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“Death by proxy”: Ethics and classification in epidemiology
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Soc. Sci. Med. Vol. 47, No. 9, pp. 1147±1153, 1998 # 1998 Published by Elsevier Science Ltd. All rights reserved S0277-9536(98)00186-5 Printed in Great Britain 0277-9536/98 $19.00 + 0.00
``DEATH BY PROXY'': ETHICS AND CLASSIFICATION IN EPIDEMIOLOGY AILEEN J. PLANT1* and R. LOUISE RUSHWORTH2 1
Department of Public Health, Clifton St. Campus, University of Western Australia, Western Australia 6907, Australia and 2Centre for Health Services Research, Faculty of Health, University of Western Sydney, Macarthur, Australia
AbstractÐEpidemiology is reductionist in that it usually relies on creating categories of people or risk factors. Classi®cation must be undertaken as part of any study, however by the act of choosing groups, individuals are (potentially) consigned to either a higher or lower risk group. We discuss this from an ethical perspective and consider: (a) whether the groupings commonly chosen genuinely represent the risk factor of interest, (b) the implications for individuals when consigned to groups and (c) the implications for epidemiology. # 1998 Published by Elsevier Science Ltd. All rights reserved Key wordsÐethics, epidemiology, classi®cation, HIV, indigenous, marital
INTRODUCTION
Epidemiology, de®ned by Last (1988) as ``the study of the distribution and determinants of health-related states or events in speci®ed populations and the application of this study to control of health problems'', is a major tool in public health. An epidemiologist's scienti®c questions can almost all be divided into two groups: (a) what is the magnitude of a risk factor (or an outcome) of interest? and (b) does a particular factor cause (or prevent) an outcome? Practical, simple examples of these questions could be how much smoking there is in a particular population and whether smoking causes lung cancer. Ethics is ``the branch of philosophy that deals with the distinction between right and wrong, with the moral consequences of human actions'' (Last, 1988) and from an ethical point of view, epidemiologists have to consider not only the rules of conduct of their research but also the moral outcomes of that research. In practical terms epidemiologists are more aware of the practice of their research in relation to the former than to the latter. The issues surrounding the moral outcomes of epidemiological research and public health practice are more complex but are often poorly recognised +/or poorly articulated. Each of the four key concepts of bioethics (that branch of ethics dealing with biological research) and its applications, makes requirements of professionals. For autonomy it is a respect for individual rights and freedoms; for bene®cence that professionals do good; for non-male®cence that they do no harm and for justice a fair and equitable *Author for correspondence.
allocation of resources without discrimination (Soskolne, 1989; Beauchamp and Childress, 1994). In this paper we seek to examine one particular area of epidemiology, that of classi®cation of risk factors, and the interaction between such classi®cations and ethics. We use the concepts of autonomy, bene®cence, non-male®cence and justice to examine epidemiological classi®cation. We will also suggest possible solutions to certain ethical issues we identify. INDIVIDUAL VS POPULATION
Implicit in Last's de®nition of epidemiology is that epidemiological answers should lead to interventions. This frequently, but not always, encompasses a utilitarian approach. Coughlin and Beauchamp note ``Utilitarianism is rooted in the thesis that an action or practice is right (when compared with any alternative action or practice) if it leads to the greatest possible balance of good consequences or to the least possible balance of bad consequences'' (Coughlin, 1996). For most of the 19th and 20th centuries, utilitarianism appears to have been the prevailing philosophy of many public health practitioners and its associated understanding that in order to bene®t the community as a whole, sometimes individuals may suer (Last, 1996). For instance, the legislation surrounding the compulsory use of seatbelts which was enacted in some countries was accompanied by claims that individuals may be harmed by such a law, e.g. the wearing of a seatbelt may hold the person in a physical position such that in the event of particular circumstances in a car accident the seatbelt may increase rather than decrease the risk of injury. Despite this type of argument, and not
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because the argument was in itself incorrect, the public health action (the use of seatbelts) was legislated on the basis that there was a net good for the community. Any such approach, however, does not exempt epidemiologists and other public health practitioners from the need to consider the ethics of their approaches. Rather it should have the opposite eect. A strictly utilitarian approach does not encompass the diversity of issues involved with justice that public health does, or at least should. Any evaluation of public health interventions must weigh the bene®ts of an intervention, but additionally consider the distribution of such bene®ts. There is now an acceptance that a simple ``bene®t maximisation'' approach is an inadequate framework in which to capture the complexities of ethics and public health. Issues of equity must be considered in ethical epidemiological practice, although deciding ``what is equity?'' is not a simple question. Frequently public health practitioners refer to equality of access to health care or to equal use and equal health (according to need) (McDermott et al., 1996). The majority of studies undergo formal ethical approval. It follows, it would seem, that epidemiological studies can be presumed to be ethical. Ethics committees, however, are usually (quite rightly) concerned with matters such as informed consent and non-male®cence. If the purpose of epidemiology, however, lies in improving public health, then the ethical approach demands more. For example, ethics committees do not (as a general rule) consider the implications for people not in a particular study, but to whom the results could be extrapolated.
tors'' with the exception of some trials (experiments) where the allocation is randomised. Epidemiology has to take this reductionist approach; it is integral to epidemiology. Imagine trying to determine associations and causes of health problems, identify and estimate the extent of health problems of populations and plan health services, if a reductionist and classi®catory approach were not possible. Having accepted that it is part of the role and function of the epidemiologist to classify both the ``risk factors'' and outcomes of their studies in order for human health to bene®t, we still have some remaining questions. Do the classi®cations commonly chosen genuinely represent the risk factors of interest? What are the implications of dierent classi®cations for individuals, as well as for populations? What are the implications of classi®cations for epidemiological practice? We will explore these ideas using three common classi®cations of risk factors in epidemiology namely those usually used for HIV/AIDS in developed countries, the risk factors of ``indigenous cultural group'' and ``marital status''. We have chosen the ®rst of these because there have already been some changes in the description of risk categories for HIV/AIDS and such changes provide a useful example. Our choice of indigenous group was used because it is clearly, in itself, unchangeable. Marital status was chosen because it is common, is a socially derived classi®cation and, intuitively, is not likely to be the real risk for many diseases. Epidemiologists, of course, usually recognise the limitations of their classifying but do not always make the limitations explicit. Those using the data may not understand these ``coded'' limitations with the result that actions with unethical consequences may follow.
