbents.
INTRODUCTION
"In view of the intermittent and transitory character of much female occupation,
it may be doubted whether the difficulty will ever be overcome". Stevenson
(1927).
The analysis of mortality by type of paid occupation is important for the study of social
stratification and the prevention of particular hazards, but, for women, has still not reached any
clear resolution. Women's mortahty differs from mens's, and so do their occupations. This paper
presents a new approach to identifling women's occupations with particularly high or low risks
of death. A woman's work history is often intermittent and her current occupation transitory. It
is therefore unclear whether the intrinsic hazards of a particular occupation are best revealed by
looking at the relative mortality of women in given occupations at one point in time. Such
differentials as may appear could reflect general differences in lifestyle. Underlying differences
associated with long tenure of particular occupations may be masked by the mixed histories of
those whose occupations are less fixed. The latter issue is addressed here. We use two data sets
with a common occupational classification, related to mortality in one and to occupational
mobility in the other, the OPCS Longitudinal Study (LS) and the Women and Employment Survey
(WES) respectively. The classification adopted is an expansion of the Registrar General's Social
Class. It splits the big category of women's occupations into office and shop jobs. The latter are
also of interest as a common destination of the downward occupational mobility that WES
documented (Dex, 1987:70).
This paper is one of the first to make use of the mortality follow-up to 1989 linked in the LS to
the 1971 Census. The retrospective work histories collected by the Women and Employment
Survey in 1980 enable us to infer the employment histories that preceded the snapshots of
occupation recorded at the 1971 Census. 1971 is taken as the point of reference as the only date
before 1980 for which Census data are available. It also maximizes the period of follow-up.
Routine analysis of the occupational mortality of men has been conducted in England and Wales
since 1861. The first attempt to analyze that of women did not occur until 1908 (Registrar
1
General, 1908). In 193 1 the occupational mortality of single women was considered for the first
time (Registrar General, 193 1) and married women's own occupation was first recorded in 197 1
(OPCS, 1978). The dramatic increase in the labour force participation of women in the post-war
period increases the need to investigate their occupational mortality.
The Decennial Supplement compares occupations recorded at death registration with the number
of persons recorded in the respective occupation at the Census. However the under-reporting of
occupation at death registration means that the numerator does not correspond to the
denominator, the population at risk. This is termed the numerator-denominator bias (OPCS,
1986a). This bias is greater for women than for men because the recording of women's
occupation at death registration is worse than that of men's. In the 1970-72 Decennial
Supplement (OPCS, 1978), 20 per cent of all women aged 15-64 could be assigned to an
occupation at death registration compared with 49 per cent in the 1971 Census. There are two
related reasons why the recording of women's occupation at death registration is so poor, both
arising from the instructions to registrars (OPCS, 1978; Roman, Beral and Inskip, 1985). The
instructions state: 'in the case of a woman who is not employed at the date of her death the last
111time occupation should not be recorded unless she has been in paid employment for most of
her life'. Thus, the Decennial Supplement only records an occupation if it was full time, thus
excluding women who had been employed part time. At the 1971 Census 39 per cent of women
in paid employment were part timers (42 per cent in 1991 (Employment Gazette, 1992)).
Secondly women whose employment is intermittent are not classified to an occupation at death.
These discrepancies between the Census and death registration render mortality rates by woman's
occupation in the standard Decennial Supplement method near meaningless (McDowall, 1983).
The inception of the Office of Population Censuses and Surveys (OPCS) Longitudinal Study (LS)
following the 1971 Census broke new ground for the study of occupational mortality. It is a
prospective study of persons enumerated at the Census. Using the occupation information
provided at the Census linked to register deaths the occupational mortality rate can be calculated
matching population at risk to outcome. Women's occupational mortality has been studied for
deaths in the first 10 years of follow up using this source (Moser et al, 1990).
2
This study suggests that women in six occupation orders (hrnace, forge, foundry, rolling mill
workers; engineering and allied trades workers; textile workers; makers of other products; drivers
of stationary engines, cranes etc; and warehousemen, storekeepers, packers and bottlers) had
standardised mortality ratios above that of all women aged 15-59. However this difference was
only significant for the relatively few women working in engineering and allied trades. Five
occupation orders had mortality levels sigdicantly lower than all women, food drink and tobacco
workers; clerical workers; sales workers; administrators and managers; professional, technical
workers and artists. Moser and colleagues conclude that although significant differences in
mortality between occupation groups were evident, these were more likely to be associated with
a common lifestyle rather than to specific occupational hazards. Other work on the LS indicates
that the social class gradient in mortality is less severe for women than it is for men (Goldblatt,
1990).
The previous analysis of occupational mortality of women in the LS suffered from two limitations.
The first relates to the classification of occupations, the second to the lifetime perspective on
women's occupations. The classification of occupations was developed when the vast majority
of employees were men working in manufacturing industries. This classification is unsuitable for
classifling women's occupations for several reasons. Occupational segregation means that
women's employment is concentrated in a relatively small number of occupations which differ
markedly from men's. In the 1971 LS, 75 per cent of women were concentrated in just four
occupational of 26 occupational orders (Moser, Pugh and Goldblatt, 1990). These large
categories for women were also small categories for men. Paid work remained sexually
segregated. Over 80% of the labour force in 1971 were in occupations in which their own sex
was over-represented (Hakim 198 1, using 223 occupations). Though the classifications detects
large feminized occupational groups they do not distinguish very finely the skills and
responsibilities that women's jobs encompass, covering a wider range of tasks than is the case of
male dominated job categories. The classification often fails to differentiate between women
doing differing jobs in the same industry. Neither does it distinguish between full and part time
employment, nor include categories for unwaged labour in the home (Martin and Roberts, 1984).
Alternative occupational classifications for women have been developed. Martin and Roberts
3
made a simple modification of the RGs occupational classification by subdividing categories
accounting for a large proportion of women's employment. This discriminates more finely among
some women's jobs (Martin and Roberts, 1984). The resulting schema has 12 categories.
S d a r l y Dale, Arber and Gilbert (1985) developed a classification scheme which differentiated
women's occupations more finely by distinguishing between full time and part time employment.
Neither of these classifications have been used to study mortality. A third classification of
women's occupations was developed by Roberts and Barker. Using cross sectional data they
identsed 'work positions' which combined women's paid employment with their fertility histories
(Roberts and Barker, 1985). A similar classification has been used to consider the effect, for
women's mortahty, arising fi-omthe dual burden of domestic responsibilities and paid employment
(Weatherall et al, 1993).
The second limitation of the earlier analyses of women's occupational mortality is partly met by
such joint treatment of occupatiori and fertility. The problem is that a woman's paid occupation
may not necessarily reflect her long-term way of Me in the same way that a man's paid occupation
does. While employment is assumed to be of central importance to a man's life, it may not be for
women, whose domestic responsibilities are also assumed to have greater, if not paramount
importance. Though most women are in paid employment for most of their working lives, at any
one point in time a large proportion of women are out of the labour force, for reasons largely
relating to their domestic responsibilities. After such breaks women often return to occupations
that do not reflect their skills or training, experiencing occupational downward mobility (Dex,
1987). Thuty-seven percent of mothers in the Women and Employment Survey with a job before
and after childbearing returned to jobs at a lower level than the one they held before their first
birth (Martin and Roberts, 1984). Similar incidences of downward mobility after childbearing
have been found in the National 'Training Survey and the MRC National Survey of Health and
Development (Stewart and Greenhalgh, 1984, Joshi and Newel1 1987). These jobs are often
transitory. In due course, some women recover occupational status.
Thus, particularly for women, a cross sectional snapshot may not record a person in their main
occupation. Recording a woman in a temporary occupation will introduce error to the assessment
of mortality in that occupation because she will not have been exposed for a reasonable length of
4
time to any hazards that may be associated with that occupation. Thus, occupational hazards may
be masked iflong term incumbents are swamped by occupationally mobile workers doing similar
jobs on a less permanent basis.
We bring the classification devised by Martin and Roberts to the study of mortality, to address
both the problems of classification and mobility. We use it to draw on evidence from the Women
and Employment Survey about occupational and family building history to distinguish women in
the LS whose occupations are less likely to be transient. It also enables us to investigate whether
sales workers are more like manual workers than other non-manual women workers as far as
mortality analysis is concerned. In the standard social class scheme they cannot be distinguished
from other "junior" non-manual workers. The next section describes our sources of data and our
classification of occupation. The following one sets out the methods to be used in our two-stage
analysis. The fist stage, on occupational mobility, is reported in the fourth part of the paper, and
the fiflh reports findings from the LS on the relation of occupation in 1971 to mortality and also
to permanent sickness in 1981. The findings are discussed and summarized in the concluding
section.
SOURCES AND CLASSIFICATION OF DATA
1. Sources of Data
The two data sets used here are the Women and Employment Survey (WES) and the OPCS
Longitudinal Study (LS). The first is used to identifL sub-groups within occupations that are
relatively stable, ie. include few women whose main paid occupation was different. As
occupational mobility is associated with domestic responsibilities, women's fertility data are used
in the search for stable sub-groups. The LS provides evidence on the mortality of women in such
sub-categories of occupation.
