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The social epidemiologic concept of fundamental cause
Andrew Ward
Published online: 13 March 2008
� Springer Science+Business Media B.V. 2008
Abstract The goal of research in social epidemiology is not simply conceptual
clarification or theoretical understanding, but more importantly it is to contribute to,
and enhance the health of populations (and so, too, the people who constitute those
populations). Undoubtedly, understanding how various individual risk factors such
as smoking and obesity affect the health of people does contribute to this goal.
However, what is distinctive of much on-going work in social epidemiology is the
view that analyses making use of individual-level variables is not enough. In the
spirit of Durkheim and Weber, S. Leonard Syme makes this point by writing that
just ‘‘as bad water and food may be harmful to our health, unhealthful forces in our
society may be detrimental to our capacity to make choices and to form opinions’’
conducive to health and well-being. Advocates of upstream (distal) causes of
adverse health outcomes propose to identify the most important of these
‘‘unhealthful forces’’ as the fundamental causes of adverse health outcomes.
However, without a clear, theoretically precise and well-grounded understanding of
the characteristics of fundamental causes, there is little hope in applying the sta-
tistical tools of the health sciences to hypotheses about fundamental causes, their
outcomes, and policies intended to enhance the health of populations. This paper
begins the process of characterizing the social epidemiological concept of funda-
mental cause in a theoretically respectable and robust way.
Keywords Fundamental cause � Social epidemiology � Causality �Necessary cause � Sufficient cause � Social-context variable
A. Ward (&)
Health Policy and Management, School of Public Health, University of Minnesota, 420 Delaware
Street S.E, Minneapolis, MN 55455-0392, USA
e-mail: [email protected]
123
Theor Med Bioeth (2007) 28:465–485
DOI 10.1007/s11017-007-9053-x
Introduction
In the principal article of the recent book, Is Inequality Bad for Our Health?,
Norman Daniels, Bruce Kennedy, and Ichiro Kawachi make the following claim:
To act justly in health policy, we must have knowledge about the causal
pathways through which socioeconomic (and other) inequalities work to
produce differential health outcomes [1].
The causal pathways in which Daniels, Kennedy and Kawachi are most
interested are not those that originate in the relatively proximate (downstream) risk
behaviors or even access to care. Instead, they believe that it is only by looking
much further upstream to socio-economic conditions, and examining the causal
pathways that link them to health outcomes, that it is possible to affect just, lasting
positive health outcomes ([1]. Also, see [2]). In that context, their claim echoes an
earlier one by Bruce Link and Jo Phelan to which social epidemiologists often refer.
This 1995 claim, made in the Journal of Health and Social Behavior, was:
... medical sociologists and social epidemiologists need to take as their task the
identification and thorough consideration of social conditions that are what we
term ‘‘fundamental causes’’ of diseases. We call them ‘‘fundamental causes’’
because, as we shall see, the health effects of causes of this sort cannot be
eliminated by addressing the mechanisms that appear to link them to disease
[3].
The ‘‘fundamental causes’’ with which Link and Phelan were (and still are)
concerned include, but may not be limited to, the socioeconomic inequalities
referred to by Daniels, Kennedy, and Kawachi. Still, what is common to both sets of
claims is that truly efficacious, just health policies that aim to improve the health of
populations, and reduce health disparities, must identify fundamental causes of
health outcomes and, when those health outcomes are adverse, change the
fundamental causes. Implicit in this claim is that while changes in non-fundamental
causes may eliminate or mitigate specific adverse health outcomes, the elimination
or equitable mitigation will be transitory. In some cases, new adverse health
outcomes, or new non-fundamental, mediating (intervening) mechanisms, linking
fundamental causes to adverse health outcomes, will emerge [3–6]. In other cases,
the discovery or control of remaining non-fundamental mediating (intervening)
mechanisms may be differentially distributed (e.g., on socio-economic status), thus
creating (or perpetuating) health disparities [3, 7, 8]. Therefore, according to
advocates of fundamental causes, creating just public health policy that will bring
about a lasting elimination or equitable mitigation of adverse health outcomes
requires both an understanding of what it means to be a fundamental cause, and an
identification of those causes (if any) that are genuinely fundamental causes.
Unfortunately, there is considerable vagueness and ambiguity attended to discus-
sions of fundamental causes. Moreover, other than an inchoate conception of distal
vs. proximate (or basic vs. surface) causes, there seems to be little agreement about
the conceptual underpinnings of the concept. To that end, the objective of the
466 A. Ward
123
present paper is to characterize, in a theoretically careful, though robust way, the
social epidemiological concept of fundamental cause.
Necessary, sufficient and component causes
A good place to begin is with Kenneth Rothman’s 1976 paper ‘‘Causes’’ (Also, see
[9]). Early on, Rothman offers a general characterization of a cause that he intends
to bridge the gap between metaphysical and epidemiological approaches to the
conceptual framework for causes [10]. According to Rothman, a ‘‘cause is an act or
event or a state of nature which initiates or permits, alone or in conjunction with
other causes, a sequence of events resulting in an effect.’’1 With this characterization
in mind, let us consider a simple causal diagram [12]. Suppose that we have two
events,2 X and Y, causally related to one another in the sense that X is the cause of
Y. It is possible to represent, graphically (in a manner suggestive of path analysis),
this relationship between X and Y as:
X! Y
In this representation, the direction of the arrow indicates the ‘‘direction’’ of
causality (cause to effect). The use of this graphical representation also reflects the
assumption that the causal relation is asymmetric (X causes Y, but Y is not a cause
of X).
There are several ways to taxonomize this relationship, but a traditional
taxonomy of the relations captured by the causal use of the ‘?’ is to say that X
causes Y in one or more of the following ways:
(1) X is a necessary cause of Y
(2) X is sufficient cause of Y
(3) X is a necessary and sufficient cause of Y
(4) X is a neither a necessary nor a sufficient cause of Y (See [9–12, 14–20]).
Sometimes the claim is made that this taxonomy is sufficient only for cases in
which the relationship between X and Y is deterministic. Equating non-determin-
istic relationships with probabilistic relationships, the claim is that when the
relationship between X and Y is probabilistic, the taxonomy is, at best, inadequate.
