2007 the Social Epidemiologic Concept of Fundamental Cause

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]

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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

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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

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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.

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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


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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.’’

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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


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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

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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


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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

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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].


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.


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.


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


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.

References

1. Daniels, Norman, Bruce Kennedy, and Ichiro Kawachi. 2000. Justice is good for our health. In Isinequality bad for our health?, ed. Joshua Cohen and Joel Rogers, 3–33. Boston, MA: Beacon Press.

2. Robert, Stephanie A., and James S. House. 2000. Socioeconomic inequalities in health: An enduring

sociological problem. In Handbook of medical sociology, ed. Chloe Bird, Peter Conrad and Allen

Fremont, 5th ed., 79–97. Upper Saddle River, NJ: Prentice Hall.

3. Link, Bruce G., and Jo Phelan. 1995. Social conditions as fundamental causes of diseases. Journal ofHealth and Social Behavior 35, extra issue: 80–94.

4. Link, Bruce G., and Jo Phelan. 1996. Editorial: Understanding sociodemographic differences in

health—the role of fundamental social causes. American Journal of Public Health 86, no. 4:

471–473.

5. Lutfey, Karen, and Jeremy Freese. 2005. Toward some fundamentals of fundamental causation:

socioeconomic status and health in the routine clinic visit for diabetes. American Journal of Soci-ology 110, no. 5: 1326–1372.

6. Williams, David R. 1990. Socioeconomic differentials in health: A review and redirection. SocialPsychology Quarterly 53, no. 2: 81–99.

7. Link, Bruce G., and Jo Phelan. 2000. Evaluating the fundamental cause explanation for social

disparities in health. In Handbook of medical sociology, ed. Chloe Bird, Peter Conrad and Allen

Fremont, 5th ed., 33–46. Upper Saddle River, NJ: Prentice Hall.

482 A. Ward

123

8. Phelan, Jo C., and Bruce G. Link. 2005. Controlling disease and creating disparities: A fundamental

cause perspective. Journal of Gerontology series B, 60B: 27–33.

9. Rothman, Kenneth J. 2002. Epidemiology: An introduction. New York, NY: Oxford University Press.

10. Rothman, Kenneth J. 1976. Causes. American Journal of Epidemiology 104, no. 6: 587–592.

11. Rothman, Kenneth J., and Sander Greenland. 1998. Causation and causal inference. In Modernepidemiology, ed. Kenneth Rothman and Sander Greenland, 2nd ed., 7–28. Philadelphia, PA:

Lippincott Williams and Wilkins.

12. Pearl, Judea. 2000. Causality: Models, reasoning, and inference. Cambridge: Cambridge University

Press.

13. Kim, Jaegwon. 1993. Causation, nomic subsumption, and the concept of event. In Supervenience andmind: Selected philosophical essays, ed. Jaegwon Kim, 3–21. Cambridge: Cambridge University

Press.

14. Rothman, Kenneth J., and Sander Greenland. 2005. Causation and causal inference in epidemiology.

American Journal of Public Health Supplement 1, 95, no. S1: S144–S150.

15. Parascandola, M., and D.L. Weed. 2001. Causation in epidemiology. Journal of Epidemiology andCommunity Health 55: 905–912.

16. Karhausen, L.R. 2000. Causation: The elusive grail of epidemiology. Medicine, Health Care andPhilosophy 3: 59–67.

17. Charlton, Bruce G. 1996. Attribution of causation in epidemiology: Chain or mosaic? Journal ofClinical Epidemiology 49, no. 1: 105–107.

18. Bigelow, John, and Robert Pargetter. 1990. Metaphysics of causation. Erkenntnis 33: 89–119.

19. Susser, Mervyn. 1973. Causal thinking in the health sciences: Concepts and strategies in epidemi-ology. New York: Oxford University Press.

20. Nowak, Stefan. 1960. Some problems of causal interpretation of statistical relationships. Philosophyof Science 27, no. 1: 23–38.

21. Mellor, D.H. 1995. The facts of causation. London: Routledge.

22. Glymour, Bruce. 2003. On the metaphysics of probabilistic causation: Lessons from social epide-

miology. Philosophy of Science 70: 1413–1423.

23. Hausman, Daniel M., and James Woodward. 1999. Independence, invariance and the causal Markov

condition. British Journal for the Philosophy of Science 50: 521–583.

24. Hausman, Daniel M. 1998. Causal asymmetries. Cambridge: Cambridge University Press.

25. Hitchcock, Christopher. 1995. The Mishap at Reichenbach fall: Singular vs. general causation.

Philosophical Studies 78: 257–291.