The Women and Employment Survey was conducted in 1980 by OPCS. It is a representative
sample of 5 5 8 8 women who were aged between 16 and 59 in 1980 and resident in a private
household in Britain. It achieved a response rate of 83 per cent. The Women and Employment
Survey collected retrospective lnformation on marriage, child bearing and job histories. Each job
5
that a woman had ever had was allocated to one of the 12 occupational categories in the survey's
own classification mentioned above. For this paper (and the published report) child care
occupations are combined with semi-skilled domestic work, resulting in 1 1 occupation categories.
These are shown in Table 1 . This classification has been used for all analyses of both sources
presented here.
The LS is a one per cent sample of the population enumerated in England and Wales at the 1971
Census. Its geographical coverage therefore differs from the WES which also includes Scotland.
Though it might have been desirable to omit the Scottish women from the WES analyses to
maintain strict comparability they were retained to boost sample size. There is no evidence of
Scottish employment patterns differing greatly from the rest of Great Britain. Another difference
between the data sets is lack of information from the 1971 Census on childbearing by women who
had never married. As the proportion of mothers of dependent children who were never married
women was low in 1971 (1%) this discrepancy is not serious (OPCS, 1986).
From the job histories in WES, we extracted occupational careers since leaving school until April
1971, the time from which survival and mortality can be followed up in the LS. Thus for each
woman in WES her occupation at April 1971 was considered as the current occupation she would
have reported had she been in the LS. Details of her previous jobs, including whether they were
full time or part time, and their type of occupation were recorded along with the duration. An
occupational history to 1971 can only be considered for women aged less than 5 1 in 1971 as data
in 1980 was only collected from women aged under 60. Marital and fertility histories up until
April 1971 were also extracted.
'The 1971 Census classified 49 per cent of women aged 15-64 to a specific occupational unit.
W E S suggests that a much larger fraction would have had paid occupation(s) at some time. The
low proportion of women classified by the Census is due to the way occupational information was
collected: on 'main employment last week, or of the most recent job if retired or out of work' with
the caveat that 'housewives who did not have a job last week should not provide any information'.
Thus, data on women's occupation in the 1971 Census principally relates to women in a job in the
week before Census, and not many others who might have reported an occupation in WES. To
6
ensure comparability we restrict our analyses to those in employment in April 1971. Information
gained from the WES is linked to groups of women in the LS, not individual LS members.
In the LS information collected at death registration is linked to individuals' Census records. In
this paper we use data obtained in the follow up sample of women aged 16-49 at the 1971
Census, to examine all cause mortahty in the period 1976-1989. The upper age limit was chosen
to maintain consistency with the analyses from the Women and Employment Survey. Deaths in
the period 1971-75 have been discarded to allow for immediate effects of health selection.
Persons in employment tend to be healthier than their counterparts because a certain level of
health is required to remain in employment (Fox and Collier, 1976). Within our sample, who were
all in employment, we will have missed those who had already dropped out of employment
altogether because of poor health. By discarding evidence on deaths in the immediate follow-up
period we are making some allowance for any health selection of the less fit into certain
occupations, eg those that are relatively undemanding and can be done part-time.
2. Classification of Occupations
The classification of occupations offered in the LS in 1971 was the Registrar General's
Classification of Occupations 1971. We recoded these as far as possible, to the WES framework
set out in Table 1, which had been derived fiom the 1980 RG classification of occupations. This
presented some problems. The RGs classification had 223 occupation codes in 1971 and 3 5 1
codes in 1981. Thus, occupations that had formed one occupation code in 1971 often formed
several in 1981 destined for different WES categories. Arbitrary allocations had to be made in
a few cases.
The occupations of women in 1971 according to the LS and the Women and Employment Survey
are compared in Table 2. Distinct differences can be observed particularly in the apparent underrepresentation of skilled workers (and corresponding over-representation of semi-skilled domestic
occupations) in the WES. These differences could arise in part from the difference in classification
discussed above or in recall or sampling biases in WES. Up to a point, they are also consistent
with WES using more inclusive definitions of paid employment, covering jobs, such as mail order
agent, or child minder, often not recorded in the Census (Joshi and Owen, 1987). The two LS
7
occupational distributions shown in Table 2 compare all employed women alive in 1971 with
those who survived to 1980. As they are broadly similar, this suggests that occupational
differences in survival are not a major source of the discrepancy. Indeed, it also suggests that
mortality differentials among women's occupations thus defined are not very startling.
METHOD
The analysis is in two parts: occupational mobility in W S and the LS; and occupational
differentials in mortality and morbidity, based on the LS.
1. Occupational Mobility
Evidence on occupational mobility or stability up to April 1971 was taken from the Women and
Employment Survey. The aim is to identifjl occupations in which the probability of a cross
sectional survey recording long term incumbents is high. These would be occupations without
large numbers of occupationally mobile workers. The proportion of time in spent paid
employment up to 1971 in the occupation current at 1971 is the main measure used. We do not
mclude time spent out of the labour force, in the denominator as we are particularly interested in
occupational change within paid work. For occupations with high proportion of other work
behind them, the highest and lowest occupations ever held were also considered to see whether
the mobility was upward or downward. The analysis is carried out for women who were under
5 1 and in employment in 1971. The upper age limit is imposed by the design of the survey, the
restriction to women in employment results from the incomplete coverage of non-employed
women's occupation in the Census. We also have a direct measure of occupational stability in the
LS for those who recorded occupations at both the 1971 and 1981 censuses. Definition changes
between the two Censuses pose some difficulties. Moreover, this measure only indicates what
a woman was doing at two points in time, it does not necessarily follow that the woman has only
worked in this occupation for ten years.
2. Occupational Mortality
Mortality for different groups was compared using odds ratios estimated on LS data. These were
estimated using logistic regression, of a binary outcome variable, standardising for age at entry
8
and period of follow up, a method developed for the LS by Weatherall (1992). Effects of
explanatory variables are estimated relative to a base category.
The logistic model with main effects only was as follows:
log(odds of death) = a + bl (period of follow up)
+ b2 (age in 1971)
+ b3 (occupation in 1971)
+ b4 (indicator of living standards)
'The basic model (Model 1) includes bl to b3, with extensions to b4 (Model 2), fitted over the
sample who were in employment in 1971. Interactions were investigated by estimating parameters
a to b4 in the sub-sample thought to be more stable according to the several measures of fifth type
of variable indicating occupational stability.
The model is fitted using binomial errors. The dependent variable is the log odds of death during
a period of follow-up among survivors at the beginning of each period. Each of the explanatory
variables was treated as a categorical variable. Occupation had 11 categories of which clerical
workers were the base group. To standardize for age, terms were included for five year age
ranges. To allow for the length of exposure and ageing after 1971, the period of follow up enters
the model, grouped into three categories; 1976-1980; 1981-1985; 1986-1989. The last one ends
at the latest date of deaths available at the time of writing.
Car access was included in the model as a proxy for the household living standard, to determine
whether any observed occupational differences might be due to particular hazards associated with
that occupation could be accounted fkom a common lifestyle shared by women in that occupation.
The household standard of living was proxied by a binary indicator of no cars or one or more cars.
Car access was found by Moser et a1 to be a good discriminator of women's mortality (Moser,
Goldblatt and Pugh, 1990) and is positively correlated with household income in the 1983 FES
(Davies, Joshi and Clarke, 1993).
9
To allow for transient holders of Census occupations two other variables were also considered:
the age of the youngest child and whether the woman worked full time or part time.
A second dependent variable was also given some consideration, the log odds of being reported
permanently sick at the 1981 census. This was to see if this alternative, and by no means ideal,
indicator of poor health picked up or amplified any of the differentials discernible in the mortality
rates.
RESULTS
1. Occupational Mobility
The penultimate column of Table 3 shows the proportion of time in paid employment spent in the
occupation recorded in April 1971. For the whole sample of women under 5 1, this is 67%. It is
under 50 per cent for just three occupational categories - other intermediate non-manual, the small
sample of semi-skilled factory workers and other semiskilled workers other than those in domestic
type service occupations. For women in teaching and clerical occupations over 80 per cent of their
time in employment was in the current occupation. Shop assistants, the saleswomen in whom we
are particularly interested, appear to be the fourth most transient category, having spent 55 per
cent of their time in the same occupation. The last column of Table 3 shows the amount of time
spent in any paid work. This averages 146 months, just over 12 years, for the whole sample, but
tends to be above this for those who were doing the least skilled occupations in 1971, and less
for those in occupations requiring longer education.
In the analysis of this denominator by age shown in the bottom row of Table 3, the number of
months of employment rises with age, though not by as much as age itself, as few of the older
women had been employed continuously. The distribution of occupations by age reported in the
body of Table 3 reveals occupational segregation exists between women of different ages. Older
women tend to predominate in sales and services. Younger women, who tend to be better
educated, are better represented in the (broadly defined) professions p o s e r , Goldblatt and Pugh,
1990).
