American Journal of Epidemiology
Copyright O 2000 by The Johns Hopkins University School of Hygiene and Public Health
All rights reserved
Vol. 151, Mo. 8
Printed In USA.
LETTERS TO THE EDITOR
RE: "SEEKING CAUSAL EXPLANATIONS IN SOCIAL EPIDEMIOLOGY"
Kaufman and Cooper's recent commentary, "Seeking
Causal Explanations in Social Epidemiology" (1), along
with their response (2) to the rejoinder by Muntaner (3),
raises provocative questions about the validity of study
designs routinely used by social epidemiologists to quantify
and analyze determinants of social inequalities in health.
Seeking to improve social epidemiology's concepts and
methods, Kaufman and Cooper draw attention to ways they
believe social epidemiologists routinely violate the counterfactual assumption that, for a risk estimate to be valid, a person who is "exposed" would be the same person if "unexposed," except for the fact of exposure.
Yet, according to Kaufman and Cooper, the realities of
racism mean that a person in the United States who is Black
would never be the "same" person if she or he were White.
By contrast, a given individual would or could not be
exposed to, say, lead without altering all other aspects of that
person's life. By this logic, comparisons across categories of
exposure to lead would be meaningful and interpretable,
whereas etiologic inferences based on comparisons of health
status across the social groups of "Black" and "White"
would be invalid. The same problem, according to Kaufman
and Cooper, affects studies comparing health status across
groups categorized in relation to gender, age, and, to a lesser degree, social class (given possibilities of class mobility).
Stated simply, you would not be who you are (and therefore
exposed to your lifelong history of health-damaging and
health-promoting situations) if you belonged to a different
social group. Related methodological issues raised by
Kaufman and Cooper involve both correlations among
exposures imposed by membership in social groups and limitations of individualistic methodologies to gauge how
social structures shape population health.
From our view, however, the problems Kaufman and
Cooper pose have more to do with epidemiologic imagination—and responsibilities—than with deficiencies in methods. The starting point for considering the "exchangeability"
criterion is that we are, first and foremost, equivalent as
human beings, with equivalent rights to health and wellbeing (4, 5). Can we imagine a world without racism, without class inequality, without gender inequality? Surely we
can. Can we ask how health status is affected by membership in groups who benefit from or are oppressed by these
different types of inequality? Of course we can. Can we
likewise ask how being a member of one birth cohort, as
compared with another, affects health? Absolutely. Can we
conceptualize "exposure" in relation to different levels (e.g.,
individual, family, neighborhood, region, nation) and time
periods (e.g., across the life course, within specified birth
cohorts)? Certainly. Not only can we ask these questions, we
must, if we are to monitor social inequalities in health and
generate empiric evidence relevant to policies and social
movements promoting improvement of, and social equity in,
health (6-11).
Consider, for example, the recent influential study by
Cooper et al. (12), comparing population rates of hypertension among seven different populations of west African
descent, spanning from West Africa to North America.
Surely no person bom and raised in West Africa would be
the "same person"—in relation to entire sets of exposures
to adverse or beneficial conditions—if she or he had been
born or raised in North America. By the logic Kaufman and
Cooper propose, risk estimates from such a study based on
comparisons across groups defined by geographic region
would be uninterpretable. The authors nevertheless offered
the plausible etiologic interpretation that their study results
"demonstrate the determining role of social conditions in
the evolution of hypertension risk in these populations"
(12, p. 160) by indicating that social conditions, not just
gene frequencies, are relevant to shaping population rates
of hypertension.
