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P A R T
I
HEALTH OF THE NATION
Part I of the book presents the broad outcomes achieved by the health care system and
a conceptual framework for understanding health determinants. This part consists of two
critical areas represented by two chapters: health outcomes (Chapter 1) and conceptual
framework of health determinants (Chapter 2). Chapter 1 focuses on the nation’s health
outcomes. After a summary of the U.S. achievements in combating behavior risks, health
problems and disparities are highlighted, with particular attention to vulnerable populations. Since the United States is often compared to other nations in terms of its
achievements and deficiencies, the concept of global health is also introduced. Chapter
2 introduces some dominant health determinants conceptual framework both international and domestic. The chapter also includes articles that illustrate what a conceptual framework is and how a conceptual framework might be used to understand health
and healthcare problems and identify solutions. Part I provides the outcome measurement for the other parts of the book that address input and process respectively. Part
I is also a foundation for the rest of the book, providing a “big-picture” view on how
much we have accomplished and how much we have yet to achieve. A clear grasp of the
materials in Part I will assist in developing a more comprehensive and balanced critique
of the U.S. health care system.
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Health Outcomes
T
are wide discrepancies in the health status of
populations within the country, comparing
only the health status of white Americans
to other countries produced the same dismal results. White Americans are still doing
worse than other developed nations for all
standard measures of health status. The U.S.
also has one of the highest amendable death
rates, defined as mortality caused by bacterial infections, treatable cancers, diabetes,
cardiovascular disease, cerebrovascular disease, and complications from common surgical procedures (Nolte and McKee 2008).
Comparing 50-to-74-year-old Americans to
Europeans while adjusting for wealth still
placed Americans at worse health than the
Europeans (Davies et al. 2007). While
Americans were worse off for all levels of
health, the discrepancy between Americans
and Europeans were worst for poor
Americans.
Yet, the U.S. has by far the most costly
health system in the world, using up 17
percent of the country’s gross domestic
product, and has the highest rate of specialist physicians per capita (Davies et al.
2007; Simms 2009). Both physicians and
patients consistently provide low ratings
to the health care system, with reports of
facing numerous barriers to care as well
he World Health Organization
(WHO) defines health as “a complete
state of physical, mental, and social
well-being, and not merely the absence of
disease or infirmity” (WHO 1948). Over the
past century, the United States has made
great strides in improving the health of its
populations. Since 1900, the average lifespan of persons in the U.S. has lengthened by
greater than 30 years and 25 years of this
gain are attributable to advances in public
health (CDC 1999). The ten public health
achievements include vaccination, motorvehicle safety, safer workplaces, control of
infectious diseases, decline in deaths from
coronary heart disease and stroke, safer and
healthier foods, healthier mothers and babies, family planning, fluoridation of drinking water, and recognition of tobacco use as
a health hazard.
Despite these achievements, the U.S.
still ranks low among the developed nations
in health status. Out of 30 developed nations in the Organization for Economic
Cooperation and Development (OECD),
the U.S. is near the bottom in all standard
measures of health status (Schroeder 2007).
In 2004, the U.S. ranked 46th in life expectancy and 42nd in infant mortality out
of 192 nations. While it is true that there
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C H A P T E R
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CHAPTER 1 HEALTH OUTCOMES
as inadequacies of insurance coverage. Compared
to other counties, U.S. patients pay much more out
of pocket for their medical expenses and are less
likely to have a regular source of care, which then affects getting timely care (Avendano et al 2009).
In addition, the health status of individuals in the
U.S. is mired with inequalities and disparities as a result of numerous factors, including but not limited
to socioeconomic status (SES), race/ethnicity, and insurance coverage. SES most commonly incorporates
measures of income, education, and occupation. An
unfortunate truism in the U.S., and in nearly every
other developed country, is that individuals with
higher SES have better health. They also have greater
ability to access health services and obtain better quality care. SES is related to health and health care in
two ways that have been previously labeled material
deprivation and lack of social participation (Marmot
2002). Material deprivation includes access to material goods that are required for good health, including clean water and good sanitation, adequate
nutrition and housing, reliable transportation, and a
safe and comfortable environment. Social participation includes having time for leisure activity and
group participation, having friends or family around
for entertainment and support, opportunities for professional achievement, and ultimately having sufficient control over one’s life that leads to fulfillment
and satisfaction. Without access to material goods
and supportive social participation, health may falter,
and greater barriers may be experienced in obtaining
needed health care services.
One of the most prominent inequalities within
the U.S. health care system is defined by race (Davies
et al. 2007; Blendon et al. 2007). However, race/
ethnicity frequently serves as a proxy measure for
other factors that are more appropriate explanatory
factors than skin color. Race/ethnicity can be a reflection of biological factors; socioeconomic status;
cultural practices, beliefs, or acculturation; or political factors (King and Williams 1995). Race/ethnicity
may also serve as a proxy measure of experiencing
discrimination. In the case of health outcomes,
race/ethnicity may serve as a proxy for biological factors (blacks are more prone to sickle cell anemia, for
example), cultural behaviors or practices regarding
health, or access to material goods and services that
support health. In the case of health care experiences,
race/ethnicity may serve as a proxy for socioeconomic factors (enabling the purchase of services), language factors (creating barriers to accessing services),
or discrimination based on skin color.
