American Journal of Bioethics
The Evidence Suggests We Should Care About Social Inequalities in Health David H. Rehkopf, Stanford University Laust H. Mortensen, University of Copenhagen Despite the title of the article by Preda and Voigt (2015), our view is that the article does not present a critique of why we should care about social factors affecting health. It is also not about a field of study, or a critique of a model, or a critique of a body of research. What the authors are criticizing is a position on social inequalities in health purportedly taken in a series of commissioned reports, including several chaired by Michael Marmot. The authors summarize this position as “health equity through social change” (HESC), but this model is the authors’ own construction, which limits the reach of the author’s critique, particularly the aspects directed at the assumptions about justice. The authors focus primarily on critiquing two aspects of the HESC model: the normative argument for action to reduce social inequalities in health and the policy recommendations proposed to achieve this. The article touches upon numerous issues worthy of discussion, but it is impossible to exhaustively cover them all here. In this peer commentary, we describe how social determinants of health research relates to social inequalities in health research. We then discuss the role of empirical evidence, which prompts us to question the authors’ conclusion regarding the evidence for both the justification for reducing social inequalities in health and the work to address social determinants of health. We also note that the authors attempt to critique the evidence for social determinants of health, but not for individual autonomous decisions to impact health, and we believe that more useful conclusions can be drawn if evidence for each is considered in a more balanced manner. Study of the social determinants of health and study of the causes of social inequalities in health are two diverse fields that are producing useful empirical work that generally has the goal of improving health. Varying differentiations of social are used throughout these fields, and in the article, and it is important to realize the function of each for addressing their critiques of these fields. First, the social can be considered, as described in this article, as “the circumstances in which people are born, grow up, live, work and age, and the systems put in place to deal with illness. These circumstances are in turn shaped by a wider set of forces: economics, social policies, and politics” (World Health Organization [WHO] 2014). It is this definition of social, the broad, that is of relevance for
determining whether social inequalities are unjust. In contrast, when discussing specific definitions of the social, for example, a particular measure of socioeconomic position, the causal effects of that factor must be demonstrated through a balance of evidence in order to justify action on that factor to improve health. That is, if the broad definition is used, then it is reasonable to assume that everything has social causes, but this is not true in if the narrow definition is used. We discuss in the following both types of evidence, that which answers the broader, more fundamental question about the extent to which environmental, genetic, and stochastic processes each contribute to social inequalities in health, and second, whether specific interventions on social determinants of health are warranted. The authors take issue with the possibility of studying social and economic causes, and based on this assume that causation is not knowable in this field. This then sets up their central argument that knowing that health inequalities are not determined by individual free will is apparently impossible. We disagree. First, however, let us be clear that certainty of causation never exists in the physical and social sciences, whether these are studying factors that are amenable to randomization or not. In the empirical sciences, certainty of causation is a spectrum, not a two-category entity. The evidence for social causation will almost always have to be balanced against other causal mechanisms producing social inequalities in health: effects of health on social factors and confounding from common causes of health and social factors. In addition, causal effects may be highly contingent on the presence (or absence) of other causal components, which means that there is uncertainty about what the causal effect will be under difference circumstances. Thus, it is more useful, if perhaps less satisfying, to think about a spectrum of studies that are of use for studying social causes, and the collective balance of evidence. In the social sciences, social causation becomes understandable through a triangulation of evidence across observational studies, quasi-experimental studies, and experimental studies. In the natural sciences the field of physics and in social sciences the field of economics have succeeded in producing useful knowledge without randomized trials, so we should not give up on this in health. In fact, there is rapidly expanding development in coming to clearer conclusions about causation
Address correspondence to David Rehkopf, Stanford University, 1265 Welch Road, Stanford, CA 94305, USA. E-mail: [email protected]
56 ajob
March, Volume 15, Number 3, 2015
Caring About Social Determinants of Health
