The population of north Glasgow is skewed to the
lower end of the
socioeconomic scale, but we still found socioeconomic gradients in
myocardial infarction among people who overall are least advantaged.
This socioeconomic variation is seen in event rate and most obviously
in the proportion of people reaching hospital alive. No variation is
seen in case fatality in hospital. These findings are reflected in the
socioeconomic variation in the proportion of people dying outside
hospital and the case fatality in the community overall. Socioeconomic
disadvantage thus increases the chance of a person having a myocardial
infarction, decreases the chance of reaching hospital alive, and
increases the chance of dying during the attack. This gradient is found
in both women and men.
Event rates
We found a large socioeconomic variation in the
event rate in men
and women. This agrees with studies using various markers of
socioeconomic group which show that deprivation, a shorthand for poorer
education, poorer housing, increasing poverty, and lack of employment,
relates to increasing event rates.14-16 Furthermore,
socioeconomic variations in the extent of coronary risk factors in a
population are associated with socioeconomic variation in disease
prevalence.24 This supports the idea of reducing the
unequal distribution of risk as a prime objective for local and
national health promotion activities.
Arrival at hospital
The socioeconomic differences we and
others have found may reflect
poorer awareness of the importance of symptoms such as crushing chest
pain or arm pain among those who are less well
educated.18-19 Alternatively, the proportion of sudden
deaths may rise by association with cigarette smoking.25
Seventy one per cent of all deaths in men but only 63% of deaths in
women occurred outside hospital, reflecting the greater proportion of
women arriving alive at hospital. A similar socioeconomic gradient was
seen in men and women. We have already shown that women are more likely
to reach hospital after a call to the family doctor, whereas men are
more likely to go directly.5 Perhaps referral patterns
also vary subtly according to patients' backgrounds.
Only two thirds of patients were admitted to hospital. The remaining
third died outside hospital, limiting the impact of treatments in
hospital.
Death rate in admitted patients
We found no social class
variation in case fatality in hospital.
This is consistent with the Scottish Office's data on mortality in
hospital 30 days after a myocardial infarction, which show little
variation when standardised for social class.26 A greater
case fatality in hospital has been reported among people who are less
well educated20 and among African-American women (with
higher unemployment rates) compared with white women,27
and this was only partly explained by differences in case mix. Our
findings may reflect a lack of bias in the care given to different
socioeconomic groups. The case mix of hospital admissions may vary by
socioeconomic quarter.20 Severely ill people from deprived
background might be more likely to die outside hospital because of
delays in admission. If care shows a socioeconomic bias against
deprived people this might cancel out a better case mix.
Cardiologists and general physicians differ in their management of
patients during myocardial infarction28 and unstable
angina.29 Do they differ in how they care for patients
with myocardial infarction of different socioeconomic groups?
Socioeconomic bias applies to angiography for men in
Glasgow30 and elsewhere31 but not
to
invitation to rehabilitation after myocardial
infarction.32 Furthermore, men and women are treated
similarly once they are receiving care for myocardial
infarction.5
Community case fatality
The increase in overall case fatality
with deprivation may have
several explanations. Non-fatal events in deprived people may be less
frequently recognised - that is, the denominator for case fatality in
the more deprived groups may be comparatively more incomplete. Death,
however, is enumerated similarly for all social groups. Any undercount
in the denominator would imply an underestimate of the socioeconomic
gradient.
Several factors could explain the variation in the numerator between
socioeconomic groups. Firstly, the number of concomitant illnesses,
particularly respiratory disease, increases with increasing
deprivation.33
Secondly, coronary disease itself may be different in different
socioeconomic groups, perhaps manifesting more often among deprived
people as sudden death through the mediation of factors such as higher
rates of cigarette smoking.25
Thirdly, there may be a social class gradient in the ability to heal or
to ward off insults to various organs. In Glasgow recovery from various
surgical procedures for cancer is worse among people who are deprived
after adjustment for stage of disease and treatment.34
Finally, the potential for resuscitation, available for 38% of people
who died outside hospital in north Glasgow, was fulfilled in less than
a third of that number.35 This proportion is much greater
elsewhere.34 The advent of Heartstart Scotland - the
equipping of all emergency ambulances with semiautomatic
defibrillators - has had little effect on successful resuscitation
outside hospital in north Glasgow35 in contrast to other
places.36 Exploration of the possible reasons for these
differences is required to maximise the benefit of available services
such as Heartstart Scotland.
The quality of Glasgow MONICA registration data in terms of
completeness, accuracy, and consistency over time has been
documented.5-6 Carstairs and Morris deprivation scores
are better than occupational classification in discriminating between
deprived socioeconomic groups as many of those on the register are
unemployed.5 Postcode of residence, but not occupation, is
routinely coded on both death certificates and hospital discharge data.
