POVERTY & HEALTH: Commentary
Why Epidemiologists Cannot Afford to Ignore Poverty
From the Department of Society, Human Development and Health, Harvard School of Public Health, Boston, Massachusetts.
Correspondence: Nancy Krieger, Department of Society, Human Development and Health, Kresge 717, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115. E-mail: email@example.com.
Epidemiologists cannot afford to ignore poverty. To do so would, first, wrongly obscure the devastating impact of poverty on population health, and, second, undercut our commitment to scientific rigor. At issue is doing correct science, not “politically correct” science. Blot poverty and inequity from view, and not only will we contribute to making suffering invisible but our understanding of disease etiology and distribution will be marred. To make this case, I address current debates about the causal relationships between poverty and health, and provide examples of how failing to consider the impact of socioeconomic position has biased epidemiologic knowledge and harmed the public’s health. By definition, the people we study are simultaneously social beings and biologic organisms—and we cannot study the latter without taking into account the former. It is the responsibility of all epidemiologists, and not only social epidemiologists, to keep in mind the connections between poverty and health.
The topic of poverty is nothing new to epidemiology. Indeed, our field’s emergence as a scientific discipline in the early 19th century was intimately entangled with research on destitution, spurred by the global public health impact of that era’s massive transformations in ways of living and of dying.1–4 The Industrial Revolution and the unleashing of laissez-faire capitalism sparked the creation of a fast-growing impoverished urban working class, massive increases in international trade, and an expanding military presence in colonized countries and outposts across the 5 continents.1–4 Cities in Europe and the Americas swelled in size, as did their levels of squalor, stench, poverty, and disease.1–4 Cholera and yellow fever were brought to the “West” by army routes and commerce, including the slave trade. These devastating “emerging diseases” of the age were all the more dreadful because they were lethal maladies of unknown etiology and inexplicable onset.1–4 To these diseases and the other endemic causes of death, the poor disproportionately succumbed.1–4 Available jobs paid starvation wages and were dangerous; slum housing was unsafe, crowded, and without private plumbing; malnutrition and other comorbidities were rampant; and the poor could not afford to flee these conditions when pestilence struck.1–4 Through the urgent study of these problems, epidemiology, as a self-designated field of scientific study, was born.1
Epidemiology’s early focus on poverty was thus a necessity, not an option. But in this widely-trumpeted era of the human genome,5–7 what relevance does poverty have to epidemiology today?
One ready answer: in a world where 2 in 5 of our planet’s 6+ billion people lack sanitation and live on less than $2 a day (ie, “absolute poverty,” as defined by the World Bank), where 1 in 5 lack access to clean water and live in extreme poverty on less than $1 a day, and where less than 1% of the world’s adult population owns 40% of the world’s wealth while 50% owns less than 1%,8–10 documenting and analyzing links between impoverishment and population health remains a public health imperative. The magnitude of the problem is vividly portrayed in the maps of global inequities in poverty, wealth, and health shown in Figure 1.8
Second, even in the world’s wealthy countries—where most of the institutions that teach epidemiology are located—economic deprivation remains strongly associated with morbidity and mortality.11–18 For example, I live in Boston, Massachusetts, home to “74 colleges, universities and prestigious research institutions,”19 including 2 schools of public health20 and 3 medical schools.21 My colleagues and I recently have shown that in Boston, fully 25 to 30% of premature deaths before age 75 occurring in 1999–2001 in the city’s poorest census tracts would not have happened if their residents had died at the same age-specific mortality rates as persons residing in the most affluent census tracts (Fig. 2).22 Statewide, risk of premature mortality increased with level of poverty and was nearly 2.5 times higher among persons living in the most compared with the least impoverished census tracts.23 In 2006, 12% of the total US population and 20% of US children under age 524—including, respectively, 8 and 12% of white non-Hispanics, 25% and 38% of the black population, and 22% and 31% of Hispanics24—lived in households below the notoriously low25 US poverty line. Whether one conducts epidemiologic research in impoverished or wealthy countries, economic deprivation is present and it matters.