while working with observational data (Van der Laan and Rose 2011). Another particularly useful approach has been through quasi-experimental methods of analysis, where researchers on the social determinants of health and health inequalities have borrowed tools from econometrics. Much of this work has been on the examination of the effects of social policies. For example, the introduction of the earned income tax credit in states is associated with decreases in maternal smoking and decreases in low birth weight (Strully, Rehkopf, and Xuan 2010). Receiving income from tax refunds targeted at low-wage workers is associated with a number of short-term improvements in healthrelated risk factors (Rehkopf, Strully, and Dow 2014). Such studies are examples of potential importance for informing policy recommendations such as those suggested by Marmot and colleagues. Quasi-experimental studies also address a popular myth about social determinants of health—that it is not politically feasible to address them. Social determinants of health are actively being changed every single day, and analyses examining public policies make that point clearly. In addition, contrary to what is asserted by the authors, there actually are ways that experimentation can be used for studying the importance of social causes in social inequalities in health. To give one example, work conducted as a random experiment created fictional vignettes of patients with acute coronary syndrome who had identical characteristics but were black or white (Green et al. 2007). Not only did this study find that blacks were given less appropriate treatment, but it also found that while there was no difference in self-reported attitudes toward blacks and whites, physicians who scored higher on an implicit bias test were the ones who suggested less efficacious treatments for blacks. Finally, for the concerns of the unjust nature of social inequalities in health, descriptive evidence comparing health inequalities across time and place is informative. These studies strongly suggest that social inequalities differ dramatically by place and time, are very small in some countries (Rosero-Bixby and Dow 2009), and have varied in the United States over recent decades (Krieger et al. 2008). The context-contingent variability of social inequalities does not give us specific recommendations for exactly how social determinants causally affect health, but they are strong evidence for the fact that social inequalities in health vary depending on social environment. The authors appear to be quite unbalanced in trying to assess the contribution of social factors versus individual autonomous trade-offs to contribute to social inequalities in health—they do not attempt to assess the evidence for the latter, only critique the former. It is also important to ask: What is the evidence for decisions being the work of autonomous actors, versus those actors being influenced by social and economic structures? In essence, there are just three broad categories that can contribute to health differences: environmental, genetic, and stochastic. It is impossible that stochastic ones produce social differences. So what, then, is the evidence for the
March, Volume 15, Number 3, 2015
genetic? To give one example, a large consortium study of more than 100,000 individuals identified that ~2% of the variance in educational attainment is related to genetics (Rietveld et al. 2013). By this standard of the biological inevitability of one of the commonly discussed social determinants of health, we would conclude that most of what determines this factor is due to the environment. We agree with the authors that addressing social inequalities in health should not be addressed only through addressing inequalities in social determinants of health. It is a myth that there is a general trade-off between efficacy and equity in public health interventions; this depends entirely on the intervention. General social policy can act to improve overall population health and also reduce inequalities (Harper et al. 2014). Action to address disparities in the role of medical care is also critical. Our point of disagreement is that we believe it is vital not to confuse the evidence for the importance of social environment versus autonomous action for producing social inequalities in health with evidence for specific interventions on social determinants of health. As researchers in this field, we also see work on the latter as having enough promise that efforts to understand effective interventions and policy changes related to social determinants of health should continue. &
REFERENCES Green, A. R., D. R. Carney, D. J. Pallin, et al. 2007. Implicit bias among physicians and its prediction of thrombolysis decisions for black and white patients. Journal of General Internal Medicine 22(9): 1231–1238. Available at: http://dx.doi.org/10.1007/s11606-0070258-5 Harper, S., E. C. Strumpf, S. Burris, G. D. Smith, and J. Lynch. 2014. The effect of mandatory seat belt laws on seat belt use by socioeconomic position. Journal of Policy Analysis and Management 33(1): 141–161. Available at: http://dx.doi.org/10.1002/ pam.21735 Krieger, N., D. H. Rehkopf, J. T. Chen, et al. 2008. The fall and rise of US inequities in premature mortality: 1960–2002. PLoS Medicine 5(2): e46. Epub 2008/02/29. doi: 07-PLME-RA-0909 [pii] 10.1371/ journal.pmed.0050046. PubMed PMID: 18303941; PubMed Central PMCID: PMC2253609. Available at: http://dx.doi.org/10.1371/ journal.pmed.0050046 Preda, A., and K. Voigt. 2015. The social determinants of health: Why should we care? American Journal of Bioethics 15(3): 25–36. Rehkopf, D. H., K. W. Strully, and W. H. Dow. 2014. The shortterm impacts of Earned Income Tax Credit disbursement on health. International Journal of Epidemiology 43(6): 1884–1894. doi: 10.1093/ije/dyu172 Rietveld, C. A., S. E. Medland, J. Derringer, et al. 2013. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340(6139): 1467–1471. Available at: http://dx.doi.org/10.1126/science.1235488 Rosero-Bixby, L., and W. H. Dow. 2009. Surprising SES gradients in mortality, health, and biomarkers in a Latin American
ajob 57
American Journal of Bioethics
population of adults. Journals of Gerontology Series B: Psychological Sciences and Social Sciences 64(1): 105–117. Strully, K. W., D. H. Rehkopf, and Z. Xuan. 2010. Effects of prenatal poverty on infant health: State earned income tax credits and birth weight. American Sociological Review 75: 534–562. Available at: http://dx.doi.org/10.1177/0003122410374086
Van der Laan, M. J., and S. Rose. 2011. Targeted learning: Causal inference for observational and experimental data. New York, NY: Springer. World Health Organization. 2014. Review of social determinants and the health divide in the WHO European Region: Final report. Copenhagen, Denmark: WHO Regional Office for Europe.