However, while it is not without its critics [21, 22], there is a standard way around
this objection. We can accept the claim of Daniel Hausman and James Woodward
1 Rothman [10]. Rothman and Greenland [11], offer a somewhat more restrictive characterization of a
cause as ‘‘an antecedent event, condition, or characteristic that was necessary for the occurrence of the
disease at the moment it occurred, given that other conditions are fixed.’’ (emphasis added).2 There is a voluminous philosophical literature devoted to the logical and ontological characterization of
events. A succinct definition, accepted (to a greater or lesser extent) by many writers, is due to Jaegwon
Kim. According to Kim, an event is ‘‘a concrete object (or n-tuple objects) exemplifying a property (or
n-adic relation) at a time. In this sense of ‘event’, events include states, conditions, and the like, and not
only events narrowly conceived as involving changes.’’ [13].
Social epidemiologic concept of fundamental cause 467
123
that ‘‘probabilistic causation is deterministic causation of probabilities.’’3 What this
means is that ‘‘X is a probabilistic cause of Y if and only if X is a deterministic
cause of the chance of Y, ch(Y), where this is identified with the objective
probability of Y’’ [23]. In this case, we can say that if X is a necessary cause of Y,
then whenever X does not occur, either Y does not occur or the probability of Y
occurring (i.e., the chance of Y, ch(Y)), in the language of Hausman and
Woodward) is less than it would have been if X had occurred. In contrast, if X is a
sufficient cause of Y, then whenever X occurs, either Y occurs or the probability of
Y occurring (i.e., the chance of Y, ch(Y), in the language of Hausman and
Woodward) is greater than it would have been if X had not occurred (See [10, 15]).
If X is both a necessary and sufficient cause of Y, then we have a conjunction of
sufficient cause and necessary cause. That is to say, whenever X occurs, either Y
occurs or the probability of Y occurring is greater than if X had not occurred, andwhenever X does not occur, either Y does not occur or the probability of Y
occurring is less than it would have been if X had occurred. Finally, if X is neither a
necessary nor a sufficient cause of Y, then whenever X occurs there is no guarantee
either that Y will occur, or that the probability of the occurrence of Y will be greater
than if X had not occurred. Moreover, if X is neither a necessary nor a sufficient
cause of Y, then whenever X does not occur, there is no guarantee either that Y will
not occur, or that the probability of the occurrence of Y will be less than if X had
occurred.
Within the context of this taxonomy of causes, it is important to recognize that
neither X nor Y may be unitary; instead, X may be a constellation (complex) of
causes, and Y may be a constellation (complex) of effects [9]. Also, see [26–28]).
Using language introduced by Rothman, we may call the constituent elements of a
complex of causes, ‘‘component causes,’’ and we may call the constituent elements
of a complex of effects, ‘‘component effects’’ ([9]. Also, see [29]). In the case of the
component causes, for every specific causal complex of which the component cause
is a proper subset of the set of component causes constituting the causal complex,
that component cause will be either a necessary cause, or neither a necessary nor a
sufficient cause. For example, suppose that A is a non-redundant component cause
of a causal complex C (i.e., no other constituent elements of C, different from A, are
by themselves sufficient to case the effect Y), where C is a sufficient but not
necessary cause of some effect Y, and A is not, by itself, a sufficient cause of Y. In
this case, following J.L. Mackie, we can say that A is an insufficient but necessary
(INUS) cause of Y [30, 31]. Notice that in this case, there are two senses of
‘‘necessity’’ that must be kept separate. Since A is a non-redundant component
cause of the causal complex C, which is a sufficient but not necessary cause of Y,
then A is necessary in the sense of being a non-redundant component of C. If one
eliminated A from the causal complex C, C would no longer be a sufficient but not
necessary cause of Y. However, suppose that there are two causal complexes, C and
3 Hausman and Woodward [23]. Also, see Hausman [24] and Karhausen [16]. This is not the only way to
handle cases of ‘probabilistic causation’. Hitchcock [25] provides a summary of approaches making use
of probability spaces and partitions of probability spaces.
468 A. Ward
123
C0, both of which are sufficient but not necessary causes of Y. Further, suppose that
none of the constituent elements of C are constituent elements of C0, and none of the
constituent elements of C0 are constituent elements of C. In this case, while A
remains necessary in the sense of being a non-redundant component cause of C, it is
not necessary in the sense of being an irreplaceable cause of Y. Finally, a
component cause, A, of a specific causal complex C is neither a sufficient nor a
necessary component cause of an effect, Y, just in case there is some other causal
complex, C0, which is a sufficient cause of Y, and to which the component cause, A,
does not belong.
We can use this taxonomy and vocabulary to classify some simple examples.
As Rothman writes, under ordinary conditions (ceteris paribus), ‘‘the possession
of a vermiform appendix is necessary for appendicitis, and infection with the
tubercle bacillus is a necessary cause for tuberculosis’’ [10]. In other words, under
ordinary conditions (what, following Mackie [31]. We can refer to as the ‘‘causal
field’’ of reference) appendicitis cannot occur if there is no vermiform appendix,
and tuberculosis cannot occur if the tubercle bacillus is not present (See [27, 32,
15]). A standard bar examination question about responsibility provides a good
example of a sufficient, but not necessary cause: ‘‘If a person is pushed from the
top of a tall building and, while falling, is shot, which of the events is the cause of
the person’s death?’’ In the context of the necessary—sufficient taxonomy, we can
say that the problem for assigning responsibility is that while both events (i.e.,
being pushed from the top of a tall building and being shot while falling) are
sufficient causes (under ordinary circumstances, both events will inevitably result
in the person’s death), neither is a necessary cause. The person will die from the
fall if not shot, and will die from the shot if not from the fall. Again, returning to
Rothman, another example of a sufficient cause is that under ordinary
circumstances the inheritance of the PKU gene and phenylalanine in a diet are,
together, a sufficient cause for the occurrence of mental retardation [10]. What is
significant about Rothman’s example is that while neither inheritance of the PKU
gene nor phenylalanine in a diet are, by themselves, sufficient causes of mental
retardation, they are both causal components of a causal complex that is itself a
sufficient cause, under ordinary circumstances, for mental retardation. The case of
a cause that is a necessary and sufficient cause for an effect is more difficult. A
simple example that is sometimes given is that, under ordinary circumstances,
heat, air (O2) and fuel are singularly necessary and jointly sufficient for fire. Thus,
if we think of the component causes heat, air and fuel as constituting the causal
complex C, then we can then say that, under ordinary circumstances, C is both a
necessary and sufficient cause for fire.