Beyond these substantive problems, there is still another reason why epidemiologists cannot afford to ignore poverty: our commitment to scientific rigor, no matter what our topical interests. At issue is doing correct science26—and not, as some would have it, “politically correct” science.27 Blot poverty and inequity from view, and our understanding of disease etiology and distribution will be marred. To make this case, I address 2 unspoken questions in our field to argue why it is our intellectual responsibility to address poverty and health.
QUESTION 1: DO WE REALLY NEED MORE RESEARCH ON POVERTY AND HEALTH?
Stated simply: yes. Though consensus may exist that poverty and poor health are associated, there is considerable division as to why they are linked. In the United States and globally, longstanding arguments continue to rage over whether “the poor” fare poorly because of (a) their own innate deficiencies, whether moral, intellectual, or biologic; (b) a causal arrow that runs principally from poor health to economic poverty, with illness interfering with earning (and learning) capacity; or (c) social injustice, requiring redistributive justice (which is where the weight of the evidence lies).11–18,25–34 Within the United States and other wealthy countries, additional debates focus on whether poverty’s harm is due to material want versus psychosocial stress, and thus on whether the public health and policy focus should be on “poverty,” ostensibly affecting a minority, versus the “socioeconomic gradient,” ostensibly affecting everyone.11–18,33–36 Not surprisingly, these disputes hinge on how poverty is conceptualized, measured, and analyzed. Ongoing arguments, now centuries old, continue to question whether “poverty” and “the poor” should be defined with reference to “absolute” versus “relative” measures, income versus consumption, and solely economic deprivation versus additional aspects of social exclusion.11–18,30–36
These sharp debates arise because of their policy and political ramifications: who stands to gain, and who stands to lose? On one side of the poverty-health debates are proponents of the unbridled free market; on the other, are those who seek a more democratically controlled and egalitarian economy.11–18,25,30–33 Disputes between “neomaterialist” and “psychosocial” epidemiologists—both of whom seek to increase social equality and reduce health inequities—are likewise heated, with their focus not on whether but how inequality harms health, and hence what the societal remedies should be.13–18,35,36
Beyond the overtly political aspects of the poverty health debates looms still another problem: the complexity of causal inference, especially when studying population health.37–41 For obvious reasons, researchers cannot ethically randomize people to various levels of economic resources. One alternative is to analyze the health impact of economic policies whose enactment varies by time or space. Even so, it can be difficult to disentangle the impact of a particular policy from the effects of other contemporaneous societal changes.37,38 Another alternative is to conduct longitudinal analyses of socioeconomic position and health across the life course, although few population-based longitudinal datasets have high-quality data on both health status (eg, based on physical examination and biomarkers, rather than self-reported health) and socioeconomic position (at the individual, household, or area level, let alone all 3).37,38 Grappling with these problems has led to improvements in methods, questions, and data for epidemiology overall. For example, epidemiology’s recent adoption of multilevel, life course, instrumental variable, and propensity score analytic methods have all been propelled by debates over how social conditions shape health.37,38
There accordingly are at least 2 reasons for continuing to study poverty and health. One is to keep before the public’s eye the magnitude of the problem, so that the suffering can be made actionable, rather than be ignored or accepted as inevitable.11–18 Doing this work, and doing it well, is a core public health function of epidemiology.
The second reason is to make good on the claims of science to adjudicate among competing claims.39–41 To those who charge that investigating links between poverty and health is political, not scientific,27 the obvious rejoinder is that it is even more political to ignore these connections than to study them.14–17,25,26,33,40,41 Our testing of ideas in the public domain, using rigorous and transparent methods, is what allows us to move beyond mere opinion and prevents ideology from being the sole arbiter of what counts as knowledge.26,40,41 As long as poverty exists and is associated with health, debates will rage over why these connections exist. Consequently, one of the essential “uses of epidemiology” (famously argued by Jeremy Morris in his pathbreaking 1957 epidemiology textbook by this name42) is precisely to ensure the existence of sound population-based data on poverty and health. With such data, we can rigorously test hypotheses regarding the direction of the causal arrows and measure the magnitude of poverty’s toll on population health.