Until recently, the U.S. was the only developed
nation that does not guarantee its citizens access to
health care through a system of universal health coverage. In 2000, WHO released a report ranking
countries on the quality of their health systems. The
report placed the U.S. in the 37th spot for health system performance and 72nd for health outcome performance (out of 191), primarily because of its failure
to ensure access to primary care for the uninsured
and because of the relatively low life expectancy and
high infant mortality despite the fact that the U.S.
spends more than all the other nations on health care
(World Health Organization 2000). With the exception of individuals living in close proximity to free
health care clinics or community health centers, the
uninsured are particularly vulnerable to financial barriers in accessing health care (Kronick 2009; Levy
and Meltzer 2008). Once a person is insured, there
are three mechanisms by which insurance may be related to health and health care experiences: (1) health
plan policies may affect care-seeking and cost-sharing
behaviors of beneficiaries, (2) providers’ incentives
and reimbursement strategies may influence provider
behavior, and (3) perceptions of health insurance
plans may create feelings of stigma and affect the use
of services and reports of quality.
This chapter focuses on the nation’s health. After
summarizing our achievements in combating behavior risks, we highlight our health problems and disparities, particularly for one of the most vulnerable
populations, the American Indians. Since the United
States is often compared to other nations in terms of
its achievements and deficiencies, the concept of
global health is also introduced. Below are synopses
of the readings included for this chapter.
In We Can Do Better—Improving the Health of
the American People, the author points out that the
greatest opportunity to improve the health of
Americans and reduce the number of premature
deaths lies in personal behavior. History has shown
this as a possible solution. There has been a marked
increase in the use of seatbelts in the last couple of
decades, and recently, Americans have decreased
their high consumption of saturated fats. There was
also the rapid fall of tobacco use from the mid-1960s
to the present with the help of laws, regulations, and
litigations, including smoke-free public areas and increased tax on cigarettes.
The next problem to be tackled will be obesity,
which poses the same obstacles smoking once did on
the population. The largest hurdle in dealing with
the obesity epidemic is the use of BMI to classify obesity, since the method often misclassifies individuals
with large amounts of muscle mass as obese.
Litigation is also more difficult since the food industry is not as concentrated as the tobacco industry.
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HEALTH OUTCOMES
There are more stakeholders involved in the food
industry.
Improving population health also requires using
non-behavioral determinants of health, such as social
and environmental factors. Class, as defined by income, total wealth, education, employment, and
residential neighborhood, is often an ignored determinant of health, despite obvious gradients in health
among members of different social classes. The
United Kingdom is at the forefront of addressing effects of class on health. In 1998, they placed the
Acheson Commission in charge of reducing health
disparities, focusing particularly on social policies
for health care, which is absent in the U.S. health
care policy framework. Access and quality of care
can also influence the health status of a population.
The U.S. trails in access to care with 45 million people lacking insurance and several million more underinsured. Lack of insurance or insufficient
insurance often leads to poor health because it limits an individual’s access to the health care system.
It is difficult to improve population health in the
U.S. for several reasons. The system focuses on the
health of the middle and upper class, more so than
it does on the affected poor with worse health outcomes. Most progress in health care only occurs
when the middle class takes action and brings the
problem to the forefront. One of the reasons for this
is that the poor have no representation in politics.
There is no active labor movement in the U.S., unlike
other developed nations. In addition, it is difficult to
increase the role of U.S. government in health care
due to the American culture of individual responsibility that results in reluctance to intervene.
In U.S. Disparities in Health: Descriptions,
Causes, and Mechanisms, the authors cite Healthy
People 2010’s definition of “health disparities” as
differences that occur by gender, race or ethnicity,
education or income, disability, geographic location,
or sexual orientation. Disparities in race/ethnicity
have been shown in certain diseases. Compared to
whites, blacks have higher standard mortality rates
(SMR) for homicides, hypertensive heart disease,
esophageal cancer, and pulmonary circulation, and
lower SMRs for suicide, leukemia, and COPD.
Socioeconomic status (SES) has been found to contribute to a large portion of racial/ethnic disparities.
A gradient within the SES correlates to a gradient in
health outcomes with lower SES associated with
poorer health.
Disparities have also been known to change over
a life course. There are higher disparities among infants at birth depending on their mother’s education,
income, and lifestyle behaviors, but these disparities
5
drop off during childhood, adolescence, and young
adulthood. Disparities widen once again during
middle age and finally decrease in older populations,
most likely as a result of the “weaker” individuals in
the population dying off at earlier ages to leave a
healthier population at this late stage of life.
In Changing Patterns of Mortality Among
American Indians, the authors note that the mortality rates of American Indians have shown an alarmingly increasing trend in recent years. For the
Navajos, the largest tribe living on a reservation, the
mortality rate began to increase at 46 per 100,000 individuals since the mid-1980s, while whites continued to decrease their rates within that same time
period. The major source of mortality came from
lung cancer, diabetes, and cardiovascular disease
while there were decreases in deaths caused by infectious diseases. Morbidity among Navajos saw an
increase in non-insulin-dependent diabetes as a result of the increasing rates of obesity made worse by
changes in diet and activity patterns. Access to
screening and prevention services is limited to the
Navajo community. The best solutions to tackle the
growing problem of mortality from chronic conditions within this population are primary prevention,
i.e., the prevention or reduction of the underlying
causes of risk factors. In addition, implementing a
broad range of services, rather than only health services, may be better at solving chronic diseases.
In Towards a Common Definition of Global
Health, the authors start by reviewing two related
terms: public health and international health. Public
health emerged in Europe and the United States from
social reforms and an increased understanding of
medicine, including a better understanding of the
causes and treatments of infectious diseases. Public
health has four important factors: (1) evidence-based
decisions, (2) a focus on population care, rather than
individual needs, (3) an emphasis on seeking social
justice and equity, and (4) prevention rather than
treatment. International health focuses on health care
abroad, relating more to health practices, policies
and systems, and stressing differences among countries. Public health is applied to international health
as a means to fix the problems and challenges that affect mostly low-income or middle-income countries.