CLASSIFICATION AND THE ETHICAL APPROACH
Our view is that for studies in epidemiology to be deemed ethical, they must not only be judged as such for those people actually studied but also for those in the wider population for whom the results have a (potential) impact. This implies that for an epidemiological study to be ethical it must encompass the principles of autonomy, bene®cence, nonmale®cence and justice for both the study participants and the relevant wider population. One of the most important epidemiological activities, particularly at the local and national health department level, is analysing patterns of health and disease in populations. The process of classi®cation of populations being studied into the groups of interest (e.g. age and sex, ethnic group) forms a major part of such analysis. Generally, categories are chosen by epidemiologists and usually re¯ect, in some part, the interests, values and concerns of the community. Classi®cation also occurs in other forms of epidemiological studies where epidemiologists allocate cases to categories based on ``risk fac-
DO THE CLASSIFICATIONS CHOSEN GENUINELY REPRESENT THE RISK FACTOR OF INTEREST?
In many instances in developed countries the risk factors for HIV are published as homosexual, bisexual, heterosexual, intravenous drug use, receipt of contaminated blood products or some similar classi®cation (Ancelle-Park et al., 1990; Dore et al., 1996; Nador et al., 1996; Raman et al., 1996). The categories were chosen initially because the risk factors for AIDS were unknown. AIDS was ®rst described in a group of young men who were homosexual and in the urgent search for the cause, classi®cations of homosexual, bisexual and heterosexual were appropriate. The groupings chosen for HIV/AIDS predominantly centre on sexual orientation rather than sexual behaviour. For instance a person with a bisexual orientation may never act on those inclinations. Such a person is at very low risk of HIV (given the fact that other means of contracting the virus are remote, e.g. the blood supply is safe). The
Death by proxy
real risk of contracting HIV via sexual activity depends on several factors. These include the frequency of sexual intercourse; the probability that any particular episode of intercourse will be with a person who is infectious and whether the risk was modi®ed in any way, such as through condom use. With time, a clearer de®nition of the ``at-risk'' sexual behaviour became more widely used (e.g. men who have sex with men) but, despite this, some statistics tend still to be published in the original risk categories, although in some instances the reported categories have been modi®ed (Ancelle-Park et al., 1990; Anonymous, 1996). We recognise that those reporting the data usually understand the implications of their data. We remain concerned to ensure however that the reporting be as clearly understood by the reader. The other major category used to explain risk for HIV/AIDS is intravenous drug use. The real factor here is not the intravenous use per se but the sharing of (frequently contaminated) needles. Of course, the use of intravenous drugs may be associated with needle sharing for some people and at some times, but it is not a universal habit and hence not a universal risk among intravenous drug users. In Australia, published data often identify Aboriginality as a ``risk factor'' for poor health and early death. Newspapers and television use headlines such as ``Australian Aboriginal women 10 times more likely to die in childbirth, 10 times more likely to be murdered''. Do we believe that Aboriginality is the risk factor of interest? The answer to this question is clearly no. We do not expect the Aboriginal medical student to die in childbirth, or to be at particular risk of homicide. We recognise that there are other factors which may be associated in some way with Aboriginality such as poor access to health services, cultural identity, which are more important than the classi®cation of Aboriginal. Of course, some component of risk may be speci®cally related to being Aboriginal. For instance all Aboriginal people have been aected by European settlement and this (probably) has ¯ow-on eects on health although obtaining scienti®c evidence to prove this is dicult. Regardless, much of the dierential between Aboriginal and non-Aboriginal health can be explained by other, already known risk factors which are not a direct function of Aboriginality. This has been demonstrated in one study in which about half of the variation in childhood hospitalisation rates for diarrhoea between Aboriginal communities was shown to be due to environmental conditions such as sanitation, water supply and the eects of overcrowding (Munoz et al., 1992). Over time the fact that risk factors are not a proxy for a population sub-group has been better recognised and arguments made that there is a more scienti®cally valid way of presenting such information (Coughlin, 1996). At the same time as
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recognising the real risk factors that lie behind the label of ``Aboriginality'', it is essential that we do not permit alternative explanations to hide the very real dierential in health experienced by Aborigines, that aects virtually every cause of Aboriginal mortality and morbidity (Plant et al., 1995). The diculty that public health experiences with the biological concept of race has been described by others (Cooper and David, 1986). As well, some studies have highlighted where much of the apparent risk due to race disappears when economic circumstances are included in the analysis (Ansell et al., 1993). In a similar way, marital status is likely to be a re¯ection of many other factors in an individual's life that can in¯uence their health, not merely the possession of a marriage certi®cate. Again the question must be raised as to whether a married person in a situation without sucient resources for the physical essentials such as food and shelter will be more likely to have a better health outcome than an unmarried person who has adequate resources for living. The role of emotional security is also likely to have a health impact, although whether this is necessarily a function of marriage is far less clear. In all these examples there is some dissociation between the classi®cation and the ``real'' nature of the risk factor. The ``risk factor'' which is identi®ed and used is a ``proxy'' for the real risk. This is not to suggest that epidemiologists do not recognise the dierence between cause and risk but rather that the assumed risk, when distant from the real risk, is likely to have ethical implications. WHAT ARE THE IMPLICATIONS OF CLASSIFICATION FOR INDIVIDUALS ASSIGNED TO GROUPS?