In the sciences (social and natural), assertions of causal relations are often
assertions of necessary causal relations (See [33, 17]). To understand this focus on
necessary causes, consider the example of the claim that, under ordinary
circumstances (ceteris paribus; relative to the causal field of reference), ‘‘smoking
causes lung cancer.’’ Here smoking is the cause (X), and lung cancer is the effect
(Y). Even ignoring for a moment that ‘smoking’ is much too broad a character-
ization of the event serving as the cause in the causal relationship (e.g., there are
various kinds of smoking), it relatively easy to recognize that is not the case either
Social epidemiologic concept of fundamental cause 469
123
that smoking always causes lung cancer, or that smoking always results in an
increased probability of lung cancer. No matter what the etiological time-period is
(where the etiological time-period is the time-period covered by the causal
relationship), there are cases in which either there are instances of smoking did not
cause lung cancer, or there are instances of smoking that did not increase the
probability of lung cancer.4 Thus, because it is not the case either that the
occurrence of lung cancer always follows the occurrence of smoking, or that the
probability of lung cancer when smoking occurs is always greater than it would
have been if smoking had not occurred, it follows that smoking is not a sufficient
cause of lung cancer [14, 35]. At most, we can say that the average incidence rate of
lung cancer, over a specified etiological time-period, in a specific population ofpeople who smoke, is greater than the average incidence rate of lung cancer, over a
specified etiological time-period, in another specific population of people who do
not smoke. Thus, the connection between (X)—smoking—and (Y)—lung cancer—
is, in this case, a contingent generalization based on a specific selection of
parameters, and so indicates the importance of precisely specifying the target
population (as well as specifying the causal field of reference). If we choose the
target populations in a different way, it is quite possible that we will end up without
this difference in average incidence of lung cancer (e.g., if we retrospectively
choose the population of people who never develop lung cancer but who
nevertheless smoke) (See [14]).
Equally importantly though, even if the concept of cause is given this population-
level probabilistic characterization in terms of average incidence (incidence
proportions), no finite number of observations are ever sufficient to support the
claim that an event is a sufficient cause for the occurrence of another event. Recall
that an event X is a sufficient cause for an event Y only if whenever X occurs, either
Y occurs or the probability of Y occurring is greater than if X had not occurred. It is
the modality of ‘‘whenever’’ that creates the problem. No finite number of
observations is sufficient to justify the claim that whenever X occurs, Y occurs. It is
this (a version of the problem of inductive inferences first made famous by David
Hume) and related problems that led to Karl Popper’s claim that falsification
(instead of confirmation) is at the center of all genuine scientific explanations (See
[36]). In other words, Popper claimed that rather than attempting to justify (confirm)
claims about an event being a sufficient cause for another event, the correct
approach is to attempt to refute scientific hypotheses about causal connections [36].
‘‘Only the falsity of a theory,’’ writes Popper, ‘‘can be inferred from empirical
evidence, and this inference is a purely deductive one’’ [37]. Thus, in the smoking
case, once we have a precisely formulated hypothesis (including a specification of
the ‘‘ordinary conditions’’ as well as the etiological time-period and the target
population) about the causal relationship of smoking to lung cancer, we should
4 See Kelsey et al. [34], who characterize smoking as a risk factor for (as opposed to a cause of) lung
cancer precisely because ‘‘some lung cancer occurs in nonsmokers, and most smokers do not develop
lung cancer.’’ Other writers claim that risk factors are causes. For example, Link and Phelan [4], write
that social conditions ‘‘expose people to risk factors, and those risk factors cause disease, thereby
producing patterns of disease in populations.’’
470 A. Ward
123
attempt to find refutations of the relationship by finding instances of smokers who
do not have lung cancer. Since we can do this (at least with a sufficiently large
extensional definition of ‘smoking’), then we know that smoking is not, for at least
some characterizations of the hypothetical connection between smoking and lung
cancer, a sufficient condition for lung cancer.
These, and related problems associated with justifying (confirming) claims about
sufficient causes, lead to a refocus on examining causal conditions as necessary
causal conditions. In the case of the earlier example of infection with the tubercle
bacillus as a necessary cause for tuberculosis, the idea, couched once again at the
population level, is that in the case of people who have both the tubercle bacillus
and tuberculosis:
If they had not acquired the tubercle bacillus, then, all other things being equal
(ceteris paribus; relative to the causal field of reference), they would not have
tuberculosis, or the probability of their having tuberculosis would be less than
if they had never acquired the bacillus.
In the case of smoking as a necessary cause of lung cancer, the idea, couched
once again at the population level, is that in the case of people who have lung cancer
and have smoked:
Had they not smoked, then, all other things being equal (ceteris paribus;
relative to the causal field of reference), they would not have lung cancer, or
the probability of their having lung cancer is less than if they had smoked.
The example of smoking and lung cancer, perhaps more clearly than the example
of the tubercle bacillus and tuberculosis, demonstrates the importance of precisely
specifying the etiological time-period, the target population, the cause, the effect,
and the causal field of reference. Suppose that we change the causal field of
reference so that the smokers about whom we make the claim live in an
environment that suffices, on its own without the people smoking, to cause lung
cancer. For instance, imagine that the people live in an environment in which there
is a high concentration of airborne asbestos particles. In this case (more specifically,
for the people living in this environment), smoking is not a necessary cause for lung
cancer (See [38, 39]). Alternatively, suppose that we change the characterization of
the effect to include only those types of lung cancer not physically (biologically)
linked to smoking. Given this change in the characterization of the effect, smoking
is not a necessary cause of lung cancer qua lung cancer as narrowly specified.
