Tracking Social and Biological Experiences: The Social Etiology of
Cardiovascular Disease
Lisa F. Berkman
Circulation 2005;111;3022-3024
DOI: 10.1161/CIRCULATIONAHA.104.509810
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Editorial
Tracking Social and Biological Experiences
The Social Etiology of Cardiovascular Disease
Lisa F. Berkman, PhD
T
he social gradient in cardiovascular disease (CVD) is
well known. There are literally scores of studies
showing that men and women who are socially disadvantaged are at increased risk of developing CVD and have
a worse prognosis once they develop the disease.1 During the
last 40 years, in most industrialized countries, a clear pattern
has emerged showing that each increase in socioeconomic
position confers a decreased risk in cardiovascular morbidity
and mortality. Men between the ages of 25 and 64 who are the
most disadvantaged have an !2.5-fold risk of dying of CVD.
For women, the risks are even greater (3.4-fold risk).2 Similar
trends are seen for risk-related disorders, including hypertension and diabetes. The causes and mediating pathways by
which this occurs are not nearly as well characterized,
however. Identifying the biological and behavioral mechanisms that link economic and social disadvantage to cardiovascular morbidity and mortality provides valuable insights
into the causes of CVD and information about where along
the spectrum of disease development we may effectively
intervene to improve outcomes in disadvantaged populations.
There is little debate about the social patterning and distribution of CVD. There is, however, ongoing debate about the
reason for the observed patterns.
See p 3071
Much of the social gradient was attributed originally to the
uneven distribution of a number of health behaviors related to
diet, tobacco consumption, physical inactivity, compliance
with therapeutic regimens, and differential access to highquality medical care. As the story goes, as better educated,
economically advantaged men and women learned about the
risks that are related to tobacco, obesity, and inactivity, they
changed their behaviors and subsequently reduced their
cardiovascular risks, often giving rise to even greater disparities in coronary heart disease (CHD). We now know that
differences in health behaviors account for a part of the
disparities in CHD but leave much unexplained.3 It is also
becoming increasingly clear that only a small part of the
association results from the impact of CVD on economic and
social mobility.4 The story is more complex, remains mysterious, and from a public health standpoint is even more
The opinions expressed in this article are not necessarily those of the
editors or of the American Heart Association.
From the Harvard School of Public Health, Boston, Mass.
Correspondence to Dr Lisa F. Berkman, Harvard School of Public
Health, 677 Huntington Ave, Boston, MA 02115. E-mail
lberkman@hsph.harvard.edu
(Circulation. 2005;111:3022-3024.)
© 2005 American Heart Association, Inc.
Circulation is available at http://www.circulationaha.org
DOI: 10.1161/CIRCULATIONAHA.104.509810
important because we have been unable to reduce disparities
even though we know so much about the causes of heart
disease.
Although CHD mortality rates have fallen steadily during
the last several decades, we have hardly made a dent in
reducing the incidence of disease nor have we reduced the
social disparities related to socioeconomic position or race/
ethnicity in either morbidity or mortality.5,6 Reducing both
disparities and morbidity in the population remains a major
challenge to public health and to medicine. Until we have a
better understanding of the causal links and pathways by
which social disadvantage translates into disease, we may
have a hard time reducing the burden of disease in the
population. Furthermore, according to the World Health
Organization’s Global Burden of Disease estimates, CHD
will be the major cause of death throughout the world by
2010,7 and most of the prevention programs that the West has
have exported have not been effective.8
There are two general areas in which we need more
information to build our understanding of the ways in which
social position influences CHD. The first relates to the
identification of biological pathways that mediate the social
experience of disadvantage and lead to increased risk. The
second relates to understanding the nature of the social
environment to identify precisely what it is about socioeconomic position that is so important to health. Often, scientists
working in biomedicine understand the importance of the first
of these areas (identifying the biological mechanisms) but
underestimate the importance of understanding the nature of
the social experience. To understand why this second issue is
so important, think of a crude indicator of some social
experience—say current occupation—and contemplate why it
might be related to cardiovascular risk. For instance, we
would like to know if the risk is related to the nature of the job
experience itself, whether it is stressful or demanding, or to
hazardous physical exposures on the job, or to the income it
provides, or to the neighborhoods in which people with
certain occupations live, or to the level of education needed to
attain a specific job. We may also wonder about the extent to
which current circumstances build on previous experiences or
exposures that provide protection throughout the life course.
In deepening our understanding of social context and social
experiences, one of the major advances in epidemiology has
been the incorporation of life-course perspectives into our
thinking. So, not only is it important to look at outcomes
longitudinally but also increasingly we have come to appreciate the need to assess the development of social and
biological risks longitudinally.
Epidemiological approaches to evaluating the association
between socioeconomic position and CVD are strongest
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Berkman
methodologically when we can (1) obtain data on biological
pathways likely to mediate social exposures and disease
outcomes, (2) incorporate multilevel analytic approaches in
which data are collected both at the “area” level as well as the
individual level, and (3) obtain data that are longitudinal with
regard to both risks and outcomes. The studies reported by
Hemingway and associates9 and others in this issue address
these 3 major issues involved in understanding the causes and
biological pathways by which CVD is shaped by social
disadvantage. They provide new insights but also have some
serious limitations that further stress the need to incorporate
both longitudinal and contextual frameworks into work in this
area.