10
Table 3 shows occupational stability varies between the age groups. In gerieral, the older women
have spent proportionally less time in their 1971 occupation than younger women. They have had
a greater chance of experiencing different occupations. Nevertheless, in several individual
occupations ( nursing, shop assistants, skilled and domestic type work and unskilled) the histories
are more homogeneous among the oldest age group than among those aged 35-44.This could
possibly reflect patterns of re-establishment of original occupations after a more mixed
occupational experience in mid-life. Controlling for age does not increase stability notably for any
individual age group. Both of the larger groups which appear particularly upstable among all ages
(other intermediate and other semi-skilled) also appear relatively unstable ib each constituent age
group. This is despite their both being "rag-bag" categories, allowing job mobility within them
to go undetected.
I
A woman's occupational history is also associated with her domestic responbibilities. Most women
who had a child before 1971 had an interrupted employment histork. Table 4 shows the
proportion of time in paid work spent in the occupation recorded in 1971, for women who had
never or ever had a child, by age of the youngest child aged less than 15 in 1971, and for all
mothers with no child under 15 in 197 1. Sample size was insufficient to bonsider the age of the
woman and the age of the youngest child jointly.
Table 4 clearly shows an effect of child bearing on occupational stability.) Childless women had
spent more than three quarters of their employment in their 1971 occupa/tion compared to 56%
for all mothers, around 60% among mothers with children under 15. With the exception of
professional women, an extremely small sample in "top jobs", women who 1 have never had a child
show a higher proportion of time in the labour force spent in the 1911 occupation than the
average mother in each occupational group. Teaching appears as
occupation which is
relatively easy to combine with motherhood. In the three occupational grqups which showed the
most instability in Table 3, (other intermediate, semi skilled factory wQrkers and other semiskilled) women without children showed relatively low stability, oust unfer half all time in their
'own' occupations), but the occupational histories were particularly unstbble among mothers of
dependent children. Mothers of children under 15 working in other semi-skilled occupations had
spent only about one third of their paid employment in such jobs. Tablt 4 also shows stability
11
rates for women who had no child under 15 in 1971. For most occupations the rates well above
those for women whose children are under 15, and close below those of the sub-set who had
never had a child.
Many mothers return to part time employment. Table 5 shows occupational stability by whether
the woman was working full or part time in 1971. Part time work is self defined. Full-timers had
spent 71% of their careers in their current occupation and part-timers 60%. This direction of
difference applies generally across all occupations with a sample size in each group over 15. In
the unstable group other semi-skilled (also the small sample of semi-skilled factory workers),
selecting full timers increases stability but does not raise the proportion of time spent in these
occupations to more than 45 per cent. Thus, up to a point, the practice of ignoring part-timers
at death registration has some rationale. They tended, at least in 1971, to have more of a mixed
record behind them than most full-timers, but full-timers did not have totally consistent histories
either.
Along with age, it is clear from Tables 4 and 5 that occupational stability is related, for most
occupations, to the absence of dependent children and to full time employment. In terms of
identifLing an efficient global discriminator of occupational stability it is worth considering
whether working full time or not having a dependent child is a better measure than working full
time and not having a dependent child. These results are shown in Table 6. A dependent child is
defined as aged under 15 in 1971, then the minimum school leaving age.
Overall, for women in full time jobs without dependent children, 75 per cent of their time in paid
employment was in the occupation recorded in 1971 compared with 70 per cent of the broader
group who either have full-time work or no dependent child, and 67% for the sample as a whole.
Neither of these criteria is spectacularly successful at picking out the unmixed occupational
history. Table 6 shows that working full time and not having a dependent child is a better
discriminator of occupational stability, as far as it goes, within most, but not all occupational
categories. For other intermediate occupations never having a child is marginally better (see
Table 4). For teachers, the envelope of either full time employment or no dependent children is
better at isolating unmixed histories than their intersection. Full time employment alone is
12
marginally better still.
Where did the mobile workers come from? Many of the other intermediate non-manual jobs had
been upwardly mobile, only 3% of the time before 1971 had been in the top 3 categories. Many
of these other intermediate jobs are more senior office positions which recruit from clerical
workers. Of the time up to 1971 44%had been spent in the same occupation, 34% in clerical jobs,
7% in shop jobs and 12 % in various manual jobs. Little of the mobility into this occupation was
'
downwards' because the occupations above it, for example, teaching or nursing, tend to need
specific qualifications and training, which help protect against downgrading (Joshi and Newel1
1987).
The other large mobile group, other semi-skilled had spent the majority of their time semi-or
unskilled manual jobs (35% plus the 41% in their own category), but downward mobility was
also evident. 25% had been in 'higher' occupations, 10% in clerical and jobs. The small group
of factory workers had very mixed previous experience, both higher and lower, with clerical jobs
accounting for almost as much time (27%) as their current occupation (3 1%). The time behind
shop workers not spent in shop work (45% altogether) was predominantly in lower manual
occupations (27%). Higher occupations, almost all clerical, accounted for 14% of the balance, or
19% if factory and skilled manual work are ranked above shop work (see Joshi 1984). Thus,
although women's employment histories have a reputation for downward mobility, this was not
a majority experience among those employed in 1971. In a cross-sectional snapshot, most women
were in occupations in which they had spent the majority of their working lives.
Supplementary evidence on occupational stability is drawn form the LS itself in Table 7. This
takes women under 5 1 in 1971 who were in paid employment at both Censuses and shows those
recorded in the same occupation group at both Censuses as a percentage of women in that
occupation in 1971. Overall 58 per cent of women in paid employment at both Censuses were
recorded in the same occupation at both points in time, a lower degree of homogeneity here,
where occupation is recorded for only two points, than the 67% recorded in Tables 3-6, where
every month of the occupation history is counted. Probably for this reason, Table 7 has generally
smaller estimates throughout than Table 3, broadly retaining the same pattern. The rate of
13
repeating occupation at two Censuses ranges from 90 per cent of teachers to 11 per cent of
intermediate workers, of whom an exceptionally small number satisfjr the criterion of having
occupations at two Censuses. Apart from this surprisingly small group, those with relatively low
rates of repetition are all of the manual categories, not just other semi-skilled workers and factory
workers (better represented here), who appear unstable in both analyses. Of those who were shop
assistants in 1971 with employment at 1981, half were shop workers at both dates.
In summary, many occupational categories appear to be reasonably stable. Teachers, clerical
workers, professionals, nursing, and semi-skilled domestic work all had incumbents in 1971 who
had worked more than seven tenths of their paid time in the same category. In all but the last of
these, more than half those with two census jobs had repeated the 1971 occupation at the 1981
census. The three most unstable occupational categories in the WES analysis were other
intermediate, semi-skilled factory work and other semi-skilled. Each accounted for well under half
their incumbents' paid time. Shop assistants, along with the unskilled, had spent about half their
working lives in their 1971 occupation. As indicators of occupational stability, both working full
time and not having a child aged under 15 in 1971 appear to discriminate roughly, though not
perfectly. Both these two categories tend to over-represent younger women.
2. Health Outcomes and Occupation in the LS
Occupational Mortality
1. All Employed in 1971
The sample of 49,088 women who were classified in the LS as being in paid employment in 1971
have been followed up to record any mortality from 1971 to 1989. The relative odds of dying by
occupation at 1971 are shown in Table 8 controlling for age and period of follow up (1976- 1989).
This Table also presents the estimates from the extended model controlling for material
circumstances in terms of car access. The results of these analyses are also shown in Figure 1.
Housing tenure was considered as a second indicator of material circumstances but proved to be
highly collinear with car access in this sample of only employed women.
Seven occupations are shown in model 1 to have significantly (p<0.05) raised mortality ratios
compared to the base group clerical workers: all the manual groups, shop assistants (as expected),
14
and rather unexpectedly, the intermediate non-manual group, who, on the whole, have higher pay
and status than clerical workers. Nurses are the only occupational group to suggest a lower risk
of dying than clerical workers, although the relative odds are slight and not significant. The range
of occupational mortality risks is moderate. The worst is scarcely more than 50% more than the
best. In comparison SMRs among male occupations vary by a factor around 2 from worst to best
among occupation orders I to XXVI (Goldblatt and Fox, 1990) or between male Social Classes
I and V (Fox Goldblatt and Jones 1990).
The effect of adjusting for car access is minimal. The adjusted estimates are plotted as crosses
more or less alongside the unadjusted estimates and their confidence limits in Figure 1. The
mortality differential for professionals, teachers and intermediate non-manual workers is slightly
raised, remains the same for nurses, and reduces for all other occupations. When material
circumstances were introduced into Goldblatt and Fox's (1990) model of male occupational
mortality, the impact was very similar, a minor reduction in the excess mortality of manual
occupations. In that study the level of living was proxied by housing tenure. All of the
subsequent models were also estimated including car access but as the effect on mortality ratios
was minimal they have not been presented. Only a very small part of the disadvantages of the
manual occupations can be attributed in this way to lower household living standards, as proxied
by car access. The variable itself has an independent and significant effect on mortality. Those
without car access were, all else equal, 27% more likely to die than those with cars.