Finally, if the lung cancer-effect, the background conditions, the cause (e.g., the
specific type of smoking) and target population are chosen ‘‘in the right way’’ (with
the proper precision), then smoking will be both a necessary and a sufficient cause
for lung cancer. In this case, the smoking (cause)—lung cancer (effect) case begins
to look much more like the tubercle bacillus—tuberculosis case where, under
ordinary circumstances, the tubercle bacillus is both a necessary and sufficient
condition for tuberculosis. The upshot is that all claims about necessary causes (as
well as about other kinds of causes in the taxonomy) occur in the context of manyassumptions. Without making these assumptions (e.g., assumptions about the target
population, the nature of the examined effects) explicit, it is impossible to
Social epidemiologic concept of fundamental cause 471
123
taxonomize a cause, and it is impossible to determine the warrant (good or bad) of a
causal claim [40].
Fundamental causes
With the comments in Sects. ‘‘Introduction’’ and ‘‘Necessary, sufficient and
component causes’’ as background, we can better understand the concept of
‘‘fundamental cause’’ that recent social epidemiologists5 use in their analyses. As
suggested by the quotation from Link and Phelan in Sect. ‘‘Introduction’’ [3],
fundamental causes are not just any kinds of causes. Fundamental causes, as
conceived by Link and Phelan, are distal causes of health outcomes relative to the
more proximate risk factors commonly claimed to be the causes (typically adverse)
of health outcomes (e.g., health behaviors such as smoking). Moreover, while risk
factors may change over times and populations, advocates of fundamental causes
claim that such causes maintain an ‘‘enduring’’ relationship to the health outcomes
with which they are causally associated [3, 41–43]. An important caveat in this
characterization, often glossed over, concerns the character of the health outcomes.
Although the earlier example about smoking and lung cancer may have suggested a
relatively narrow characterization of the health outcome, this is not, typically, what
advocates of fundamental causes intend. Instead, following Link and Phelan, since a
single cause (or a single collection of component causes that together form a causal
complex) ‘‘can affect multiple health outcomes,’’ then, properly speaking, we
should understand the ‘Y’ in the causal diagram, ‘‘X ? Y’’, as a place holder for a
variety of different values and not one specific value.6 Using language borrowed
from James Woodward, we can say that claims of the form ‘‘X is a fundamental
cause of Y’’ are type-causal claims ([39]. Also, see [23]). Thus, we need to
understand properly the claim that fundamental causes maintain an enduring
(persistent) relationship to the health outcomes with which they are causally
associated. It is really the claim that the causal link between a fundamental cause
and a collection of a variety of specific health outcomes endures even ‘‘through
changes either in the mechanisms or in the [specific] outcomes [of a certain type]’’
([3]. Also, see [2]). As Karen Lutfey and Jeremy Freese write, in assertions of the
form ‘‘X is a fundamental cause of Y’’, ‘‘Y must be multiply realizable, in the sense
that there are many different ways in which Y can occur’’ [5]. In this respect, ‘Y’
functions as a type-level variable; a variable that can be realized by a variety of
different, more specific health outcomes. For example, consider the claim that lower
socio-economic status is ‘‘related to mortality from each of the broad categories of
chronic diseases, communicable diseases, and injuries ... and from each of the 14
major causes of death in the International Classification of Diseases’’ [44]. In the
5 Though see House [41], who traces the idea back as far as the 1843 work of the German physician and
pathologist, Rudolf Virchow.6 Link and Phelan [3]. This captures the claim of Lutfey and Freese [5], that the effect of a fundamental
cause ‘‘must be multiply realizable, in the sense that there are many ways’’ for the effect of interest to
occur.
472 A. Ward
123
context of an assertion of the form ‘‘socio-economic status is a fundamental cause of
mortality,’’ we can say that ‘mortality’ is a type-level description of an effect that is
realized multiply in the various kinds of adverse health outcomes including the 14
major causes of death in the International Classification of Diseases. The upshot is
that if X is a fundamental cause of Y, then the causal relationship between X and a
variety of specific instances of Y persist even if there are changes in the mediating
factors between X and one or more of the specific instances of Y, or the specific
instances of Y change [2, 4].
Moreover, not only is the effect of a fundamental cause multiply realizable, so
too is the fundamental cause itself [5]. To vary the point made above in the
quotation from Lutfey and Freese, X (the fundamental cause) must be multiply
realizable, in the sense that there are many different ways in which X can occur.
This can occur in at least two different ways. First, suppose that the fundamental
cause is a specific aspect of socio-economic status, say, poverty level. If we then
make the claim that poverty status is a fundamental cause of mortality, we are not
saying that a specific person’s poverty status is the cause of his or her mortality.
Instead, what we are claiming is that, relative to a causal field of reference, there is a
necessary connection between the various events that fall under the type-level
description ‘poverty status’, and the variety of different health outcomes that fall
under the type-level description ‘mortality’. Second, suppose that we claim that
socio-economic status is a fundamental cause of poverty status. Since socio-
economic status is ‘‘a composite measure that typically incorporates economic
status, measured by income; social status, measured by income; and work status,
measured by occupation’’ [45], it follows that ‘poverty status’ is a type-level
description under which fall various events and (sub-) level types of events. Thus,
fundamental cause claims are type-causal claims in that both the descriptions of the
fundamental causes as well as the descriptions of the effects of fundamental causes
are type-level descriptions.
One should not underestimate the importance of understanding claims about
fundamental causes as type-causal claims (in the sense identified above) rather than
as token-causal claims about narrowly individuated, particular events. Typically,
social epidemiologists center their attention on adverse health outcomes quacollections of specific ailments [4]. Within this collection, there may be a variety of
more specific health outcomes, such as lung cancer, diabetes and coronary heart
disease, all of which collaborate, in one way or another, to warrant claims about the
occurrence of the adverse health outcome effect. For example, in the 1996 paper
‘‘The Effects of Poverty, Race, and Family Structure on U.S. Children’s Health:
Data from the NHIS, 1978 through 1980 and 1989 through 1991,’’ Laura
Montgomery et al. [46] use National Health Interview Survey (NHIS) data to
investigate possible causes of adverse health outcomes (poor or fair health) as
determined by the guardian-reported health status of children. The dependent
variable in their analyses captures, collectively, one or more specific instances of
health states that, cumulatively, lead the guardians to report children as having
either fair or poor health. Put a bit differently, the dependent variable, Y, in the
analysis is a type-level variable that captures specific instances of adverse health
states and determined by the guardians of children. In this example, changing the
Social epidemiologic concept of fundamental cause 473
123
intermediate causes that connect fundamental causes to the collection of events that
fall under a specific type-level effect may result in a decrease or elimination of
specific instances of health states that contributed to the guardians’ reports of poor
or fair health. However, according to advocates of fundamental causes, unless one
eliminates the fundamental causes, one or more instances of the type-level effect
will remain, or new events of that type will emerge, or the discovery (or control) of
remaining non-fundamental mediating (intervening) mechanisms may be differen-
tially distributed [2, 3, 5].