QUESTION 2: WHY BOTHER ABOUT POVERTY IF YOU’RE NOT A “SOCIAL EPIDEMIOLOGIST”?
What if your primary interest, as an epidemiologist, has nothing to do with the links between poverty and health? Do you still need to pay attention to how economic circumstances affect health?
Yes, for 2 reasons. One is the serious problem of confounding: many of the exposures epidemiologists are interested in coexist and are jointly embodied—not necessarily because they are causally connected, per se, but because they are entangled by the ways people actually live in their societal context, replete with constraints as well as possibilities.14,16,40 The second is the problem of selection: whom we study sets the range of possibility for comparisons. If the range is too narrow, whether by design or by selection bias, the constrained variability may preclude detecting important etiologic exposures, or may bias estimates of their effect.
Consider the shock waves still rippling from release of the Women’s Health Initiative (WHI) results in 2002.43,44 Whatever controversies may persist over links between hormone therapy and adverse or beneficial cardiovascular outcomes,43–50 the evidence now clearly shows that the failure of some observational studies to control adequately economic affluence—and its inevitable association with better health and a greater likelihood of being prescribed and being able to afford hormone therapy—wrongly found that hormone therapy reduced risk of cardiovascular disease.44,46,50 Prior to the WHI results, however, proponents of hormone therapy discounted these concerns, arguing that controlling for education, or studying women who belonged to one overall occupational group (eg, nurses), was sufficient to address socioeconomic confounding.44,51,52
What harm was caused by failing to take class seriously? One answer lies in the population burden of iatrogenic breast cancer brought about by uncritical use of hormone therapy.44,53
Recall that epidemiologic data had clearly shown that the absolute risk of breast cancer was higher than that of cardiovascular disease among perimenopausal women, particularly among the great majority who were nonsmokers.44,53 Thus, recommendations for hormone therapy effectively asked these women to increase their short-term and not inconsiderable risk of cancer, with the hope of decreasing their long-term risk of cardiovascular disease.44,53 The trade-off has been costly. Studies conducted between 2002 and 2005 in the United States, United Kingdom, Australia, and Norway suggest that hormone therapy accounts for somewhere between 10 and 25% of observed breast cancer cases.54–57 In the United Kingdom, this has been estimated to translate to an extra 20,000 breast cancers among women ages 50–64 in the past decade alone.54 New results, moreover, using post-WHI cancer registry data, indicate that between 2002 and 2003, US breast cancer rates fell by 7–11%, with this extraordinary decline especially evident among the types of breast cancer most linked to hormone therapy, ie, estrogen-receptor positive tumors among postmenopausal women.58–61 If, as suspected, this drop is shown to be causally related to the decline in hormone therapy, above and beyond any concurrent reduction of mammography rates,58–61 it would profoundly underscore the serious harms that can arise if epidemiologists ignore the impact of socioeconomic position on health.
Consider, as well, how socially-patterned selection bias can compromise investigation of causal associations. A thoughtful study demonstrates this problem by exploring unexpected results in a population-based case-control analysis of Hodgkin lymphoma.62 In the original study, the response rate for cases was 87% but only 65% for controls—the latter rate albeit on par with those reported in most current population-based epidemiologic studies.63,64 Comparing the sociodemographic characteristics of participating versus nonparticipating controls, the investigators found that among the controls, there was over-representation of women who were older, less educated, of color, and of higher birth order and higher parity.62 The net result was that adjustment of odds ratios for bias “strengthened previously null findings for education and for parity, breast-feeding and miscarriages in young adult women.”62 Thus, the initial study’s neglect of the socioeconomic patterning of selection bias “resulted in a failure to identify potential etiologic leads.”62 One can only wonder how epidemiologic knowledge would change if every study were able to compare and adjust for the sociodemographic characteristics and life experiences of the participants and nonparticipants.
Consequently, far from being a “nuisance” issue, the social patterning of who is and is not in our epidemiologic studies has major implications for etiologic analysis. By definition, the people we study are simultaneously social beings and biologic organisms16,40,41—and we risk serious error if we attempt to study the latter without taking into account the former.