26. Pearce, Neil. 1990. White Swans, Black Ravens, and Lame Ducks: Necessary and sufficient causes in

epidemiology. Epidemiology 1, no. 1: 47–50.

27. Marini, Margaret Mooney, and Burton Singer. 1988. Causality in the social sciences. Social Meth-odology 18: 347–409.

28. Montefiore, Alan. 1956. Professor Gallie on necessary and sufficient conditions. Mind 65, no. 260:

534–541.

29. Greenland, Sander, and Babette Brumback. 2002. On overview of relations among causal modeling

methods. International Journal of Epidemiology 31: 1030–1037.

30. Mackie, J.L. 1965. Causes and conditions. American Philosophical Quarterly 2, no. 4: 245–264.

31. Mackie, J.L. 1974. The cement of the universe: A study of causation. Oxford: Oxford University

Press.

32. Mosley, Albert. 2004. Does HIV or poverty cause AIDS? Biomedical and epidemiological per-

spectives. Theoretical Medicine 25: 399–421.

33. Nagel, Ernest. 1987. The structure of science: Problems in the logic of scientific explanation, 2nd ed.

Indianapolis, IN: Hackett Publishing Co.

34. Kelsey, Jennifer L., Alice S. Whittemore, Alfred S. Evans, and W. Douglas Thompson. 1996.

Methods in observational epidemiology, 2nd ed. New York, NY: Oxford University Press.

35. Eells, Ellery. 1991. Probabilistic causality. Cambridge: Cambridge University Press.

36. Popper, Karl R. 1965. Conjectures and refutations: The growth of scientific knowledge. New York:

Harper Torchbooks.

37. Popper, Karl R. 1985. The problem of induction. In Popper selections, ed. David Miller, 101–117.

Princeton: Princeton University Press.

38. Van Fraassen, Bas C. 1980. The scientific image. Oxford: Clarendon Press.

39. Woodward, James. 2003. Making things happen: A theory of causal explanation. Oxford: Oxford

University Press.


123

40. Maldonado, George, and Sander Greenland. 2002. Estimating causal effects. International Journal ofEpidemiology 31: 422–429.

41. House, James S. 2002. Understanding social factors and inequalities in health: 20th century progress

and 21st century prospects. Journal of Health and Social Behavior 43, no. 2: 125–142.

42. Link, Bruce G., Mary E. Northridge, Jo C. Phelan, and Michael L. Ganz. 1998. Social epidemiology

and the fundamental causal concept: On the structuring of effective cancer screens by socioeconomic

status. The Milbank Quarterly 76, no. 3: 375–402.

43. Williams, David R., and Chiquita Collins. 1995. U.S. socioeconomic and racial differences in health:

Patterns and explanations. Annual Review of Sociology 21, 349–386.

44. Phelan, Jo C., et al. 2004. ‘Fundamental causes’ of social inequalities in mortality: A test of the

theory. Journal of Health and Social Behavior 45, no. 3: 265–285.

45. Dutton, D.B., and S. Levine. 1989. Overview, methodological critique, and reformulation. In

Pathways to health, ed. J.P. Bunker and D.S. Gomby, 29–69. Menlo Park, CA: The Henry J. Kaiser

Family Foundation.

46. Montgomery, Laura E., John L. Kely, and Gregory Pappas. 1996. 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. American Journal of Public Health 86, no. 10: 1401–1405.

47. Hempel, Carl G. 1965. Typological methods in the natural and the social sciences. In Aspects ofscientific explanation and other essays in the philosophy of science, ed. Carl G. Hempel, 155–171.

New York: The Free Press; Salmon, Wesley C. 1998. Causality and explanation. New York: Oxford

University Press.

48. Ehring, Douglas. 1997. Causation and persistence: A theory of causation. New York: Oxford

University Press.

49. Weber, Max. 1968. The theory of social and economic organization. Translated by A.M. Henderson

and Talcott Parsons. New York: The Free Press.

50. Lynch, John, and George Kaplan. 2000. Socioeconomic position. In Social epidemiology, ed. Lisa

Berkman and Ichiro Kawachi, 13–35. New York: Oxford University Press.

51. Moffitt, Robert. 2003. Causal analysis in population research: An economist’s perspective. Popu-lation and Development Review 29, no. 3: 448–458.

52. Link, Bruce G., and Jo Phelan. 2002. McKeown and the idea that social conditions are fundamental

causes of diseases. American Journal of Public Health 92, no. 5: 730–732.