The point about understanding fundamental cause claims as type-causal claims is
not a trivial one. In discussions of causation, causality and causal relations, writers
(especially philosophically oriented writers) often draw a distinction between token-
causation (singular causation) and type-causation (general causation) (See [47, 25]).
Referring back to the simple case of X ? Y, where X is the cause and Y is the
effect, advocates of token-causation (See [38]). claim that X and Y are tokens
(particular instances) of types of events. For example, X might be a particular
behavior of an individual (e.g., the episode of smoking a cigarette at a particular
time and place) while Y might be a particular health state (e.g., the episode of
having a particular kind of cancer at a particular time and place). In contrast,
advocates of type-causation claim that X and Y are types of events (which may or
may not have specific tokens in the actual world). Typically, examples such as
‘‘smoking causes cancer’’ either count as genuine instances of type-causation or, as
suggested earlier, as generalizations based on the distribution of specific tokens of
smoking and cancer (particular people smoking and particular instances of cancer in
persons) in a specified population relative to a causal field of reference. Ellery Eells
is an example of someone who claims that ‘‘smoking cases cancer’’ is a genuine
instance of type-causation. He writes:
The surgeon general says that smoking is a positive causal factor for lung
cancer. This, of course, is a type-level causal claim, about the properties of
being a smoker and of developing lung cancer. And it is consistent with
various pertinent possibilities regarding token events, and the token causal
relations between them [35].
It is for this reason that type-causation is sometimes called ‘‘property causation’’
[35].
One of the problems with countenancing this analysis of type-causation is that
the introduction of properties distinct from their instantiation in specific events
raises complex issues of ontology that have no simple, or generally agreed upon
resolution. Thus, for present purposes, it suffices to note that, within social
epidemiology as well as health services research, advocates of fundamental causes
are not directly interested in the question of whether we should, or need to
distinguish type-causation and token-causation as two distinct kinds of causation.
Instead, as the examples above demonstrate, they are interested in cases where
causes are collections of more specific causes (i.e., events or (sub-) types of events),
and effects are collections of more specific outcomes (i.e., events or (sub-) types of
events). Whether or not these more specific causes and outcomes (collected under
the type-level descriptions of causes and effects) can always be understood as
474 A. Ward
123
collections of event tokes, and casual relations as relations obtaining between event
tokens, is not generally a topic of interest amongst social epidemiologists. For this
reason, I will say, generally, that a claim such as ‘‘X causes Y’’ is, within a social
epidemiologic framework, a claim to the effect that changing the value of X, located
in one or more specific events or (sub-) type of events that fall under the type-level
description ‘X’, will change the value of Y located in one or more specific events or
(sub-) type of events7 that fall under the type-level description ‘Y’. Just how
narrowly specified and particularized these ‘‘more specific events or (sub-) type of
events’’ are, is a pragmatic question determined by the nature of the research and the
interest of those conducting the research. This leaves open the possibility that claims
such as ‘‘ X causes Y’’ could all be analyzed into claims ‘‘that changing the value of
X in particular, spatiotemporally located individuals will change the value of Y
located in particular individuals’’ [39], without requiring that all useful analyses
must take this form.
Given this characterization of the role of type-level descriptions and the
pragmatic nature of the token-type distinction, there is no particular problem with
providing operational definitions of the relevant concepts and, based on those
operational definitions, constructing ‘‘conceptual models.’’ The operational defini-
tions, in effect, place parameters on which specific events or (sub-) types of events
fall under the type-level descriptions of the causes and effects in claims about
fundamental causes [47]. Indeed, in this context it is useful to recall a remark from
Max Weber’s The Theory of Social and Economic Organization. According to
Weber, in ‘‘all cases, rational or irrational, sociological analysis both abstracts from
reality and at the same time helps us to understand it, in that it shows with what
degree of approximation a concrete historical phenomenon can be subsumed under
one or more ... concepts’’ [49].
Using the above remarks as a general framework, we can make the following
assertion: X (which is an element of a causal complex) is, relative to a causal field of
reference, a fundamental cause of Y only if:
(i) Changing the value of X, instantiated in one or more specific events or (sub-)
type of events is, relative to the causal field of reference, a necessary cause of
changing the value of Y instantiated in one or more specific events or (sub-)
type of events.
(ii) There is no different description of the instantiations of X such that, relative to
that description and the causal field of reference in (i), changing the value of X
is a necessary cause of changing the value of Y identified in (i).
Recent social epidemiologists, in the broadly Western cultural tradition, add a
further qualification to (ii). They claim that the necessary causes identified by X are
specific social conditions (e.g., socio-economic conditions). Put a bit differently,
and using broadly Weberian language, they claim that it is necessary to subsume the
descriptions of the events or (sub-) type of events that instantiate X under specific
socio-economic concepts. The point of qualifying condition (ii) in this way is to
7 Instead of sub-types of events, one might instead make use of complex events. See Ehring [48].
Social epidemiologic concept of fundamental cause 475
123
eliminate claims that a so-called reductionist (or eliminativist) account is a ‘‘better’’
account of the necessary causal relationship (See [3], [42]). For example, sometimes
people claim that explanations in which only the vocabulary of individual
characteristics (e.g., a person being a smoker) is used are better explanations that
those in which different, non-individualistic vocabularies are used (e.g., measure-
ments of socio-economic status which ‘‘indicate particular structural positions
within society’’ [50]). If one accepts such claims, and the implicit reductionism or
eliminativism entailed by such claims, then socio-economic status (SES) qua SES is
not a fundamental cause of adverse health outcomes of a particular kind. Instead, it
is the events, or (sub-) type of events described in the vocabulary of individual
characteristics that are the ‘‘fundamental causes’’ of adverse health outcomes of a
particular kind.
