PUBH6005_Assessment Brief # 2_Assessemnt Assignment_Due week 6 Page 1 of 3

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Context:

This assignment covers learning topics from Module 2.1 and 2.2

PUBH6005: Epidemiology Assignment

This assessment is aimed at consolidating the students understanding of Module 2 content

By prescribing this assessment, students are able to reflect on their understanding of study

design, sampling and population risk

ASSESSMENT 2 – Quiz

Subject Code and Name PUBH6005 Epidemiology

Assessment Assignment

Individual/Group Individual

Length 1000 words (+/- 10%)

Learning Outcomes This assessment addresses the following subject learning

outcomes:

• Differentiate between different types of research
designs, including observation and experimental and
mixed methods designs

• Assess levels of evidence and make
recommendations

Submission Week 6 Sunday 11:55pm AEST

Weighting 30%

Total Marks 100 marks

PUBH6005_Assessment Brief # 2_Assessemnt Assignment_Due week 6 Page 2 of 3

Instructions:

This assignment has two parts. PART 1 involves reading three research articles, and applying

what you have learned about epidemiological measures and study design to answer a series

of short answer questions. PART 2 requires you to consider several health issues and decide

the most appropriate study design for investigating that health issue.

Students are to log in to their Blackboard account and complete the assignment in the

prescribed link on the Blackboard page.

PART 1

The Whitehall study is a ground-breaking longitudinal (prospective cohort) study that clearly

demonstrated the association between social determinants of health (the social gradient)

and morbidity and mortality (cardiovascular disease) in a population of British civil servants

(Breeze et al., 2001; Chandola et al., 2008; Marmot et al., 1978).

Read these papers and answer the following questions.

1. What is the sampling frame for each phase of the Whitehall study (Whitehall I and

II)? (5 marks)

2. How was disease risk assessed (both in data collection and analysis) in each of the

three studies and why? (15 marks)

3. To what extent can the results of each of the three studies be generalised to other

populations (include reasons for your answer)? (10 marks)

4. Would it be feasible to conduct a similar study in Australia using an existing cohort

such as the 45 and up study cohort or the Australian Women’s longitudinal study

cohort? Why or why not? (20 marks)

PART 2

For each of the following scenarios identify the best study design to explore each health

issue and explain your reason for choosing this study design. Include an explanation of

advantages and disadvantages of using the selected study design and include any ethical

considerations. Support your reasons with justification and referenced examples of research

studies.

1. Causal relationship between lung cancer and smoking (10 marks)

2. Association between depression and binge eating in a population of obese

adolescents and adults (10 marks)

3. Long term effects of detention on the mental and physical health of asylum

seekers (10 marks)

PUBH6005_Assessment Brief # 2_Assessemnt Assignment_Due week 6 Page 3 of 3

4. Relationship between folate supplementation during pregnancy and development of

autism in offspring (10 marks)

5. Testing of a drug for use in elderly people diagnosed with Alzheimer’s disease (10

marks)

Submission Instructions:

Access assignment link on Blackboard under Assessment 2 – Assignment via Assessment in

main navigation menu in Blackboard. The assignment questions are embedded in

Blackboard and you can submit your answers directly into Blackboard.

Assessment Criteria:

• Knowledge and understanding of the appropriate use of epidemiological study

designs

• Analysis and application with synthesis of new knowledge to the strengths and

weaknesses of different epidemiological study designs

• Analysis and application with synthesis of new knowledge of study design

characteristics to select the most appropriate to the study question

• General assessment criteria:

o Shows a sophisticated understanding of the key issues

o Shows ability to interpret relevant information and literature in relation to

chosen topic

o Demonstrates a capacity to explain and apply relevant concepts

o Shows evidence of reading beyond the required readings

o Justifies any conclusions reached with well-formed arguments and not

merely assertions

• Correctly uses academic writing, presentation and grammar:

o Complies with academic standards of legibility, referencing and

bibliographical details (including reference list)

o Writes clearly, with accurate spelling and grammar as well as proper

sentence and paragraph construction

o Uses appropriate APA style for citing and referencing research

Journal ofEpidemiology and Community Health, 1978, 32,

244

–

249

Employment grade and coronary heart disease in
British civil servants
M. G. MARMOT, GEOFFREY ROSE, M. SHIP

L

EY, AND P. J. S. HAMILTON
From the Department ofMedical Statistics andEpidemiology, London School ofHygiene and Tropical Medicine

SUMMARY The relationship between grade of employment, coronary risk factors, and coronary
heart disease (CHD) mortality has been investigated in a longitudinal study of 17 530 civil servants
working in London. After seven and a half years of follow-up there was a clear inverse relationship
between grade of employment and CHD mortality. Men in the lowest grade (messengers) had
3-6 times the CHD mortality of men in the highest employment grade (administrators). Men in the
lower employment grades were shorter, heavier for their height, had higher blood pressure, higher
plasma glucose, smoked more, and reported less leisure-time physical activity than men in the
higher grades. Yet when allowance was made for the influence on mortality of all of these factors
plus plasma cholesterol, the inverse association between grade of employment and CHD mortality
was still strong. It is concluded that the higher CHD mortality experienced by working class men,
which is present also in national statistics, can be only partly explained by the established coronary
risk factors.

A striking feature of the British mortality statistics
is that death from coronary heart disease (CHD) is
now more common in working class men and
women than in those of higher status (Registrar
General, 1978). Such vital statistical data have been
useful in pointing to occupational groups possibly
at high risk. They do not, however, suggest reasons
for the class gradient in disease. To identify and, if
possible, explain any social class gradient in CHD
mortality in a group of employed men, data were
analysed from the Whitehall study of civil servants
(Reid et al., 1974).
The Whitehall study was initiated by Professor

Reid. It was based on a survey of male civil servants
working in London who were examined between
1967 and 1969, and whose subsequent mortality has
been followed (Reid et al., 1976; Rose et al., 1977a).
The present paper reports CHD mortality in
seven and a half years of follow-up for men employed
in different grades. The association between em-
ployment grade, CHD mortality, and the major
coronary risk factors is then examined.

Methods
18403 men attended the initial screening examin-
ation. Each man received a standardised question-
naire which, among other items, asked for his
grade of employment. Men were then classified
into administrative, professional, executive, clerical,

and ‘other’ grades. The ‘other’ grade was the
lowest in status, and included mainly messengers
and other unskilled manual workers. Excluded
from this analysis were 873 men from the Diplomatic
Service and the British Council, among whom the
classification of employment status was not com-
parable. Thus the present analysis is confined to
17 530 men from other departments.
The initial examination included the London

School of Hygiene Cardiovascular Questionnaire
(Rose et al., 1977b) and standardised questions on
smoking history, respiratory symptoms, medical
treatment, and leisure-time activities. Electro-
cardiograms were classified according to the
Minnesota Code (Rose and Blackburn, 1968), and
blood pressure, plasma cholesterol, blood glucose,
height, and weight were determined in standardised
fashion (Reid et al., 1974).
For over 99% of the subjects, their records in the

Central Registry of the National Health Service
were identified and tagged, and a copy of the death
certificate has been provided for each subject who
has since died within the United Kingdom. Mortality
follow-up is now complete for seven and a half
years. There have been 1086 deaths in this period, of
which 462 were assigned to CHD (ICD codes
410414) (World Health Organisation, 1967).
Death certificates were coded by the Office of
Population Censuses and Surveys.

24

4

Employment grade and coronary heart disease in British civil servants

Adjustment for age wa
method, using the total p
Where the age-adjusted I
for the distribution of
was similarly carried out
multivariate analysis m;
logistic equation, which
the extent to which dif
grades were attributable ti
each risk factor. This wa
relative increase in risk
increase in, say, blood
of the top (administrativi
nitude of the difference:
calculation was equal i
means between the admi
of the grades below.

L._

L-4 –
E

2 –

8 a Administr
Professio

03 Clerical
^

I
Other

0 uJv -l
Age – b40-49
No. __ o
of . oX

G

men ‘

I
Fig. 1 Coronary heart disee
ofdeaths) in seven and a halj
grade and age.
inc ugures on -4poi n so

s carried out by the direct
opulation as the standard.
rates were further adjusted
another risk factor, this
by the direct method. The
ade use of the multip

le

also yielded estimates of

Within each age group, there is a regular stepwise
relationship between grade of employment and risk
of CHD death; the lower the grade, the higher the
risk. Overall, the men in the lowest (‘other’) grade
had 3-6 times the CHD mortality rate of the men
in the highest (administrative) grade.

fferences in risk between GRADE AND OTHER RISK FACTORS
o the independent effect of To explain this large difference in CHD mortality,
as done by calculating the it is necessary to analyse the age-adjusted distribution
c expected from a given of coronary risk factors in the different grades
pressure, taking the risk (Table 1). It can be seen that systolic blood pressure
e) grade as 1 0. The mag- shows a clear negative association with grade,
in risk factor used in this whether expressed as mean blood pressure or as
to the difference in the per cent of men having a value > 160 mmHg. By
inistrative grade and each contrast, for plasma cholesterol the gradient is in

the other direction: the higher the grade, the
higher the plasma cholesterol.

rative 4

1

The proportion of current cigarette smokers was

rnat Execu41ve more than twice as high in the ‘other’ grade (60-9 %)tnat I Executive 42 as it was among administrators (28 8 %). There was
little difference between the grades in the mean of
body mass index, but the distribution was different:
in the lower grades more men were heavy for their

40 height and more were light for their height.
51 At the initial examination men were questioned

57 X briefly about their leisure-time activities, and these
have been classified as ‘inactive’, ‘moderately

159 2 8 W active’, or ‘active’. More of the upper grade men
reported ‘active’ leisure-time pursuits. This may be

9 especially relevant, since none of these men was
employed in a physically demanding job.
There was also a striking positive association

between grade and height. Men in the ‘other’
grade were on average more than five centimetres

0_ shorter than men in the administrative grade.
50-59 60-64 More than 20% of administrators were over six feet

O ° 0O ,^ Q° tall, but fewer than 10% ofmen in the bottom grade.
Ln- ^ 0 ° @ – Height is presented here because in this population

shorter men have a higher CHD mortality (Table 2).
asemortality (and number In multivariate analysis, this association is in-
!f(years by civil service dependent of other coronary risk factors, including

grade.
-ine ngures on top OI tne nlstograms are tne numt)ers
of CHD deaths.

Results

GRADE AND CHD MORTALITY

Figure 1 presents the mortality from CHD in each
grade and age group over the seven and a half
years of follow-up. There was no a priori reason
for ranking professional and executive grades
differently, and their CHD death rates were in fact
identical; the results for these two grades have
therefore been pooled throughout the analysis.