The quantity and nature of the eects of ``labelling'' individuals at risk of an outcome because of their inclusion in a pre-determined group are largely unknown. Such labelling undoubtedly leads to some degree of stress and perhaps feelings of helplessness, if the outcome is perceived as undesirable. Such stress and helplessness have an eect on both physical and emotional health (Farhood et al., 1993; Levi, 1993). Imagine having a high risk of death assigned to you, regardless of whether the risk is real or not. We have good evidence that a placebo eect can work for recovery in many instances (Bienenfeld et al., 1996). Can a ``you are at an increased risk of death'' interpretation of health-related information work in a similar way, but in the opposite direction? A similar eect has been described in other diseases where the eect of personal attitude has been shown to in¯uence the ®nal outcome (Kure et al., 1991; Molassiotis et al., 1997). The very real concern is that classi®cation without good reason may needlessly ``rob'' individuals of their sense of health. Of course, even with real rather than proxy risk factors, people may be
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robbed of their sense of health as not all those with a particular risk factor experience the associated disease, e.g. not everyone with high blood pressure will experience stroke. People from indigenous groups frequently feel despair at the health statistics provided in formal settings, such as classrooms, and informal settings, such as casual conversation. At some level, to be part of a group that lives less long, can appear to be perceived as being less deserving of living. Moreover, the eect that the descriptions of the health risks associated with being unmarried has on the person who may already feel inadequate because of not being married is unknown. Nor is the eect of knowing the association of poorer health outcomes for unmarried men, even if the individual did not want to be married. The second implication of classi®cation in epidemiological analysis may be that if the assumed grouping does not accord with the individuals' perceptions of their role, they may not identify with any intervention which uses these (rejected) groupings. So, if an individual male identi®es himself as heterosexual but in fact is an active bisexual, he may not ``hear'' messages about AIDS prevention, safe-sex or bisexuality. As a result he may fail to make behavioural adjustments which he might otherwise have made with appropriately targeted messages which concentrated on the behaviour rather than the grouping (hence the developments of explicit description of behaviours and categories such as ``men-who-have-sex-with-men''). Along the same line of argument, a heterosexual female may not perceive herself to be at risk of HIV because of her sexual orientation when she may be at risk due to either the frequency of sexual encounters or, due to speci®c social reasons, the probability of encountering an infected individual. Moreover, the absence of an explicit description of the actual risk factor may lead an individual to feel that their risk is not modi®able (``I am Aboriginal; therefore I have an increased risk of heart disease; therefore there is no point in worrying about the blood pressure problem I have; it won't make any dierence''). Alternatively, given that they already have the label, it is not worth doing anything about the risk (``I am a drug user; therefore, everyone knows I am at risk of AIDS; why bother about clean needles''). Certainly some literature suggests that increasing awareness of risk may actually increase risk behaviour (Robles et al., 1995). Lastly, the individual or group may suer discrimination because of putative risk. For example, a person may be denied housing or employment because they are part of a group with a higher proportion of the risk factor, e.g. homosexual men being denied employment because they might have HIV.
WHAT ARE THE IMPLICATIONS OF CLASSIFICATIONS FOR POPULATIONS?
The eects of classi®cation within observational epidemiological studies can lead to a range of ¯owon eects on society. The ®rst and perhaps the most important is the implicit classi®cation of ``other'' groups which in turn lessens the apparent responsibility of (usually) the majority of the population. This can lead to an unwitting change of attitude to the aected group. The following scenario outlines such a circumstance: ``Indigenous people (such as Australian Aboriginal, Native American, Inuit, Maori) have an increased risk of diarrhoea....Aborigines ...nothing anyone can do about that, they always have increased risks of sickness''. The alternative approach could be ``increased risk of diarrhoea... who? people with no running water or sewage system... well who wouldn't be at risk of diarrhoea, there is a need for action, no group should be without running water or adequate sewage disposal''. The identi®cation then naming of the perceived (i.e. indigenous) risk factor instead of the real risk (sewage and water issues, socio-economic issues) permits and enhances stigmatisation and thus avoids the real issue and the appropriate solution. Similarly, discussion of the risk of infectious disease in the context of drug use instead of in that of needle sharing, permits society, all too often, to focus on the issues that are insoluble or extremely dicult such as controlling illicit drugs. In turn this hinders debate about those issues that are not only the real risk factors for infectious diseases, but which may actually have solutions, e.g. providing needles and syringes. By classifying marital status as a risk factor it seems likely that we have again used a proxy for something society may be able to address. No-one seriously suggests longer life can be attained by arranging marriages for unmarried people. Perhaps if we tried harder to determine the real risk factors which may well be feeling secure in our society, or feeling supported in daily existence, then we could better identify interventions that might make a dierence. It is dicult to escape the conclusion that epidemiology, by failing to categorise the risk factors into appropriate classi®cations, permits society to have an attitude, at some level, that the group in question ``deserves'' the poor outcome. The other likely eect of classi®cation that does not truly address the real risk factors is that there is potential for spending scarce resources where they may not lead to optimum health bene®t. For example, although there have been many attempts at improving the health status of Aboriginal people through provision of direct health services, the expenditure has resulted in minimal health gains. Rather it appears that money needs to be spent on providing
Death by proxy
other services such as education, better housing, improving access to fresh water, improving sewerage systems, etc. WHAT ARE THE IMPLICATIONS FOR EPIDEMIOLOGICAL PRACTICE?
Epidemiology, as described at the start of this paper, seeks to describe accurately the distribution and determinants of health and illness in populations and in so doing inform public health action to improve health. Central to this activity is the accuracy of the description of population health. We are obviously limited by the data that are available. We do, however, have a responsibility to interpret data for politicians, administrators and the public. Those who may or may not be at a disadvantage deserve better description of the nature of their situation rather than current approaches. Despite the obvious limitations of much classi®cation, it is dicult to manage population health statistics without such manipulation. Indeed, if no breakdowns were given and totals only were used, this would mask health inequalities even more and miss vital opportunities for disadvantaged groups to have improved health and better access to health care. Another major advantage of classi®cation from an epidemiological perspective is that continuation of the classi®cations over time permits better interpretation of trend data. Moreover epidemiological studies amass large datasets containing numerous items of information. If public health change is to occur, classi®cation is an essential part of the analysis and interpretation of categorical (non-numerical) data. From a public health perspective it could be argued that the use of proxy classi®cations permits targeting of scarce health resources. This is certainly true, it is far better that AIDS education be directed towards homosexual men rather than towards elderly women who have a low risk of AIDS and, hence, better value can be obtained for the resources invested. It could, however, just as readily be argued that directing the resources to the real risk instead of the proxy risk would be an even better use of resources and that as such it represents a more ethical approach. If, as epidemiologists we do not classify risk factors correctly, there is a danger of being less relevant to our audience, or even of failing by providing the wrong advice. We risk failing in our mission, that of improving public health. WHAT ARE THE ETHICAL ISSUES OF CLASSIFICATION IN EPIDEMIOLOGY?