Global health is considered a mixture of both
public health and international health. It focuses on
problems with an international scope, rather than
where the problem exists, embracing all health
threats in addition to infectious diseases and maternal and child care that are problems in low-income
and middle-income countries. Important topics in
global health consist of under- and over-nutrition,
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CHAPTER 1 HEALTH OUTCOMES
HIV/AIDS, tobacco use, malaria, and mental health.
While global health emphasizes prevention, it also
covers aspects of clinical medicine, including treatment and rehabilitation. The proposed definition of
global health states that “global health is an area for
study, research, practice that places a priority on improving health and achieving equity in health for all
people worldwide . . . emphasizing transnational
health issues, determinants, and solutions involving
many disciplines within and beyond the health sciences and promotes interdisciplinary collaboration
synthesis of population-based prevention with individual clinician care.”
References
Avendano et al. “Health Disadvenatges in US Adults
Aged 50 to 74 Years: A Comparison of the Health
of Rich and Poor Americans With That of
Europeans.” American Journal of Public Health.
99(2009):540-548.
Blendon et al. Disparities in Health: Perspectives of A
Multi-Ethnic, Multi-Racial America. Health Affairs.
26(2007):1437-1447.
The Centers for Disease Control and Prevention (CDC).
Ten Great Public Health Achievements—United
States, 1900-1999. MMWR April 02, 1999/
48(12);241-243.
Davies et al. “Mirror, Mirror on the Wall: An
International Update on the Comparative
Performance of American Health Care.” The
Commonwealth Fund, 2007.
King G; Williams D. Race and health: A multidimensional approach to African-American health. In
B. Amick III, S. Levine, A.Talov, and D. Chapman
Walsh (Eds.), Society and Health. Pp.93-130, New
York, Oxford University Press, 1995.
Kronick, R. Health Insurance Coverage and Mortality
Revisited. Health Services Research 44(2009):
1211-1231
Levy, H; Meltzer, D. The Impact of Health Insurance on
Health. Ann. Rev. Public Health 29(2008):399-409.
Marmot, M. The influence of income on health: Views
of an epidemiologist. Does money really matter? Or
is it a marker for something else? Health Affairs
21(2):31-46, 2002.
Nolte E; McKee CM. Measuring the health of nations:
Updating an earlier analysis. Health Aff 2008;27:
58-71.
Schroeder SA. Shattuck Lecture. We can do better—
improving the health of the American people.
N Engl J Med 2007;357:1221-8.
Simms, Chris. Inequalities in the Ameican health-care
system. The Lancet. 373(2009):1252
World Health Organization (WHO). Preamble to the
Constitution. Geneva, Switzerland, 1948.
World Health Organization (WHO). World health report 2000: Health system performance. Geneva,
Switzerland, 2000.
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R E A D I N G
1
We Can Do Better—Improving the
Health of the American People
HEALTH STATUS OF THE AMERICAN PUBLIC
Source: Schroeder SA. Shattuck Lecture. We can do
better—improving the health of the American people.
N Engl J Med 2007;357:1221-8. Copyright © 2007
Massachusetts Medical Society. All rights reserved.
Among the 30 developed nations that make up the
Organization for Economic Cooperation and Development (OECD), the United States ranks near the
bottom on most standard measures of health status
(Table 1).1-4 (One measure on which the United States
does better is life expectancy from the age of 65 years,
possibly reflecting the comprehensive health insurance
provided for this segment of the population.) Among
the 192 nations for which 2004 data are available, the
United States ranks 46th in average life expectancy from
birth and 42nd in infant mortality.5,6 It is remarkable
how complacent the public and the medical profession
are in their acceptance of these unfavorable comparisons, especially in light of how carefully we track
health-systems measures, such as the size of the budget
for the National Institutes of Health, trends in national
spending on health, and the number of Americans who
lack health insurance. One reason for the complacency
may be the rationalization that the United States is more
ethnically heterogeneous than the nations at the top of
the rankings, such as Japan, Switzerland, and Iceland.
It is true that within the United States there are large disparities in health status—by geographic area, race and
ethnic group, and class.7-9 But even when comparisons
are limited to white Americans, our performance is dismal (Table 1). And even if the health status of white
Americans matched that in the leading nations, it would
still be incumbent on us to improve the health of the entire nation.
The United States spends more on health care than
any other nation in the world, yet it ranks poorly on
nearly every measure of health status. How can this
be? What explains this apparent paradox?
The two-part answer is deceptively simple—
first, the pathways to better health do not generally
depend on better health care, and second, even in
those instances in which health care is important,
too many Americans do not receive it, receive it
too late, or receive poor-quality care. In this lecture, I first summarize where the United States
stands in international rankings of health status.
Next, using the concept of determinants of premature death as a key measure of health status, I discuss pathways to improvement, emphasizing
lessons learned from tobacco control and acknowledging the reality that better health (lower
mortality and a higher level of functioning) cannot
be achieved without paying greater attention to
poor Americans. I conclude with speculations on
why we have not focused on improving health in
the United States and what it would take to make
that happen.
7
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CHAPTER 1 HEALTH OUTCOMES
Table 1
Health Status of the United States and Rank among the 29 Other OECD Member Countries
U.S. Rank
Top-Ranked
Health-Status Measure
United States
Country in OECD*
in OECD
Infant mortality (first year
of life), 2001
All races
6.8 deaths/
25
Iceland
1000 live births
(2.7 deaths/
1000 live births)
Whites only
5.7 deaths/
22
1000 live births
Maternal mortality, 2001†
All races
9.9 deaths/
22
Switzerland
100,000 births
-(1.4 deaths/
100,000 births)
Whites only
7.2 deaths/
19
100,000 births
Life expectancy from birth, 2003
All women
80.1 yr
23
Japan (85.3 yr)
White women
80.5 yr
22
All men
74.8 yr
22
Iceland (79.7 yr)
White men
75.3 yr
19
Life expectancy from age 65,
2003‡
All women
19.8 yr
10
Japan (23.0 yr)
White women
19.8 yr
10
All men
16.8 yr
9
White men
16.9 yr
9
*The
number in parentheses is the value for the indicated health-status measure.