GRADE, CHD MORTALITY, AND CORONARY
RISK FACTORS

The next step in the analysis was to assess the
extent to which differences between the grades in
these risk factors might account for the grade
differences in CHD mortality. Figure 2 presents
the age-adjusted CHD mortality rates in each
grade, in relation to blood pressure, plasma
cholesterol, smoking, and height. Adjustment for
smoking and for height slightly reduced the relative
differences in CHD mortality between the highest
and lowest grades. Adjustment for blood glucose,

24

5

6

L

M. G. Marmot, Geoffrey Rose, M. Shipley, and P. J. S. Hamilton

Table 1 Major risk factors in different grades: age-adjusted means andper cent showing ‘elevated’ values
Grade

Professionall
Variable Administrative Executive Clerical Other
SYSTOLIC BP
Mean ± SEM 133 77±0 67 136-0±0-19 136 8±0-42 137 9±0-64
Per centA 160 10-7 12X2 13 -8 165

PLASMA CHOLESTEROL
Mean ± SEM 201-0±1 72 198 7+0 44 196 6±1-00 192-0±1-47
Percent>260mg% 12*6 10*2 10.5 7*8

SMOKING
Per cent smokers 28 8 37*3 53 0 60 9
Never smoked 33 0 23 *2 17 0 14 8
Ex-smokers 38 1 39 6 29 9 24

3

BMI (WEIGHT/HEIGHT’)
Mean ± SEM 24 S5t0 09 24 8±0-03 24 6t0-07 25.0±0-1

0

Percentp28 9*9 11-8 13*8 17 4

BLOOD GLUCOSE*
(2 hour post load)
Mean ± SEM 75S1±0 47 75-34O016 76 7±0 40 77 5±0 8

2

Percent>90mg% 10 1 9*7 12 1 13*1
Per cent diabetic 1 3 0 7 1*4 l1d

PHYSICAL ACIIVITY
Per cent inactive 26-3 29 5 43 0 56 0
Per cent moderately active 36-8 45 *3 36 *3 30-0
Per cent active 36.8 25 2 20 7 14-0

HEIGHT
Mean ± SEM 178 *5±020 176-3±0 05 174-0±0d13 173 2±0023
Per cent 183 cm (6 ft) 211 12-8 7 -6 8 *7

*Excluding diabetics.

Table 2 CHD mortality in seven and a halfyears
according to height (age-adjusted)

CHD death

Height N No. (Age-adjusted)
< 5S 60 2290 103 3-7 -S' 9" 6672 172 2 5 -6'r06433 144 2-4 >6′ Off 2132 43 2*4

body mass index, and reported physical activity had
little impact on the grade differences in mortality.
To assess the combined effect of adjustment for

these risk factors a multivariate analysis was used.
In Figure 3, the risk of the administrators is taken
as 1 0. The relative risks of the professional and
executive, the clerical, and the ‘other’ grades were
then 2-1, 3-2, and 4-0 respectively. (These estimates
of relative risk differ very slightly from those
in Figure 1, because here the adjustment for age
was carried out in a different fashion, using the
multiple logistic equation). The shaded part of the
histograms shows how much of the difference in
relative risk of each grade is attributable to differ-
ences from the administrators in the levels of risk
factors. The multiple logistic equation allows an
estimate to be made of the effect of a risk factor
on CHD death, independent of the effect of all
other risk factors. The unshaded part of the histo-
grams shows that approximately 60% of the grade
differences in CHD could not be accounted for by
differences in these factors as we assessed them
(that is, by a single screening examination).

EFFECT OF SELECTION
Another kind of explanation for these striking CHD
differences between the grades would be the effect
on mortality of selection into or out of employment.
The ‘other’ grade in particular contains a number of
men who obtained their present employment in the
civil service after they had become unfit for more
physically demanding work. For this reason alone
they may be expected to have a higher subsequent
mortality. Removing these men from the analysis,
however, still leaves a clear gradient of CHD risk
between the remaining employment grades. Men in
the clerical grade have 3-1 times the risk of those in
the administrative grade and 1.5 times the risk of
the professional and executive men.

If mortality differences between grades were due
to medical factors at recruitment, then they would
be expected to show less clearly in men who at
entry to the study appeared to be healthy. In
Figure 4, CHD mortality rates are shown for men
in each grade, classified according to whether at
entry into the study they showed any of the
following: history of shortness of breath on exertion,
or wheeze, angina or pain of possible myocardial
infarction on the standard questionnaire, history of
treatment for diabetes or vascular disease, or
electrocardiographic signs suggestive of ischaemia.
The inverse association between grade and CHD
mortality is clear and consistent among the 50%
of men with ‘disease at entry’ to the study (relative
risk 3.3), and within each grade, mortality is higher
than among the symptom-free men. Among these

‘)A6

Employment grade and coronary heart disease in British civil servants

O

Administrative

* Professional

/

Executive
o Clerical
* Other

10 l

61

5.

/
o

/
,’t

/
le

o_- o

o3

120 140
Systolic BP (mm Hg)

/I’
0

* 10′

160

3
2

*1′

0
6
5
4
3
2

0
0

*%
. ° ..”f’

0 10 20
Current cigarette consumption
per day

ee
0

.e.o
180 220 260

Plasma cholesterol (mg/l100ml)

‘.\
sk ,

o-__.. a

51′ 611 5 911
Height (feet and inches)

Fig. 2 CHD mortality in seven andahalfyearsbygradeaundotherriskfactors (age-adjusted %).
Mortality rates among ex-smokers in the four grades are shown in the left hand section of
the smoking chart.

symptom-free men, the stepwise association between
grade and mortality is seen for the higher three
grades but not for the lowest (‘other’) grade. This
suggests that selective employment of disabled
men could not be the major reason for the associ-
ation of grade with CHD mortality, except perhaps
in the lowest grade.

If medical selection were a major factor, it might
be expected that the grade differences in mortality
would be greater in the early years of follow-up
than in the later years. If the sicker men were
concentrated in the lower grades at the beginning
of the study, then, as they died off, the difference in
mortality between the grades should narrow. Figure
5 plots the cumulative probability of CHD death
(age-adjusted) for men in each grade over the
seven and a half years of follow-up. It can be seen
that the mortality differences between the grades
have in no way tended to narrow, the relative

difference remaining in fact fairly constant. Whatever
factors are responsible for the grade differences,
their effect persists throughout the follow-up period.

Discussion

In this study of civil servants, a man’s grade of
employment was a stronger predictor of his sub-
sequent risk of CHD death than any of the other
major coronary risk factors. The mortality difference
between the administrative and ‘other’ grades
was in the same direction, but greater in magnitude,
than the difference between the CHD mortality of
Social Class I and Social Class V reported for
England and Wales (Registrar General, 1978). It
may be that the grade of a civil servant identifies
relevant factors in social class level more accurately
than the much cruder classification of national
social classes, where each individual class is

6
5.
3
2 –
1

0
Z–

0
E
a
I
L)

4
3
2
0

247

M. G. Marmot, Geoffrey Rose, M. Shipley, and P. J. S. Hamilton

Fig. 3 Relative risk ofCHD death in different grades
‘explained’ by risk factors (age-standardised).
The figures on top of the histograms are the relative
risk of CHD death (age-standardised), taking the
administrative grade as 1.0. These figures are
calculated from the equation and differ slightly from
the ‘crude’ figures.
The figures in the histograms are the relative risk of
CHD death in the different grades after the effect of
the other risk factors has been taken into account.

undoubtedly very heterogeneous. In that case, the
stronger mortality gradient in the civil service
would reflect a more accurate classification rather
than a truly steeper gradient of risk.
The gradient might be due to self-selection into

lower employment grades of men with a higher risk
of CHD. Selective recruitment of men with
symptoms seems unlikely to have played a major
part. There are in general no pre-entry medical
examinations for these men; the mortality
differential was as strong in the late as in the early
period of follow-up: and, except for the lowest
grade, a clear mortality gradient was evident even
in the men who at entry to the study were apparently
symptom-free. Furthermore, most of these middle-
aged men were career civil servants, and it would
have been most remarkable if selective factors
operating 20 or more years previously could have
predicted current risk so efficiently. It thus seems
likely that medical selection, by itself, cannot
explain the substantial grade differences in mortality.
The explanation of these differences is not clear.

6
4

0
I

‘a
0

Administrative

I Professional / Executive
E Clerical
* Other

uiusseu entry NO Yes
Disease= lschaemia or angina or myocardial infarction

or
phlegm or dyspnoea or wheeze

or
diabetic or under treatment

Fig. 4 Seven and a halfyear CHD mortality by
grade and ‘disease at entry’.
The figures on top of the histograms are the numbers
of CHD deaths.

4*O

>, 3-5.
.C0
O.s.. 3-0Q.0a-0
cL)

2*O

V0R
. °21-

E 0 5C-,

00
0 1 2 3 4 5 6 7
Year of follow-up

Fig. 5 CHD mortality among total population by
year offollow-up.

Smoking is a predictor of CHD death (Reid et al.,
1976) and lower grade men smoked more than
those in higher grades. However, this difference
explained only a small part of the differences in
mortality.

248

3

0
-4 Ki 0%

1/I

Employment grade and coronary heart disease in British civil servants

Plasma cholesterol levels were actually higher in
the higher grade men. This is consistent with the
results of the National Food Survey, which show
fat intake to be higher in upper income than in
lower income households (National Food Survey,
1973). If such findings are true of the civil servants,
as is suggested by our own preliminary dietary
surveys, it seems unlikely that the grade difference
in mortality could be related to dietary intake of
saturated fat. The question of polyunsaturated/
saturated ratio needs further study.
Most men in this study were employed in physic-

ally undemanding occupations, so it is necessary to
look at leisure-time physical activity for any differ-
ences. The rough measure of physical activity used
here does show an association with CHD risk
(Rose et al., 1977a), and the somewhat higher
levels reported by the upper grade men could
therefore be a small part of the explanation of their
lower CHD risk. Had the present study included a
more precise measure of physical activity (Morris
et al., 1973), it is possible that a greater part of the
grade difference in mortality could have been
explained.
Men in the lower grades tended to have higher

blood pressure than the upper grade men, in line
with previous reports from other populations
(Syme, 1974; Dyer, 1976; Holme, 1976). In a
separate analysis, we have shown that the greater
degree of obesity among the lower grade men does
not account for the higher blood pressure. It is of
course possible that a greater part of the excess
CHD in the lower grades would have been explained
if blood pressure measurements had been multiple
or more representative of the men’s normal
conditions of life: for each man we had only one
measurement, recorded under standardised
conditions.

It appears, then, that the evidence available to us
on these men’s risk factor status when they entered
the study leaves unexplained a large part of the
subsequent intergrade differences in death from
CHD. This suggests either that there are other
major risk factors which we did not measure, or
else perhaps that the pattern of risk was already
determined by genetic constitution or earlier
upbringing. Certainly the independent association
between short height and CHD risk is consistent
with the operation of some combination of genetic
endowment and early nutrition. However, the
association between grade and mortality was again
largely independent of the differences in height.
This suggests the need for continued search for
potential aetiological factors in the adult lifestyle or
environment of these men. In particular, attention
should be paid to better characterisation of diet,

including nutrients other than fat, and to psycho-
social differences between the grades.