We will now consider the ethical issues of classi®cation in epidemiology using the four concepts of autonomy, bene®cence, non-male®cence and justice. Most of the examples we have used relate to justice and to a lesser extent autonomy. Any study or
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analysis, however, that is weak on these two concepts will inevitably result in public health actions which have inadequate levels of bene®cence and non-male®cence. Autonomy (previously described as that which requires of professionals a respect for individual rights and freedoms) is usually not a problem within a particular study as individual rights are protected via the ethics committees that oversee research. However, maintenance of autonomy becomes more problematic when considering the implications of a study for the wider community. Some of the examples given above include the eect on feelings of well-being and the potential for people to have their rights aected merely by being placed in a proxy risk factor group. Bene®cence (previously explained as that which requires that professionals do good) again is usually adequately dealt with in the context of the study but the nature of epidemiology implies that we must ful®l this obligation to the wider community, not merely those in the studied group. There is clearly an obligation for epidemiologists to ensure that the wider community bene®ts from epidemiological ®ndings. As knowledge develops, as it has in many areas such as HIV, and the real risk factors become clearer, there is a need to change our classi®cations in ways which facilitate improved health for the wider community. By inappropriate classi®cation of individuals we may fail to ``do good'' to those in need, inadvertently fail to encourage society to face the real issues that may improve health or even to spend money unwisely, all of which may have been improved by considering an ethical approach. The implications of non-male®cence (previously explained as that which requires of professionals that they do no harm) are much less clear than those of bene®cence. Nevertheless when we classify incorrectly we potentially do harm to both individuals and society. This may involve individuals who feel harmed, individuals who have not bene®tted from epidemiology whether in a study or not and the negative eects on society. From a societal perspective, perhaps the greatest harm is that inappropriate classi®cation may lead to inappropriate solutions. From an individual perspective the harm that results from inappropriate classi®cation is likely to be the feeling of helplessness or the nonmodi®ability of the risk factor. Considerations of justice (previously explained as that which requires of professionals a fair and equitable allocation of resources without discrimination), especially issues concerning social justice, are critical ethical issues for epidemiology. Epidemiological studies have great potential for in¯uencing where resources are directed, and if this advice is based on classi®cations that do not represent the real risks, then potential bene®ts are reduced and the meeting of the real need is denied.
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Further, if epidemiologists utilise scarce health resources, yet fail to provide correct advice, then this must constitute unethical behaviour, even if not intentionally so. The issues of equity cannot be ignored by epidemiologists. CONCLUSION
Epidemiological practice always interacts with ethical considerations. Epidemiologists recognise this most readily in regard to obtaining institutional ethics committee approval before conducting a particular study. The ethical implications of other types of epidemiological practice, such as analysing population statistics, are just as important. Classi®cation is an essential element of epidemiological analysis but, as we have demonstrated, can negatively impact on individuals, society and the provision of health services. Recognising the implications of such classi®cation is a necessary ®rst step to improving the situation. Changing the system of classi®cation to re¯ect the ``real'' risk more accurately, such is occurring in some areas such as HIV, is vital. Moreover, there is a need to encourage the evolution of datasets (such as population statistics) which re¯ect these risk factors. Classi®cation is fundamental to epidemiological analysis. We are not arguing ``don't classify'' nor even that is necessary to change classi®cations, but rather that there is a need to recognise when we are dealing in proxies rather than the real risk factor. Considerations of justice alone demand appraisal of the real risk factors and this demand has potential eects on the principles of autonomy, bene®cence and non-male®cence. Inherent in conducting epidemiological research is the demand for public health and clinical action, making it imperative that epidemiologists consider the ethical consequences of their work. There are a number of actions that can be taken to lessen the negative impact of classi®cation on ethical epidemiological practice. First, be aware that the problem exists. Although epidemiologists may be aware of the nature and limitations of the classi®cations they choose, those reading and acting upon the data may not be. Second, put caveats on the interpretation of the analysis so that the information can be interpreted accurately. This should include not merely spelling this out in the discussion of a paper but including sucient information in the abstract, which is where many decision-makers obtain their information, especially since abstracts are much more frequently available electronically than is the full text. An example of this could be ``the risk factors identi®ed were homosexuality (proxy for men-who-have-sex-with-men)''. Third, be prepared to change the classi®cation and analysis when things become clearer. This has already occurred in some statistics about HIV, e.g. ``homosexual'' is less frequently used now as a risk factor
than in the earlier years of the epidemic but ``intravenous drug use'' is nearly always used. Fourth, undertake studies to determine the real risk. An example of this has already been quoted where a commonly used proxy (race) became less important in predicting survival from breast cancer once economic status was included in the analysis (Ansell et al., 1993). Lastly, ensure that even when we have to measure these proxies we make our public health action centre on real risk. In the meantime it is essential that epidemiologists are aware of potential problems that may unwittingly derive from their classi®cation choices and that eorts are made to ensure that public health action and ethics are not compromised. REFERENCES
Ancelle-Park, R., Brunet, J., Couturier-Moren, E., Popovici, F., Apetrei, R. and Beldescu, N. (1990) Update: Acquired Immunode®ciency Syndrome, Europe. MMWR 39(47), 850±853. Anonymous (1996) AIDS associated with injecting drug use, US 1995. MMWR 45(19), 392±398. Ansell, D., Whitman, S., Lipton, R. and Cooper, R. (1993) Race, income and survival from breast cancer at two public hospitals. Cancer 72(10), 2974±2978. Beauchamp, T. and Childress, J. (1994) Principles of Biomedical Ethics. Oxford University Press, New York. Bienenfeld, L., Frishman, W. and Glasser, S. (1996) The placebo eect in cardiovascular disease [review]. American Heart Journal 132(6), 1207±1221. Cooper, R. and David, R. (1986) The biological concept of race and its application to public health and epidemiology. Journal of Health Politics, Policy and Law 11(1), 97±116. Coughlin, S. (1996) Ethically optimized study designs in epidemiology. In Ethics and Epidemiology. eds. S. Coughlin and T. Beauchamp, pp. 145±155. Oxford University Press, Oxford. Dore, G., Li, Y., Grulich, A. and Hoy, J. et al. (1996) Declining incidence and later occurrence of Kaposi's sarcoma among persons with AIDS in Australia: the Australian AIDS cohort. AIDS 10(12), 1401±1406. Farhood, L., Zurayk, H., Chaya, M., Saadeh, F., Meshefedjian, G. and Sidani, T. (1993) The impact of war on the physical and mental health of the family: the Lebanese experience. Social Science and Medicine 36(12), 1555±1567. Kure, G., Kure, S., Watson, L. and Bahnson, C. (1991) Personality as a risk factor in large bowel cancer: data from the Melbourne Colorectal Cancer Study. Psychological Medicine 21(1), 29±41. Last, J. (1988) A Dictionary of Epidemiology. Oxford University Press, New York. Last, J. (1996) Professional standards of conduct. In Ethics and Epidemiology, eds. S. Coughlin and T. Beauchamp, pp. 53±75. Oxford University Press, Oxford. Levi, L. (1993) Conditions of life, life-styles and health in a highly developed country. Seishin Shinkeigaku Zasshi (Psychiatria et Neurologia Japonica) 95(3), 259±270. McDermott, R., Plant, A. and Mooney, G. (1996) Has access to hospital improved for Aborigines in the Northern Territory? Australian and New Zealand Journal of Public Health 20(6), 589±593. Molassiotis, A., Van Den Akker, O., Milligan, D. and Goldman, J. (1997) Symptom distress, coping style and biological variables as predictors of survival after bone
Death by proxy marrow transplantation. Journal of Psychosomatic Research 42(3), 275±285. Munoz, E., Powers, J. and Mathews, J. (1992) Hospitalisation patterns in children from 10 Aboriginal communities in the Northern Territory. Med. J. Aust. 156, 524±533. Nador, R., Cesarman, E., Chadburn, A., Dawson, D., Ansari, M., Sald, J. and Knowles, D. (1996) Primary eusion lymphoma: a distinct clinicopathologic entity associated with the Kaposi's sarcoma-associated Herpes virus. Blood 88(2), 645±656. Plant, A., Condon, J. and Durling, G. (1995) Northern Territory Health Outcomes. Morbidity and Mortality.