The Carstairs and Morris score has been criticised for its complexity
and for not relating to people but to geographical areas. However, it
remains useful in describing variation over a wide range of morbidity,
mortality, and other health related population
measurements.2 38-39 Calculation of rates for
deprivation quarters of the population using the 1991 census population
as denominator for all of the data from 1985-91 might be criticised.
However, there are no intercensal estimates made at that population
level. As our data refer to 1985-91 we used the closest census
population, that of 1991.
Implications and conclusions
Tackling inequalities in health
has only recently received
government emphasis.40 Reductions in mortality from
coronary heart disease principally reflect reduction in risk factors in
a population.41 Socioeconomic variation in health and
disease has been recognised for hundreds of years.42
Action to reduce the variation has many years of inaction at all levels
to redress.
Disease registers are valuable datasets for exploring variation in
diseases in a population. Examination of subgroups, such as patients
admitted to a coronary care unit or a trial, will always give a biased
picture when 34% of people never reach hospital alive and two thirds
of deaths occur before hospital admission. Those allocating scarce
healthcare resources should therefore consider socioeconomic variation
not only in community death rates but also at other points in the
disease process such as the chance of dying outside hospital and
therefore of reaching hospital care alive.
We have shown that the greatest socioeconomic variation in death is
during the prehospital phase of myocardial infarction and coronary
death. Thus treatments applied equitably in hospitals across
socioeconomic groups during acute myocardial infarction will have
little impact on socioeconomic variation in death rates. If the deaths
outside hospital were not inevitable and patients reached hospital and
received hospital treatment then acute care could have an impact on the
socioeconomic variation in coronary mortality.
Further investigation is required to understand the reasons for the
differences in prehospital mortality in terms of different patterns of
accessing care, differences between socioeconomic groups in treatment
before the attack, and socioeconomic gradients in disease severity
before strategies can be devised to address this aspect of
socioeconomic variation in myocardial infarction and coronary death.
| Key messages |
| Socioeconomic variation in rates of coronary events was
greater for women than men
The largest social class gradient was in the proportion of
deaths occurring outside hospital
Overall, 68% of all people who died of coronary events did so
before admission
Acute hospital care applied to only 66% of all cases and
therefore could affect only 32% of all deaths
Reduction in socioeconomic variation in mortality from
coronary disease is best addressed by reducing the variation of event
rates - that is, by primary and secondary prevention
Allocation of resources for reduction of coronary mortality
should take account of social class differences and the relative
potential effect of hospital care and primary and secondary
prevention |
We thank K Barrett, C Brown, C Bauwens, H Bilkhu, C Bowman, B
Fitzpatrick, J Graham, M Hastings, M Irving, E Kesson, W Leslie,
M-K McCluskey, W Millar, M Mitchell, J Palmer, M Robb, M Sharkey, M
Shewry, M Thornton, W Tunstall-Pedoe, A Urie, and G Watt for their
contribution to establishing the register, compiling the manual of
operations, and collecting, coding, managing, and checking and
verifying the data. We would be unable to maintain the register without
the unfailing goodwill of the general practitioners of north Glasgow.
We are also grateful for the support of ISD, the Information and
Statistics Division of the Common Services Agency; hospital records
officers and their staff in Glasgow Royal Infirmary and University NHS
Trust, West Glasgow Hospitals and University NHS Trust, and Stobhill
Hospital Trust; and other records departments throughout the United
Kingdom. We thank the staff of the deaths unit of the Office of the
Procurator Fiscal, Glasgow, the staff of offices of other procurators
fiscal throughout Scotland, and staff of coroner's offices in England
for their willing cooperation. Although we are unable to acknowledge
them individually, many other people and agencies have generously
supported the work of the Glasgow MONICA project register. The views
expressed in this paper are ours alone and do not necessarily reflect
those of the funding body or of those acknowledged above as previous or
current members of staff.
Funding: The Scottish MONICA project was funded by grants from
the Chief Scientist Office of the Scottish Office Home and Health
Department.
Conflict of interest: None.
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(Accepted 6 December 1996)
MONICA Project,
Royal Infirmary, Glasgow G31 2ER
Caroline Morrison,
consultant in public health
medicine
Wilma Leslie, senior research
nurse
Department of Applied Statistics,
PO Box 240,
University
of Reading,
Reading RG6 6FN
Mark Woodward,
senior lecturer in statistical
epidemiology
Cardiovascular Epidemiology Unit,
Ninewells Hospital and Medical School,
Dundee DD1 9SY
Hugh
Tunstall-Pedoe,
professor
Correspondence to: Dr
Morrison.