Table 8 includes all women who were in an occupation in 1971. A number of these women would
be short term incumbents of these occupations and may be distorting any mortality effects
associated with that occupation. Evidence presented above showed that women who were
working fill time in 1971 had spent a higher proportion of their time in paid employment in the
occupation they were recorded in 197 1 than part time workers.
Confining the sample to the 64% employed fill time (in Table 9) only makes a slight difference
to the estimates compared with all women. The gap between worst and best has opened - as we
expected given our exclusion of the more occupationally unstable part-timers, but it has hardly
opened very wide, from 57% to 70%.
15
Table 4 showed that women who did not have a dependent child were more likely to be
occupationally stable than women who did. This sub-sample is heterogenous, it includes women
who have not started child bearing, women whose chddren are independent and women who have
remained childless. Table 9 also shows the mortality analysis for women who did not have a child
under 15 in 1971. Considering this sub-group of women has only a modest effect on the mortality
ratios compared with all women, although, as with hll time workers, the mortality ratios tended
to increase for occupations that had a significantly raised mortality ratio. The excess of worst
over best occupation is 66%. There is of course considerable overlap of the two sub samples
considered in Table 9. 80% of the workers with no dependent children were hll-timers. 77% of
the fill-timers had no dependent children. An analysis (not shown) of those who satisfied both
criteria did not sharpen the estimated mortality differentials, despite the fact that women working
hll-time without dependent children were the most occupationally stable group in Table 6.
2. Women in same type of jobs, 1971 & 1981
Table 9 attributes occupational stability to the women in the LS on the basis of inference from the
Women and Employment Survey. The sub-groups that were identified as likely to be stable have
only slightly dif5erent occupational mortality patterns from all women. It could be that this is not
a good measure of prospective occupational stability, so we turn to the alternative indicator of
stability after the 1971 Census.
Table 10 and Figure 2 show the mortality ratios for women who were recorded in the same
occupation in 1971 and 1981 controlling for age and period of follow-up. Unlike the previous
tables the period of follow-up is limited to 1981-1989, with 1981-85 the base time period. The
effect of using this indicator of occupational stability is to reduce the overall number of
occupations showing a significant mortality differential to just two, semi-skilled factory workers
(odds ratio 1.77) and other semi-skilled workers (1.85). The range from best to worst occupation
is now over 2, the same range as found among men's occupations, though the low parameter is
not well determined. The consistently high mortality ratios shown by semi-skilled factory workers
is consistent with other evidence discussed below.
Two proxies for occupational stability are combined in Table 11, taking women who were in the
16
same occupation in 1971 and 1981 and who worked full time in 1971. In comparison with Table
10, two more occupation groups, skilled manual workers and semi-skilled domestic workers,
show significantly higher mortality ratios than clerical workers. In addition other intermediate
occupations have an odds ratio above 2, although this is based on just 6 deaths. Table 11 also
shows the mortality ratios for women who were in the same occupation in 1971 and 1981 and
who did not have a dependent child in 1971. Again the occupational differentials are sharpened
compared to those shown in Tables 8, 9 and 10. This time it is other semi-skilled occupations
which show a relative odds ratio above 2 (based on 16 deaths). The estimates of Table 11 suggest
greater, though less well-determined differentials than Tables 7 and 10. The high upper
confidence limits associated with the high estimates meant it was not possible to plot the whole
set on the common scale with Figures 1 and 2.
Permanent Sickness
‘Thus far there does not appear to be a great deal of clearly patterned variation in the mortality of
women by occupation. The identification of occupationally stable sub-groups increases the range
of estimated mortality differentials to something like that found among men, but not in a wholly
consistent or very well determined manner. It is possible that mortality analysis may fail to detect
any health hazards of a particular occupation that lead to general ill health without being life
threatening. There is partial evidence on morbidity in the LS in the form of responses on
permanent sickness in the Census question on economic activity.
The identification of permanently sick women in the 1981 Census only refers to women who have
not been described as housewives or retired. Neither does it apply to anyone who, though in poor
health, is still in employment. While the number of women who have retired will be small in this
sample, under 60 in 1981, the exclusion of housewives who have left the labour force due to ill
health is likely to understate poor health and may bias associations that can be detected. Overall,
1.3% of women who were recorded in an occupation in 1971 were permanently sick in 1981. This
ranged fiom none of the 393 professional women to 2% of the 4300 semi-skilled factory workers.
‘Table 12 and Figure 3 show the results fiom a logistic regression with permanent sickness in 1981
as the outcome variable. Differentials are somewhat more marked than in the mortality analysis,
17
the ratio of worst to healthiest being 2.4. Manual occupations showed significantly higher
chances of recording permanent sickness than clerical and most other non-manual groups, by
factors approaching 2 (2.3 for semi-skilled factory workers). Thus far, a similar and slightly more
marked pattern than for mortality. The odds ratio of 2 for nurses' permanent sickness contrasts
with their relatively low mortality Semi-skilled factory workers showed an odds ratio above two.
Salesworkers were on a par with 'other intermediates,' above clerical workers, but not
significantly so. Professional women had to be excluded from the model because none of this
small group was recorded as permanently sick in 1981. Table 13 shows the estimates of being
permanently sick in 1981 for two occupationally stable sub-samples: full time workers and women
with no dependent children. These sub-groups show similar estimates to all women. This
suggests that the patterns of permanent sickness by 1971 occupation cannot have been
systematically different for the excluded groups presumed to have mixed occupational histories
behind them.
DISCUSSION
This paper attempts to overcome two problems in the study of female occupational mortality. We
adopt a classification that had been developed specifically for women's occupations in the Women
and Employment Survey. We use that survey itself to identify sub-groups of women that were
occupationally stable. The LS was used to consider the occupational mortality of all employed
women and for identifying occupationally stable sub-groups of women. One third of all
employment histories up to 1971 had been in occupations other than the one then current. As this
rate varied across demographic and labour market groups, it was possible to identifL both
relatively stable occupations and sub-groups of women who were likely to have spent a large
proportion of their employment experience in the occupation recorded at Census. Professionals,
teachers and nurses appeared to be stable categories; full time workers and women without
dependent children were occupationally stable. Three occupations were consistently unstable,
other intermediate workers, semi-skilled factory workers and other semi-skilled workers.
The mortality analysis suggested that differentials between women's occupations are modest, and
little affected by household economic resources. They may, however, approach those recorded
18
for men's among the sub-groups identified as occupationally stable. Semi-skilled factory workers,
who had been shown to be occupationally unstable, were one of the occupations that consistently
showed significantly high mortality relative to clerical workers. For other categories estimates
were not always consistent or well determined. Saleswomen did not emerge as being particularly
endangered. On a health hierarchy we would place them on a par with skilled manual workers,
though on a pay hierarchy they would be placed beneath them. Moreover, there was some
evidence of a greater occupation effect for women becoming permanently sick rather than dying.
We find some support for the idea that occupational instability obscures underlying differentials
in mortality associated with women's occupation, though we have also found that 'unstable'
occupations (intermediate, semi-skilled factory and other semi-skilled) tend to show raised
mortality even before the likely mobile cases have been discarded.
The findings here of some occupational differentials in women's mortality are more significant
than in earlier results fiom the LS (Moser, Goldblatt and Pugh, 1990, Sloggett et a1 forthcoming).
The former used a finer occupational classification, the latter a broader one than used here. A
possible reason for the different findings is that neither of the other studies had as much evidence
on mortality, ten and fifteen years of follow-up respectively as opposed to nearly nineteen. A
reason to be cautious about comparison is that this analysis is confined to employed women under
5 1 in 1971. Once non-employed women are considered, the importance of household
characteristics appears to gain salience.
We found fairly consistent high mortality and sickness rates among women doing semi-skilled
factory work. This is itself consistent with Moser and colleagues' finding of significantly raised
mortality in engineering and allied trades (Moser et al, 1990). It is also consistent with evidence
such as that in the Women and Employment Survey which showed a positive correlation between
stress and factory work (Joshi, 1984). Our finding of relatively high mortality among the nonmanuals in the 'other intermediate group' is unlikely to be explained by our finding that much of
the experience behind these workers was in lower ranked, mainly clerical occupations. It is more
likely to have a common explanation with that of the relatively raised longstanding morbidity
reported by Arber (1989) for women in SEG 2. This category comprises Employers and
Managers who are classed within W S category 'other intermediate'. Such jobs are often not
19
traditionally female. If it is indeed such jobs responsible for the higher risk, it could take more
time to accumulate the evidence.