It is, though, precisely at this point that advocates of social conditions as
fundamental causes make their counter-claim. Social epidemiologists agree that
while there may be no fixed rule on what types of variables there are, nevertheless it
is important to distinguish at least two different types: social-context variables and
individual-level variables.8 According to advocates of social conditions as
fundamental causes, social conditions (i.e., events or (sub-) types of events
described using the vocabulary of social-context properties or complexes of social-
context properties) are necessary causes of some events or (sub-) types of events
grouped together under the type-level description of the effect. Moreover, no
different description of those social conditions (e.g., individual-level descriptions)
captures both the necessary causal relationship and the desired theoretical generality
(See [5, 52]). In other words, social epidemiologists who advocate fundamental
causes believe that the necessary causes (i.e., the ‘X’ in X ? Y, where X ? Y
indicates the presence of a fundamental cause) have a very specific characteristic;
viz., the causes are social-context events or (sub-) types of events that function as
necessary causes of the types of health outcomes of interest [53]. As Link and
Phelan write, ‘‘social conditions have been, are, and will continue to be irreducible
determinants of health outcomes and thereby deserve their appellation of
‘fundamental causes’ of disease and death’’ [52].
Framing the idea of ‘‘fundamental cause’’ in this way avoids having to focus on
the difference between proximate and (relatively more) distal causes as the
distinguishing characteristic of fundamental causes. At best, such a distinction is
only a relative one. For any causal relationship in which X is a cause of Y, there is
‘‘always’’ (unless there are ‘‘final causes’’) going to be a cause for X, X0, making X a
more proximate cause of Y relative to X0, and X0 a more distal cause, relative to X,
of Y. To suppose that this is not the case is tantamount to the claim that there are
uncaused causes. Thus, unless one wants to adopt an instrumental view of causal
claims, characterizing fundamental causes in terms of proximate vs. distal causes
(See [5]) is not helpful since such characterizations are always relative
8 See Moffitt [51]. Moffitt has a related, albeit somewhat different taxonomy of variable types. Moffitt
mentions ‘‘four types that have been used in a number of different applications: environmental or
ecological variables, demographic group variables, twin and sibling relations, and natural experiments.’’
476 A. Ward
123
characterizations.9 The characterization of ‘‘fundamental cause’’ in terms of
necessary causes (where the relevant events or (sub-) type of events are described
in social-context terms) avoids this issue. Although the generative mechanisms
through which fundamental causes are able to influence the outcome of interest may
change (i.e., even though the mediator variables may change) [54], as long as the
fundamental causes remain, the possibility of an occurrence of the (adverse)
outcome will persist precisely because fundamental causes are necessary causes. In
addition, by explicitly identifying fundamental causes as social-context events or
(sub-) types of events, the social epidemiological conception of fundamental cause
intentionally and self-consciously eschews the ‘‘individualization of epidemiology’’
[53].
At the same time, we must be very careful with this distinction. Too often writers
who want to distinguish fundamental causes from other, more ‘‘superficial’’ causes
of adverse health outcomes, refer to ‘‘social structures’’ as the causes of adverse
health outcomes without being precise about the meaning of ‘social structure’. Thus,
at the very least, we must exercise caution in distinguishing between individual-
level variables, social-context variables, and structural variables (See [55, 56]).
Individual-level variables refer to ‘‘individual physiological and psychological
factors’’ [57]. as well as individual behaviors, such as an individual’s smoking or an
individual’s drinking [58]. Social-context variables refer to events or (sub-) types of
events in which individuals have characteristics that emerge and are present only in
social situations. The poverty status of an individual is a traditional example of a
social-context variable (See [59]) because it is presupposes a context of people
interacting with one another and the establishment of social norms [50]. Finally,
structural variables, sometimes called ecological variables, refer to characteristics of
groups (analogous to social facts in the older, Durkheimian language) and either not
at all, or only derivatively, to the individuals composing the groups. For example,
population density is a structural variable that does not refer to any specific
characteristic or set of characteristics of the individuals constituting the population
(See [60, 61]). In contrast, age distribution ‘‘measured by proportion of the female
population aged 0–24 years’’ represents, derivatively,10 individual level properties
[56, 51]. All three kinds of variables are important and, as Barbara Wells and John
Horm write, an ‘‘ecological approach that uses groups, rather than individuals, as
the unit of study is thought to be an important complement to measures of health
attributes. Such an approach may help capture the context of communities, cultures,
and other groupings’’ ([62]. See also [63]). Failure to sort these different kinds of
variables out leads to traditional kinds of fallacies. For example, to suppose that one
9 This claim does not entail that the distal vs. proximate distinction is not sometimes a useful one. As
Professor Bryan Dowd, Health Policy and Management, University of Minnesota, rightly notes, causal
diagrams such as Directed Acyclic Graphs (DAGs) capture the distinction and use it. However, this is
consistent with the claim that the distinction is not useful for capturing the meaning of ‘‘fundamental
cause.’’10 The group-level property represents the individual-level property in a derivatively in that while
individuals do have ages (as opposed to population density—individuals do not have ‘‘density’’ in the
relevant sense), the age distribution is a characteristic of the group.
Social epidemiologic concept of fundamental cause 477
123
can, from individual-level variables alone, determine the character and context of
group-level variables is an instance of the ‘‘atomistic fallacy.’’ At the other extreme,
to suppose that one can determine, from group-level variables alone, the character
and content of individual-level variables is an instance of the ‘‘ecological fallacy’’
([64]. See also [65, 63]). Furthermore, once these various levels are distinguished,
and reductionism abandoned, then two other kinds of fallacies emerge. The
‘‘psychologistic fallacy’’ comes from ‘‘assuming that individual-level outcomes can
be explained exclusively by individual-level characteristics,’’ while the ‘‘sociolo-
gistic fallacy’’ comes from ‘‘ignoring the role of individual-level factors in a study
of groups’’ [66].