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1979±1991. Northern Territory Department of Health and Community Services, Darwin. Raman, S., Menzies, R., McDonald, A., Grigges, E. and Levy, M. (1996) Validation of reported risk exposure in persons with newly diagnosed HIV infection. Comm. Dis. Intell. 20(1), 2±5. Robles, R., Cancel, L., Colon, H., Matos, T., Freeman, D. and Sahai, H. (1995) Prospective eects of perceived risk of developing HIV/AIDS on risk behaviors among injection drug users in Puerto Rico. Addiction 90(8), 1105±1111. Soskolne, C. (1989) Epidemiology: questions of science, ethics, morality and law. American Journal of Epidemiology 129(1), 1±18.
Soc. Sci. Med. Vol. 47, No. 9, pp. 1147±1153, 1998 # 1998 Published by Elsevier Science Ltd. All rights reserved S0277-9536(98)00186-5 Printed in Great Britain 0277-9536/98 $19.00 + 0.00
``DEATH BY PROXY'': ETHICS AND CLASSIFICATION IN EPIDEMIOLOGY AILEEN J. PLANT1* and R. LOUISE RUSHWORTH2 1
Department of Public Health, Clifton St. Campus, University of Western Australia, Western Australia 6907, Australia and 2Centre for Health Services Research, Faculty of Health, University of Western Sydney, Macarthur, Australia
AbstractÐEpidemiology is reductionist in that it usually relies on creating categories of people or risk factors. Classi®cation must be undertaken as part of any study, however by the act of choosing groups, individuals are (potentially) consigned to either a higher or lower risk group. We discuss this from an ethical perspective and consider: (a) whether the groupings commonly chosen genuinely represent the risk factor of interest, (b) the implications for individuals when consigned to groups and (c) the implications for epidemiology. # 1998 Published by Elsevier Science Ltd. All rights reserved Key wordsÐethics, epidemiology, classi®cation, HIV, indigenous, marital
INTRODUCTION
Epidemiology, de®ned by Last (1988) as ``the study of the distribution and determinants of health-related states or events in speci®ed populations and the application of this study to control of health problems'', is a major tool in public health. An epidemiologist's scienti®c questions can almost all be divided into two groups: (a) what is the magnitude of a risk factor (or an outcome) of interest? and (b) does a particular factor cause (or prevent) an outcome? Practical, simple examples of these questions could be how much smoking there is in a particular population and whether smoking causes lung cancer. Ethics is ``the branch of philosophy that deals with the distinction between right and wrong, with the moral consequences of human actions'' (Last, 1988) and from an ethical point of view, epidemiologists have to consider not only the rules of conduct of their research but also the moral outcomes of that research. In practical terms epidemiologists are more aware of the practice of their research in relation to the former than to the latter. The issues surrounding the moral outcomes of epidemiological research and public health practice are more complex but are often poorly recognised +/or poorly articulated. Each of the four key concepts of bioethics (that branch of ethics dealing with biological research) and its applications, makes requirements of professionals. For autonomy it is a respect for individual rights and freedoms; for bene®cence that professionals do good; for non-male®cence that they do no harm and for justice a fair and equitable *Author for correspondence.
allocation of resources without discrimination (Soskolne, 1989; Beauchamp and Childress, 1994). In this paper we seek to examine one particular area of epidemiology, that of classi®cation of risk factors, and the interaction between such classi®cations and ethics. We use the concepts of autonomy, bene®cence, non-male®cence and justice to examine epidemiological classi®cation. We will also suggest possible solutions to certain ethical issues we identify. INDIVIDUAL VS POPULATION
Implicit in Last's de®nition of epidemiology is that epidemiological answers should lead to interventions. This frequently, but not always, encompasses a utilitarian approach. Coughlin and Beauchamp note ``Utilitarianism is rooted in the thesis that an action or practice is right (when compared with any alternative action or practice) if it leads to the greatest possible balance of good consequences or to the least possible balance of bad consequences'' (Coughlin, 1996). For most of the 19th and 20th centuries, utilitarianism appears to have been the prevailing philosophy of many public health practitioners and its associated understanding that in order to bene®t the community as a whole, sometimes individuals may suer (Last, 1996). For instance, the legislation surrounding the compulsory use of seatbelts which was enacted in some countries was accompanied by claims that individuals may be harmed by such a law, e.g. the wearing of a seatbelt may hold the person in a physical position such that in the event of particular circumstances in a car accident the seatbelt may increase rather than decrease the risk of injury. Despite this type of argument, and not
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because the argument was in itself incorrect, the public health action (the use of seatbelts) was legislated on the basis that there was a net good for the community. Any such approach, however, does not exempt epidemiologists and other public health practitioners from the need to consider the ethics of their approaches. Rather it should have the opposite eect. A strictly utilitarian approach does not encompass the diversity of issues involved with justice that public health does, or at least should. Any evaluation of public health interventions must weigh the bene®ts of an intervention, but additionally consider the distribution of such bene®ts. There is now an acceptance that a simple ``bene®t maximisation'' approach is an inadequate framework in which to capture the complexities of ethics and public health. Issues of equity must be considered in ethical epidemiological practice, although deciding ``what is equity?'' is not a simple question. Frequently public health practitioners refer to equality of access to health care or to equal use and equal health (according to need) (McDermott et al., 1996). The majority of studies undergo formal ethical approval. It follows, it would seem, that epidemiological studies can be presumed to be ethical. Ethics committees, however, are usually (quite rightly) concerned with matters such as informed consent and non-male®cence. If the purpose of epidemiology, however, lies in improving public health, then the ethical approach demands more. For example, ethics committees do not (as a general rule) consider the implications for people not in a particular study, but to whom the results could be extrapolated.