Analysis of self-assessed health in the 1984 Health and Lifestyle Survey found that all manual
groups and sales women were more likely to consider themselves in poor health (Macran et al,
1994, Macran et al, 1993). However the latter paper finds that occupational patterns are not
consistent across types of health indicator. Counts of illness symptoms were relatively high
among those with factory, unskilled or intermediate occupations. The unskilled were generally
in the worst health, and shop workers emerged as being between manuals and other non-manuals
on most counts, much as they do here.
Why have we not found stronger evidence of specific occupational hazards? One answer could
be that there are indeed hazardous occupations which are covered up by the classification used
here. Another is that women do not generally get dangerous types of work. Occupational hazards
may expose a worker to accidents which may result in death or they may expose a worker to
substances which are detrimental to health in the long term, for example asbestos. Women rarely
work in many occupations where the risk of accidents is high, for example, mining or building.
Unequal access to the labour market, and conventions of what work is suitable for women seems
to protect most of them against many types of hazard. A third possibility is that intermittent job
histories may protect many women fi-om prolonged exposure to noxious substances over time.
We have shown the usefblness of the classification of occupations used here, derived specifically
for considering women's occupations, and also its limitations. The occupation groups comprise
a wide range of jobs. It is possible that using a finer breakdown of individual jobs would result
in a more notable effect of occupation on mortality. There may, for example, be hidden hazards
for the small minority of women in 'mens jobs' obscured by their small number. Work summarizing
the occupational mortality ofwomen fi-om the 1970-72 Decennial Supplement reports that 63 per
cent of the occupational units (jobs) considered had at least one significantly raised mortality ratio
among the causes of death examined (Roman, Beral and Inskip, 1985).
A hrther lunitation of our use of this classification of occupations is the low proportion of women
20
who could be classified. The Census only effectively collects an occupation for women currently
in the labour force. The 1971 Census does not record, for 51% of women aged 15-64 whether
they had ever been employed, nor what their last, or most usual, occupation was. If there is an
occupation effect on morbidity or mortality it is plausible that some of their victims would have
left the labour force (witness the analysis of permanent sickness presented here). Such possible
occupation effects cannot be examined without knowledge of previous occupations, or even
longer follow-up in the LS. Data collection techniques for the recording of women's occupations
could be improved. Until then the effect of occupation on women's mortality remains, at lease
partially, obscured. There is also scope for better techniques of collecting data on womenls
health.
We can reach some conclusions beyond recommending better data. The indications of this study
are that females as well as males in manual jobs face higher mortality than clerical workers. For
neither women nor men is the occupational risk attributable to household circumstances. This
strongly suggests some health disadvantage attaches to the occupation rather than the incumbents.
There is not yet much long term evidence on women entering non-traditional occupations, but it
should be particularly important to monitor their health, as well that of women employed longterm in manual work.
21
References
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Countries, Gower, Aldershot, 250-279.
Dale, A., Gilbert N. and Arber, S. (1985) 'Integrating women into class theory' Sociolom Vol 19 no
3, 384-409.
Davies, H., Joshi, H. and Clarke, L. (1993) Is it cash the deprived are short of! BSPS Conference
paper, Newcastle, September 1993.
Dex, S . (1987) Women's Occupational Mobility, Macmillan Press, London.
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Fox A.J. and Collier, P.F. (1976) 'Low mortality rates in industrial cohort studies due to selection for
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Fox A.J., Goldblatt P. and Jones D. (1 990) ' Social Class Mortality Differentials: Artifact, Selection of
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Goldblatt, P. and Fox, A.J. (1990) 'Mortality of men by occupation' In Goldblatt, P. (eds)
1,ongitudinal Study: Mortality and Social Organisation. LS Series no 6, London: HMSO 110-129.
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Joshi, H. and Newell, M. L. (1987) Job downgrading after childbearing. In M Uncles (ed) London
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Joshi, H. (1984) Women's participation in paid work: further analysis of the Women and Employment
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Joshi, H. and Owen, S. (1987) 'How long is piece of elastic? The measurement of female activity
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HMSO, London.
Macran, S., Clarke, L. and Joshi, H. (1993) Women's Health: Dimensions and Differentials. Paper
presented at the XXII General Population Conference, IUSSP, Montreal.
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Macran, S., Clarke, L., Sloggett, A. and Bethune, A. (1994) Women's Socio-economic status and selfassessed hea1th:identifjring some disadvantaged groups, Sociolop of Health and Illness, Vol. 16 No 2,
182-208.
Martin, J. and Roberts, C. (1984) Women and employment: A lifetime perspective, Department of
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Moser, K., Goldblatt, P. and Pugh, H. (1990) 'Occupational mortality of women in employment' In
Goldblatt, P. (ed) Longitudinal Studv: Mortalitv and Social Oryanisation. LS Series no 6, 129-144,
HMSO, London.
Moser, K., Pugh, H. and Goldblatt, P. (1990) 'Mortality and the social classification of women' In
Goldblatt, P. (eds) Longitudinal Study: Mortality and Social Organisation, LS Series no 6, 145-162,
HMSO, London.
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OPCS, (1986a) Occupational Mortality: The Registrar General's Decennial Supplement for Great Britain
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HMSO, London.
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Roman, E., Beral, V. and Inskip, H. 'Occupational Mortality among women in England and Wales' British
Medical Journal, 292, pp 194-196.
Sloggett A., Clarke L., Joshi H. E. and Eames (forthcoming) Ecological and Individual Factors in
Women's Mortality in England. in Clarke J and Zaba B (eds) Environment and Population Change. Liege:
Ordina (in press).
Stevenson, T.H.C. (1927) Decennial Supplement, England and Wales, 1921, HMSO, London.
Stewart, M. and Greenhalgh, C. (1984) Work history patterns and the occupational attainments of
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Medicine. 285-297.
23
Table 1 Women's Occupational Groups
1 . Professional occupations
Barrister, solicitor, chartered and certified accountant, university teacher, doctor, dentist, physicist, chemist,
pharmacist, dispensing optician, qualified engineer, architect, town planner, cMl servant (Assistant
Secretary and above).
2. Teachers
Primary and secondary school teacher, teachers in further and higher education (not universities), head
teacher, nursery teacher, vocational and industrial trainer.
3. Nursing, medical and social occupations
SRN, SEN, nursing auxiliary, midwife, health visitor, children's nurse, matron, dental nurse, dietician,
radiographer, physiotherapist, dispenser, medical technician, houseparent, welfare occupations (inc social
workers), chiropodist, occupational therapist.
4. Other intermediate non-manual occupations
Civil Servants (Executive Officer to Senior Principal and equiv. in central and local govt), computer
programmer, systems or 0 & M analyst, librarian, surveyor, personnel officer, manager, self-employed
farmer, shop keeper, publican, hotelier, buyer, company secretary, writer, journalist, artist, designer,
windowdresser, entertainer, musician, actress.
5. Clerical occupations.
Typist, secretary, shorthand writer, clerk, receptionist, personal assistant, cashier (not retail), telephonist,
office machine operator, computer operator, punch card operator, data processor, draughtswoman,tracer,
market research interviewer, debt collector.
6. Shop assistant and related sales occupations
People selling goods in wholesale or retail establishments, cashier in retail shop, check-out and cash and
wrap operator, petrol pump attendant, sales representative, demonstrator, theatrelcinema usherette,
programme seller, insurance agent.
7. Skilled occupations
Hairdresser, manicurist, beautician, make-up artist, cook, domestic and institution housekeeper, nursery
nurse, travel stewardess, ambulance women, van driver and deliveries, baker, weaver, knitter, mender,
darner, tailoress and dressmaker (whole garment), clothing cutter, milliner, upholsterer, bookbinder,
precision instrument assemblers, laboratory assistant, driving instructor, policewoman.
8. Semi-skilled factory work
Assembler, packer, labeller,grader, sorter, inspector, machinist, machine operator, people wrapping, filling
or sealing containers, spinner, doubler, twister, winder, reeler.
9. Semi-skilled domestic work
Waitress, barmaid, canteen assistant, childminder, playground or playgroundsupervisor, nanny, au pair,
home help, care attendant, ward orderly, housemaid, domestic worker.
10. Other semi-skilled occupations
Agricultural worker, groom, kennel maid, shelf-filler, bus conductress, ticket collector, postwoman, mail
sorter, laundress, dry cleaner, presser, mail order and catalogue agent, market and street trader, collecting
saleswoman, traffic warden, telephone operator.
11. Unskilled occupations
Cleaner, charwoman, kitchen hand, labourer, messenger.
Source:Martin and Roberts (1984)
24
Table 2
Distribution of occupation,Women and Employment Survey and OPCS LS, 1971
Women aged 16-59 in 1980
I
Occupation
Survey
WES
N=2509
OPCS LS
Survivors to 1980
N=496501
Professional
0.4
0.9
1.o
Teacher
4.8
5.3
5.3
Nursing
6.6
6.6
7.3
Other Intermediate
4.2
5.9
6.0
Clerical
29.5
32.1
31.8
Shop Assistant
11.7
8.2
10.6
Skilled occupation
7.8
9.8
8.1
Semi-skilled factory
1.7
10.8
9.8
22.6
9.9
9.9
Other semi-skilled
7.3
4.1
4.0
Unslulled
3.4
6.4
6.3
Semi-skilled domestic
-
OPCSLS
N=49088
Source: Women and Employment Survey, LSHTM analyses (WES)and OPCS Longitudinal
Study (LS) as analysed at LSHTM
'The sample size is larger for h s calculation because it does not exclude women who have missing data on the other
co-variates.