53. Diez-Roux, Ana V. 1998b. On genes, individuals, society, and epidemiology. American Journal ofEpidemiology 148, no. 11: 1027–1032.

54. Baron, Reuben M., and David A. Kenny. 1986. The moderator-mediator variable distinction in social

psychological research: Conceptual, strategic, and statistical considerations. Journal of Personalityand Social Psychology 51, no. 6: 1173–1182.

55. Schwartz, S., E. Susser, and M. Susser. 1999. A future for epidemiology? Annual Review of PublicHealth 20: 15–33.

56. Tesh, Sylvia Noble. 1988. Hidden arguments: Political ideology and disease prevention policy. New

Brunswick, NJ: Rutgers University Press.

57. Emmons, Karen M. 2000. Health behaviors in a social context. In Social epidemiology, ed. Lisa F.

Berkman and Ichiro Kawachi, 242–266. Oxford: Oxford University Press.

58. Beland, Francois, Stephen Birch, and Greg Stoddart. 2002. Unemployment and health: Contextual-

level influences on the production of health in populations. Social Science and Medicine 55:

2033–2052.

59. Pearce, Neil. 1996. Traditional epidemiology, modern epidemiology, and public health. AmericanJournal of Public Health 86, no. 5: 678–683.

60. Durkheim, Emile. 1982. The rules of sociological method—second edition. In The rules of socio-logical method and selected texts on sociology and its methods, ed. Steven Lukes, translated by

W.D. Hall, 31–163. New York: The Free Press (first published in 1901).

61. Giddens, Anthony. 1984. The constitution of society. Berkeley: University of California Press.

62. Wells, Barbara L., and John W. Horm. 1988. Targeting the underserved for breast and cervical cancer

screening: The utility of ecological analysis using the national health interview survey. AmericanJournal of Public Health 88, no. 10: 1484–1489.

63. Susser, Mervyn. 1994. The logic in ecological: I. The logic of analysis. American Journal of PublicHealth 84, no. 5: 825–829.

64. Selvin, Hanan C. 1958. Durkheim’s suicide and the problems of empirical research. AmericanJournal of Sociology 63, no. 6: 607–619.

484 A. Ward

123

65. Morgenstern, Hal. 1982. Uses of ecological analysis in epidemiologic research. American Journal ofPublic Health 72, no. 12: 1336–1344.

66. Diez-Roux, Ana V. 1998a. Bringing context back into epidemiology: Variables and fallacies in

multilevel analysis. American Journal of Public Health 88, no. 2: 216–222.

67. Collins, Randall. 1981. On the microfoundations of macrosociology. American Journal of Sociology86, no. 5: 984–1014.

68. Betson, David M., and Jennifer L. Warlick. 2006. Measuring poverty. In Methods in social epide-miology, ed. J. Michael Oakes and Jay S. Kaufman, 112–133. San Francisco, CA: Jossey-Bass.

69. Ross, Catherine E., and John Mirowsky. 1995. Does employment affect health? Journal of Healthand Social Behavior 36, no. 3: 230–243.

70. Gottfredson, Linda S. 2004. Intelligence: Is it the epidemiologists’ elusive ‘‘fundamental cause’’ of

social class inequalities in health? Journal of Personality and Social Psychology 86, no. 1: 174–199.

71. Schulz, Amy, and Mary E. Northridge. 2004. Social determinants of health: Implications for envi-

ronmental health promotion. Health Education and Behavior 31, no. 4: 455–471.

72. Armstrong, Donna. 1999. ‘Controversies on epidemiology,’ teaching causality in context at the

University of Albany, School of Public Health. Scandinavian Journal of Public Health 2: 81–84.

73. Koopman, James S., and John W. Lynch. 1999. Individual causal models and population models in

epidemiology. American Journal of Public Health 89, no. 8: 1170–1174.

74. Susser, Mervyn, and Ezra Susser. 1996. Choosing a future for epidemiology: II. From black box to

Chinese boxes and eco-epidemiology. American Journal of Public Health. 86, no. 5: 674–677.

75. Duncan, Craig, Kelvyn Jones, and Graham Moon. 1996. Health-related behavior in context: A

multilevel modeling approach. Social Science and Medicine 42, no. 6: 817–830.

76. Syme, S. Leonard. 1994. The social environment and health. Daedalus 23, no. 4: 79–86.


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2007 the Social Epidemiologic Concept of Fundamental Cause