It would seem, then, that Kaufman and Cooper's critique
of social epidemiologic studies comparing health outcomes
across social groups is misplaced. Moreover, additional
weaknesses they identify reflect, in part, the relatively limited effort—in terms of data collecting and funding—devoted to elucidating how social disadvantage translates into
poor health. Thus, it may seem that there is too much
emphasis on answering such crude questions as: "do differences in socioeconomic circumstances account for BlackWhite mortality differentials?" or "are socioeconomic differentials in mortality increasing over time?" However, to
take the first example, different social processes underlie the
Black-White differences in particular health outcomes (13,
14), and over time the contribution of these different health
outcomes to the overall health disadvantage of Black people
has changed substantially (8, 14, 15). The higher risk of
hypertension among African Americans compared with
White Americans, for example, along with the lower risk of
myocardial infarction among older Black men, especially
after numerous risk factors have been taken into account
(13, 16, 17), cannot be attributed in any simple way to
socioeconomic conditions in adulthood (13, 16). Among the
operative social and biologic causal processes, some are
likely to involve intergenerational influences (18), with their
origins stretching back to periods of systematic discrimination even greater than that operating today, while others may
be more rapidly responsive to present day social change (9,
14, 19). A challenge to etiologic reasoning is thus to conceptualize and operationalize how social conditions influence development and health from before birth through old
age (and on to future generations) and, thus, how the social
literally becomes biologic, that is, embodied (9, 19-21). The
very facts that health differentials are dynamic and that the
processes generating them change should attest to the possibility of imagining (and working toward) greater health
equality.
In sum, while we agree with Cooper and Kaufman that
social epidemiology should rigorously posit—and test—
explanations of social inequalities in health that refute
analyses that "blame the victim" or misperceive intermediary processes as fundamental causes, we differ with their
assessment of the goals, methods, and contributions of
social epidemiology. That we even have the level of aca831
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Letters to the Editor
demic and political debate we do today over the extent and
causes of social inequalities in health (1-3, 11, 20-28) is, in
no small measure, attributable to the work of social activists,
epidemiologists, and others who have dared to imagine, theorize, and demonstrate that social inequalities in health are
neither fixed nor inevitable, but instead are socially structured and can be altered. To condemn social epidemiology
for falling into error by assuming that social groups are (or
could be) in any way "exchangeable" is, surely, to miss the
rather larger point of our common humanity.
REFERENCES
1. Kaufman JS, Cooper RS. Seeking causal explanations in social
epidemiology. Am J Epidemiol 1999;150:113-20.
2. Cooper RS, Kaufman JS. Is there an absence of theory in social
epidemiology? The authors respond to Muntaner. Am J
Epidemiol 1999; 150:127-8.
3. Muntaner C. Invited commentary: social mechanisms, race,
and social epidemiology. Am J Epidemiol 1999;150:121—6.
4. Universal declaration of human rights. Adapted and proclaimed by the United Nations General Assembly. Resolution
217A (HI). December 10, 1948.
5. Doyal L, Gough I. A theory of human need. New York, NY:
Guilford Press, 1991.
6. Townsend P, Davidson N, Whitehead M. Inequalities in health:
the Black report and the health divide. London, UK: Penguin
Books, 1990.
7. Drever F, Whitehead M, eds. Health inequalities: decennial
supplement. London, UK: The Stationery Office, 1997. (Series
DS no. 15).
8. National Center for Health Statistics. Health, United States
1998 with socioeconomic status and health chartbook.
Hyattsville, MD: National Center for Health Statistics, 1998.
9. Kuh D, Ben-Shlomo Y, eds. A lifecourse approach to chronic
disease epidemiology: tracing the origins of ill-health from
early to adult life. Oxford, UK: Oxford University Press, 1997.
10. World Health Organization. Equity in health and health care: a
WHO/SIDA initiative. Geneva, Switzerland: World Health
Organization, 1996.
11. Berkman LF, Kawachi I, eds. Social epidemiology. New York,
NY: Oxford University Press, 2000.
12. Cooper R, Rotimi C, Ataman S, et al. The prevalence of hypertension in seven populations of west African origin. Am J
Public Health 1997;87:160-8.
13. Davey Smith G, Neaton JD, Wentworth D, et al. Mortality differences between Black and White men in the USA: contribution of income and other risk factors among men screened for
the MRFTT. MRFTT Research Group. Multiple Risk Factor
Intervention Trial. Lancet 1998;351:934-9.