†OECD
data for five countries are missing.
‡OECD
data for six countries are missing.
PATHWAYS TO IMPROVING
POPULATION HEALTH
Health is influenced by factors in five domains—
genetics, social circumstances, environmental exposures, behavioral patterns, and health care (Fig. 1).10,11
When it comes to reducing early deaths, medical care
has a relatively minor role. Even if the entire U.S. population had access to excellent medical care—which it
does not—only a small fraction of these deaths could
be prevented. The single greatest opportunity to improve health and reduce premature deaths lies in personal behavior. In fact, behavioral causes account for
nearly 40% of all deaths in the United States.12
Although there has been disagreement over the actual
number of deaths that can be attributed to obesity
and physical inactivity combined, it is clear that this
pair of factors and smoking are the top two behavioral causes of premature death (Fig. 2, not included).12
Addressing Unhealthy Behavior
Clinicians and policymakers may question whether
behavior is susceptible to change or whether attempts
to change behavior lie outside the province of traditional medical care.13 They may expect future successes to follow the pattern whereby immunization
and antibiotics improved health in the 20th century.
If the public’s health is to improve, however, that improvement is more likely to come from behavioral
change than from technological innovation. Experience demonstrates that it is in fact possible to
change behavior, as illustrated by increased seat-belt
use and decreased consumption of products high in
saturated fat. The case of tobacco best demonstrates
how rapidly positive behavioral change can occur.
The Case of Tobacco
The prevalence of smoking in the United States declined among men from 57% in 1955 to 23% in
2005 and among women from 34% in 1965 to 18%
in 2005.14,15 Why did tobacco use fall so rapidly?
The 1964 report of the surgeon general, which linked
smoking and lung cancer, was followed by multiple
reports connecting active and passive smoking to
myriad other diseases. Early antismoking advocates,
initially isolated, became emboldened by the cascade
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READING 1: We Can Do Better—Improving the Health of the American People
of scientific evidence, especially with respect to the
risk of exposure to secondhand smoke. Countermarketing—first in the 1960s and more recently by
several states and the American Legacy Foundation’s
“truth ®” campaign—linked the creativity of
Madison Avenue with messages about the duplicity
of the tobacco industry to produce compelling antismoking messages16 (an antismoking advertisement
is available with the full text of this article at
www.nejm.org). Laws, regulations, and litigation,
particularly at the state and community levels, led to
smoke-free public places and increases in the tax on
cigarettes—two of the strongest evidence-based
tobacco-control measures.14,17,18 In this regard, local
governments have been far ahead of the federal government, and they have inspired European countries
such as Ireland and the United Kingdom to make
public places smoke-free.14,19 In addition, new medications have augmented face-to-face and telephone
counseling techniques to increase the odds that clinicians can help smokers quit.15,20,21
It is tempting to be lulled by this progress and
shift attention to other problems, such as the obesity epidemic. But there are still 44.5 million smokers in the United States, and each year tobacco use
kills 435,000 Americans, who die up to 15 years earlier than nonsmokers and who often spend their final
years ravaged by dyspnea and pain.14,20 In addition,
smoking among pregnant women is a major contributor to premature births and infant mortality.20
Smoking is increasingly concentrated in the lower
socioeconomic classes and among those with mental
illness or problems with substance abuse.15,22,23
People with chronic mental illness die an average of
25 years earlier than others, and a large percentage
of those years are lost because of smoking.24
Estimates from the Smoking Cessation Leadership
Center at the University of California at San
Francisco, which are based on the high rates and intensity (number of cigarettes per day plus the degree
to which each is finished) of tobacco use in these
populations, indicate that as many as 200,000 of the
435,000 Americans who die prematurely each year
from tobacco-related deaths are people with chronic
mental illness, substance-abuse problems, or
both.22,25 Understanding why they smoke and how
to help them quit should be a key national research
priority. Given the effects of smoking on health, the
relative inattention to tobacco by those federal and
state agencies charged with protecting the public
health is baffling and disappointing.
The United States is approaching a “tobacco tipping point”—a state of greatly reduced smoking
prevalence. There are already low rates of smoking
in some segments of the population, including physi-
9
cians (about 2%), people with a postgraduate education (8%), and residents of the states of Utah
(11%) and California (14%).25 When Kaiser
Permanente of northern California implemented a
multisystem approach to help smokers quit, the
smoking rate dropped from 12.2% to 9.2% in just
3 years.25 Two basic strategies would enable the
United States to meet its Healthy People 2010
tobacco-use objective of 12% population prevalence:
keep young people from starting to smoke and help
smokers quit. Of the two strategies, smoking cessation has by far the larger short-term impact. Of the
current 44.5 million smokers, 70% claim they would
like to quit.20 Assuming that one half of those 31
million potential non-smokers will die because of
smoking, that translates into 15.5 million potentially
preventable premature deaths.20,26 Merely increasing the baseline quit rate from the current 2.5% of
smokers to 10%—a rate seen in placebo groups in
most published trials of the new cessation drugs—
would prevent 1,170,000 premature deaths. No
other medical or public health intervention approaches this degree of impact. And we already have
the tools to accomplish it.14,27
Is Obesity the Next Tobacco?
Although there is still much to do in tobacco control, it is nevertheless touted as a model for combating obesity, the other major, potentially preventable
cause of death and disability in the United States.