It is to be hoped that from a better understanding
of the reasons for social class difference in disease,
some means may emerge of protecting groups at
such greatly increased risk.

It is a pleasure to acknowledge the continued help
of the Civil Service Medical Department. The study
was supported by a grant from the Tobacco Research
Council.

Reprints from M. G. Marmot, Department of
Medical Statistics and Epidemiology, London
School of Hygiene and Tropical Medicine, Keppel
Street, London WC1E 7HT.

References

Dyer, A. R., Stamler, J., Shekelle, R. B., and Schoen-
berger, J. (1976). The relationship of education to
blood pressure. Findings on 40 000 employed
Chicagoans. Circulation, 54, 987-992.

Holme, I., Helgeland, A., Hjermann, I., Lund-Larsen,
P. G., and Leren, P. (1976). Coronary risk factors and
socioeconomic status. The Oslo study. Lancet, 2,
1396-1398.

Morris, J. N., Chave, S. P. W., Epstein, L., and Sheehan,
D. J. (1973). Vigorous exercise in leisure-time and the
incidence of coronary heart disease. Lancet, 1, 333-339.

National Food Survey Committee (1973). Ministry of
Agriculture, Fisheries and Food. Household Food
Consumption and Expenditure 1970 and 1971. HMSO:
London.

Registrar General (1978). Occupational Mortality 1970-
72: Decennial Supplement. HMSO: London.

Reid, D. D., Bret, G. Z., Hamilton, P. J. S., Jarrett, R.
J., Keen, H., and Rose, G. (1974). Cardiorespiratory
disease and diabetes among middle-aged male civil
servants. Lancet, 1, 469-473.

Reid, D. D., Hamilton, P. J. S., McCartney, P., Rose, G.,
Jarrett, R. J., and Keen, H. (1976). Smoking and
other risk factors for coronary heart disease in British
civil servants. Lancet, 2, 979-984.

Rose, G., and Blackburn, H. (1968). Cardiovascular
Survey Methods. wHo: Geneva.

Rose, G., Reid, D. D., Hamilton, P. J. S., McCartney,
P., Keen, H., and Jarrett, R. J. (1977a). Myocardial
ischaemia, risk factors and death from coronary heart
disease. Lancet, 1, 105-109.

Rose, G., McCartney, P., and Reid, D. D. (1977b). Self-
administration of a questionnaire on chest pain and
intermittent claudication. British Journal of Preventive
and Social Medicine, 31, 4248.

Syme, S. L., Oakes, T. W., Friedman, G. D. et al.
(1974). Social class and racial differences in blood
pressure. American Journal of Public Health, 64,
619-620.

World Health Organisation (1967). International Class-
ification ofDiseases, 8th revision. wHo: Geneva.

249

Elizabeth Breeze, MSc, CStat, Astrid E. Fletcher, PhD, David A. Leon, PhD,
Michael G. Marmot, PhD, MBBS, Robert J. Clarke, MD, MRCP,
and Martin J. Shipley, MSc

Elizabeth Breeze, Astrid E. Fletcher, and David A.
Leon are with the Department of Epidemiology and
Population Health, London School of Hygiene and
Tropical Medicine, London, England. Michael G.
Marmot and Martin J. Shipley are with the Interna-
tional Centre for Health and Society, Department
of Epidemiology and Public Health, University Col-
lege Medical School, London. Robert J. Clarke is
with the Clinical Trial Service Unit and Epidemio-
logical Studies Unit, University of Oxford, Oxford,
England.

Requests for reprints should be sent to Eliza-
beth Breeze, MSc, CStat, London School of Hy-
giene and Tropical Medicine, Keppel Street, Lon-
don WC1E 7HT, England (e-mail: elizabeth.breeze@
lshtm.ac.uk).

This article was accepted May 24, 2000.

A B S T R A C T

Objectives. This study examined (1)
the relation of employment grade in
middle age to self-reported poor health
and functional limitations in old age and
(2) whether socioeconomic status at ap-
proximately the time of retirement mod-
ifies health differentials in old age.

Methods. Survivors of the Whitehall
Study cohort of men were resurveyed.
Respondents were aged 40 to 69 years
when they were originally screened in
1967 to 1970.

Results. Compared with senior ad-
ministrators, men in clerical or manual
(low-grade) jobs in middle age had
quadruple the odds of poor physical per-
formance in old age, triple the odds of
poor general health, and double the odds
of poor mental health and disability. At
most, 20% of these differences were ex-
plained by baseline health or risk fac-
tors. Men who moved from low to mid-
dle grades before retirement were less
likely than those who remained in low
grades to have poor mental health.

Conclusions. Socioeconomic status
in middle age and at approximately re-
tirement age is associated with morbid-
ity in old age. (Am J Public Health. 2001;
91:277–283)

February 2001, Vol. 91, No. 2 American Journal of Public Health 277

There is a small but growing body of evi-
dence from the United Kingdom that socioeco-
nomic differentials in mortality persist into old
age1–3 and may even be widening.4,5 Although
rate ratios tend to be smaller for older people
than for younger people in the United Kingdom
and the United States,4–6 absolute differentials
can still be large.5

There is little equivalent information on
self-reported morbidity. Analyses of cross-
sectional studies show that self-reported health
and disability, respiratory function, and blood
pressure are all worse among older people in
disadvantaged socioeconomic groups.7,8 Analy-
ses of the Office for National Statistics Lon-
gitudinal Study in England and Wales showed
that adverse socioeconomic circumstances were
associated with self-reported limiting long-
term illness after a 20-year follow-up period
among survivors.9

The first Whitehall Study, an investiga-
tion of male British civil servants that was ini-
tiated in the late 1960s, showed an inverse mor-
tality gradient (all causes and major causes)
across employment grades.10 The Whitehall II
Study, following a later cohort, revealed gra-
dients in morbidity in middle age across so-
cioeconomic groups.11,12 A resurvey of the sur-
vivors of the first cohort enabled us to study the
long-term effects of employment grade on self-
reported illness in old age.

Methods

Data Source

In the Whitehall Study, 19 029 men, most
aged 40 to 69 years, were examined between
1967 and 1970 to identify cardiorespiratory
disease and its risk factors.13 Participants com-
pleted a questionnaire concerning their jobs,
their personal and family medical histories,
and their smoking habits. Approximately two
thirds of the respondents were also asked about

car ownership and physical activity related to
work, and one third were asked about leisure
activity in general. A clinical examination in-
cluded height and weight, blood pressure, elec-
trocardiogram, and a blood sample analyzed
for cholesterol and blood sugar. Participants
were registered with the National Health Ser-
vice Central Register for mortality notification
(99% were successfully located).

Resurvey

The resurvey took place in 1997–1998
after a successful pilot study of 400 survivors
in 1996.14 The National Health Service Cen-
tral Register identified the health authority in
which the cohort member was registered with
a family doctor. Chief executives of the rele-
vant health authorities granted permission to
the register to provide addresses of survivors
(or, failing this, to forward mail to them). In-
vitation letters, consent forms, and question-
naires were sent to individuals, along with up
to 2 reminders. A short version of the ques-
tionnaire covering priority information was sent
with the second reminder. The resurvey ques-
tionnaire included questions on socioeconomic
status (SES) and retirement, diseases diagnosed

Do Socioeconomic Disadvantages Persist
Into Old Age? Self-Reported Morbidity in
a 29-Year Follow-Up of the Whitehall
Study

February 2001, Vol. 91, No. 2278 American Journal of Public Health

TABLE 1—Resurvey Responses by Selected Characteristics: Whitehall Study, 1997–1998

Total No. Invited Completed Full Completed Short
to Take Part Questionnaire, No. (%) Questionnaire, No. (%) χ2 P

Age at resurvey, y
<75 3029 2316 (76) 262 (9) 75–79 2937 2236 (76) 272 (9) ≥80 2571 1616 (63) 339 (13) < .001

Baseline employment grade
High 555 443 (80) 23 (4)
Middle 6743 5052 (75) 657 (10)
Low 1239 673 (54) 193 (16) < .001

Baseline smoking status
Never 2078 1588 (76) 186 (9)
Ex-smoker 3370 2496 (74) 318 (9)
Pipe/cigar smoker 332 249 (75) 28 (8)
Cigarette smoker 2753 1832 (67) 341 (12) < .001

Baseline evidence of cardiovascular disease
Yes 1114 813 (73) 127 (11)
No 7133 5353 (75) 746 (10) .437

Baseline respiratory symptoms
No phlegm 6399 4666 (73) 638 (10)
Persistent cough/phlegm 1070 748 (70) 110 (10)
Increasing cough/phlegm 409 267 (65) 56 (14)
Hospital admission in past 647 481 (74) 69 (11) .018

Total 8537 6168 (72) 873 (10)

by a doctor, and ability to carry out everyday
activities.

Outcome Measures

We used 4 measures of self-reported
morbidity: general poor health, poor mental
health, poor physical performance, and dis-
ability. Those rating their health as poor or
very poor on a 5-point scale ranging from
very good to very poor were classified as
being in poor general health. Poor mental
health was defined as a score below 60% of
the maximum on the 5-item mental health
section of the Short Form 36 Health Survey
(SF-36).15 Poor physical performance was de-
fined as a score below 40% of the maximum
on the 10-item physical performance section
of the SF-36, which asks people to state
whether their health limits their activity ex-
tensively, a little, or not at all. Finally, dis-
ability was classified as an inability to engage
in at least 1 of 5 instrumental activities of daily
living (cooking a hot meal, cutting toenails,
dressing oneself, doing light housework and
simple repairs, and going up and down stairs
and steps).

Data on mental health, physical perform-
ance, and disability were available only for those
who completed the full questionnaire. The SF-
36 indexes were scored as recommended.16 As
a result of missing data, 4% of those complet-
ing the full questionnaire were not assigned a
mental health score, 3% were not assigned a
physical performance score, and fewer than 1%
were excluded from the disability analyses.

Socioeconomic and Risk Factor
Measures

The main baseline socioeconomic clas-
sification used was employment grade (high,
middle, or low). High grades comprised sen-
ior managers and administrators; middle grades
comprised executives and professionals (e.g.,
economists, statisticians, and scientists) in less
senior positions; and low grades included cler-
ical staff, printing room officers, security of-
ficers, messengers, and catering staff.