tors'' with the exception of some trials (experiments) where the allocation is randomised. Epidemiology has to take this reductionist approach; it is integral to epidemiology. Imagine trying to determine associations and causes of health problems, identify and estimate the extent of health problems of populations and plan health services, if a reductionist and classi®catory approach were not possible. Having accepted that it is part of the role and function of the epidemiologist to classify both the ``risk factors'' and outcomes of their studies in order for human health to bene®t, we still have some remaining questions. Do the classi®cations commonly chosen genuinely represent the risk factors of interest? What are the implications of dierent classi®cations for individuals, as well as for populations? What are the implications of classi®cations for epidemiological practice? We will explore these ideas using three common classi®cations of risk factors in epidemiology namely those usually used for HIV/AIDS in developed countries, the risk factors of ``indigenous cultural group'' and ``marital status''. We have chosen the ®rst of these because there have already been some changes in the description of risk categories for HIV/AIDS and such changes provide a useful example. Our choice of indigenous group was used because it is clearly, in itself, unchangeable. Marital status was chosen because it is common, is a socially derived classi®cation and, intuitively, is not likely to be the real risk for many diseases. Epidemiologists, of course, usually recognise the limitations of their classifying but do not always make the limitations explicit. Those using the data may not understand these ``coded'' limitations with the result that actions with unethical consequences may follow.
CLASSIFICATION AND THE ETHICAL APPROACH
Our view is that for studies in epidemiology to be deemed ethical, they must not only be judged as such for those people actually studied but also for those in the wider population for whom the results have a (potential) impact. This implies that for an epidemiological study to be ethical it must encompass the principles of autonomy, bene®cence, nonmale®cence and justice for both the study participants and the relevant wider population. One of the most important epidemiological activities, particularly at the local and national health department level, is analysing patterns of health and disease in populations. The process of classi®cation of populations being studied into the groups of interest (e.g. age and sex, ethnic group) forms a major part of such analysis. Generally, categories are chosen by epidemiologists and usually re¯ect, in some part, the interests, values and concerns of the community. Classi®cation also occurs in other forms of epidemiological studies where epidemiologists allocate cases to categories based on ``risk fac-
DO THE CLASSIFICATIONS CHOSEN GENUINELY REPRESENT THE RISK FACTOR OF INTEREST?
In many instances in developed countries the risk factors for HIV are published as homosexual, bisexual, heterosexual, intravenous drug use, receipt of contaminated blood products or some similar classi®cation (Ancelle-Park et al., 1990; Dore et al., 1996; Nador et al., 1996; Raman et al., 1996). The categories were chosen initially because the risk factors for AIDS were unknown. AIDS was ®rst described in a group of young men who were homosexual and in the urgent search for the cause, classi®cations of homosexual, bisexual and heterosexual were appropriate. The groupings chosen for HIV/AIDS predominantly centre on sexual orientation rather than sexual behaviour. For instance a person with a bisexual orientation may never act on those inclinations. Such a person is at very low risk of HIV (given the fact that other means of contracting the virus are remote, e.g. the blood supply is safe). The
Death by proxy
real risk of contracting HIV via sexual activity depends on several factors. These include the frequency of sexual intercourse; the probability that any particular episode of intercourse will be with a person who is infectious and whether the risk was modi®ed in any way, such as through condom use. With time, a clearer de®nition of the ``at-risk'' sexual behaviour became more widely used (e.g. men who have sex with men) but, despite this, some statistics tend still to be published in the original risk categories, although in some instances the reported categories have been modi®ed (Ancelle-Park et al., 1990; Anonymous, 1996). We recognise that those reporting the data usually understand the implications of their data. We remain concerned to ensure however that the reporting be as clearly understood by the reader. The other major category used to explain risk for HIV/AIDS is intravenous drug use. The real factor here is not the intravenous use per se but the sharing of (frequently contaminated) needles. Of course, the use of intravenous drugs may be associated with needle sharing for some people and at some times, but it is not a universal habit and hence not a universal risk among intravenous drug users. In Australia, published data often identify Aboriginality as a ``risk factor'' for poor health and early death. Newspapers and television use headlines such as ``Australian Aboriginal women 10 times more likely to die in childbirth, 10 times more likely to be murdered''. Do we believe that Aboriginality is the risk factor of interest? The answer to this question is clearly no. We do not expect the Aboriginal medical student to die in childbirth, or to be at particular risk of homicide. We recognise that there are other factors which may be associated in some way with Aboriginality such as poor access to health services, cultural identity, which are more important than the classi®cation of Aboriginal. Of course, some component of risk may be speci®cally related to being Aboriginal. For instance all Aboriginal people have been aected by European settlement and this (probably) has ¯ow-on eects on health although obtaining scienti®c evidence to prove this is dicult. Regardless, much of the dierential between Aboriginal and non-Aboriginal health can be explained by other, already known risk factors which are not a direct function of Aboriginality. This has been demonstrated in one study in which about half of the variation in childhood hospitalisation rates for diarrhoea between Aboriginal communities was shown to be due to environmental conditions such as sanitation, water supply and the eects of overcrowding (Munoz et al., 1992). Over time the fact that risk factors are not a proxy for a population sub-group has been better recognised and arguments made that there is a more scienti®cally valid way of presenting such information (Coughlin, 1996). At the same time as
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recognising the real risk factors that lie behind the label of ``Aboriginality'', it is essential that we do not permit alternative explanations to hide the very real dierential in health experienced by Aborigines, that aects virtually every cause of Aboriginal mortality and morbidity (Plant et al., 1995). The diculty that public health experiences with the biological concept of race has been described by others (Cooper and David, 1986). As well, some studies have highlighted where much of the apparent risk due to race disappears when economic circumstances are included in the analysis (Ansell et al., 1993). In a similar way, marital status is likely to be a re¯ection of many other factors in an individual's life that can in¯uence their health, not merely the possession of a marriage certi®cate. Again the question must be raised as to whether a married person in a situation without sucient resources for the physical essentials such as food and shelter will be more likely to have a better health outcome than an unmarried person who has adequate resources for living. The role of emotional security is also likely to have a health impact, although whether this is necessarily a function of marriage is far less clear. In all these examples there is some dissociation between the classi®cation and the ``real'' nature of the risk factor. The ``risk factor'' which is identi®ed and used is a ``proxy'' for the real risk. This is not to suggest that epidemiologists do not recognise the dierence between cause and risk but rather that the assumed risk, when distant from the real risk, is likely to have ethical implications. WHAT ARE THE IMPLICATIONS OF CLASSIFICATION FOR INDIVIDUALS ASSIGNED TO GROUPS?