Of the three kinds of variables, social-context variables are the ones that seem to
straddle what is otherwise a symptom of the agency-structure dichotomy, and the
attendant distinction between micro-sociology and macro-sociology.11 Whereas
individual-level variables are agency variables, and group-level variables are
(social) structural variables, social-context variables incorporate elements from
both. On the one hand, individuals realize social-context characteristics such as
poverty status. In this respect, social-context variables have characteristics of
individual-level variables. On the other hand, the realization of social-context
variables occurs only in social contexts, and, in this respect, social-context variables
have characteristics of group-level variables. Thus, David Betson and Jennifer
Warlick, after noting that the adjective poor is used to describe an individual
characteristic, continue by writing that it is a condition ‘‘below average or could be
viewed as unacceptable’’ [68]. thereby recognizing the relative (social-context)
character of poverty [68]. Similarly, Catherine Ross and John Mirowsky note that
social causation proponents often claim that individual employment status is a
‘‘social cause’’ of health status [69]. Like poverty, employment status is a social-
context variable because employment status is relative to specific social structures
and the norms that exist in those social structures. Indeed, social-context variables
constitute the kind of bridge between agents (individuals) and social structures
(groups) one finds in the work of Anthony Giddens (See [61]). Moreover, because
the variables are instantiated in (and by) individuals, they permit, methodologically,
an analysis of fundamental causes that avoids, at least in its initial formulation,
problems associated with multi-level analyses.
Possible problems
One might object here that treating fundamental causes as necessary causes has its
own problems. The first problem seems to be that the claim that X is a fundamental
cause of Y only if X is a necessary cause of Y results in characterizing too many
causes as fundamental causes. Recall Rothman’s example of the tubercle bacillus as
a necessary cause for tuberculosis. If X is a fundamental cause of Y only if X is a
11 Giddens [61] and Collins [67]. As Giddens [61] writes, if ‘‘interpretative sociologies are founded, as it
were, upon an imperialism of the subject, functionalism and structuralism propose an imperialism of the
social object.’’ Like Giddens, I reject this dualism (and so too multi-level analysis that depend exclusively
on the distinction), and want to recognize that there are ‘‘social practices ordered across space and time’’.
478 A. Ward
123
necessary cause of Y, then it seems to follow that the tubercle bacillus (more
precisely, the set of events or (sub-) types of events that fall under the type-level
description ‘tubercle bacillus’) is a fundamental cause of tuberculosis. This, though,
misses the logical character of the claim that X is a fundamental cause of Y only if
X is a necessary cause of Y. The claim amounts only to saying that all instances of
fundamental causes are also instances of necessary causes without, at the same time,
claiming that all instances of necessary causes are instances of fundamental causes.
In order for X ? Y to be an instance of fundamental causation in the relevant socialepidemiological sense, two criteria must be satisfied. First, X must be a necessary
cause of Y in the sense explicated above (Sect. ‘‘Fundamental causes’’). Second, the
necessary cause of Y, X, must be one or more social-context events (e.g., the
poverty status of a person) or one or more (sub-) types of social-context events. It is
only when both criteria are satisfied that we have a genuine instance of fundamental
causation in the social epidemiological sense.
Of course, precising the definition of ‘fundamental cause’ in this way does not
preclude an analogous use of the concept when the first criterion is satisfied (i.e., the
cause is a necessary cause) but the second criterion is relaxed (or changed). Nothing
in the way that social epidemiologists use the concept of fundamental cause
precludes the existence of analogous kinds of ‘‘fundamental’’ causation in which the
causes are something other than events or (sub-) types of events described in the
vocabulary of social-context properties.12 For example, Link and Phelan write that
because of their pervasive effects and relation to resources such as money and
power, characteristics such as race/ethnicity and gender ‘‘should be considered as
potential fundamental causes of disease as well’’ ([3]. Also, see [41, 71]). Examples
such as these are provocative precisely because of the debate about whether race/
ethnicity and gender are, in an important sense, socially constructed (and so must be
described using the vocabulary of social-context properties). If they are character-
istics that emerge and have meaning only in social contexts, then they are social-
context variables and one can treat them straightforwardly as candidates for
fundamental causes. However, even if one denies that they are social-context
variables, to the degree that they have the effects Link and Phelan attribute to them,
there does not seem any principled reason to exclude them as analogues to the social
epidemiological conception of fundamental cause. Instead, the appropriate response
to the example of the tubercle bacillus suggests the appropriate response to the case
of race/ethnicity and gender variables. In particular, the appropriate response is that
social epidemiologists qua social epidemiologists are interested in a specific level of
explanation—viz., a level in which claims about fundamental causes refer to events
or (sub-) types of events described in the vocabulary of social-context properties. Of
course, even in the tubercle bacillus—tuberculosis case, social epidemiologists may
be interested in whether there are social conditions that serve as the fundamental
causes of the tubercle bacillus, and so may be interested in tuberculosis as a specific
kind of adverse health event type. What is important, is that for the social
12 See Gottfredson [70], for an argument that ‘‘the general intelligence factor, g’’ (a paradigmatic
individual-level property) has all the requisite properties of a fundamental cause.
Social epidemiologic concept of fundamental cause 479
123
epidemiologist interested in fundamental cases, it is a mistake to collapse all causes
into individual-level causes. Even though individualistic epidemiology has been the
dominant tradition in the United States and Britain since the turn of the century,13
‘‘focusing exclusively on the individual level without taking group-level factors into
account’’ is, as Ana Diez-Roux writes, to commit the ‘‘psychologistic or
individualistic fallacy’’ [53]. The moral we should draw from Diez-Roux’s remark
is that a fully general account of fundamental causes of adverse health outcomes
must incorporate the social epidemiological concept of fundamental cause as well asanalogous conceptions of fundamental cause in which the causes are not all events
or (sub-) types of events described using the vocabulary of social-context properties
(See [55, 74]). A virtue of focusing on an approach to fundamental causes that
avoids the exhaustive dualism of individual and group-level characterizations by
using social-context variables is that it avoids both ecological and psychologistic or
individualistic fallacies while acknowledging the possibility of multiple approaches
to questions of causality (Duncan et al. [75]).
The remarks in the preceding two paragraphs lead to a second potential problem
in which we have a chain of causes and effects, where multiple causes in the chain
are necessary causes. For example, suppose that we have the following:
X! X0 ! Y
Moreover, suppose that X0 is a necessary cause of Y, and that X is a necessary cause
of X0. Can we still say that X0 is a fundamental cause of Y? The answer is ‘‘Yes’’.