Other socioeconomic indicators were car
ownership and, measured retrospectively at the
resurvey, housing tenure at baseline (owner vs
renter). These variables were found to be clear
discriminators of mortality rates among older
people in the United Kingdom in the 1970s,1

were incorporated in the Townsend index of
deprivation,17 and have subsequently been used
as socioeconomic indicators.5,18

Respondents were considered to have
preexisting cardiovascular disease if they had
at least 1 of the following at baseline: an ab-
normal electrocardiogram; self-reported
symptoms of angina, claudication, or poten-
tial myocardial infarction19; medication for
high blood pressure; or a hospital admission
for a heart condition. We adjusted for car-
diorespiratory disease clinical risk factors that
existed at baseline because these risk factors
are associated with later disability20–22 and
can lead to more general problems in func-
tioning and health. The variables used in the
analyses were as follows: being in the top
quintile in terms of systolic or diastolic blood

pressure or total cholesterol level (assessed
with the entire 1960s cohort), body mass
index of 30 kg/m2 or greater, blood sugar level
above 96 mg/dL, persistent or increasing du-
ration of cough or phlegm or hospital admis-
sions for respiratory disease, and 4 or more
hospital admissions for other reasons.

Statistical Analysis

Chi-square tests for heterogeneity were used
to determine univariate associations. Logistic re-
gression (Stata 5 for Windows 3.123) was used to
estimate odds ratios (ORs) and 95% confidence
intervals (CIs) for each outcome.All models in-
cluded adjustment for age at resurvey (younger
than 75 years, 75–79 years, 80 years or older).

Results

At the time of the resurvey, there were 8537
men from the original screening who, accord-
ing to National Health Service Central Register
records, were alive and living in Great Britain.
Of these individuals, 6168 completed a full
questionnaire (72%) and 873 a short one (10%),
209 of the latter by telephone. Seven percent of
respondents had been in high employment
grades at the initial screening, 12% had been in
low grades, and 81% had been in middle grades.
The median age of respondents at the resurvey
was 77 years (range: 67–97), and the median
follow-up interval was 29 years (range: 26–31).

Response rates were lowest among men in
low employment grades, older men, smokers,

February 2001, Vol. 91, No. 2 American Journal of Public Health 279

TABLE 2—Distribution (%) of Characteristics of Resurvey Respondents, by
Employment Grade at Baseline: Whitehall Study, 1997–1998

Employment Grade at Baseline, %
High Middle Low

(n = 466) (n = 5708) (n = 866) �2 P

Resurvey
Age, y

<75 37.8 37.5 30.1 75–79 38.2 36.4 29.3 ≥80 24.0 26.1 40.5 < .001

Net income < $16 500 0.9 8.2 47.8 < .001 Had risen 1 grade category . . . 39.7 50.8 < .001 Had paid job after leaving Civil Service 44.9 22.8 18.7 < .001 Cardiovascular disease

Angina 11.4 14.5 16.7 .03
Heart attack 10.5 11.4 15.0 .006
Stroke 7.3 8.4 8.2 .74

Baseline
Cardiovascular disease 11.4 13.3 14.5 .26
Top quintile

Systolic blood pressure 7.3 12.7 15.6 < .001 Diastolic blood pressure 10.7 13.3 13.6 .27 Total cholesterola 23.4 19.0 16.8 .15

Body mass index > 30 kg/m2 1.5 2.7 4.2 .01
Blood sugar > 96 mg/dLa 3.9 4.3 5.0 .52
Respiratory symptoms

No respiratory problem 78.1 75.7 71.8
Persistent phlegm 9.2 12.0 15.4
Increasing phlegm 2.8 4.3 7.2
Hospital admission for respiratory disease 9.9 8.0 5.7 < .001

Ever had 4 or more hospital admissions 11.2 8.9 11.0 .05
(not cardiovascular or respiratory)

Smoking status
Never smoked 33.3 25.2 20.8
Ex-smoker 36.1 41.5 32.3
Smoked 1–9 cigarettes or pipe/cigar 16.6 12.8 12.3
Smoked 10–19 cigarettes 6.2 11.2 20.9
Smoked 20 or more cigarettes 7.7 9.4 13.8 < .001

Physical activitya

Walked to work, min
0–9 20.6 18.6 19.6
10–19 43.9 43.9 44.6
≥ 20 35.5 37.5 35.8 .83

Leisure activity
None 18.7 19.9 25.5
Inactive 6.0 7.8 13.2
Moderately active 38.7 44.4 36.5
Active 36.7 27.9 24.8 < .001

Other socioeconomic measures
Rented accommodation 4.8 9.2 38.9 < .001 No cara 6.6 14.7 51.3 < .001 Not married 4.7 8.0 21.7 < .001

aSample sizes were smaller for this variable.

and those with increasing symptoms of cough
or phlegm at baseline (Table 1). Table 2 shows
that socioeconomic indicators were strongly
correlated with employment grade, as were
smoking, leisure activity, and respiratory dis-
ease. Men in the lower employment grades
were more likely to be in the top quintile in
terms of systolic blood pressure and more likely
to have a body mass index above 30 kg/m2.

Twenty-one percent of respondents expe-
rienced at least 1 of the outcomes, and these
individuals differed markedly from the other

participants. Whereas two thirds of men with
poor mental health scores had low ratings on
at least 1 of the 5 items of the SF-36 scale, only
6% of the remaining cohort did; those with
poor physical performance ratings were lim-
ited by their health in at least 7 activities,
whereas only 30% of the remaining partici-
pants were limited in more than 3 activities.

Respondents in low employment grades
were at greatest risk of adverse outcomes for
nearly all of the component morbidity items
(Table 3), the differentials being greatest for

the more severe physical limitations. In com-
parison with those in the high employment
grades, men in the middle employment grades
had a statistically significant excess risk for 8
of the physical performance limitations.

Figure 1 shows that higher percentages
of respondents in low employment grades
were at risk for each of the morbidity out-
comes. These individuals had more than 4
times the odds of poor physical performance
relative to men in high employment grades, 3
times the odds of poor general health, and 2.5
times the odds of poor mental health or a dis-
ability (Table 4). Staff in middle employment
grades had a statistically significant excess
risk of poor general health and poor physical
performance.

Baseline clinical indicators of cardiores-
piratory disease, clinical risk factors, and risk
behavior (smoking) reduced the odds ratios for
men in the low employment grades by at most
20%. The other baseline indicators of SES nei-
ther reduced the estimates of employment ef-
fects nor explained a substantially larger por-
tion of the outcomes (data not shown). Not
being married at the original screening was an
additional factor involved in poor mental health
status at follow-up, but it only marginally re-
duced the excess odds associated with being
in the low employment grades.

After adjustment for all baseline charac-
teristics that were independent risk factors for
the morbidity outcomes, employment grade at
baseline remained a significant factor in all of
the outcomes (Table 4). Compared with men in
the high employment grades, those in the mid-
dle grades had statistically significant excess
odds of poor physical performance, and those
in the low grades had excess risks for all 4 mor-
bidity outcomes.

We looked for evidence of additional so-
cioeconomic factors measured at resurvey that
could ameliorate, or add to, disadvantages ex-
perienced in middle age. After adjustment for
other factors, having a job after retirement was
not associated with any of the outcomes. How-
ever, Table 5 shows that low income after leav-
ing the Civil Service (less than $16 500 per
year in 1997–1998) was associated with an
approximate doubling of the risk of 3 of the
outcomes among those in the middle em-
ployment grades but not those in the low
grades. On the other hand, moving up a grade
category between screening and retirement
was associated with a smaller risk of poor
mental health among those in the low em-
ployment grades.

Finally, we examined lifetime cardiovas-
cular disease reported at the resurvey as a pos-
sible factor on the causal pathway between SES
and poor health or functional limitations. As
can be seen in Table 2, there were inverse as-
sociations between a diagnosis of angina or

February 2001, Vol. 91, No. 2280 American Journal of Public Health

TABLE 3—Odds Ratios for Morbidity Outcomes, by Baseline Employment Grade, Adjusted for Age at Resurvey: Whitehall
Study, 1997–1998

Baseline Employment Grade
Morbidity Measure Sample, No. (%) High, OR Middle, OR (95% CI) Low, OR (95% CI) P

Mental health
Nervous most/all of the time 5899 (1.4) 1.00 1.06 (0.4, 2.7) 2.26 (0.8, 6.2) .045
Down in dumps most/all of the time 5902 (0.7) 1.00 1.57 (0.4, 6.6) 1.72 (0.3, 8.9) .78
Calm none/little of the time 5958 (7.1) 1.00 1.02 (0.7, 1.5) 1.52 (1.0, 2.4) .027
Downhearted most/all of the time 5929 (1.5) 1.00 3.10 (0.8, 12.7) 5.82 (1.3, 25.4) .011
Happy none/little of the time 6022 (5.3) 1.00 1.41 (0.8, 2.4) 2.16 (1.2, 3.9) .010

Physical performance limited extensively by health in:
Vigorous activities 6005 (31.2) 1.00 1.11 (0.9, 1.4) 1.49 (1.1, 2.0) .002
Moderate activities 6031 (8.4) 1.00 1.31 (0.9, 2.0) 2.54 (1.6, 4.0) < .001 Lifting or carrying groceries 6019 (5.9) 1.00 2.63 (1.3, 5.2) 6.17 (3.1,12.5) < .001 Climbing several flights of stairs 6027 (16.9) 1.00 2.11 (1.5, 3.0) 3.63 (2.5, 5.3) < .001 Climbing 1 flight of stairs 6003 (4.8) 1.00 3.19 (1.4, 7.2) 8.16 (3.5,19.0) < .001 Bending, kneeling, stooping 6039 (10.9) 1.00 2.05 (1.3, 3.2) 3.94 (2.5, 6.3) < .001 Walking more than half a mile 6029 (14.8) 1.00 1.64 (1.2, 2.3) 2.86 (1.9, 4.2) < .001 Walking half a mile 5954 (10.0) 1.00 1.92 (1.2, 3.0) 3.63 (2.2, 5.9) < .001 Walking 100 yards 5960 (4.1) 1.00 4.23 (1.6, 11.5) 9.05 (3.2, 25.2) < .001 Bathing and dressing oneself 6052 (3.4) 1.00 3.22 (1.2, 8.8) 9.00 (3.2, 25.1) < .001

Activities of daily living
Unable to do:

Cutting toenails 6111 (8.6) 1.00 1.60 (1.0, 2.5) 3.21 (2.0, 5.2) < .001 Cooking a hot meal 6078 (4.6) 1.00 1.15 (0.7, 1.9) 1.86 (1.0, 3.3) .015 Light housework, simple repairs 6098 (3.5) 1.00 1.50 (0.8, 3.0) 3.17 (1.5, 6.6) < .001

Unable to do or difficulty witha:
Dressing self 6106 (6.3) 1.00 1.69 (1.0, 2.8) 2.64 (1.5, 4.6) .001
Going up and down stairs/steps 6104 (17.4) 1.00 1.81 (1.3, 2.5) 3.08 (2.2, 4.4) < .001

Note. OR = odds ratio; CI = confidence interval.
aToo few were unable to do the task to allow the outcome to be modeled.