Smoking and obesity share many characteristics
(Table 2). Both are highly prevalent, start in childhood or adolescence, were relatively uncommon until
the first (smoking) or second (obesity) half of the
20th century, are major risk factors for chronic disease, involve intensively marketed products, are more
common in low socioeconomic classes, exhibit major
regional variations (with higher rates in southern and
poorer states), carry a stigma, are difficult to treat,
and are less enthusiastically embraced by clinicians
than other risk factors for medical conditions.
Nonetheless, obesity differs from smoking in
many ways (Table 2). The binary definition of smoking status (smoker or nonsmoker) does not apply to
obesity. Body-mass index, the most widely used
measure of obesity, misclassifies as overweight people who have large muscle mass, such as California
governor Arnold Schwarzenegger. It is not biologically possible to stop eating, and unlike moderate
smoking, eating a moderate amount of food is not
hazardous. There is no addictive analogue to nicotine
in food. Nonsmokers mobilize against tobacco because they fear injury from secondhand exposure,
which is not a peril that attends obesity. The food
industry is less concentrated than the tobacco
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CHAPTER 1 HEALTH OUTCOMES
Table 2
Similarities and Differences between
Tobacco Use and Obesity
Characteristic
Tobacco Obesity
High prevalence
Yes
Yes
Begins in youth
Yes
Yes
20th-century phenomenon
Yes
Yes
Major health implications
Yes
Yes
Heavy and influential
Yes
Yes
industry promotion
Inverse relationship to
Yes
Yes
socioeconomic class
Major regional variations
Yes
Yes
Stigma
Yes
Yes
Difficult to treat
Yes
Yes
Clinician antipathy
Yes
Yes
Relative and debatable definition
No
Yes
Cessation not an option
No
Yes
Chemical addictive component
Yes
No
Harmful at low doses
Yes
No
Harmful to others
Yes
No
Extensively documented
Yes
No
industry duplicity
History of successful litigation
Yes
No
Large cash settlements by industry
Yes
No
Strong evidence base for treatment
Yes
No
Economic incentives available
Yes
Yes
Economic incentives in place
Yes
No
Successful counter-marketing
campaigns
Yes
No
industry, and although its advertising for children
has been criticized as predatory and its ingredientlabeling practices as deceptive, it has yet to fall into
the ill repute of the tobacco industry. For these reasons, litigation is a more problematic strategy, and industry payouts—such as the Master Settlement
Agreement between the tobacco industry and 46
state attorneys general to recapture the Medicaid
costs of treating tobacco-related diseases—are less
likely.14 Finally, except for the invasive option of
bariatric surgery, there are even fewer clinical tools
available for treating obesity than there are for treating addiction to smoking.
Several changes in policy have been proposed to
help combat obesity.28-30 Selective taxes and subsidies could be used as incentives to change the foods
that are grown, brought to market, and consumed,
though the politics involved in designating favored
and penalized foods would be fierce.31 Restrictions
could also apply to the use of food stamps. Given recent data indicating that children see from 27 to 48
food advertisements for each 1 promoting fitness or
nutrition, regulations could be put in place to shift
that balance or to mandate support for sustained
social-marketing efforts such as the “truth®” campaign
against smoking.16,32 Requiring more accurate labeling of caloric content and ingredients, especially in
fast-food outlets, could make customers more aware
of what they are eating and induce manufacturers to
alter food composition. Better pharmaceutical products and counseling programs could motivate clinicians to view obesity treatment more enthusiastically.
In contrast to these changes in policy, which will require national legislation, regulation, or research investment, change is already underway at the local
level. Some schools have banned the sale of soft
drinks and now offer more nutritionally balanced
lunches. Opportunities for physical activity at work,
in school, and in the community have been expanded
in a small but growing number of locations.
Nonbehavioral Causes of Premature Death
Improving population health will also require addressing the nonbehavioral determinants of health
that we can influence: social, health care, and environmental factors. (To date, we lack tools to change
our genes, although behavioral and environmental
factors can modify the expression of genetic risks
such as obesity.) With respect to social factors, people with lower socioeconomic status die earlier and
have more disability than those with higher socioeconomic status, and this pattern holds true in a stepwise fashion from the lowest to the highest
classes.33-38 In this context, class is a composite construct of income, total wealth, education, employment, and residential neighborhood. One reason for
the class gradient in health is that people in lower
classes are more likely to have unhealthy behaviors,
in part because of inadequate local food choices and
recreational opportunities. Yet even when behavior
is held constant, people in lower classes are less
healthy and die earlier than others.33-38 It is likely
that the deleterious influence of class on health reflects both absolute and relative material deprivation
at the lower end of the spectrum and psychosocial
stress along the entire continuum. Unlike the factors
of health care and behavior, class has been an “ignored determinant of the nation’s health.”33
Disparities in health care are of concern to some policymakers and researchers, but because the United
States uses race and ethnic group rather than class as
the filter through which social differences are analyzed, studies often highlight disparities in the receipt
of health care that are based on race and ethnic
group rather than on class.
But aren’t class gradients a fixture of all societies? And if so, can they ever be diminished? The
fact is that nations differ greatly in their degree of
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social inequality and that—even in the United
States—earning potential and tax policies have fluctuated over time, resulting in a narrowing or widening of class differences. There are ways to address
the effects of class on health.33 More investment
could be made in research efforts designed to improve our understanding of the connection between
class and health. More fundamental, however, is the
recognition that social policies involving basic aspects of life and well-being (e.g., education, taxation,
transportation, and housing) have important health
consequences. Just as the construction of new buildings now requires environmental-impact analyses,
taxation policies could be subjected to health-impact
analyses. When public policies widen the gap between rich and poor, they may also have a negative
effect on population health. One reason the United
States does poorly in international health comparisons may be that we value entrepreneurialism over
egalitarianism. Our willingness to tolerate large gaps
in income, total wealth, educational quality, and
housing has unintended health consequences. Until
we are willing to confront this reality, our performance on measures of health will suffer.