25
Table 3 Percentage of time in paid work in the occupation current in 1971, by age group and 1971 occupation, women in employment in 1971
15-24
25-34
-
n
2
79
3. Nursing
4. Other
intermediate
35-44
-
74
42
75
29
84
121
39
37
67
39
37
37
60
44
87
305
77
165
73
137
81
740
130
55
69
66
50
59
66
73
29
55
66
293
32
54
64
195
143
149
11
41
16
31
42
149
69
105
75
141
73
568
164
32
42
42
41
56
41
184
171
44
19
59
17
62
21
57
84
172
76
77 1
65
56 1
63
573
67
2509
146
31
91
53
79
56
68
68
23
80
46
5. Clerical
91
334
6. Shop
7.Skilled
occupations
8. Semi-skilled
factory
9. Semi-skilled
domestic
76
82
91
79
150
74
116
10. Other
semi-skilled
41
28
35
11. Unskilled
54
22
All
81
833
Months
49
79
Average months
per employed
woman
n
10
n
6
1 . Professional
2. Teaching
n
5
All ages
under 51
n
2
-
?40
45-5 1
Y
O
5
62
YO
-
80
7
126
202
TO
268
Source: WES
26
YO
YO
96
117
117
168
32
146
Table 4 Percentage of time employed in the same occupation as that observed in 1971, by selected descriptions of fertility history
Never had a child
Ever had
a child
(Age of youngest child)
0-4
-
n
6
YO
-
n
4
83
79
79
3. Nursing
4. Other
intermediate
73
49
93
5 . Clerical
6. Shop
7.Skilled
occupations
8. Semi-skilled
factory
9. Semi-skilled
domestic
5-9
All with no
dependent
children
10-14
-
n
2
YO
-
n
1
42
92
10
74
15
5
73
11
16
57
28
18
52
75
33
26
6
66
40
14
88
456
75
284
86
60
80
84
67
75
119
50
174
36
60
95
45
57
53
100
49
62
49
6
30
36
80
202
71
366
67
71
70
118
10. Other
semi-skilled
49
31
39
153
36
34
31
11. Unskilled
63
30
55
54
38
12
77.5
1176
56.4
1333
60.9
294
Y
O
1 . Professional
2. Teaching
All
Y
O
Yo
64
81
n
111
5
70
48
72
66
83
530
50
57
36
168
22
60
70
9
49
12
62
66
78
3 13
48
36
31
48
71
55
12
59
18
61
42
60.2
399
59
270
72
1546
18
9
-
12
Source: WES
27
24
YO
n
1
6
91
71
131
Table 5
Percentage of time in paid employment in same occupation as 1971, by
occupation and whether worked full or part time in 1971
Occupation in 1971
Full Time
Part
Time
YO
n
YO
n
-
8
-
2
Teachers
83
101
74.7
19
Nursing
70.9
115
66.3
49
Other intermediate
43.4
96
-
10
Clerical
82.3
591
77.1
147
Shop Assistant
59.2
172
49.5
116
Skilled occupation
68.4
195
58.9
41
Semi-skilled factory
-
11
28
30
Semi-skilled domestic work
75.9
33 1
70.4
115
Other semi-skilled
44.6
59
38.8
123
Unskilled
62.3
55
47.5
29
All
71.4
1690
60.2
79 1
Professional
Source: WES
28
Table 6
Percentage of time in paid employment in same occupation as 1971, by
occupation, full time employment and no dependent child 1971
Occupation in 1971
Full time OR
no dependent
child
Full time AND
no dependent
child
YO
n
Y
O
n
-
6
74.5
8
Teacher
80.7
82
82.7
110
Nursing
71.0
115
70.2
131
Other Intermediate
47.2
69
43.8
97
Clerical
83.8
487
81.8
627
Shop Assistant
67.2
125
56.5
213
Skilled occupation
71.4
8
68.6
165
Semi-skilled factory
54.7
114
43.1
14
Semi-skilled domestic
79.6
239
76.0
394
Other semi-skilled
46.3
35
46.9
94
Unskilled
63.5
55
60.1
58
All
74.6
1298
70.3
191.1
Professional
Source: WES
29
Table 7 Proportion of women by occupation in 1971 who were recorded in the same occupation in 1981
Occupation 1971
n
% in same occupation
1981
Professional
159
61.9
Teachers
1663
89.6
Nurses
1736
74.6
113
11.4
Clerical
6952
77.1
Shop Assistant
1137
49.6
Shlled Manual
1244
42.1
Semi-skdled factory
1444
45.2
Semi-Skilled domestic
1388
43.5
Other Semi-Skilled
383
32.7
Unskilled
830
41.1
17049
58.2
Intermediate
All
Source: OPCS Longitudinal Study
30
N
c
c
0
d
3
P
2
I
x
d
r.
N
1
N
x
2
r.
1
01
W
9
Y
2
I-
2
n
z
n
0
2
01
Y
3
n
r.
c1
0
9
r.
3
N
$
r.
$
I
2
d
2
d
0
Y
3
2 I=
N
W
o
n
m
0
o
t01
N
o
s
o
0
W
2
I
I-
-?
e4
Y
2
N
3
In
3
I
0
9
4
r!
3
I-
00
0
0
I
z
0
2
W
0
n
0
F
d
n
?
2
3
n
Y
N
2
Y
1
I
01
01
U
d
d
x
n
2 b
d
P
N
01
c?
n
m
0
9
I
0
0
01
1
\4
2
N
0
8 8
0
0
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-?
1
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01
I-
0
9
r.
2
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..
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?,
L
m
Table 9 Mortality odds ratios by occupation adjusted for age in 1971 and duration of follow up:
full time workers and women with no dependent children 1971.
Full Time employed
No dependent children
N=31291
Occupation in197 1
Deaths
76-89
N=30066
O.R.
t
P
Deaths
76-89
O.R.
t
P
Professional
10
1.os
0.15
0.881
12
1.29
0.86
0.388
Teachers
79
1.23
1.64
0.1
57
1.12
0.81
0.42
Nurses
65
0.94
-0.42
0.676
61
0.96
-0.25
0.8
Intermediate
123
1.28
2.33
0.02
107
1.29
2.29
0.022
Clerical
330
1.oo
358
1.oo
Shop Assistant
92
1.32
2.34
0.02
137
1.25
2.17
0.03
Skilled Manual
167
1.26
2.42
0.015
168
1.31
2.85
0.004
Semi-SkilledFactory
206
1.5
4.45
0
21 1
1.55
4.92
0
Semi-skilleddomestic
101
1.6
4.05
0
143
1.33
2.78
0.005
Other Semi-Slulled
77
1.6
3.66
0
78
1.59
3.63
0
Unskilled
46
1.43
2.25
0.025
105
1.54
3.81
0
Source: OPCS Longitudinal Study
32
Table 10
Women in the same occupation 1971 and 1981: Mortality odds ratios
controlling for age and follow-up
Total cases= I1 165
All Women
Occupation in 1971 & 1981
Deaths
81-89
O.R.
t
P
4
1.12
0.21
0.83 1
Teachers
47
1.22
1.21
0.228
Nurses
30
0.79
-1.16
0.244
6
1.9
1.52
0.128
170
1.oo
Shop Assistant
42
1.17
0.88
0.379
Slulled Manual
46
1.33
1.7
0.089
Semi-Slulled Factory
73
1.77
4.02
0
Semi-skilled domestic
59
1.27
1.55
0.121
other semi-Slulled
21
1.85
2.6
0.009
Unskilled
34
1.16
0.79
0.432
Professional
Intermediate
Clerical
Source: OPCS Longitudinal Study
33
Table 11 Women in the same occupation 1971 & 1981: Mortality odds ratios adjusted for age and follow-up.
Full time employed and women with no dependent children.
Full time employed
1971 N=10769
Occupation
in 1971
Deaths
81-89
t
P
O.R.