FIGURE 1—Prevalence of poor outcomes (%) at resurvey, by employment grade
at baseline: Whitehall Study, 1997–1998.

heart attack and baseline employment grade.
These 2 conditions were also associated with
poor health (odds ratios of 2.5 and 3.5, re-
spectively, after adjustment for all baseline
health indicators, age, and employment grade)
and poor physical performance (ORs of 1.9
and 2.1, respectively). Heart attack was also
associated with disability (OR = 1.5) and poor
mental health (OR = 1.3). However, the asso-
ciations between employment grade and these
outcomes were essentially unchanged when

experience of angina and heart attack was taken
into account.

Discussion

The survivors of the 1960s Whitehall co-
hort were mostly in good health, with only 21%
having any of the morbidity outcomes. Each
of 4 self-reported morbidity outcomes was
more prevalent among men in lower Civil Ser-

vice employment grades than among men in
high grades nearly 30 years after screening.
Men in the low employment grades had a 4-
fold risk of physical performance limited by
health, a 3-fold risk of poor health, and more
than a 2-fold risk of poor mental health and
disability.

Previous research has shown that com-
bining socioeconomic indicators yields stronger
gradients in mortality than using a single mea-
sure.1,18 In the present analysis, neither car own-
ership nor housing tenure in middle age added
to the predictive power of employment grade
with regard to the 4 outcomes.

Before it is concluded that SES in mid-
dle age is responsible for the associations found,
possible biases should be considered. First, the
response rate was lower among those in the
low employment grades. Because baseline data
were available for nonrespondents, we assessed
the implications of this difference. We ran mod-
els assuming that nonrespondents who had any
other risk factors (e.g., heavy smoking or high
body mass index) would have experienced the
adverse morbidity outcomes. Under these as-
sumptions, those in the low grades still had
more than 3 times the risk of poor physical per-
formance and twice the risk of the other mor-
bidity outcomes. Although the assumptions
were crude, they suggest that nonresponse dif-
ferentials did not substantially bias the esti-
mated effects of employment grade.

February 2001, Vol. 91, No. 2 American Journal of Public Health 281

TABLE 4—Odds Ratios for Outcomes, by Baseline Employment Grade, Adjusted for Age at Resurvey and Other Independent
Baseline Risk Factors: Whitehall Study, 1997–1998

Adjusted for Age, Fully Adjusted,a

Outcome Baseline Grade OR (95% CI) OR (95% CI)

Rated health as poor/very poor* (n = 6951) High 1.00 1.00
Middle 1.75 (1.0, 3.0) 1.62 (0.9, 2.8)
Low 3.06 (1.7, 5.5) 2.50 (1.4, 4.5)

Poor mental health score* (n = 5921) High 1.00 1.00
Middle 1.10 (0.7, 1.6) 1.05 (0.7, 1.5)
Low 2.19 (1.4, 3.4) 1.88 (1.2, 2.9)

Poor physical performance score* (n = 5965) High 1.00 1.00
Middle 2.04 (1.3, 3.3) 1.93 (1.2, 3.1)
Low 4.32 (2.6, 7.2) 3.67 (2.2, 6.2)

Unable to do at least 1 activity of daily living* (n = 6080) High 1.00 1.00
Middle 1.22 (0.8, 1.7) 1.15 (0.8, 1.6)
Low 2.36 (1.6, 3.5) 2.05 (1.4, 3.1)

Note. OR = odds ratio; CI = confidence interval.
aThe models included adjustment for the following baseline factors found to be independently associated with outcomes: self-rated health

(age, clinical signs of cardiovascular disease, top quintile diastolic blood pressure, body mass index > 30 kg/m2, respiratory symptoms, ever
hospitalised at least 4 times for reasons other than cardio-respiratory disease, smoking habit) ; mental health score (age, married or not,
smoking habit); physical performance score (age, high body mass index, respiratory symptoms, hospitalised for non cardio-respiratory
disease, smoking habit); disability (age, high body mass index, high blood sugar level/diabetic, respiratory symptoms, smoking habit).

*P < .001.

TABLE 5—Association of Selected Health Outcomes With Characteristics After Retirement, by Employment Grade: Whitehall
Study Resurvey, 1997–1998

Employment Gradea

Middle, OR Low, OR Interaction
Outcome Characteristic at Resurvey (95% CI) (95% CI) P

Poor mental health score Income < $16 500 (vs higher) 1.95 (1.4, 2.8) 0.81 (0.5, 1.4) .012 Higher grade category at retirement (vs same/lower) 0.82 (0.6, 1.0) 0.44 (0.3, 0.8) .033

Poor physical performance score Income < $16 500 (vs higher) 2.05 (1.5, 2.9) 1.05 (0.6, 1.7) .020 Higher grade category at retirement (vs same/lower) 1.00 (0.8, 1.3) 0.64 (0.4, 1.0) .19

Unable to do at least 1 activity Income < $16 500 (vs higher) 1.79 (1.3, 2.4) 0.98 (0.6, 1.6) .027 of daily living Higher grade category at retirement (vs same/lower) 0.92 (0.7, 1.1) 0.71 (0.4, 1.1) .46

Note. Odds ratios were adjusted for age and independent risk factors. OR = odds ratio; CI = confidence interval.
aToo few of those in high grades had low incomes to allow separate analyses, and, by definition, they could not rise a category.

Second, we considered the possibility that
men in the lower employment grades might
have a more negative outlook generally. Ex-
cluding those who reported being “nervous
most of the time” or “happy little of the time”
did not substantially alter the results (data not
shown).

While self-reported measures are subjec-
tive, they are predictive of mortality independ-
ently of clinical health.24,25 McCallum et al.26

attributed their finding of a contrary effect to
individuals’ basing their subjective ratings on
objective comorbidities and disability. Self-
reported functional status has also been associ-
ated with mortality in old age.27,28 Methodo-
logical studies of the SF-36 suggest that it is
reasonably sensitive to lower levels of morbid-
ity,29 that it is reliable and internally consistent,30

and that it is suitable for use with older people.31

There are several possible explanations for
an employment grade differential in old age. First,

ill health could precede low socioeconomic sta-
tus. However, health disadvantages in middle age
seem to be an unlikely explanation of differentials
in old age. After adjustment for baseline health,
behavior, and marital status, the odds ratios for re-
spondents in low vs high employment grades
were 3.7 (95% CI=2.2, 6.2) for poor physical
performance, 2.5 (95% CI = 1.4, 4.5) for poor
health, 2.0 (95% CI=1.4, 3.1) for disability, and
1.9 (95% CI=1.2, 2.9) for poor mental health.
Participants in the resurvey had already survived
nearly 30 years. Only 18% of the original low-
grade cohort members could take part, most hav-
ing died. By definition, the survivors must have
been less vulnerable to fatal disease than their
deceased colleagues, yet those in the low em-
ployment grades were still more likely to have
severe morbidity in old age than those who had
been in the higher grades in middle age.

Second, there could have been a cumulation
of psychologic stress affecting biological coping

mechanisms (e.g., cortisol production, decrease
in parasympathetic activity).32 In a later cohort
of civil servants (Whitehall II), degree of control
in one’s job explained a substantial proportion of
differences in coronary heart disease incidence
among the different grades33,34 and was associ-
ated with psychiatric disorders.35 This could not
be tested with the Whitehall I cohort.

Third, there could have been cumulating
disadvantages in regard to material resources,
opportunities to promote health, and lifestyle
between the baseline and resurvey. We have
information on the cohort at only 2 points in
time. There was some evidence that circum-
stances arising in later life could add to or ame-
liorate disadvantages. Having a low income
exacerbated health problems for middle-grade
staff, whereas rising a grade category amelio-
rated risk of poor mental health among staff
who had been in the low employment grades.
Although we cannot rule out a health selection

February 2001, Vol. 91, No. 2282 American Journal of Public Health

effect, we do not believe that it wholly accounts
for the differences. Men in middle employ-
ment grades who had low incomes in retire-
ment were slightly more likely to have left the
Civil Service for medical reasons (7% vs 4%)
or because of redundancy (17% vs 15%), but
these differences were not sufficient to account
for a 2-fold increase in risk. While being men-
tally fit might have increased the chances of
rising a grade, the greater job control in a higher
employment grade might have improved men-
tal health.

The socioeconomic differentials found in
this study probably underestimate those in the
general population in that all of the men in the
cohort had experienced relatively good em-
ployment and pension provisions in the Civil
Service. Moreover, the resurvey respondents
had better self-perceived health than that re-
ported in other studies. The mean scores for the
mental health and physical performance scales
were 82.1% and 77.3%, respectively, as com-
pared with 79.7% and 64.4% found in popula-
tion studies in 3 local districts in Britain36 and
mean scores ranging from 68% to 73% and
54% to 72% in 6 localities in outer London.37

The findings in this article add to our pre-
viously reported evidence2,9 of long-term so-
cioeconomic effects on morbidity. Moreover,
the further differentiation in outcomes by
SES in retirement suggests that there is a con-
tinuing accumulation of disadvantage in old
age. Strong socioeconomic differentials were
found among the survivors of a privileged and
relatively healthy group.

Contributors
E. Breeze helped design the documents, carried out
the analyses, and drafted the paper. A. E. Fletcher,
D. A. Leon, M. G. Marmot, R. J. Clarke, and M. J. Ship-
ley all commented on drafts and approved the final
version. R. J. Clarke was instrumental in initiating and
designing the resurvey and coordinating the field-
work; all of the authors participated in the steering
committee for the study.

Acknowledgments
The British Heart Foundation funded the resurvey, in-
cluding support for Elizabeth Breeze and Martin J.
Shipley. Michael J. Marmot was supported by a Med-
ical Research Council research professorship. The sur-
vey was approved by the ethics committees of the Lon-
don School of Hygiene and Tropical Medicine, the
University of Oxford, and University College London.

We would like to thank all of the participants
who completed questionnaires. Assistance provided
by staff from the health authorities and the Office
for National Statistics was invaluable. We also grate-
fully acknowledge the contributions of the team at the
Clinical Trials Unit in Oxford (Rory Collins, Dr Linda
Youngman, Pamela Bell, Paul Sherliker, and Smita
Shah).

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CLINICAL RESEARCH
Prevention and epidemiology

Work stress and coronary heart disease:
what are the mechanisms?
Tarani Chandola1*, Annie Britton1, Eric Brunner1, Harry Hemingway1, Marek Malik2,
Meena Kumari1, Ellena Badrick1, Mika Kivimaki1, and Michael Marmot1

1Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK; 2Department of Cardiac and Vascular Sciences,
St George’s University of London, London, UK

Received 1 August 2007; revised 14 November 2007; accepted 22 November 2007; online publish-ahead-of-print 23 January 2008

See page 579 for the editorial comment on this article (doi:10.1093/eurheartj/ehm641)

Aims To determine the biological and behavioural factors linking work stress with coronary heart disease (CHD).