CONCLUSION: SOCIETAL RELATIONSHIPS AND PROCESSES OF IMPOVERISHMENT ARE THE CONTEXT OF EPIDEMIOLOGY
The voices and self-reported experiences of the poor—and not just renditions of their lives by “outsiders”—are essential.25,32–34,65–67 However, epidemiology’s concern cannot simply be about “the poor.” A comparison group is needed. By analogy, were we to study the impact of smoking on the health of smokers alone, we would be able to ascertain only the differential exposure and susceptibility among the exposed, rather than the impact of exposure versus no exposure.68
More profoundly, the “poor” do not exist in isolation—they are as integrally a product of the workings of each society’s political economy as any other economic group, including the wealthy.13–17,25,32–34,69 The “poor” are not “the problem”; rather, the problem lies in the societal relationships and processes leading to and perpetuating impoverishment. Health inequities are created by unfair and unjust policies and practices that preferentially reward certain groups, economically and socially, at the expense of others.12,70 A corollary is that unfair relationships between groups shape characteristics of the groups themselves, including their health status. That is, group properties can arise because of relationships among groups, not because these characteristics are somehow “innate.”26,70 Mistake one for the other, and the causal arrows will point in the wrong direction.
This is why social relationships are at the crux of Peter Townsend’s 1986 classic article “Why are the many poor?”69 This commentary was concerned with persistent socioeconomic and health inequities in the United Kingdom, and followed the famous UK Black Report,71 which Townsend coauthored and which put health inequities on the map for our generation.11,12,40,41 As argued by Townsend, it’s not simply that there are rich and poor; rather, there are rich because there are poor.69 To achieve health equity, Townsend concluded, “The only long-term remedy is to restrict the power and wealth of the rich, to dismantle the present structures of social privilege, and to build social institutions based on fair allocation of wealth and on social equality.” These are testable propositions. It is long past time to alter the equation linking poverty and poor health. In its place, and consonant with our discipline’s deep roots, let me propose: social justice + human rights = health equity.
ABOUT THE AUTHOR
NANCY KRIEGER is a social epidemiologist and a professor at the Harvard School of Public Health. Her work includes empirical research on the impact of class, racism, and gender on health; improving methods to monitor and analyze health inequities; analyzing the history and politics of epidemiology; and developing ecosocial theory to guide epidemiologic research on determinants of population health.
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1. Krieger N. Epidemiology and social sciences: towards a critical reengagement in the 21st century. Epidemiol Rev
2. Porter D. Health, Civilization and the State: A History of Public Health From Ancient to Modern Times
. London, UK: Routledge; 1999.
3. Hays JN. The Burdens of Disease: Epidemics and Human Responses in Western History
. New Brunswick, NJ: Rutgers University Press; 1998.
4. Coleman W. Death is a Social Disease: Public Health and Political Economy in Early Industrial France
. Madison, WI: University of Wisconsin Press; 1982.
5. National Human Genome Research Institute, National Institutes of Health. The Genes and Environment Initiative (GEI)
. Available at: www.genome.gov/19518663
. Accessed January 10, 2007.
6. United States Centers for Disease Control and Prevention, National Office of Public Health Genomics. Genomics 2006 Program Review Book
. Atlanta, GA: CDC, US Public Health Service; 2006. Available at: www.cdc.gov/genomics/activities/ogdp/2006.htm
. Accessed January 20, 2007.
7. Costa LG, Eaton DL, eds. Gene-Environment Interactions: Fundamentals of Ecogenetics
. Hoboken, NJ: John Wiley & Sons; 2006.
8. Newman M, Dorling D, Barford A, et al. Worldmapper—the world as you’ve never seen it before. Available at: www.worldmapper.org/index.html
. Accessed June 6, 2007.
9. United Nations Human Development Report 2006. Beyond Scarcity: Power, Poverty, and the Global Water Crisis
. Available at: http://hdr.undp.org/hdr2006/
. Accessed June 6, 2007.
11. World Health Organization Commission on Social Determinants of Health. Towards a conceptual framework for analysis and action on the social determinants of health. Discussion paper for the Commission on the Social Determinants of Health, Draft, May 5, 2005. Available at: www.who.int/social_determinants/knowledge_networks/en/
. Accessed June 8, 2007.