The Naturalistic Fallacy in Ethical Discourse on the Social Determinants of Health Daniel Goldberg, East Carolina University In this commentary, I respond to Preda and Voigt (2015) by arguing that the problems in the literature regarding ethics and the social determinants of health center on the commonality of the naturalistic fallacy in public health and social epidemiologic discourse. The commentary argues that public health stakeholders and prominent public intellectuals often move “just so” from empirical analysis of the state of health inequalities to conclusions regarding ethical implications and policy considerations. Many of the problems Voigt and Preda correctly identify could be ameliorated with greater attention to the complex and nonobvious steps in the normative arguments needed to move from natural epidemiologic facts to ethical and policy recommendations. The commentary goes on to note the existence of ethical theories in population health contexts that—as the authors seem to recommend—expressly reject health exceptionalism. The response concludes with some criticism of the authors’ argument that practical difficulties in implementing needed policy changes necessarily cast doubt on their normative foundations (even if those foundations are poorly articulated by proponents of said policies). Preda and Voigt’s needed corrective regarding deficiencies in normative discourse surrounding the social determinants of health (SDOH) should be situated in a larger body of work critiquing the concept of health equity (e.g., Wilson 2011; Kelleher 2014). Sridhar Venkatapuram (2011, 175), for example, argues that the health equity approach suffers from a number of conceptual weaknesses, including but not limited to vagueness in regarding the “scope and target of moral action” (e.g., relative or absolute health differences? which causes? which consequences? which possibilities for mitigation?). There is a very real danger that the concept of health equity, and arguably its parent (cousin?) concept of “social
justice,” may be reduced to empty slogans for public health stakeholders endorsing particular changes in structural social and economic conditions. Griffin Trotter (2008, 452) criticizes the tendency to presume that the meaning of such fraught terms “is already settled and generally known.” Calling out academic public health in particular for this failing, Trotter argues that the concept of social justice is “cited to justify simpleminded dogmas about ‘eliminating health disparities,’ . . . yet virtually never characterized in its theoretical details or acknowledged in its multiplicity of competing and incompatible forms” (Trotter 2008, 452). Yet of course the difficulties that Preda and Voigt correctly illuminate do not necessarily mean that the concepts of health equity or social justice should be abandoned. While significant legwork must be done to develop a normatively robust account of health equity, ethically sophisticated accounts of social justice (Powers and Faden 2006) in population health policy do exist and are at the center of a vibrant conversation in public health ethics/populationlevel bioethics. Common to any normatively plausible exposition of the social determinants of health is avoidance of the naturalistic fallacy. That is, ethical analysis of the evidence regarding the social determinants of health perforce begins by examination of that evidence. Policy and ethical discourse on the SDOH cannot proceed without a sufficient understanding of the social epidemiologic evidence base that animates scholarship, practice, and policy on the SDOH. But to derive normative conclusions from this major (empirical) premise requires a host of normative moves that, as Preda and Voigt (2015) correctly point out, are neither facile nor uncomplicated. And this is where so much of what passes for normative recommendations in SDOH policy discourse fails: It moves directly from
Address correspondence to Daniel Goldberg, Bioethics & Interdisciplinary Studies, East Carolina University, 600 Moye Blvd, Mailstop 641, Greenville, NC 27834, USA. E-mail: [email protected]
58 ajob
March, Volume 15, Number 3, 2015
Copyright of American Journal of Bioethics is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
The Evidence Suggests We Should Care About Social Inequalities in Health David H. Rehkopf, Stanford University Laust H. Mortensen, University of Copenhagen Despite the title of the article by Preda and Voigt (2015), our view is that the article does not present a critique of why we should care about social factors affecting health. It is also not about a field of study, or a critique of a model, or a critique of a body of research. What the authors are criticizing is a position on social inequalities in health purportedly taken in a series of commissioned reports, including several chaired by Michael Marmot. The authors summarize this position as “health equity through social change” (HESC), but this model is the authors’ own construction, which limits the reach of the author’s critique, particularly the aspects directed at the assumptions about justice. The authors focus primarily on critiquing two aspects of the HESC model: the normative argument for action to reduce social inequalities in health and the policy recommendations proposed to achieve this. The article touches upon numerous issues worthy of discussion, but it is impossible to exhaustively cover them all here. In this peer commentary, we describe how social determinants