No dependent children 1971
N= 10076
Deaths
8 1-89
O.R.
t
P
Professional
3
1.26
0.39
0.699
2
1.09
0.12
0.908
Teachers
42
1.39
1.79
0.073
31
1.40
1.64
0.102
Nurses
16
0.68
-1.42
0.156
17
0.83
-0.71
0.479
Intermediate
6
2.22
1.86
0.063
5
2.00
1.49
0.137
Clerical
110
1.oo
119
1.oo
Shop
Assistant
18
1.21
0.72
0.468
33
1.34
1.46
0.146
Skilled
Manual
39
1.51
2.17
0.030
36
1.46
1.96
0.050
Semi-Skilled
Factory
54
1.92
3.86
0.000
54
1.94
3.95
0.000
Semi-skilled
domestic
21
1.80
2.42
0.015
27
1.19
0.79
0.428
Other SemiSkilled
14
1.93
2.26
0.024
16
2.15
2.81
0.005
Unskilled
9
1.73
1.55
0.121
20
1.39
1.34
0.181
Source OPCS Longitudinal Study
34
Table 12
Odds ratios of being permanently sick in 1981 by occupation and age in 1971
All Women under 51
Total cases= 436 7
Occupation in 1971
Sick 81
O.R.
t
P
Professional
0
na
na
na
Teachers
15
0.95
-0.18
0.856
Nurses
39
2
3.61
0
Intermediate
28
1.32
1.26
0.206
Clerical
96
1
Shop Assistant
40
1.31
1.4
0.16
Skilled Manual
59
1.77
3.4
0
Semi-Skilled Factory
87
2.32
5.61
0
Semi-skilled domestic
65
1.63
3
0.003
Other Semi-Skilled
26
1.84
2.72
0.007
Unskilled
52
1.98
3.9
0
20-24
23
1
25-29
26
1.73
1.91
0.056
30-34
34
2.27
3.01
0.003
35-39
75
3.96
5.73
0
40-44
121
5.55
7.46
0
45-49
228
9.3
-
10.08
0
Age in 1971
Source: OPCS Longitudinal Study
35
Table 13
Odds ratios of being permanently sick 1981 by occupation 1971 by age for
women who worked full time or had no dependent children in 1971, age
standardized
No dependent children
N=265 16
Full Time employed
N=27525
Occupation in
1971
Sick 81
t
P
Sick
81
O.R.
O.R.
t
P
Professional
0
na
na
na
0
na
na
na
Teachers
13
0.8
-0.61
0.54
12
0.98
-0.1
0.94
Nurses
28
1.8
2.63
0.01
26
1.81
2.63
0.01
Intermediate
23
1
0.17
0.86
26
1.4
1.47
0.14
Clerical
81
1
87
1
Shop Assistant
19
1.2
0.6
0.55
29
1.17
0.72
0.47
Skilled Manual
45
1.5
2.11
0.04
43
1.48
2.08
0.04
Semi- Skilled
71
2.3
4.94
0
72
2.35
5.25
0
Semi-skilled
domestic
21
1.5
1.64
0.1
40
1.68
2.65
0.01
Other SemiSkilled
17
1.5
1.47
0.14
21
1.84
2.47
0.01
Unskilled
14
2
2.28
0.02
27
1.83
2.67
0.01
Factory
Source OPCS Longitudinal Study
36
Mortality by Occupation in 1971
Figure 1:
All women employed in 1971, controlling for age and follow up
x Adjusted for car access
Relative Odds Ratio
4.0
3.0
2.0
1.o
0.0
Prof
Teach
Nurse
Inter
Cler
Shop Skill Factr
WES Occupational Group
I 95% /C.I I Odds ratio
Dom
0th ss
Unsk
Figure 2:
Women in the same occupation in 1971 and 1981
Mortality by Occupation, controlling for age and follow up
Odds relative to Clerical
~
4.0
3 .O
2.0
'I
T
1.o
0.0
- -
Prof
Teach
Nurse
Inter
1-
Cler
Shop
Skill
Factr
WES Occupational Group
+Odds Ratio
I----
Dom
Othss
Unsk
I
I
I
I
I
L
4
0
I
I
I
I
I
I
I
I
I
1
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
0
cc;
I
I
I
I
1-b
I
I
1
I
I
I
I
I
I
I
I
t+l
,
I
I
I
I
I
I
I
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m
E
a"
I
0
0
I
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0
Pi
0
WORKING PAPERS USING
OPCS LONGITUDINAL STUDY
*We do not supply copies of papers which have been
subsequently published, or for various other reasons have
been discontinued
No
*
1
Title
Author ( 8 )
Migration and health of the elderly.
D. Dawkins
1982
*
*
2
Housing tenure: an example of using record
linkage to study differentials in cancer
incidence, survival and mortality.
3 A review of the literature on migration in
England and Wales.
*
4 Social mobility around the time one has
children. Now published in Lonsitudinal
Studv No 2, 1985; OPCS, HMSO, London.
* 5 Cause of death amongst people registered
with cancer in 1971-75.
D. Leon
1983
E. Hoinville
1983
A.J. Fox
1984
D. Leon
A. Adelstein
1983
* 6 Bereavement and cancer: some results using
data from the LS. Now published in British
Medical Journal, 25 August 1984, 289: 461-464.
D.R . Jones
P.O. Goldblatt
D.A. Leon
1984
*
7 From official health statistics to interactive
epidemiology data.
A.J. Fox
D.R. Jones
D. Leon
1983
*
8 LS mortality 1971-81 in regional heart study
areas. Some preliminary notes on the
relationship with region and water hardness.
*
9 Water nitrates and stomach cancer: some
1984
P.O. Goldblatt
mortality results from the OPCS Longitudinal
Study.
D.R. Jones
1984
- "10 Years ont1.
Now published in: PoDulation Trends, 1984;
A. Brown
A . J . Fox
37: 20-22.
1984
Preliminary outline of projects to be covered
I l l 0
years on" .
A.J. Fox
.E.
M .D. Grundy
*10 OPCS Longitudinal Study
*11
D . R . Jones
by
*12 Cancelled
'13
E.M.D. Grundy
A.J. Fox
Migration during early married life.
Now published in Journal of EuroDean
Association for PoDulation Studies. 1985,
1984
1: 237-263.
K.A. Moser
P. Goldblatt
14 Mortality of women in private and non-private
households using data from the OPCS Longitudinal
Study.
1984
H.S. Pugh
15 Estimating the extent of homeworking.
1984
A.J. Fox
P.O. Goldblatt
*16 Social class mortality differentials: artefact
selection or life circumstances?
Now published in Journal of Epidemioloqy and
Communitv Health, 1985, 39: 1-8.
1984
*17 Cause of death in widow(er)s and spouses.
Now published in Journal of Biosocial Science
D.R. Jones
P.O. Goldblatt
1987, 19; 1: 107-121.
1984
*18 Unemployment and mortality in the OPCS
K.A.
A.J.
D.R.
P.O.
Longitudinal Study. Now published in
The Lancet, December 1984: 1324-1329.
Moser
Fox
Jones
Goldblatt
1984
*I9 Divorce, widowhood, remarriage and geographic
E.M.D. Grundy
mobility.
Now published in Journal of
Biosocial Science, 1985, 17: 415-435.
20
1984
Some notes on the effects of level of aggregation D.R. Jones
on analysis of mortality in the OPCS LS by area.
1984
*:21 Male socio-demographic mortality differentials
from the OPCS Longitudinal Study 1971-81.
A.J.
D.R.
K.A.
P.O.
Shortened version published in PoDulation Trends
1985, 40: 10-16. Full version published in
Proceedings of the American Statistical
Association Meetinq, August 13-16, 1984.
f22
Fox
Jones
Moser
Goldblatt
1984
D.R. Jones
P.O. Goldblatt
Mortality following widowhood: some further
results from the OPCS Longitudinal Study.
Now published in Stress Medicine, 1986, 2:
1984
129-140.
D.R. Jones
and others
23 Mortality 1971-81 and migration in England and
Wales in 1966-71: some data from the OPCS
Longitudinal Study.
1984
D.R. Jones
24 Introductory notes on regression models in the
analysis of mortality data in the OPCS LS.
*25 Change in death rates with length of follow-up.
1985
.
A.J. Fox
P.O. Goldblatt
1985
f26 Mortality of women in the OPCS Longitudinal
Study: differentials by own occupation and
household and housing characteristics.
27 An investigation of alternative methods of
calculating person-years-at-riskin the
OPCS LS.
K.A. Moser
P.O. Goldblatt
1985
D.R. Jones
1985
*28 Migration and fertility behaviour in England
E.M.D. Grundy
*29 A Longitudinal perspective on recent socio-
A.J. Fox
E.M.D. Grundy
and Wales. Now published in Journal of
Biosocial Science, October 1986, 17, 4: 415-435.
demographic change. Now published in the
Proceedinss of British Societv for PoDulation
Studies' Conference on IIMeasurins
SocioDemosraDhic Chanse", Occasional Paper 34
OPCS .
f 3 0 Unemployment and mortality: further evidence
from the OPCS Longitudinal Study. A shortened
version published in The Lancet, February 1986:
365-367.
1985
1985
K.A.
A.J.
D.R .
P.O.
Moser
Fox
Jones
Goldblatt
1985
Stress and heart disease: evidence of association
between unemployment and heart disease from the
OPCS Longitudinal Study.
The Postsraduate Medical Journal, 1986, 62: 797-799.
Proceedings of The Coronary Prevention Group
Conference on 18-19 November 1985, tlDoesStress
Cause Heart Attacks?": 123-130.