14. Williams DR, Collins C. US socioeconomic and racial differences in health: patterns and explanations. Annu Rev Sociol
1995;21:349-86.
15. Ewbank DC. History of Black mortality and health before
1940. Milbank Q 1987;65(suppl 1): 100-28.
16. Fray JCS, Douglas JG, eds. Pathophysiology of hypertension
in Blacks. New York, NY: Oxford University Press, 1993.
17. Keil JE, Sutherland SE, Hames CG, et al. Coronary heart disease mortality and risk factors in Black and White men. Arch
Intern Med 1995;155:1521-7.
18. Lopes AA, Port FK. The low birth weight hypothesis as a plausible explanation for the Black/White differences in hypertension, NIDDM, and end-stage renal disease. Am J Kidney Dis
1995;25:350-6.
19. Krieger N. Embodying inequality: a review of concepts, measures, and methods for studying health consequences of discrimination. Int J Health Serv 1999;29:295-352.
20. Krieger N. Epidemiology and the web of causation: has anyone seen the spider? Soc Sci Med 1994;39:887-903.
21. Najman J, Davey Smith G. Health inequalities and the embod-
iment of social class. Aust N Z J Public Health (in press).
22. Pearce N. Traditional epidemiology, modern epidemiology,
and public health. Am J Public Health 1996;86:678-83.
23. Shy CM. The failure of academic epidemiology: witness for
the prosecution. Am J Epidemiol 1997; 145:479-84.
24. McMichael AJ. Prisoners of the proximate: loosening the constraints on epidemiology in an age of change. Am J Epidemiol
1999;149:887-97.
25. Susser M. Does risk factor epidemiology put epidemiology at
risk? Peering into the future. J Epidemiol Community Health
1998^2:608-11.
26. Rothman KJ, Adami H-O, Trichopolous D. Should the mission
of epidemiology include the eradication of poverty? Lancet
1998;352:810-13.
27. Kaplan GA. The role of epidemiologists in the eradicability of
poverty. (Letter). Lancet 1998;352:1627.
28. McMichael AJ. The role of epidemiologists in the eradicability of poverty. (Letter). Lancet 1998;352:1627.
Nancy Krieger
Department of Health and Social
Behavior
Harvard School of Public Health
Boston, MA 02115
George Davey Smith
Department of Social Medicine
University of Bristol
Bristol BS8 2PR, UK
THE A UTHORS REPLY
While we acknowledge the importance of the issues
raised by Krieger and Davey Smith (1), they seem to us only
tangential to the focus of our recent article (2). The statistical concept of "exchangeability" we were discussing (3) is
unrelated to the idea of universal human rights; in fact, conflating the two risks obfuscation. We argued that the standard method of analysis used for racial comparisons in etiologic studies is logically flawed and often serves to reinforce
racist explanations of health differentials.
Krieger and Davey Smith are concerned that we are not
exercising sufficient "epidemiologic imagination" (1, p.
831). Imagination is surely a valuable exercise but should
not, in our opinion, be confused with observation. Can we
imagine a world without racism or without some other prevailing social institution? Can we ask questions about the
relations that pertain in that setting, including questions
about health status? Of course. But once we start posing
questions about imaginary settings we are forced into
numerous assumptions and extrapolations, and ultimately
we usually don't know if our answer is anywhere even
remotely near the truth.
Their reference to our study of hypertension across the
African Diaspora (4) can serve as a case in point for this
argument as well. The values reported in the paper are, for
the most part, directly observed. Mean sodium excretion
was 76.6 mEq/day in West Africa and 172 mEq/day in
Chicago, for example. These were the observed values.
Suppose we had adjusted these values for national income
levels and reported that, if West Africans were to have the
same per capita income as urban African Americans, their
sodium excretion would be 200 mEq/day. This certainly
involves some epidemiologic imagination. It might be
Am J Epidemiol
Vol. 151, No. 8, 2000
Letters to the Editor
right, or at least close enough. Or it might be altogether
wrong. To validate the estimate we must imagine going
back in time to observe a world with a different history
(e.g., in which the slave trade never occurred, without centuries of European colonial rule in West Africa, and so on).