Probing Biological Mechanisms
Recent work on biological mechanisms related to CVD has
identified new biomarkers related to inflammatory, sympathetic, and parasympathetic pathways and metabolic processes.10 Markers related to C-reactive protein, heart rate variability, and glucose metabolism and insulin resistance—
themselves causing physiological cascades that impact other
known risks— have emerged as central factors in the development of CVD.11 One of the most fascinating findings
related to these biomarkers is their association with physical
and psychosocial stressors.12 Thus, these biological processes
hold the potential to link a range of stressful exposures,
whether physical, social or psychological, to the onset and
course of CVD.
The findings from the Whitehall study published in this
issue of Circulation show the way in which heart rate
variability (HRV) varies by grade of employment and the
extent to which it clusters with other risks related to the
metabolic syndrome.9 This study of British civil servants has
been of central importance in identifying the ways in which
social hierarchies produce increases in risk of a number of
diseases and disorders, of which CVDs have been of prime
importance. The authors report that increasingly high occupational grade is related to decreasing heart rate and increasing HRV, risks that we know from other studies are protective
against cardiovascular events. Heart rate and HRV are also
associated with most indicators of the metabolic syndrome,
even when excluding subjects with the frank clinical syndrome. The authors argue that HRV mediates the influence of
social position on subsequent cardiovascular risk, in this case
risk related to the metabolic syndrome. Because the data from
this study are cross-sectional, this is an intriguing but controversial argument. Although the correlation between chronically impaired autonomic function and social position is
solid as is the correlation between HRV and the metabolic
syndrome, equally plausible is that components of the metabolic syndrome such as weight/hip circumference, impaired
glucose function, or blood pressure–influence patterns of
HRV. Longitudinal data on the course of the development of
risk would be invaluable here. For instance, if some of these
risks are laid down in early life or result from long-term
exposures in adulthood, we might identify whether patterns of
autonomic function are precursors of the metabolic function
or the result of disturbances in them.
Social Etiology of Cardiovascular Disease
3023
Data from studies that are strong on the clinical side but
weaker in assessing social experience may add to our knowledge of physiological cascades. We might then extrapolate
from these patterns to studies such as the Whitehall study. For
instance, data from the Framingham study show that autonomic dysregulation is present in the early stages of hypertension and that altered HRV predicts the new onset of
hypertension in men. Patterns are not so clear among women
in the Framingham study.13 HRV is also associated with
diabetes and impaired levels of fasting blood glucose, although the Framingham data are cross-sectional and it is as
reasonable to suspect that fasting blood glucose is involved in
the pathogenesis of autonomic dysregulation as the reverse.14
Reaven and colleagues15 have also argued that metabolic
abnormalities, particularly insulin resistance, are primary
influences on sympathetic activity and the development of
hypertension. In fact, the authors of the Whitehall study note
in their discussion that consistent with this hypothesis,
components of the metabolic syndrome explained 27% of the
social gradient in low-frequency power. Similar arguments
could be made for measures of obesity such as waist-to-hip
ratio. Thus, one could have as easily set up the Whitehall
analyses to examine the effects of components of the metabolic syndrome on heart rate and HRV and inferred causal
processes leading from glucose metabolism to other
outcomes.
Need for Population-Based Longitudinal Studies
As we search for the ways in which social conditions affect
cardiovascular health, it is critical to enroll random samples
of populations that are truly representative of the wide range
of men and women in particular nations or communities. The
diversity of social experiences related to economic and
occupational conditions cannot be captured any longer by
looking at white men in the workforce and excluding women,
minorities, and people who flow into and out of the workforce
because of market fluctuations and job insecurities. The
authors of the Whitehall study note that they are looking at a
“general population.” These analyses do not include women
and racial/ethnic minorities are excluded to avoid “confounding.” Because the Whitehall study is already a truncated
cohort in terms of range of occupational experiences, the
exclusion of such large segments of the UK population makes
generalizability precarious. Do the authors really mean to
suggest that job strain, HRV, and health behaviors “explain”
the gradient in heart disease? What about the gradients we see
for men and women who are not in the workforce? The
contribution of the Whitehall study to our understanding of
social gradients in heart disease has been immense,16 and in
terms of understanding biological mediation it has been at the
forefront of studies in this area. In light of the rising
importance of area-level effects, however, we may do well to
broaden our understanding of the range of social and economic exposures that travel with occupational grade of
employment. If, as other study findings suggest, the effects of
living in an impoverished and disadvantaged area remain
strong in future studies in which individual level indicators
are available, then entirely new areas of investigation are
open.
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3024
Circulation
June 14, 2005
Finally, much of epidemiology is longitudinal in the sense
of assessing risk and then following people prospectively into
the future, but this is not enough. Studies would be able to
draw stronger inferences if they were longitudinal in assessing exposures and identifying social and physiological cascades leading to disease onset and survival. No one study can
do everything, and this study gives us a peek at a long-term
process. We need an epidemiology that will help us sort out
the time course of the development of risks, with attention
paid to both the social and biological exposures and the
mediating pathways.
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KEY WORDS: Editorials
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