31 Socio-economic differentials in cancer.
f32
D.A. Leon
A review paper written for the International
Agency for Research in Cancer.
1985
Socio-economic differences in cancer and heart
disease. In "Health Inequalities in European
Countries1I,Proceedings of ESF/ESRC Workshops.
Gower Press 1988, ed. A.J. Fox.
D.A. Leon
R. Wilkinson
f33 Mortality and deprivation: evidence from the
OPCS Longitudinal Study. Edited proceedings
of the Eugenics Society Symposium 1985
The Political Economy of health and Welfare.
Ed W.M. Keynes.
A.J.
Fox
D.A. Leon
f34 Retirement migration and its consequences in
England and Wales. Aseins and Societv, 7:
59-82, 1987.
E.M.D. Grundy
*35 Some preliminary notes on status incongruity
B. Scott
and mortality.
1986
1985
"36
D.R. Jones
Heart disease mortality following bereavement.
Now published in 1
Attacks? Proceedings of Conference of The
Coronary Prevention Group 1 8 - 1 9 November 1 9 8 5 :
77-102.
Heart disease mortality following widowhood:
D. R Jones
some results from the OPCS Longitudinal Study.
Journal of Psvchosomatic Research, 1 9 8 7 , 3 1 ; 3 :
325-333.
*37
*38
"39
Racial minorities in the London labour and
housing markets: a longitudinal analysis
1971-81.
To Appear as "Racial minorities and
industrial change" In Misration. EmDlovment
and the New Urban Order.
Ed. M. Cross. Cambridge University Press,
Comparative Ethnic and Race Relations Series.
C. Hamnett
W. Randolph
C. Evans
Preliminary notes on changes in male economic
activity patterns, 1 9 7 1 - 8 1 .
A.J. Fox
Socio-demographic mortality differentials: new
longitudinal perspectives. Paper written for
Symposium "The Social Aetiology of I1l-Healthlf
at French Ministry of Research and Technology,
Paris, March 2 0 , 1 9 8 6 . Now published in the
Revue d'eDidemiolosie et de sante Dublime,
A.J. Fox
35:
*40
41
*42
20-27,
1985
1986
1986
1987
Cancelled
Using the OPCS Longitudinal Study to classify
ethnic origin.
J. Webster
Social class mortality differentials of men
aged 1 5 - 6 4 in 1 9 8 1 : a note on first results
from the OPCS Longitudinal Study for the period
P.O.Goldblatt
1986
1986
1981-83.
(Updated version in Pomlation Trends no 51)
f43
Unemployment and mortality, 1 9 8 1 - 8 3 : follow up
of the 1 9 8 1 LS Census sample.
A shortened version published in the British
Medical Journal, 10 January 1 9 8 7 , 2 9 4 : 8 6 - 9 0
K.A.
P.O.
A.J.
D.R.
Moser
Goldblatt
Fox
Jones
1986
.44
f.45
46
Labour market restructuring in Greater London
1 9 7 1 - 8 1 : Evidence from the OPCS Longitudinal
Study.
C. Hamnett
W. Randolph
Socio-tenurial polarisation in London: a
longitudinal analysis, 1 9 7 1 - 8 1 .
Shortened version in Urban Studies.
C. Hamnett
W. Randolph
The social classification of women.
(Now reprinted as SCOWW - see p. 7 ) .
H. Roberts
R. Barker
1986
1986
1986
47
48
*49
-
Have inequalities in health widened?
(Mortality differences in the 1 9 7 0 s and early
A.J. Fox
P.O. Goldblatt
1980s).
1986
Modelling socio-economic change: an application
M.C. Shewry
1987
of generalised linear models to changes in the
circumstances of individuals between 1 9 7 1 and 1 9 8 1 .
Longitudinal insights into the ageing population. A.J. Fox
In D. Evered and J.Whelan (Eds). Research and the 1 9 8 7
A
CIBA Foundation Symposium,
John Wiley & Sons, London.
*50 New longitudinal insights into relationships
between unemployment and mortality.
Stress Medicine, Vol 4 , No 1, January-March 1 9 8 8
pp 1 1 - 1 9 .
51 A social classification scheme for women.
A.J. Fox
M.C. Shewry
1987
H. Roberts
R. Barker
1987
*52 What are people doing when they grade women's
work? m
i 1 m , Vol 40
No. 1 March 1 9 8 9 .
H. Roberts
R. Barker
1987
53 Mortality differences at working ages: the use
of generalised linear models to compare measures.
P. Goldblatt
Inequalities in women's health: developing an
alternative approach. A shorter version published
in 1
, 30 April 1 9 8 8 ,
K. Moser
H. Pugh
P. Goldblatt
2 9 6 : 1221-1224.
1987
Social class differences in mortality in Great
Britain around 1 9 8 1 .
Journal of Institute of British Actuaries.
S. Haberman
D. Bloomfield
Socio-economic status and cancer: results from
the OPCS Longitudinal Study.
M. Kogevinas
M.G. Marmot
A.J. Fox
54
*55
56
1987
1987
1988
*57
f58
Inequalities in women's health in England and
Wales: mortality among married women according
to social circumstances, employment
characteristics and life cycle stage
Published in Senuq, Vol XLVI, pp 7 1 - 8 4 , 1990.
K. Moser
H. Pugh
P. Goldblatt
Mortality of employed men and women.
A
I
I
J
I
I
J
Vol 20, Part 3: pp 285-306, 1 9 9 1 .
P. Goldblatt
A.J. Fox
D. Leon
1988
1988
59
Mortality of men by occupation.
P. Goldblatt
A.J. Fox
1988
60 Associations between unemployment and
fertility among young women in the early 1980s.
61 The social and geographical mobility of South
Asians and Caribbeans in Middle Age and later
Working Life.
*62 Smoking, class and lung cancer mortality among
women.
Social Science and Medicine, Vol. 32,
NO. 10, pp 1105-1110.
B. Penhale
1989
A. Stuart
1989
H.
C.
P.
S.
Pugh
Power
Goldblatt
Arber
1989
- economic status and breast cancer in
England and Wales: time trends in incidence,
survival and mortality.
63 Socio
M. Kogevinas
P. Goldblatt
H. Pugh
1989
64
The Longitudinal Study: households, families
and fertility.
(Now available as LS User Guide No. 1).
65 Family and demographic circumstances and
mortality among married women of working ages
B. Penhale
1989
A. Mercer
P. Goldblatt
H. Pugh
1989
66 Occupational Mortality of women aged 15-59 at
death in England and Wales.
K. Moser
P. Goldblatt
1990
67 English and French households in historical
perspective.
Also in INSEE ( I n s t i t u t N a t i o n a l d e l a
S t a t i s t i q u e e t d e s & t u d e s &conomiques) no 8,
Paris: February 1991.
68 Living arrangements of young adults in France
and England.
R. Wall
1990
B. Penhale
1990
69 Residence patterns of the elderly in England
and France.
(Also in INSEE, as no 67 above)
70 Age difference asymmetry and a two-sex
perspective.
R. Wall
1990
M. Ni Bhrolchain
1990
*71 Geographical variations in female labour force
participation: an application of multilevel
modelling.
*72 Measuring housing deprivation using the OPCS
Longitudinal Study.
(Updated version).
C. Ward
A. Dale
1991
M. Williams
A. Dale
1992
WORKING PAPERS ARE AVAILABLE FREE ON REQUEST
TELEPHONE: 071 477 8486
USER GUIDES TO THE OPCS LONGITUDINAL STUDY
1
Households, families and fertility.
B. Penhale
1990
2
The measurement of ethnicity.
A. Stuart
1990
3
The analysis potential of the LS.
I. Plewis
1990
4
User guide to computing with the LS*
(Second edition).
Brian Dodgeon
Modelling categorical data with GLIM.
C. Ward
5
1992
1991
6
* M. Rosato
Using the OPCS Stage I11 Epidemiological package.
1991
introduction to the area based variables in
the LS.
R. Creeser
A comparison of mortality measures in the OPCS
R. Weatherall
Longitudinal Study
1992
7 . An
a.
9. A guide to the fertility and infant mortality
datastream
1993
R. Creeser
1992
10. An examination of the quality of OPCS Longitudinal P. Babb
Study data for use in fertility analysis
L. Hattersley
1992
11. Using SPSSX Statistical Procedures with the LS
S. Gleave
R. Creeser
B. Dodgeon
1993
* Only available to those individuals who have made arrangements
to work with the LS at OPCS.
SCOWW: The Social Classification of Women's Work.
R. Barker
H. Roberts
1990
USER GUIDES ARE AVAILABLE FREE ON REQUEST
TELEPHONE: 0 7 1 477 8486
********
THE OPCS LONGITUDINAL STUDY USER MANUAL
Order forms are available on request. The cost is f15, and includes
the Manual, an accompanying Data Dictionary disk, and postage and
packing. (The Manual is available without the Data Dictionary for a
charge of f5.00 to cover administration, postage and packing).