Methods

and results

A total of 10 308 London-based male and female civil servants aged 35 – 55 at phase 1 (1985 – 88) of the Whitehall II
study were studied. Exposures included work stress (assessed at phases 1 and 2), and outcomes included behavioural
risk factors (phase 3), the metabolic syndrome (phase 3), heart rate variability, morning rise in cortisol (phase 7), and
incident CHD (phases 2 – 7) on the basis of CHD death, non-fatal myocardial infarction, or definite angina. Chronic
work stress was associated with CHD and this association was stronger among participants aged under 50 (RR 1.68,
95% CI 1.17 – 2.42). There were similar associations between work stress and low physical activity, poor diet, the
metabolic syndrome, its components, and lower heart rate variability. Cross-sectionally, work stress was associated
with a higher morning rise in cortisol. Around 32% of the effect of work stress on CHD was attributable to its effect
on health behaviours and the metabolic syndrome.

Conclusion Work stress may be an important determinant of CHD among working-age populations, which is mediated through
indirect effects on health behaviours and direct effects on neuroendocrine stress pathways.

– – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –
Keywords Work stress † Autonomic nervous system † Myocardial infarction † Angina † Coronary heart disease

Psychosocial

Introduction
Stress at work is associated with an increased risk of coronary heart
disease (CHD) but the mechanisms underlying this association
remain unclear.1 Work stress may affect CHD through direct acti-
vation of neuroendocrine responses to stressors, or more indirectly
through unhealthy behaviours which increase the risk of CHD, such
as smoking, lack of exercise, or excessive alcohol consumption. One
of the main axes of neuroendocrine stress responses is the auto-
nomic nervous system (ANS). Repeated activation of the ANS is
characterized by lowered heart rate variability, which has been
associated with work stress among men in cross-sectional
studies.2,3 Furthermore, work stress may affect dysregulation of
the hypothalamic – pituitary – adrenal axis,4 which is associated with
disturbances in the circadian rhythm of cortisol and the develop-
ment of the metabolic syndrome.5,6

Accumulation of work stress is associated with higher risks of
the metabolic syndrome,7 and incident obesity.8 However, there
are few longitudinal studies examining the effect of cumulative
work stress on other intermediate mechanisms, despite evi-
dence that chronic stress predicts cardiovascular mortality and
morbidity.9 It is important to examine cumulative exposures in
order to show dose – response relations,10 which would con-
tribute a causal understanding of the association between
work stress and CHD. In addition, there is little longitudinal evi-
dence on the mechanisms by which work stress affects CHD.
Stronger associations between work stress and CHD risk
among working-age populations would also increase the speci-
ficity of this association.

This study addresses the following questions: 1 Is the accumu-
lation of work stress associated with higher risks of incident
CHD and risk factors? 2 Is this association stronger among

* Corresponding author. Tel: þ44 20 7679 5629, Fax: þ44 20 7813 0242. Email: t.chandola@ucl.ac.uk
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2008. For permissions please email: journals.permissions@oxfordjournals.org.

European Heart Journal (2008) 29, 640–648
doi:10.1093/eurheartj/ehm584

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working-age populations? 3 Does work stress affect CHD directly
through neuroendocrine mechanisms and/or indirectly through
behavioural risk factors for CHD?

Methods

Study sample and design
The Whitehall II study conducted in 1985 – 88 (phase 1) recruited
10 308 participants from 20 civil service departments in London.
After initial participation, data collection was carried out in 1989 – 90
(phase 2), 1991 – 93 (phase 3), 1995 (phase 4), 1997 – 99 (phase 5),
2001 (phase 6), and 2002 – 04 (phase 7). Phases 2, 4, and 6 were
postal questionnaires, and phases 3, 5, and 7 also included a clinical
examination. Full details of the clinical examinations are reported else-
where.11 Ethical approval for the Whitehall II study was obtained from
the University College London Medical School Committee on the
ethics of human research. Informed consent was obtained from the
study participants.

Assessment of work stress
Self-reported work stress was measured by the job-strain question-
naire.12 Participants report job-strain when their responses to the
job demands questions are high and decision latitude ( job control)
questions are low (defined as being above or below the median
score for the measures of job demands and decision latitude). In
addition, participants are said to have iso-strain when they report job-
strain and are socially isolated at work (i.e. without supportive co-
workers or supervisors).7,13,14 A cumulative measure of work stress
was created by adding together the number of times the participant
reported iso-strain at phases 1 and 2 (range 0 – 2), giving us a
measure on the duration of exposure to work stress, although
measured on two occasions only. Participants who lacked work
stress data at either phase were assigned a missing value. The preva-
lence of work stress (iso-strain) was lowest in the highest civil
service grade.

Follow-up measurements
CHD events included fatal CHD (ICD9 codes 410 – 414 or ICD10
I20 – 25) or incident non-fatal myocardial infarction (MI) from phases
2 – 7 (an average of 12 years of follow-up), with or without angina.
Non-fatal MI was defined following MONICA criteria15 based on
study electrocardiograms, hospital acute ECGs, and cardiac enzymes,
and excluded participants with existing MI at phase 1 or 2. Incident
angina was defined on the basis of clinical records and nitrate medi-
cation use, excluding cases based solely on self-reported data
without clinical verification and participants with definite angina at
phase 1 or 2.

Biological risk factors for CHD included the ATPIII16 metabolic syn-
drome measured at phase 3, its components (waist circumference:
men .102 cm, women .88 cm; serum triglycerides: �150 mg/dL;
HDL cholesterol: men ,40 mg/dL, women , 50 mg/dL; blood pressure:
�130/�85 mmHg or on antihypertensive medication; fasting glucose:
�110 mg/dL); morning rise in cortisol and low heart rate variability
(both measured at phase 7).

For the evaluation of heart rate variability, 5 min of RR interval data
were collected and analysed both in the time domain [standard devi-
ation of all intervals between normal-to-normal sinus rhythm R
waves (SDNN)] and in the frequency domains: low frequency 0.04 –
0.15 Hz (ms2) and high frequency 0.15 – 0.4 Hz (ms2). These measures

were log-transformed to obtain a more normal distribution for the
regression analyses.

For the evaluation of cortisol, participants were asked to provide
samples of saliva collected at waking and 30 min after waking. Partici-
pants were asked to record time of waking. Samples were posted
back and stored at 2808C for subsequent hormone analysis. Cortisol
was measured as previously described.17 Morning rise in cortisol was
calculated as the difference between cortisol levels at waking and
30 min after waking.

Behavioural risk factors (at phase 3) for CHD included alcohol,
smoking, activity, and diet. Alcohol consumption in the previous
week was categorized into non-drinker, recommended (1 – 14 units
for women/1 – 21 units for men), and unsafe (14þ units for women/
21þ units for men). Cigarette smoking categories were non-
smoker, ex-smoker, 1 – 9 cigarettes/day, 10 – 19 cigarettes/day, and
20þ cigarettes/day. Physical activity was measured by self-reported
frequency of moderate activities (3þ times a week, at least once a
week, at least once a month, never). Diet was measured by self-
reported fruit or vegetable consumption (less than weekly, less than
daily, and at least daily). For logistic regression analyses, these health
behaviours were coded into binary variables of current vs. never/
ex-smokers, unsafe drinkers vs. non/recommended limit drinkers,
less than daily fruit/vegetable consumption vs. daily, and no physical
activity vs. some activity.

Missing data and statistical methods
There were 10 308 civil servants who participated in the baseline
(phase 1) study. By phase 7, of the 9692 participants still alive, 6484
attended the clinical examination, 71% on whom we measured heart
rate variability. Of those participants who were asked to collect
saliva samples, 90.1% (n ¼ 4609) returned samples. Some samples
were not assayed for technical reasons. Participants taking corticoster-
oid medication were excluded from analysis (n ¼ 236). Any partici-
pants taking the first sample more than 10 min after waking were
excluded from analysis (n ¼ 634), this is the commonly used cut-off
when investigating daytime cortisol levels, as the cortisol awakening
response is already substantially under way.

A missing value on the work stress measure could indicate that the
data were not available at a particular phase, the participant dropped
out, or the participant was not in employment. There were 7721 par-
ticipants who were still in employment at phase 2 with work stress
data at phases 1 and 2. Out of these participants, 98% had follow-up
data on incident CHD, 86 – 90% had information on health behaviours
and the metabolic syndrome at phase 3, 45 – 49% had information on
heart rate variability and cortisol at phase 7.

Cox proportional hazard regression models were used to model the
association between the cumulative work stress measures (from
phases 1 and 2) and incident CHD events (from phases 2 to 7),
adjusted for age, sex, and employment grade, smoking history, total
cholesterol, and hypertension (systolic blood pressure .140 and
diastolic blood pressure .90, or on antihypertensive medication).
Logistic/linear regression models were then used to model the
association between cumulative work stress and binary/continuous
CHD risk factors. Finally, Cox proportional hazard regression
models were used again to examine the reduction in the hazard
ratios of cumulative work stress on CHD, adjusted for potential inter-
mediate pathways (health behaviours and the metabolic syndrome).
Heart rate variability and cortisol could not be examined as potential
mediators, as they were not measured in the first few phases of data
collection. All statistical significance testing used a two-sided test at
the 0.05 significance level. As the main exposure (work stress) con-
sisted of two pairwise comparisons (no report vs. one report, and

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no report vs. two reports), Bonferroni corrected P-values (a conservative
statistical adjustment to adjust for multiple comparisons) are reported
to reduce the risk of type 1 errors. Some of the analyses were strati-
fied by age-group if there was a significant interaction between age and
work stress.

Results
The distribution of all the variables in the analysis is shown in Table A1.
Table 1 displays the hazard ratios of incident CHD by cumulative
measures of work stress from phases 1 and 2. Greater reports of
work stress were associated with a higher risk of CHD. This was
true for both major CHD events (fatal events and MI) and definite
angina. Although reporting bias may lead to a spurious association
between self-reports of stress and angina pectoris,18 the estimated
risks of MI and definite angina were similar and so further analyses
combined these two CHD outcomes.

There was a significant interaction between age and two reports
of work stress (P ¼ 0.04), so the analysis is stratified by age group.
Among younger participants (aged 37 – 49 at phase 2), there was a
clear dose – response association between greater reports of work
stress and higher risks of incident CHD events. Among older par-
ticipants (aged 50 – 60), there was little association between work
stress and CHD. Stratifying by employment status at phase 5
revealed similar effects (analysis not shown).

Table 2 shows the association of work stress (measured at
phases 1 and 2) with the metabolic syndrome, its components,
and health behaviours (all from phase 3) among younger (aged
under 50) respondents in the Whitehall II cohort. Greater
reports of work stress were associated with poorer health beha-
viours in terms of eating less fruit and vegetables and less physical
activity. In addition, work stress was associated with not drinking
any alcohol (which increased the risk of CHD, Table A2). Work
stress was also associated with the overall metabolic syndrome
and four of its five components. Adjusting for health behaviours
only slightly reduced the association between work stress and
the overall metabolic syndrome.