In any case, when the estimate for this imaginary regimen
is obtained with an epidemiologic adjustment procedure, it
is no more plausible than an outright guess. To enshrine
such a number with statistical totems such as p values or
confidence intervals is simply to flatter one's imagination
with the pretense of science.
We seem to be in agreement that such questions as "Do
differences in socioeconomic circumstances account for
Black-White mortality differentials?" are ill formulated and
have little hope, under the current research paradigm, of
advancing our understanding of how racism ultimately takes
its toll. The particular illustrations they cite from the literature raise precisely this problem. For example, after adjusting Black-White mortality differentials for measured
income, Davey Smith et al. offer the caveat: "The residual
black-white differences we found in mortality after adjustment for income may indicate that, within a given socioeconomic strata, life circumstances for black people in the USA
compare unfavorably with those of whites" (5, p. 937). We
are raising the more general question faced by this analytical approach; namely, under what set of adjustments would
life circumstances for Blacks and Whites in the United
States be comparable?
In the closing paragraph, Krieger and Davey Smith
attribute the current discussion of social factors and health
to those epidemiologists and others who "dared to imagine."
While a willingness to take on established beliefs and consider radical alternatives is critical to advancing this field,
the imagination can lead us in many directions. Grim and
Wilson (6), for example, have created an imaginary explanation for why Blacks are genetically predisposed to hypertension, a hypothesis that has no evidentiary basis and yet is
repeated as established theory throughout the hypertension
literature. Ellis (7) has imagined a comprehensive "biosocial" theory to explain how genetic determinants of behavior produce the observed variations in health by social class.
If we transfer epidemiology to the realm of imagination, we
surrender our science to these tendencies as well.
Epidemiologic and statistical methods exist in order to help
quantify our inferences under some set of basic working
assumptions. It is useful, therefore, to clarify exactly what
Am J Epidemiol Vol. 151, No. 8, 2000
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these fundamental assumptions are, which was the aim of
our essay. Should we find these assumptions to be untenable
in some settings, we ought to be skeptical of the ultimate
utility of the exercise.
REFERENCES
1. Krieger N, Davey Smith G. Re: "Seeking casual explanations
in social epidemiology." (Letter). Am J Epidemiol 2000; 151:
831-2.
2. Kaufman JS, Cooper RS. Seeking casual explanations in social
epidemiology. Am J Epidemiol 1999; 150:113-20.
3. Draper D, Hodges JS, Mallows CL, et al. Exchangeability and
data analysis. J R Stat Soc (A) 1993; 156:9-37.
4. Cooper RS, Rotimi C, Ataman S, et al. The prevalence of
hypertension in seven populations of West African origin. Am
J Public Health 1997;87:160-8.
5. Davey Smith G, Neaton JD, Wentworth D, et al. Mortality differences between Black and White men in the USA: contribution of income and other risk factors among men screened for
the MRFiT. MRFIT Research Group. Multiple Risk Factor
Intervention Trial. Lancet 1998;351:934-9.
6. Grim CE, Wilson TW. Salt, slavery, and survival: physiological principles underlying the evolutionary hypothesis of saltsensitive hypertension in Western Hemisphere Blacks. In: Fray
JCS, Douglas JG, eds. The pathophysiology of hypertension in
Blacks. New York, NY: Oxford University Press, 1993:22^8.
7. Ellis L. Social status and health in humans: the nature of the
relationship and its possible causes. In: Ellis L, ed. Social stratification and socioeconomic inequality. Vol 2. Reproductive
and interpersonal aspects of dominance and status. London,
UK: Praeger, 1993:123-43.
Jay S. Kaufman
Department of Epidemiology
School of Public Health
University of North Carolina
Chapel Hill, NC 27599-7400
Richard S. Cooper
Department of Preventive Medicine
and Epidemiology
Stritch School of Medicine
Loyola University
Maywood, IL 60153