One nation attempting to address the effects of
class on health is the United Kingdom. Its 1998
Acheson Commission, which was charged with reducing health disparities, produced 39 policy recommendations spanning areas such as poverty,
income, taxes and benefits, education, employment,
housing, environment, transportation, and nutrition.
Only 3 of these 39 recommendations pertained directly to health care: all policies that influence health
should be evaluated for their effect on the disparities
in health resulting from differences in socioeconomic
status; a high priority should be given to the health
of families with children; and income inequalities
should be reduced and living standards among the
poor improved.39 Although implementation of these
recommendations has been incomplete, the mere fact
of their existence means more attention is paid to
the effects of social policies on health. This element
is missing in U.S. policy discussions—as is evident
from recent deliberations on income-tax policy.
Although inadequate health care accounts for
only 10% of premature deaths, among the five determinants of health (Fig. 1, not included), health
care receives by far the greatest share of resources
and attention. In the case of heart disease, it is estimated that health care has accounted for half of the
40% decline in mortality over the past two
decades.40 (It may be that exclusive reliance on international mortality comparisons shortchanges the
results of America’s health care system. Perhaps the
11
high U.S. rates of medical technology use translate
into comparatively better function. To date, there are
no good international comparisons of functional status to test that theory, but if it could be substantiated,
there would be an even more compelling claim for
expanded health insurance coverage.) U.S. expenditures on health care in 2006 were an estimated $2.1
trillion, accounting for 16% of our gross domestic
product.41 Few other countries even reach double
digits in health care spending.
There are two basic ways in which health care
can affect health status: quality and access. Although
qualitative deficiencies in U.S. health care have been
widely documented,42 there is no evidence that its
performance in this dimension is worse than that of
other OECD nations. In the area of access, however,
we trail nearly all the countries: 45 million U.S. citizens (plus millions of immigrants) lack health
insurance, and millions more are seriously underinsured. Lack of health insurance leads to poor
health.43 Not surprisingly, the uninsured are disproportionately represented among the lower socioeconomic classes.
Environmental factors, such as lead paint, polluted air and water, dangerous neighborhoods, and
the lack of outlets for physical activity also contribute to premature death. People with lower socioeconomic status have greater exposure to these
health-compromising conditions. As with social determinants of health and health insurance coverage,
remedies for environmental risk factors lie predominantly in the political arena.44
THE CASE FOR CONCENTRATING
ON THE LESS FORTUNATE
Since all the actionable determinants of health—personal behavior, social factors, health care, and the
environment—disproportionately affect the poor,
strategies to improve national health rankings must
focus on this population. To the extent that the
United States has a health strategy, its focus is on the
development of new medical technologies and support for basic biomedical research. We already lead
the world in the per capita use of most diagnostic
and therapeutic medical technologies, and we have
recently doubled the budget for the National
Institutes of Health. But these popular achievements
are unlikely to improve our relative performance on
health. It is arguable that the status quo is an accurate expression of the national political will—a relentless search for better health among the middle
and upper classes. This pursuit is also evident in how
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CHAPTER 1 HEALTH OUTCOMES
we consistently outspend all other countries in the
use of alternative medicines and cosmetic surgeries
and in how frequently health “cures” and “scares”
are featured in the popular media.45 The result is that
only when the middle class feels threatened by external menaces (e.g., secondhand tobacco smoke,
bioterrorism, and airplane exposure to multidrugresistant tuberculosis) will it embrace public health
measures. In contrast, our investment in improving population health—whether judged on the basis
of support for research, insurance coverage, or
government-sponsored public health activities—is
anemic.46-48 Although the Department of Health and
Human Services periodically produces admirable
population health goals—most recently, the Healthy
People 2010 objectives49—no government department or agency has the responsibility and authority
to meet these goals, and the importance of achieving
them has yet to penetrate the political process.
WHY DON’T AMERICANS FOCUS ON
FACTORS THAT CAN IMPROVE HEALTH?
The comparatively weak health status of the United
States stems from two fundamental aspects of its
political economy. The first is that the disadvantaged
are less well represented in the political sphere here
than in most other developed countries, which often
have an active labor movement and robust labor
parties. Without a strong voice from Americans of
low socioeconomic status, citizen health advocacy in
the United States coalesces around particular illnesses, such as breast cancer, human immunodeficiency virus infection and the acquired
immunodeficiency syndrome (HIV–AIDS), and
autism. These efforts are led by middle-class advocates whose lives have been touched by the disease.
There have been a few successful public advocacy
campaigns on issues of population health—efforts to
ban exposure to secondhand smoke or to curtail
drunk driving—but such efforts are relatively uncommon.44 Because the biggest gains in population
health will come from attention to the less well off,
little is likely to change unless they have a political
voice and use it to argue for more resources to improve health-related behaviors, reduce social disparities, increase access to health care, and reduce
environmental threats. Social advocacy in the United
States is also fragmented by our notions of race and
class.33 To the extent that poverty is viewed as an
issue of racial injustice, it ignores the many whites
who are poor, thereby reducing the ranks of potential advocates.
The relatively limited role of government in the
U.S. health care system is the second explanation.
Many are familiar with our outlier status as the only
developed nation without universal health care coverage.50 Less obvious is the dispersed and relatively
weak status of the various agencies responsible for
population health and the fact that they are so disconnected from the delivery of health services. In addition, the American emphasis on the value of
individual responsibility creates a reluctance to intervene in what are seen as personal behavioral
choices.
HOW CAN THE NATION’S HEALTH IMPROVE?