12. Dahlgren G, Whitehead M. Levelling Up, Part 1: A Discussion Paper on European Strategies for Tackling Social Inequities in Health
. Copenhangen, Denmark: WHO Regional Office for Europe; 2006. Available at: www.euro.who.int/
. Accessed June 8, 2007.
13. Kunitz S. The Health of Populations: General Theories and Particular Realities
. Oxford, England: Oxford University Press; 2006.
14. Smith GD, ed. Health Inequalities: Lifecourse Approaches
. Bristol, UK: Policy Press; 2003.
15. Levy BS, Sidel VW, eds. Social Injustice and Public Health
. New York: Oxford University Press; 2006.
16. Krieger N, ed. Embodying Inequality: Epidemiologic Perspectives
. Amityville, NY: Baywood Publishing Company; 2004.
17. Navarro V, Muntaner C, eds. Political and Economic Determinants of Population Health and Well-Being: Controversies and Developments
. Amityville, NY: Baywood Publishing Company; 2004.
18. Wilkinson R, Marmot M, eds. Social Determinants of Health: The Solid Facts
. 2nd ed. Oxford: Oxford University Press; 2006.
22. Chen JT, Rehkopf DH, Waterman PD, et al. Mapping and measuring social disparities in premature mortality: the impact of census tract poverty within and across Boston neighborhoods, 1999–2001. J Urban Health
23. Rehkopf DH, Haughton L, Chen JT, et al. Monitoring socioeconomic disparities in death: comparing individual-level education and area-based socioeconomic measures. Am J Public Health
25. O’Connor A. Poverty Knowledge: Social Science, Social Policy, and the Poor in Twentieth-Century US History
. Princeton, NJ: Princeton University Press; 2001.
26. Krieger N. Stormy weather: “race,” gene expression, and the science of health disparities. Am J Public Health
27. Satel S. PC, M.D. How Political Correctness is Corrupting Medicine
. New York: Basic Books; 2000.
28. Cutler D, Deaton A, Lleras-Muney A. The determinants of mortality. J Econ Perspect
29. Smith JP. Healthy bodies and thick wallets: the dual relation between health and economic status. J Econ Perspect
30. Sachs J. The End of Poverty: Economic Possibilities for Our Time
. New York: Penguin Press; 2005.
31. Stiglitz JE. Making Globalization Work
. New York: WW Norton & Company; 2006.
32. Monbiot G. Manifesto For a New World Order
. New York: WW Norton & Company; 2004.
33. Townsend P, Gordon D, eds. World Poverty: New Policies to Defeat an Old Enemy
. Bristol, UK: The Policy Press; 2002.
34. Blank RM. Selecting among anti-poverty policies: can an economist be both critical and caring? Rev Soc Econ
35. Lynch JW, Smith GD, Kaplan GA, et al. Income inequality and mortality: importance to health of individual incomes, psychological environment, or material conditions. Br Med J
36. Marmot M, Wilkinson RG. Psychosocial and material pathways in the relation between income and health: a response to Lynch et al. Br Med J
37. Berkman L, Kawachi I, eds. Social Epidemiology
. Oxford: Oxford University Press; 2000.
38. Oakes JM, Kaufman JS, eds. Methods in Social Epidemiology
. San Francisco, CA: Jossey-Bass; 2006.
39. Ziman J. Real Science: What it is, and What it Means
. Cambridge, UK: Cambridge University Press; 2000.
40. Krieger N. Epidemiology and the web of causation: has anyone seen the spider? Soc Sci Med
41. Krieger N. Theories for social epidemiology in the 21st century: an ecosocial perspective. Int J Epidemiol
42. Morris JN. Uses of Epidemiology
. London: E & S Livingston; 1957.