We can say that X0 is a fundamental cause of C, though if both X and X0 are
constituted by events or (sub-) types of events described in the vocabulary of social-
context properties, we cannot (rightly) say that X0 is, in the social epidemiological
sense, the fundamental cause of Y. Instead, since X0 is a fundamental cause of Y and
X is a fundamental cause of X0, then by the transitivity of necessary causation, it
follows that X is a fundamental cause of Y. It is true that X0 is a more proximate
cause of Y than is X, but this is consistent with both X and X0 being fundamental
causes of Y. Thus, the possibility of there being ‘‘chains of necessary causes’’ need
not pose a problem to understanding fundamental causes as necessary causes.
Indeed, this characterization captures the fact that an effect, captured using a type-
level description, having a single necessary cause is extremely low (See [55]).
Moreover, depending on the research interests of the person(s) investigating
fundamental causes, there may be several different research foci. For example, the
focus may be on X, or X0, or both. Alternatively, the focus may be on multiple levels
of necessary causes such as when X is constituted by events or (sub-) types of events
described using the vocabulary of social-context properties, and X0 is constituted by
events or (sub-) types of events described using the vocabulary of non-social-
context properties.
13 Armstrong [72], Schwartz [55] and Koopman, and Lynch [73]. As late as 1996, Pearce [59], wrote that
‘‘modern epidemiologists rarely consider socioeconomic factors and the population perspective, except
perhaps to occasionally adjust for social class in analyses of the health effects of tobacco smoke, diet, and
other lifestyle factors in individuals.’’
480 A. Ward
123
A third, related problem, focuses on cases in which the causal relation between X
and Y is mediated by one or more events that are not themselves either necessary or
sufficient causes. For example, consider the following:
X! X0 ! X00 ! Y
Let us further suppose that while X is a necessary cause of Y, and either an event or
a (sub-) type of events described using social-context descriptions, it is not a
necessary cause of either X0 or X00, and that neither X0 nor X00 are either necessary or
sufficient causes for Y. Does the requirement that all fundamental causes are
necessary causes permit occurrences of this sort? The quick answer is that ‘‘it had
better’’ since it is examples of just this kind that writers like Link and Phelan have in
mind. As they write, the idea of fundamental cause captures the idea that a link is
preserved between the fundamental cause and the effect even through changes in the
mediating ‘‘mechanisms’’ [3]. Fortunately, these sorts of examples do not pose a
problem. The claim that X is a necessary cause of Y is consistent with saying that
there is no necessary chain of intermediary causes through which the causal impact
of X on Y must pass. It may be that there must be some chain of intermediary
causes, but depending on the population of interest and the etiological time-period,
that chain of intermediary causes may change. To return again to Rothman, suppose
that we have two causal complexes, C1 and C2, where the component causes of C1
are X, Y and Z, while the component causes of C2 are X, V, W. Further, let us
suppose that both C1 and C2 are sufficient causes for some effect E, and that the
common element of C1 and C2 works through the mediating agency of the other
component causes. In this case, we can say that while C1 and C2 are sufficient
causes for E, none of V, W, Y, and Z are either necessary or sufficient causes.
However, if we per hypothesis, suppose that C1 and C2 are the only sufficient causes
of E, then we can say that X is a necessary (but not a sufficient cause) of E. That is
to say, not only is X necessary in that it is a non-redundant element of both C1 and
C2, it is also necessary in the sense of being a non-eliminable cause (a necessary
cause) of Y. Additionally, in this situation, on the assumption that we describe X in
the vocabulary of social context properties, it follows that X is a fundamental cause,
in the social epidemiological sense, of E.
Returning to the original case of X ? X0 ? X00 ? Y, X0 and X00 are necessary
component causes for Y only if X ? X0 ? X00 is the only sufficient cause for Y. In
the case where X ? X0 ? X00 is the only sufficient cause for Y, and X is the only
sufficient cause for X0, and X0 is the only sufficient cause for X00, we can say that the
causal complex is the necessary and sufficient cause for Y. Here, because
X ? X0 ? X00 is the only sufficient cause for Y, each of X, X0 and X00 are
necessary causal component of the effect Y, though none of the three is singularly,
or in conjunction with one other component cause, a sufficient cause of Y. This
analysis also brings to the forefront an important reminder about the taxonomy of
causes into necessary causes, sufficient causes, and necessary and sufficient causes:
the taxonomy is not an exhaustive one. Put differently, it is possible for two events
to be causally related to one another (e.g., X ? Y), where X is neither a necessary
cause of Y nor a sufficient cause of Y (and so, not a necessary and sufficient cause
of Y). Nevertheless, the taxonomy is useful because it permits us to focus on one of
Social epidemiologic concept of fundamental cause 481
123
the distinctive characteristics of fundamental causes, viz., that fundamental causes
are necessary causes.
Conclusion
The goal of research in social epidemiology (as well as health services research
more generally) is not simply conceptual clarification or theoretical understanding,
but more importantly it is to contribute to, and enhance the health of populations
(and so, too, the people who constitute those populations). Undoubtedly,
understanding how various individual risk factors such as smoking and obesity
affect the health of people does contribute to this goal. However, what is distinctive
of much on-going work in social epidemiology is the view that analyses making use
of individual-level variables is not enough. In the spirit of Durkheim and Weber, S.
Leonard Syme makes this point by writing that just ‘‘as bad water and food may be
harmful to our health, unhealthful forces in our society may be detrimental to our
capacity to make choices and to form opinions’’ conducive to health and well-being
[76]. Advocates of upstream (distal) causes of adverse health outcomes propose to
identify the most important of these ‘‘unhealthful forces’’ as the fundamental causes
of adverse health outcomes. However, without a clear, theoretically precise and
well-grounded understanding of the characteristics of fundamental causes, there is
little hope in applying the statistical tools of epidemiology and the health sciences to
hypotheses about fundamental causes, their outcomes, and policies intended to
enhance the health of populations. It is only after characterizing the social
epidemiological concept of fundamental cause in a theoretically respectable and
robust way that it can enter the realm of health science, and provide the framework
for well-crafted health policies. Providing a start to this process has been the goal of
the present paper.
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