Given that the political dynamics of the United States
are unlikely to change soon and that the less fortunate will continue to have weak representation, are
we consigned to a low-tier status when it comes to
population health? In my view, there is room for cautious optimism. One reason is that despite the epidemics of HIV–AIDS and obesity, our population
has never been healthier, even though it lags behind
so many other countries. The gain has come from
improvements in personal behavior (e.g., tobacco
control), social and environmental factors (e.g., reduced rates of homicide and motor-vehicle accidents
and the introduction of fluoridated water), and medical care (e.g., vaccines and cardiovascular drugs).
The largest potential for further improvement in population health lies in behavioral risk factors, especially smoking and obesity. We already have tools at
hand to make progress in tobacco control, and some
of these tools are applicable to obesity. Improvement
in most of the other factors requires political action,
starting with relentless measurement of and focus on
actual health status and the actions that could improve it. Inaction means acceptance of America’s
poor health status.
Improving population health would be more
than a statistical accomplishment. It could enhance
the productivity of the workforce and boost the national economy, reduce health care expenditures, and
most important, improve people’s lives. But in the
absence of a strong political voice from the less fortunate themselves, it is incumbent on health care
professionals, especially physicians, to become champions for population health. This sense of purpose
resonates with our deepest professional values and is
the reason why many chose medicine as a profession. It is also one of the most productive expressions of patriotism. Americans take great pride in
asserting that we are number one in terms of wealth,
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READING 1: We Can Do Better—Improving the Health of the American People
number of Nobel Prizes, and military strength. Why
don’t we try to become number one in health?
ACKNOWLEDGMENTS
Supported in part by grants from the Robert Wood Johnson and
American Legacy Foundations. The sponsors had no role in the
preparation of the Shattuck Lecture.
No potential conflict of interest relevant to this article was
reported.
I thank Stephen Isaacs for editorial assistance; Michael
McGinnis, Harold Sox, Stephen Shortell, and Nancy Adler for
comments on an earlier draft; and Kristen Kekich and Katherine
Kostrzewa for technical support.
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decrease in U.S. deaths from coronary disease,
1980–2000. N Engl J Med 2007;356:2388-98.
41. Poisal JA, Truffer C, Smith S, et al. Health spending
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44. Isaacs SL, Schroeder SA. Where the public good prevailed: lessons from success stories in health. The
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45. Gawande A. Annals of medicine: the way we age
now. The New Yorker. April 30, 2007:50-9.
46. McGinnis JM. Does proof matter? Why strong evidence sometimes yields weak action. Am J Health
Promot 2001;15:391-6.
47. Kindig DA. A pay-for-population health performance system. JAMA 2006; 296:2611-3.
48. Woolf SH. Potential health and economic consequences of misplaced priorities. JAMA
2007;297:523-6.
49. Healthy People 2010: understanding and improving
health. Washington, DC: Department of Health and
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50. Schroeder SA. The medically uninsured—will they
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R E A D I N G
2
U.S. Disparities in Health:
Descriptions, Causes, and
Mechanisms
race/ethnicity and social class. Finally, we discuss potential pathways, including exposure to chronic stress
and resulting psychosocial and physiological responses to
stress, that serve as mechanisms by which social disadvantage results in health disparities.
Source: Adler NE, Rehkopf DH. U.S. disparities in
health: descriptions, causes, and mechanisms. Annu
Rev Public Health 2008;29:235-52.
ABSTRACT
INTRODUCTION
Eliminating health disparities is a fundamental, though
not always explicit, goal of public health research and
practice. There is a burgeoning literature in this area,
but a number of unresolved issues remain. These include
the definition of what constitutes a disparity, the relationship of different bases of disadvantage, the ability to
attribute cause from association, and the establishment
of the mechanisms by which social disadvantage affects
biological processes that get into the body, resulting in
disease. We examine current definitions and empirical
research on health disparities, particularly disparities associated with race/ethnicity and socioeconomic status,
and discuss data structures and analytic strategies that
allow causal inference about the health impacts of these
and associated factors. We show that although health is
consistently worse for individuals with few resources and
for blacks as compared with whites, the extent of health
disparities varies by outcome, time, and geographic location within the United States. Empirical work also
demonstrates the importance of a joint consideration of
Few terms have had such a meteoric rise into common usage in the health literature as has “health disparities.” In the 1980s this was a key word in only
one article, and in the 1990s there were fewer than
30 such articles. In contrast, during the five years
from 2000 through 2004, more than 400 such articles appeared.3 An equivalent increase occurred in
the number of articles containing the key term of
“health inequalities.” Prior to this time, there was
substantial work on the problem of health disparities,
but it was usually framed in terms of specific factors
such as race or poverty.60
One of the first uses of the term inequality with
respect to health differences was in the title of the
Working Group on Inequalities in Health, which issued the Black Report in Great Britain in 1980. In
advance, it seemed likely that the working group
would find reductions in social class differences in
mortality following the provision of universal health
care through the National Health Service. However,
they found that the gap between the health of low
and high social class individuals had actually
15
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CHAPTER 1 HEALTH OUTCOMES
widened. Around the same time, the Whitehall Study
of British Civil Servants68 revealed significant differences in cardiovascular disease and mortality69 by
occupational level within a population of officebased workers. Notably, differences were not just between those at the top and bottom. Rather, disease
prevalence and mortality increased at each step down
in occupational grade. Spurred by these and other
data, another commission, the Independent Inquiry
into Inequalities in Health, made recommendations
for policies in Great Britain to reduce health inequalities.2
During this period, research on socioeconomic
and racial/ethnic differences in health was also being
conducted in the United States. Beginning in the
1970s, investigators linked death records to socioeconomic data from the Current Population Study, to
the U.S. Census, and to Social Security Administration records. The findings documented at a nationwide level substantially higher age-adjusted
mortality rates for nonwhites, individuals with less
education, individuals with low incomes, and for
some occupational categories.16,58,59 These data and
the British findings provided an impetus to determine the extent and nature of health disparities in
the United States and identify ways to reduce them.