of health research relates to social inequalities in health research. We then discuss the role of empirical evidence, which prompts us to question the authors’ conclusion regarding the evidence for both the justification for reducing social inequalities in health and the work to address social determinants of health. We also note that the authors attempt to critique the evidence for social determinants of health, but not for individual autonomous decisions to impact health, and we believe that more useful conclusions can be drawn if evidence for each is considered in a more balanced manner. Study of the social determinants of health and study of the causes of social inequalities in health are two diverse fields that are producing useful empirical work that generally has the goal of improving health. Varying differentiations of social are used throughout these fields, and in the article, and it is important to realize the function of each for addressing their critiques of these fields. First, the social can be considered, as described in this article, as “the circumstances in which people are born, grow up, live, work and age, and the systems put in place to deal with illness. These circumstances are in turn shaped by a wider set of forces: economics, social policies, and politics” (World Health Organization [WHO] 2014). It is this definition of social, the broad, that is of relevance for
determining whether social inequalities are unjust. In contrast, when discussing specific definitions of the social, for example, a particular measure of socioeconomic position, the causal effects of that factor must be demonstrated through a balance of evidence in order to justify action on that factor to improve health. That is, if the broad definition is used, then it is reasonable to assume that everything has social causes, but this is not true in if the narrow definition is used. We discuss in the following both types of evidence, that which answers the broader, more fundamental question about the extent to which environmental, genetic, and stochastic processes each contribute to social inequalities in health, and second, whether specific interventions on social determinants of health are warranted. The authors take issue with the possibility of studying social and economic causes, and based on this assume that causation is not knowable in this field. This then sets up their central argument that knowing that health inequalities are not determined by individual free will is apparently impossible. We disagree. First, however, let us be clear that certainty of causation never exists in the physical and social sciences, whether these are studying factors that are amenable to randomization or not. In the empirical sciences, certainty of causation is a spectrum, not a two-category entity. The evidence for social causation will almost always have to be balanced against other causal mechanisms producing social inequalities in health: effects of health on social factors and confounding from common causes of health and social factors. In addition, causal effects may be highly contingent on the presence (or absence) of other causal components, which means that there is uncertainty about what the causal effect will be under difference circumstances. Thus, it is more useful, if perhaps less satisfying, to think about a spectrum of studies that are of use for studying social causes, and the collective balance of evidence. In the social sciences, social causation becomes understandable through a triangulation of evidence across observational studies, quasi-experimental studies, and experimental studies. In the natural sciences the field of physics and in social sciences the field of economics have succeeded in producing useful knowledge without randomized trials, so we should not give up on this in health. In fact, there is rapidly expanding development in coming to clearer conclusions about causation
Address correspondence to David Rehkopf, Stanford University, 1265 Welch Road, Stanford, CA 94305, USA. E-mail: [email protected]
56 ajob
March, Volume 15, Number 3, 2015
Caring About Social Determinants of Health
while working with observational data (Van der Laan and Rose 2011). Another particularly useful approach has been through quasi-experimental methods of analysis, where researchers on the social determinants of health and health inequalities have borrowed tools from econometrics. Much of this work has been on the examination of the effects of social policies. For example, the introduction of the earned income tax credit in states is associated with decreases in maternal smoking and decreases in low birth weight (Strully, Rehkopf, and Xuan 2010). Receiving income from tax refunds targeted at low-wage workers is associated with a number of short-term improvements in healthrelated risk factors (Rehkopf, Strully, and Dow 2014). Such studies are examples of potential importance for informing policy recommendations such as those suggested by Marmot and colleagues. Quasi-experimental studies also address a popular myth about social determinants of health—that it is not politically feasible to address them. Social determinants of health are actively being changed every single day, and analyses examining public policies make that point clearly. In addition, contrary to what is asserted by the authors, there actually are ways that experimentation can be used for studying the importance of social causes in social inequalities in health. To give one example, work