Table 3 shows the association between work stress (at phases 1
and 2) and low heart rate variability (at phase 7), and morning rise
in cortisol (at phase 7) for participants at all ages (there was no sig-
nificant interaction between age and work stress). Greater reports
of work stress were associated with lower heart rate variability in
terms of lowering of the total variance and low- and high-
frequency components. There was little association with morning
rise in cortisol. However, additional cross-sectional analysis at
phase 7 between work stress and cortisol revealed significantly
elevated morning rise in cortisol among those reporting work
stress (P , 0.05). All the analyses in Table 3 were adjusted for
age, sex, employment grade, hypertension, total cholesterol,
smoking, and other health behaviours.

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Table 1 Hazard ratios (95% confidence intervals) of incident coronary heart disease events (phases 2 – 7) by cumulative
work stress (phases 1 – 2), age group: the Whitehall II study with an average follow-up of 12 years

Case definition and sample

Work stress

Linear trend P-value

No report One report Two reports

All CHD—all ages 1.00 1.23 (0.90 – 1.68) 1.33 (1.04 – 1.69) 0.01

P-valuea 0.19 0.02

P-valueb 0.37 0.04

Cases/n 416/6052 38/497 68/779

CHD death or MI—all ages 1.00 1.18 (0.75 – 1.87) 1.56 (1.12 – 2.17) 0.01

P-valuea 0.47 0.01

P-valueb 0.94 0.02

Cases/n 242/6285 24/522 43/818

Definite angina—all ages 1.00 1.34 (0.93 – 1.93) 1.43 (1.07 – 1.90) 0.01

P-valuea 0.11 0.02

P-valueb 0.23 0.03

Cases/n 337/6276 35/523 57/819

All CHD—age 37 – 49 at baseline 1.00 1.40 (0.88 – 2.22) 1.68 (1.17 – 2.42) ,0.01

P-valuea 0.16 ,0.01

P-valueb 0.32 0.01

Cases/n 174/3912 22/346 38/509

All CHD—age 50 – 60 at baseline 1.00 1.09 (0.68 – 1.77) 1.13 (0.79 – 1.63) 0.47

P-valuea 0.71 0.51

P-valueb 1.00 1.00

Cases/n 258/2314 19/170 33/300

Hazard ratios are adjusted for age, sex, employment grade, hypertension, total cholesterol, and smoking history.
aP-value adjusted for age, sex, employment grade, hypertension, total cholesterol, and smoking.
bBonferroni corrected P-value adjusted for age, sex, employment grade, hypertension, total cholesterol, and smoking.

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Table 4 displays the hazard ratios of incident CHD for the
younger respondents (aged under 50) by work adjusted for beha-
vioural risk factors and the metabolic syndrome. There was a 16%
reduction in the hazard ratios when behavioural risk factors were
adjusted for, and a similar reduction when adjusting for the overall
metabolic syndrome. Adjusting for both health behaviours and the
metabolic syndrome reduced the work stress – CHD association
by �32%.

Discussion
Cumulative work stress is a risk factor for CHD and neuroendo-
crine stress responses, especially among the younger, working-age
population. Around 32% of the effect of work stress on CHD can
be explained by the effect of work stress on health behaviours
(low physical activity and poor diet in particular) and the metabolic
syndrome.

The association between work stress and CHD was stronger
among employees younger than 50 and those still in employ-
ment. This is in agreement with previous age group analyses
of work stress19 and is consistent with the fact that more
robust work stress – CHD associations have been found in
studies employing younger20,21 than older cohorts.22,23 Among
older employees, the impact of work stress might be attenuated
because of a healthy worker survivor bias. Retirement during
the follow-up removes work stress and this exposure mis-
classification may also reduce the effect of work stress. Further-
more, an increasing number of other age-related causes of CVD
may eclipse the effect of work stress as these other causes
figure into both the numerator and the denominator of the
ratio.

An important case – control study (INTERHEART24) of 11 119
patients with a first MI and 13 648 age- and sex-matched con-
trols in 52 countries found that ‘permanent’ stress at work
was associated with over twice the odds of MI compared with
those reporting no stress at work. However, few studies have
been able to move from demonstrating associations to causality.
This article builds on the INTERHEART and other studies by
advancing a causal understanding of this association in terms of
dose – response associations, establishing the plausibility of this
association in terms of underlying biological and behavioural

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Table 2 Odds ratios (95% confidence intervals) of
health behaviours (phase 3) and metabolic syndrome
(phase 3), by cumulative work stress (phases 1 – 2):
Whitehall II respondents aged under 50 at phase 2

Model 1 Model 2 Cases/n

Health behaviours

Less than monthly fruit/vegetable

No report of
work stress

1.00 42/3575

One report 1.10 (0.43 – 2.84) 5/316

Two reports 2.12 (1.07 – 4.18) 11/461

No alcohol consumption

No report of
work stress

1.00 558/3581

One report 1.24 (0.92 – 1.67) 66/316

Two reports 1.42 (1.11 – 1.82) 101/461

No physical activity

No report of
work stress

1.00 377/3581

One report 1.07 (0.74 – 1.55) 37/316

Two reports 1.33 (1.00 – 1.78) 66/460

Current smoker

No report of
work stress

1.00 464/3580

One report 1.27 (0.93 – 1.73) 56/316

Two reports 1.11 (0.84 – 1.47) 68/460

Metabolic syndrome

High waist

No report of
work stress

1.00 1.00 231/3292

One report 1.29 (0.84 – 1.99) 1.24 (0.81 – 1.92) 26/283

Two reports 1.51 (1.08 – 2.13) 1.46 (1.03 – 2.06) 45/426

High fasting glucose

No report of
work stress

1.00 1.00 570/3201

One report 1.02 (0.74 – 1.42) 1.05 (0.76 – 1.47) 48/269

Two reports 1.40 (1.08 – 1.80) 1.43 (1.10 – 1.85) 89/410

High triglycerides

No report of
work stress

1.00 1.00 802/3308

One report 1.18 (0.89 – 1.57) 1.16 (0.87 – 1.54) 78/280

Two reports 1.33 (1.06 – 1.69) 1.30 (1.03 – 1.65) 119/425

HDL cholesterol

No report of
work stress

1.00 1.00 597/3308

One report 1.21 (0.89 – 1.63) 1.17 (0.86 – 1.59) 61/280

Two reports 1.32 (1.03 – 1.68) 1.26 (0.98 – 1.62) 95/425

Hypertension

No report of
work stress

1.00 1.00 1182/3332

One report 0.87 (0.67 – 1.13) 0.88 (0.67 – 1.14) 93/285

Two reports 1.13 (0.91 – 1.39) 1.13 (0.91, 1.40) 159/430

Continued

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 2 Continued

Model 1 Model 2 Cases/n

ATPIII metabolic syndrome

No report of
work stress

1.00 1.00 357/3308

One report 1.33 (0.93 – 1.91) 1.33 (0.93 – 1.91) 39/280

Two reports 1.72 (1.30 – 2.29) 1.69 (1.26 – 2.25) 69/425

Logistic regression odds ratios in model 1 are adjusted for age, sex, and
employment grade; logistic regression odds ratios in model 2 are additionally
adjusted for health behaviours.

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mechanisms, and demonstrating the specificity of this association
among working-age populations.

There are relatively few studies which have found associations
between work stress and (un)healthy behaviours. Work stress is
associated with smoking and exercise,25 whereas fatty food
intake increases under stressful conditions.26 Work stress has
also been linked with problem drinking, although in this cohort,
non-drinkers had the highest risk of CHD (and were more likely
to report work stress).

Previous cross-sectional analysis from the Whitehall II study has
shown low control at work is associated with poor autonomic
function,2 and neuroendocrine activation during the working
day.4 Longitudinal analyses from the study have shown that work
stress is related to CHD,14 the metabolic syndrome,7 and predicts
weight gain and incident obesity.8 This study adds to the literature
by showing a linear association between work stress and CHD
events, the components of the metabolic syndrome, and lower
heart variability. In addition, �16% of the effect of work stress
on CHD can be explained by the effect of work stress on the
metabolic syndrome. As there was little reduction in the associ-
ation between work stress and the metabolic syndrome after
adjusting for health behaviours, work stress may directly affect
neuroendocrine stress mechanisms independently of health

behaviours, resulting in increased risks of the metabolic syndrome.
Direct biological stress-effects are additionally possible through
acute work-related stressors triggering MI in susceptible individ-
uals,27 a possibility which is consistent with the relatively small
effect attenuation after adjustment for metabolic components
and the fact that the association between work stress and CHD
diluted in individuals who stopped work during follow-up. Heart
rate variability and cortisol were not measured in the early
phases of the study, so their role as a potential mediator of the
work stress – CHD association could not be examined. However,
adjusting for health behaviours did not change the association
between work stress and (low) heart rate variability, suggesting a
direct effect on the ANS and neuroendocrine function, rather
than indirect effects through health behaviours. The association
between work stress and the heart rate variability components
suggests that work stress leads to vagal withdrawal and sympath-
etic saturation indicating a prevalence of sympathetic mechanisms
leading to cardiac electrical instability.28

Cumulative work stress did not predict a greater cortisol awa-
kening response. However, there was a cross-sectional association
between work stress and greater cortisol awakening response. A
lag period of around 12 years between exposure (work stress)
and disturbances in the circadian rhythm of cortisol may not be
optimal for the detection of the hypothesized neuroendocrine
effect.

The Whitehall II cohort is a sample of primarily office-based
white-collar workers. There were few manual workers in the
cohort. It is possible that the mechanisms underlying the associ-
ation of work stress with CHD may differ in manual workers,
although there is little evidence for this hypothesis.29 Previous
research has suggested that the effect of work stress on cardiovas-
cular is less consistent among women.30 The Whitehall II cohort is
predominantly male (67%), although gender-stratified analysis
revealed similar estimates of work stress on CHD among
younger men and women. Missing data is a common problem all
cohort studies face. Non-responders at the later clinical examin-
ations were more likely to report work stress, consume less
alcohol, have poor diets and high cholesterol, come from lower
employment grades, be smokers, physically inactive, and obese,
resulting in an underestimation of these effects in the analyses.
The results on the heart rate variability and cortisol are less
robust compared with the other outcomes due to the greater non-
response at phase 7. The metabolic syndrome has been criticized
as a purely artificial construct,31 not contributing any further infor-
mation over its component risk factors, although recent results
suggest otherwise.32 This article acknowledges this debate on
the metabolic syndrome and presents results on the syndrome
itself as well as its components. There may be unmeasured con-
founders which may ‘cause’ the association between work stress
and CHD, such as other sources of stress and personality type.