The quantity and nature of the eects of ``labelling'' individuals at risk of an outcome because of their inclusion in a pre-determined group are largely unknown. Such labelling undoubtedly leads to some degree of stress and perhaps feelings of helplessness, if the outcome is perceived as undesirable. Such stress and helplessness have an eect on both physical and emotional health (Farhood et al., 1993; Levi, 1993). Imagine having a high risk of death assigned to you, regardless of whether the risk is real or not. We have good evidence that a placebo eect can work for recovery in many instances (Bienenfeld et al., 1996). Can a ``you are at an increased risk of death'' interpretation of health-related information work in a similar way, but in the opposite direction? A similar eect has been described in other diseases where the eect of personal attitude has been shown to in¯uence the ®nal outcome (Kure et al., 1991; Molassiotis et al., 1997). The very real concern is that classi®cation without good reason may needlessly ``rob'' individuals of their sense of health. Of course, even with real rather than proxy risk factors, people may be
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robbed of their sense of health as not all those with a particular risk factor experience the associated disease, e.g. not everyone with high blood pressure will experience stroke. People from indigenous groups frequently feel despair at the health statistics provided in formal settings, such as classrooms, and informal settings, such as casual conversation. At some level, to be part of a group that lives less long, can appear to be perceived as being less deserving of living. Moreover, the eect that the descriptions of the health risks associated with being unmarried has on the person who may already feel inadequate because of not being married is unknown. Nor is the eect of knowing the association of poorer health outcomes for unmarried men, even if the individual did not want to be married. The second implication of classi®cation in epidemiological analysis may be that if the assumed grouping does not accord with the individuals' perceptions of their role, they may not identify with any intervention which uses these (rejected) groupings. So, if an individual male identi®es himself as heterosexual but in fact is an active bisexual, he may not ``hear'' messages about AIDS prevention, safe-sex or bisexuality. As a result he may fail to make behavioural adjustments which he might otherwise have made with appropriately targeted messages which concentrated on the behaviour rather than the grouping (hence the developments of explicit description of behaviours and categories such as ``men-who-have-sex-with-men''). Along the same line of argument, a heterosexual female may not perceive herself to be at risk of HIV because of her sexual orientation when she may be at risk due to either the frequency of sexual encounters or, due to speci®c social reasons, the probability of encountering an infected individual. Moreover, the absence of an explicit description of the actual risk factor may lead an individual to feel that their risk is not modi®able (``I am Aboriginal; therefore I have an increased risk of heart disease; therefore there is no point in worrying about the blood pressure problem I have; it won't make any dierence''). Alternatively, given that they already have the label, it is not worth doing anything about the risk (``I am a drug user; therefore, everyone knows I am at risk of AIDS; why bother about clean needles''). Certainly some literature suggests that increasing awareness of risk may actually increase risk behaviour (Robles et al., 1995). Lastly, the individual or group may suer discrimination because of putative risk. For example, a person may be denied housing or employment because they are part of a group with a higher proportion of the risk factor, e.g. homosexual men being denied employment because they might have HIV.
WHAT ARE THE IMPLICATIONS OF CLASSIFICATIONS FOR POPULATIONS?
The eects of classi®cation within observational epidemiological studies can lead to a range of ¯owon eects on society. The ®rst and perhaps the most important is the implicit classi®cation of ``other'' groups which in turn lessens the apparent responsibility of (usually) the majority of the population. This can lead to an unwitting change of attitude to the aected group. The following scenario outlines such a circumstance: ``Indigenous people (such as Australian Aboriginal, Native American, Inuit, Maori) have an increased risk of diarrhoea....Aborigines ...nothing anyone can do about that, they always have increased risks of sickness''. The alternative approach could be ``increased risk of diarrhoea... who? people with no running water or sewage system... well who wouldn't be at risk of diarrhoea, there is a need for action, no group should be without running water or adequate sewage disposal''. The identi®cation then naming of the perceived (i.e. indigenous) risk factor instead of the real risk (sewage and water issues, socio-economic issues) permits and enhances stigmatisation and thus avoids the real issue and the appropriate solution. Similarly, discussion of the risk of infectious disease in the context of drug use instead of in that of needle sharing, permits society, all too often, to focus on the issues that are insoluble or extremely dicult such as controlling illicit drugs. In turn this hinders debate about those issues that are not only the real risk factors for infectious diseases, but which may actually have solutions, e.g. providing needles and syringes. By classifying marital status as a risk factor it seems likely that we have again used a proxy for something society may be able to address. No-one seriously suggests longer life can be attained by arranging marriages for unmarried people. Perhaps if we tried harder to determine the real risk factors which may well be feeling secure in our society, or feeling supported in daily existence, then we could better identify interventions that might make a dierence. It is dicult to escape the conclusion that epidemiology, by failing to categorise the risk factors into appropriate classi®cations, permits society to have an attitude, at some level, that the group in question ``deserves'' the poor outcome. The other likely eect of classi®cation that does not truly address the real risk factors is that there is potential for spending scarce resources where they may not lead to optimum health bene®t. For example, although there have been many attempts at improving the health status of Aboriginal people through provision of direct health services, the expenditure has resulted in minimal health gains. Rather it appears that money needs to be spent on providing
Death by proxy
other services such as education, better housing, improving access to fresh water, improving sewerage systems, etc. WHAT ARE THE IMPLICATIONS FOR EPIDEMIOLOGICAL PRACTICE?