conducted as a random experiment created fictional vignettes of patients with acute coronary syndrome who had identical characteristics but were black or white (Green et al. 2007). Not only did this study find that blacks were given less appropriate treatment, but it also found that while there was no difference in self-reported attitudes toward blacks and whites, physicians who scored higher on an implicit bias test were the ones who suggested less efficacious treatments for blacks. Finally, for the concerns of the unjust nature of social inequalities in health, descriptive evidence comparing health inequalities across time and place is informative. These studies strongly suggest that social inequalities differ dramatically by place and time, are very small in some countries (Rosero-Bixby and Dow 2009), and have varied in the United States over recent decades (Krieger et al. 2008). The context-contingent variability of social inequalities does not give us specific recommendations for exactly how social determinants causally affect health, but they are strong evidence for the fact that social inequalities in health vary depending on social environment. The authors appear to be quite unbalanced in trying to assess the contribution of social factors versus individual autonomous trade-offs to contribute to social inequalities in health—they do not attempt to assess the evidence for the latter, only critique the former. It is also important to ask: What is the evidence for decisions being the work of autonomous actors, versus those actors being influenced by social and economic structures? In essence, there are just three broad categories that can contribute to health differences: environmental, genetic, and stochastic. It is impossible that stochastic ones produce social differences. So what, then, is the evidence for the
March, Volume 15, Number 3, 2015
genetic? To give one example, a large consortium study of more than 100,000 individuals identified that ~2% of the variance in educational attainment is related to genetics (Rietveld et al. 2013). By this standard of the biological inevitability of one of the commonly discussed social determinants of health, we would conclude that most of what determines this factor is due to the environment. We agree with the authors that addressing social inequalities in health should not be addressed only through addressing inequalities in social determinants of health. It is a myth that there is a general trade-off between efficacy and equity in public health interventions; this depends entirely on the intervention. General social policy can act to improve overall population health and also reduce inequalities (Harper et al. 2014). Action to address disparities in the role of medical care is also critical. Our point of disagreement is that we believe it is vital not to confuse the evidence for the importance of social environment versus autonomous action for producing social inequalities in health with evidence for specific interventions on social determinants of health. As researchers in this field, we also see work on the latter as having enough promise that efforts to understand effective interventions and policy changes related to social determinants of health should continue. &
REFERENCES Green, A. R., D. R. Carney, D. J. Pallin, et al. 2007. Implicit bias among physicians and its prediction of thrombolysis decisions for black and white patients. Journal of General Internal Medicine 22(9): 1231–1238. Available at: http://dx.doi.org/10.1007/s11606-0070258-5 Harper, S., E. C. Strumpf, S. Burris, G. D. Smith, and J. Lynch. 2014. The effect of mandatory seat belt laws on seat belt use by socioeconomic position. Journal of Policy Analysis and Management 33(1): 141–161. Available at: http://dx.doi.org/10.1002/ pam.21735 Krieger, N., D. H. Rehkopf, J. T. Chen, et al. 2008. The fall and rise of US inequities in premature mortality: 1960–2002. PLoS Medicine 5(2): e46. Epub 2008/02/29. doi: 07-PLME-RA-0909 [pii] 10.1371/ journal.pmed.0050046. PubMed PMID: 18303941; PubMed Central PMCID: PMC2253609. Available at: http://dx.doi.org/10.1371/ journal.pmed.0050046 Preda, A., and K. Voigt. 2015. The social determinants of health: Why should we care? American Journal of Bioethics 15(3): 25–36. Rehkopf, D. H., K. W. Strully, and W. H. Dow. 2014. The shortterm impacts of Earned Income Tax Credit disbursement on health. International Journal of Epidemiology 43(6): 1884–1894. doi: 10.1093/ije/dyu172 Rietveld, C. A., S. E. Medland, J. Derringer, et al. 2013. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340(6139): 1467–1471. Available at: http://dx.doi.org/10.1126/science.1235488 Rosero-Bixby, L., and W. H. Dow. 2009. Surprising SES gradients in mortality, health, and biomarkers in a Latin American
ajob 57
American Journal of Bioethics
population of adults. Journals of Gerontology Series B: Psychological Sciences and Social Sciences 64(1): 105–117. Strully, K. W., D. H. Rehkopf, and Z. Xuan. 2010. Effects of prenatal poverty on infant health: State earned income tax credits and birth weight. American Sociological Review 75: 534–562. Available at: http://dx.doi.org/10.1177/0003122410374086
Van der Laan, M. J., and S. Rose. 2011. Targeted learning: Causal inference for observational and experimental data. New York, NY: Springer. World Health Organization. 2014. Review of social determinants and the health divide in the WHO European Region: Final report. Copenhagen, Denmark: WHO Regional Office for Europe.