43. Writing Group for the Women’s Health Initiative Investigators.Risk and benefits of estrogen plus progestin in healthy postmenopausal women. Principal results from the Women’s Health Initiative randomised controlled trial. JAMA
44. Krieger N, Löwy I; “Women, Hormones, and Cancer” Group. Hormone replacement therapy, cancer, controversies and women’s health: historical, epidemiological, biological, clinical and advocacy perspectives. J Epidemiol Community Health
45. Pettiti D. Commentary: hormone replacement therapy and coronary heart disease: four lessons. Int J Epidemiol
46. Lawlor DA, Smith GD, Ebrahim S. Commentary: the hormone replacement-coronary heart disease conundrum: is this the death of observational epidemiology? Int J Epidemiol
47. Barrett-Connor E. Commentary: observation versus intervention—what’s different? Int J Epidemiol
48. Stampfer M. Commentary: hormones and heart disease: do trials and observational studies address different questions? Int J Epidemiol
49. Harman SM, Naftolin F, Brinton EA, et al. Is the estrogen controversy over? Deconstructing the Women’s Health Initiative Study: a critical evaluation of the evidence. Ann N Y Acad Sci
50. Rossouw JE. Implications of recent clinical trials of postmenopausal hormone therapy for management of cardiovascular disease. Ann N Y Acad Sci
51. Grodstein F, Clarkson TB, Manson JE. Understanding divergent data on posthormonal hormone therapy. N Engl J Med
52. Krieger N. Postmenopausal hormone therapy [letter]. N Engl J Med
53. Rosenberg L. Hormone replacement therapy: the need for reconsideration. Am J Public Health
54. Beral V. Million Women Study Collaborators. Breast cancer and hormone-replacement therapy in the Million Women Study. Lancet
55. Bakken K, Alsaker E, Eggen AE, et al. Hormone replacement therapy and incidence of hormone-dependent cancers in the Norwegian Women and Cancer study. Int J Cancer
56. Coombs NJ, Taylor R, Wilcken N, et al. HRT and breast cancer: impact on population risk and incidence. Eur J Cancer
57. Coombs NJ, Taylor R, Wilcken N, et al. Hormone replacement therapy and breast cancer risk in California. Breast J
58. Clarke CA, Glaser SL, Uratsu CS, et al. Recent declines in hormone therapy utilization and breast cancer incidence: clinical and population-based evidence. J Clin Oncol
59. Ravdin PM, Cronin KA, Howlader N, et al. A sharp decrease in breast cancer incidence in the United States in 2003. Presented at: The 29th Annual San Antonio Breast Cancer Symposium; December 14–17, 2006; San Antonio, Texas. Available at: www.sabcs.org
. Accessed June 8, 2007.
60. Ravdin PM, Cronin KA, Howlader N, et al. The decrease in breast-cancer incidence in 2003 in the United States. N Engl J Med
61. Stewart SL, Sabatino SA, Foster SL, et al. Decline in breast cancer incidence—United States, 1999–2003. MMWR Morb Mortal Wkly Rep
62. Glaser SL, Clarke CA, Keegan TH, et al. Attenuation of social class and reproductive risk factor associations for Hodgkin lymphoma due to selection bias in controls. Cancer Causes Control
63. Morton LM, Cahill J, Hartge P. Reporting participation in epidemiologic studies: a survey of practice. Am J Epidemiol
64. Hartge P. Participation in population studies. Epidemiology
65. Schulz AJ, Mullings L, eds. Gender, Race, Class, and Health: Intersectional Approaches
. San Francisco, CA: Jossey-Bass; 2006.
66. Kaufman L, Karpati A. Understanding the sociocultural roots of childhood obesity: food practices among Latino families of Bushwick, Brooklyn. Soc Sci Med
67. Global Health Watch. Mobilizing Civil Society Around an Alternative Health Report. Available at: www.ghwatch.org/about_ghw.php
. Accessed June 8, 2007.
68. Rose G. Sick individuals and sick populations. Int J Epidemiol
69. Townsend P. Why are the many poor? Int J Health Serv
70. Krieger N. Defining and investigating social disparities in cancer: critical issues. Cancer Causes Control
71. Townsend P, Davidson N, Whitehead M. Inequalities in Health: The Black Report and the Health Divide
. London, UK: Penguin Books; 1990.
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