Epidemiology, as described at the start of this paper, seeks to describe accurately the distribution and determinants of health and illness in populations and in so doing inform public health action to improve health. Central to this activity is the accuracy of the description of population health. We are obviously limited by the data that are available. We do, however, have a responsibility to interpret data for politicians, administrators and the public. Those who may or may not be at a disadvantage deserve better description of the nature of their situation rather than current approaches. Despite the obvious limitations of much classi®cation, it is dicult to manage population health statistics without such manipulation. Indeed, if no breakdowns were given and totals only were used, this would mask health inequalities even more and miss vital opportunities for disadvantaged groups to have improved health and better access to health care. Another major advantage of classi®cation from an epidemiological perspective is that continuation of the classi®cations over time permits better interpretation of trend data. Moreover epidemiological studies amass large datasets containing numerous items of information. If public health change is to occur, classi®cation is an essential part of the analysis and interpretation of categorical (non-numerical) data. From a public health perspective it could be argued that the use of proxy classi®cations permits targeting of scarce health resources. This is certainly true, it is far better that AIDS education be directed towards homosexual men rather than towards elderly women who have a low risk of AIDS and, hence, better value can be obtained for the resources invested. It could, however, just as readily be argued that directing the resources to the real risk instead of the proxy risk would be an even better use of resources and that as such it represents a more ethical approach. If, as epidemiologists we do not classify risk factors correctly, there is a danger of being less relevant to our audience, or even of failing by providing the wrong advice. We risk failing in our mission, that of improving public health. WHAT ARE THE ETHICAL ISSUES OF CLASSIFICATION IN EPIDEMIOLOGY?
We will now consider the ethical issues of classi®cation in epidemiology using the four concepts of autonomy, bene®cence, non-male®cence and justice. Most of the examples we have used relate to justice and to a lesser extent autonomy. Any study or
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analysis, however, that is weak on these two concepts will inevitably result in public health actions which have inadequate levels of bene®cence and non-male®cence. Autonomy (previously described as that which requires of professionals a respect for individual rights and freedoms) is usually not a problem within a particular study as individual rights are protected via the ethics committees that oversee research. However, maintenance of autonomy becomes more problematic when considering the implications of a study for the wider community. Some of the examples given above include the eect on feelings of well-being and the potential for people to have their rights aected merely by being placed in a proxy risk factor group. Bene®cence (previously explained as that which requires that professionals do good) again is usually adequately dealt with in the context of the study but the nature of epidemiology implies that we must ful®l this obligation to the wider community, not merely those in the studied group. There is clearly an obligation for epidemiologists to ensure that the wider community bene®ts from epidemiological ®ndings. As knowledge develops, as it has in many areas such as HIV, and the real risk factors become clearer, there is a need to change our classi®cations in ways which facilitate improved health for the wider community. By inappropriate classi®cation of individuals we may fail to ``do good'' to those in need, inadvertently fail to encourage society to face the real issues that may improve health or even to spend money unwisely, all of which may have been improved by considering an ethical approach. The implications of non-male®cence (previously explained as that which requires of professionals that they do no harm) are much less clear than those of bene®cence. Nevertheless when we classify incorrectly we potentially do harm to both individuals and society. This may involve individuals who feel harmed, individuals who have not bene®tted from epidemiology whether in a study or not and the negative eects on society. From a societal perspective, perhaps the greatest harm is that inappropriate classi®cation may lead to inappropriate solutions. From an individual perspective the harm that results from inappropriate classi®cation is likely to be the feeling of helplessness or the nonmodi®ability of the risk factor. Considerations of justice (previously explained as that which requires of professionals a fair and equitable allocation of resources without discrimination), especially issues concerning social justice, are critical ethical issues for epidemiology. Epidemiological studies have great potential for in¯uencing where resources are directed, and if this advice is based on classi®cations that do not represent the real risks, then potential bene®ts are reduced and the meeting of the real need is denied.
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Further, if epidemiologists utilise scarce health resources, yet fail to provide correct advice, then this must constitute unethical behaviour, even if not intentionally so. The issues of equity cannot be ignored by epidemiologists. CONCLUSION
Epidemiological practice always interacts with ethical considerations. Epidemiologists recognise this most readily in regard to obtaining institutional ethics committee approval before conducting a particular study. The ethical implications of other types of epidemiological practice, such as analysing population statistics, are just as important. Classi®cation is an essential element of epidemiological analysis but, as we have demonstrated, can negatively impact on individuals, society and the provision of health services. Recognising the implications of such classi®cation is a necessary ®rst step to improving the situation. Changing the system of classi®cation to re¯ect the ``real'' risk more accurately, such is occurring in some areas such as HIV, is vital. Moreover, there is a need to encourage the evolution of datasets (such as population statistics) which re¯ect these risk factors. Classi®cation is fundamental to epidemiological analysis. We are not arguing ``don't classify'' nor even that is necessary to change classi®cations, but rather that there is a need to recognise when we are dealing in proxies rather than the real risk factor. Considerations of justice alone demand appraisal of the real risk factors and this demand has potential eects on the principles of autonomy, bene®cence and non-male®cence. Inherent in conducting epidemiological research is the demand for public health and clinical action, making it imperative that epidemiologists consider the ethical consequences of their work. There are a number of actions that can be taken to lessen the negative impact of classi®cation on ethical epidemiological practice. First, be aware that the problem exists. Although epidemiologists may be aware of the nature and limitations of the classi®cations they choose, those reading and acting upon the data may not be. Second, put caveats on the interpretation of the analysis so that the information can be interpreted accurately. This should include not merely spelling this out in the discussion of a paper but including sucient information in the abstract, which is where many decision-makers obtain their information, especially since abstracts are much more frequently available electronically than is the full text. An example of this could be ``the risk factors identi®ed were homosexuality (proxy for men-who-have-sex-with-men)''. Third, be prepared to change the classi®cation and analysis when things become clearer. This has already occurred in some statistics about HIV, e.g. ``homosexual'' is less frequently used now as a risk factor
than in the earlier years of the epidemic but ``intravenous drug use'' is nearly always used. Fourth, undertake studies to determine the real risk. An example of this has already been quoted where a commonly used proxy (race) became less important in predicting survival from breast cancer once economic status was included in the analysis (Ansell et al., 1993). Lastly, ensure that even when we have to measure these proxies we make our public health action centre on real risk. In the meantime it is essential that epidemiologists are aware of potential problems that may unwittingly derive from their classi®cation choices and that eorts are made to ensure that public health action and ethics are not compromised. REFERENCES
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1979±1991. Northern Territory Department of Health and Community Services, Darwin. Raman, S., Menzies, R., McDonald, A., Grigges, E. and Levy, M. (1996) Validation of reported risk exposure in persons with newly diagnosed HIV infection. Comm. Dis. Intell. 20(1), 2±5. Robles, R., Cancel, L., Colon, H., Matos, T., Freeman, D. and Sahai, H. (1995) Prospective eects of perceived risk of developing HIV/AIDS on risk behaviors among injection drug users in Puerto Rico. Addiction 90(8), 1105±1111. Soskolne, C. (1989) Epidemiology: questions of science, ethics, morality and law. American Journal of Epidemiology 129(1), 1±18.