The Naturalistic Fallacy in Ethical Discourse on the Social Determinants of Health Daniel Goldberg, East Carolina University In this commentary, I respond to Preda and Voigt (2015) by arguing that the problems in the literature regarding ethics and the social determinants of health center on the commonality of the naturalistic fallacy in public health and social epidemiologic discourse. The commentary argues that public health stakeholders and prominent public intellectuals often move “just so” from empirical analysis of the state of health inequalities to conclusions regarding ethical implications and policy considerations. Many of the problems Voigt and Preda correctly identify could be ameliorated with greater attention to the complex and nonobvious steps in the normative arguments needed to move from natural epidemiologic facts to ethical and policy recommendations. The commentary goes on to note the existence of ethical theories in population health contexts that—as the authors seem to recommend—expressly reject health exceptionalism. The response concludes with some criticism of the authors’ argument that practical difficulties in implementing needed policy changes necessarily cast doubt on their normative foundations (even if those foundations are poorly articulated by proponents of said policies). Preda and Voigt’s needed corrective regarding deficiencies in normative discourse surrounding the social determinants of health (SDOH) should be situated in a larger body of work critiquing the concept of health equity (e.g., Wilson 2011; Kelleher 2014). Sridhar Venkatapuram (2011, 175), for example, argues that the health equity approach suffers from a number of conceptual weaknesses, including but not limited to vagueness in regarding the “scope and target of moral action” (e.g., relative or absolute health differences? which causes? which consequences? which possibilities for mitigation?). There is a very real danger that the concept of health equity, and arguably its parent (cousin?) concept of “social
justice,” may be reduced to empty slogans for public health stakeholders endorsing particular changes in structural social and economic conditions. Griffin Trotter (2008, 452) criticizes the tendency to presume that the meaning of such fraught terms “is already settled and generally known.” Calling out academic public health in particular for this failing, Trotter argues that the concept of social justice is “cited to justify simpleminded dogmas about ‘eliminating health disparities,’ . . . yet virtually never characterized in its theoretical details or acknowledged in its multiplicity of competing and incompatible forms” (Trotter 2008, 452). Yet of course the difficulties that Preda and Voigt correctly illuminate do not necessarily mean that the concepts of health equity or social justice should be abandoned. While significant legwork must be done to develop a normatively robust account of health equity, ethically sophisticated accounts of social justice (Powers and Faden 2006) in population health policy do exist and are at the center of a vibrant conversation in public health ethics/populationlevel bioethics. Common to any normatively plausible exposition of the social determinants of health is avoidance of the naturalistic fallacy. That is, ethical analysis of the evidence regarding the social determinants of health perforce begins by examination of that evidence. Policy and ethical discourse on the SDOH cannot proceed without a sufficient understanding of the social epidemiologic evidence base that animates scholarship, practice, and policy on the SDOH. But to derive normative conclusions from this major (empirical) premise requires a host of normative moves that, as Preda and Voigt (2015) correctly point out, are neither facile nor uncomplicated. And this is where so much of what passes for normative recommendations in SDOH policy discourse fails: It moves directly from
Address correspondence to Daniel Goldberg, Bioethics & Interdisciplinary Studies, East Carolina University, 600 Moye Blvd, Mailstop 641, Greenville, NC 27834, USA. E-mail: [email protected]
58 ajob
March, Volume 15, Number 3, 2015
Copyright of American Journal of Bioethics is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