This study adds to the evidence that the work stress – CHD
association is causal in nature.10 We demonstrate, within a popu-
lation of office staff largely unexposed to physical occupational
hazards, a prospective dose – response relation between psycho-
social stress at work and CHD over 12 years of follow-up.
We confirm, during the same exposure period, the plausibility of
the proposed pathways involving behavioural mechanisms,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 3 Regression coefficients (95% confidence
intervals) of heart rate variability (phase 7) and morning
rise in cortisol (phase 7), by cumulative work stress
(phases 1 – 2): Whitehall II respondents, all ages

All ages n

Log of low frequency power

No report of work stress 0.00 2769

One report 20.09 (20.23 to 0.04) 211

Two reports 20.14 (20.25 to 20.02) 310

P-value for linear trend ,0.01

Log of high frequency power

No report of work stress 0.00 2769

One report 20.05 (20.21 to 0.11) 211

Two reports 20.14 (20.27 to 0.00) 310

P-value for linear trend ,0.05

Log of SD of NN intervals

No report of work stress 0.00 2769

One report 20.05 (20.12 to 0.01) 211

Two reports 20.05 (20.10 to 0.00) 310

P-value for linear trend ,0.05

Morning rise in cortisol

No report of work stress 0.0 2368

One report 0.00 (21.85 to 1.85) 169

Two reports 20.60 (22.11 to 0.91) 274

P-value for linear trend 0.45

All models are adjusted for age, sex, employment grade (phase 1), total
cholesterol (phase 1), hypertension (phase 1), smoking history (phase 1), and
other health behaviours (phase 3). In addition, morning rise in cortisol is adjusted
for waking up time.

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neuroendocrine and autonomic activation, and development of
risk factor clustering, represented by the metabolic syndrome.1,2,6,7

Further, those who are older (and are more likely to be retired and
less exposed to work stress) are less susceptible to the work psy-
chosocial effect, presenting a coherent pattern in our findings. This
study demonstrates that stress at work can lead to CHD through
direct activation of neuroendocrine stress pathways and indirectly
through health behaviours.

Acknowledgements
We thank all participating civil service departments and their
welfare, personnel, and establishment officers; the Occupational
Health and Safety Agency; the Council of Civil Service Unions;
all participating civil servants in the Whitehall II study; and all
members of the Whitehall II study team.

Conflict of interest: none declared.

Funding
The Whitehall II study has been supported by grants from the Medical
Research Council; Economic and Social Research Council; British
Heart Foundation; Health and Safety Executive; Department of
Health; National Heart Lung and Blood Institute (HL36310), US,
NIH; National Institute on Aging (AG13196), US, NIH; Agency for
Health Care Policy Research (HS06516); and the John D. and Cathe-
rine T. MacArthur Foundation Research Networks on Successful
Midlife Development and Socio-economic Status and Health. M.M. is
supported by an MRC Research Professorship, H.H. by a public
health career scientist award from the Department of Health, and
M.K. by the Academy of Finland (grant 117 604).

Appendix 1

Table 4 Hazard ratios of incident all coronary heart disease events (phases 3 – 7) by cumulative work stress (phases 1 – 2)
adjusted for health behaviours (phase 3) and metabolic syndrome (phase 3): Whitehall II respondents aged under 50 at
phase 2

Model 1 þAll health behaviours

No report 1.00 1.00 140/3408

One report 1.52 (0.93 – 2.48) 1.43 (0.87 – 2.34) 18/292

Two reports 1.56 (1.02 – 2.37) 1.47 (0.97 – 2.25) 26/434

P-value for linear trend 0.02 0.04

þMetabolic syndrome

No report 1.00 1.00 144/3419

One report 1.48 (0.90 – 2.41) 1.44 (0.88 – 2.36) 18/294

Two reports 1.61 (1.06 – 2.43) 1.51 (1.00 – 2.29) 27/439

P-value for linear trend 0.01 0.03

þHealth behaviours and metabolic syndrome

No report 1.00 1.00 136/3265

One report 1.41 (0.84 – 2.37) 1.27 (0.75 – 2.15) 16/275

Two reports 1.56 (1.02 – 2.39) 1.38 (0.90 – 2.13) 25/416

P-value for linear trend 0.03 0.11

Model 1 is adjusted for age, sex, and employment grade.

Table A1 Distribution of the variables in the analysis

Sex

Men 3413

Women 6895

Age group (phase 1)

35 – 39 2811

40 – 44 2663

45 – 49 2107

50 – 56 2727

Cigarette smoking (phase 1)

Never smoker 5062

Ex-smoker 3274

0 – 9 cigarettes/day 540

10 – 19 cigarettes/day 774

20 or more cigarettes/day 418

Missing 240

Moderate exercise (phase 3)

Three times/week or more 1284

One to two times/week 3695

One to three times/month 2290

Never/hardly 1042

Missing 2000

Current smoker (phase 3)

Non-smoker 7168

Smoker 1145

Missing 1995

Continued

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Appendix 2

Table A1 Continued

Fruit/vegetable consumption (phase 3)

Less than daily 8198

Daily or more 112

Missing 1998

High waist (phase 3)

Normal 7258

Male .102 cm or female .88 cm 737

Missing 2313

High waist (phase 3)
Normal 7258
Male .102 cm or female .88 cm 737
Missing 2313

High glucose (phase 3)

Normal 6006

�110 mg/dL 1603

Missing 2699

High blood pressure (phase 3)

Normal 4823

High BPa 3351

Missing 2134

Employment grade (phase 1)

High 3028

Middle 4943

Low 2337

Total cholesterol (phase 1)

,5.2 mmol/L 2510

5.2 – 6.2 mmol/L 4006

.6.2 mmol/L 3718

Missing 74

Hypertension (phase 1)

Normotensive 9461

Systolic BP .140 mmHg/diastolic BPa .90 mmHg 832

Missing 15

ISO-strain (phase 1 – 2)

No report 6363

One report 529

Two reports 829

Missing 2587

Alcohol consumption (phase 3)

Low 1625

Moderate 5399

High 1288

Missing 1996

High triglycerides (phase 3)

Normal 5770

�150 mg/dL 2252

Missing 2286

Low HDL (phase 3)

Normal 6477

Male ,40 mg/dL, female ,50 mg/dL 1542

Missing 2289

Continued
Table A1 Continued

Metabolic syndrome (phase 3)

No syndrome 6897

Metabolic syndrome 1125

Missing 2286

Heart rate variability (phase 7) n ¼ 4095

Morning rise in cortisol (phase 7) n ¼ 3490

aIncludes those on antihypertensive medications.

Table A2 Hazard ratios of incident all coronary heart
disease events (phases 3 – 7): Whitehall II respondents
aged under 50 at phase 2

Employment grade

High 1.00

Middle 1.14 (0.84 – 1.56)

Low 1.65 (1.04 – 2.60)

Work stress

No reports of work stress 1.00

One report 1.55 (0.97 – 2.46)

Two reports 1.62 (1.10 – 2.40)

Waist circumference

Normal 1.00

High waist 2.04 (1.35 – 3.09)

Triglycerides normal 1.00

High triglycerides 1.93 (1.44 – 2.59)

Glucose tolerance normal 1.00

Glucose intolerance 1.35 (0.96 – 1.89)

HDL cholesterol
Normal 1.00

Low 2.03 (1.50 – 2.74)

Blood pressure

Normal 1.00

High blood pressure/antihypertensive
medication 2.16 (1.63 – 2.87)

Overall metabolic syndrome

No syndrome 1.00

Three or more MS components 2.52 (1.82 – 3.49)

Reported fruit/vegetable consumption

Daily or more 1.00

Less than daily 2.38 (1.12 – 5.06)

Physical activity

Three times/week or more 1.00

One to two times/week 1.51 (0.93 – 2.46)

One to three times/month 1.91 (1.15 – 3.16)

Never 2.16 (1.20 – 3.90)

Continued

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Table A2 Continued

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Unsafe alcohol limits 0.71 (0.46 – 1.11)

Cigarette smoker

Non-smoker 1.00

Ex-smoker 1.04 (0.75 – 1.44)

1 – 9 cigarettes/day 2.15 (1.24 – 3.72)

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20þ cigarettes/day 3.06 (1.71 – 5.49)

Hazard ratios are adjusted for age and sex.

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CLINICAL VIGNETTE
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

doi:10.1093/eurheartj/ehm436
Online publish-ahead-of-print 16 October 2007

Pulmonary thromboembolism and ‘temporary’ patent foramen ovalis:
ischaemic stroke due to paradox embolism
Gianfranco Aprigliano*, Maksim Llambro, and Angelo Anzuini

Department of Cardiology, Santa Rita Clinical Institute, Via Catalani 4, 20131 Milan, Italy
* Corresponding author. Tel: þ39 02 23933020, Fax: þ39 02 23933087, Email: heart@casadicura-santarita.it, gianfrancoaprigliano@hotmail.com

An 80-year-old woman was admitted to the
orthopaedic department of our hospital for elec-
tive right hip prosthesis implantation after recent
fracture of the right femore. The first day after
surgery, the patient became symptomatic for
dyspnoea. Haemo-gas analysis showed hypoxia
with hypocapnia. Slight elevation of D-dimer
(14.5 mcg/mL) and normal ECG was found out.
An echocardiogram revealed right ventricle
(RV) dilatation with free wall hypokinesis and
massive tricuspidal valve regurgitation secondary
to pulmonary hypertension (Panel A). A floppy
interatrial septum was also evidenced. Lower
limb echo-Doppler showed left iliac vein throm-
bosis. Based on this evidence, pulmonary angio-
graphy was performed and bilateral
thromboembolism diagnosed (Panels B and C).
Loco-regional pulmonary thrombolysis and low
molecular weight heparin at full dosage were
started. During the second day, the patient
became symptomatic for left-side emiparesis
and afasia. Sovra-aortic trunks duplex scan,
colour flow Doppler, and CT brain scan were
negative. Transoesophageal echocardiography
revealed a floppy aneurismatic interatrial
septum (Type C), patent foramen ovalis with
right to left shunt in basal conditions and positive
micro bubble test (Panel D). Forty-eight hours later, the patient repeated the CT brain scan, showing major ischaemic stroke in right temporal lobe
(Panel E). Subsequently, a caval filter was placed. One month later, a transoesophageal echocardiogram revealed aneurismatic floppy interatrial septum
without right to left shunt even after Valsalva manoeuvre, and normal pulmonary pressure (Panel F). It seems plausible that the unexpected increase of
pulmonary pressure secondary to pulmonary thromboembolism opened the foramen ovalis permitting right to left embolism.

Panel A. Transthoracic echocardiogram showing severe tricuspidal insufficiency. LA, left atrium; RA, right atrium; LV, left ventricle; RV, right ventricle;
TV, tricuspidal valve.

Panel B. The red arrow points to massive embolism of the right pulmonary artery (RPA).

Panel C. The red arrow points to massive embolism of left pulmonary artery (LPA).

Panel D. Transoesophageal echocardiogram showing patent foramen ovalis with right-to-left shunting (red arrow).

Panel E. CT brain scan showing ischaemic area in the right temporal lobe (red arrow).

Panel F. Transoesophageal echocardiogram showing floppy interatrial septum without evidence of right-to-left shunting after Valsalva manoeuvre.

Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2007. For permissions please email: journals.permissions@oxfordjournals.org.

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