Efforts have included a report from the National
Center for Health Statistics on differences in mortality and morbidity by socioeconomic status,80
Healthy People 2010,100 which established the goal
of eliminating health disparities in addition to the
goal of improving health, and the passage of the
Minority Health and Health Disparities Research
and Education Act of 2000. This legislation established the National Center on Minority Health and
Health Disparities to coordinate activities among the
NIH institutes. The Institute of Medicine recently reviewed the NIH plan and made a number of recommendations to improve its effectiveness.99
As reflected in the dual goals of Healthy People
2010, public health research and practice aim both
to improve health and to eliminate disparities.
Previous papers in the Annual Review of Public
Health have examined substantive and methodological aspects of specific types of disparities. Some reviews concerned measurement issues and health
effects of poverty, class, and/or socioeconomic status(e.g.,1,36,61), of race and ethnicity (e.g.,64,70,105),
and of rural residence.88 None has considered disparities per se. Eliminating disparities requires a clear
definition to allow measurement and monitoring of
progress toward that goal and to understand their
causes. Here we examine the definition of health dis-
parities and empirical findings on disparities associated with race/ethnicity and socioeconomic status.
We then consider methodological challenges and solutions to understanding the causes of health
disparities.
DEFINITION OF HEALTH DISPARITIES
The literature lacks a consensually agreed on definition of health disparities. Healthy People 2010 referenced “differences that occur by gender, race or
ethnicity, education or income, disability, geographic
location, or sexual orientation.”100,p.14 Carter-Pokras
& Baquet17 identified 11 different definitions of
health disparities. Some were inclusive, some limited
disparities to those associated with race and ethnicity, and still others defined it only in terms of disparities in health care.
The various definitions imply and sometimes explicitly suggest the relevant comparison group for
establishing a disparity. Definitions of racial/ethnic
disparities suggest that a group’s health status be
compared with the majority, the population average,
or the healthiest group. Thus, one might compare
African American mortality rates to national rates, to
European Americans who are the majority group in
the United States, or to Asian Americans, who have
in aggregate the lowest mortality rates. Depending on
the relative size and the relative health of the majority group and the healthiest group, one could reach
different conclusions about the extent of a disparity.
With the exception of Murray and colleagues,78
who examined a range of socio-demographic characteristics of groups with markedly different life expectancies, most approaches to disparities start with
bases of social disadvantage, which result in differences that are unjust and avoidable.13,15 Healthy
People 2010 distinguishes between a health difference, which results from inherent biological differences (e.g., only women are subject to ovarian cancer
and men to prostate cancer), and a disparity, which
results from social factors. What constitutes a difference versus a disparity may sometimes be unclear,
however. In the example of ovarian and prostate cancer, differential investment in research on treatment
and prevention of one disease versus the other could
reflect the relative advantage of males versus females.
If men have more power to allocate resources for research and health care and differentially provide
funding for prostate versus ovarian cancer, the
resulting death rates from these diseases could constitute a disparity. This suggests that simple com-
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parisons of mortality rates are not an adequate basis
on which to evaluate health disparities. One also
needs to know the biological potential of each group.
Although women outlive men (a fact pointed to by
some who advocate for more attention to men’s
health as a disparity issue), the gap between current
life expectancy and life expectancy under optimal
conditions could potentially be greater for women
than for men.
Differences in biological potential have been
raised in relation to racial/ethnic health disparities,
suggesting these are differences rather than disparities. However, the contribution of unavoidable biological differences to overall disparities by race/
ethnicity is relatively small. A few diseases (e.g., sickle
cell anemia) have a clear primary genetic basis, but
these are of a limited number and there is little evidence for a differential genetic basis for the many diseases for which disparities occur.75 For example,
African Americans have higher rates of hypertension
than do European Americans, which some attribute
to differential genetic vulnerability. However, prevalence of hypertension among blacks is lower in
Caribbean countries than in the United States and
lower still among blacks in Africa. Hypertension rates
in Africa are, in fact, equivalent to or lower than rates
among whites in the United States.26 These findings
suggest that higher rates of hypertension for blacks in
the United States compared with other racial/ethnic
groups are more likely to be due to social factors than
to underlying biological vulnerability.
Health disparities result from both biological differences and social disparities. We focus on the latter not just because the effect is greater, but also
because they are avoidable and inherently unjust.
EMPIRICAL WORK ON DISPARITIES
The bulk of research has focused either on disparities
due to race/ethnicity or disparities due to social class
and socioeconomic resources. Disparities by gender
and geography have also been investigated, often in
terms of how these factors modify racial/ethnic or
social class disparities. Most research has not invoked an explicit model of disparities and studies are
shaped and constrained by the availability of relevant data. For example, British studies emphasize social class as determined by occupational status using
the Registrar General’s measure of social class. This
measure has been in use for many years and provides
a fine-grained hierarchical ordering of occupations.
Nothing comparable exists in the United States,
17
where national data are more likely to include
race/ethnicity than measures of socioeconomic position. For example, it was not until 1989 that education was added to the U.S. standard certificate of
death, and health records of large population groups
such as those enrolled in Kaiser Permanente often
include only race/ethnicity but not socioeconomic
status (SES). Thus, it has been easier to characterize
racial/ethnic disparities in the United States than
those linked to social class. The data show that
African Americans have higher mortality and poorer
health status than does any other group, as do Native
Americans. Overall mortality rates are surprisingly
higher for non-Hispanic whites than for Hispanics or
Asian Americans; relative mortality varies for specific causes of death.3,94 For 1999-2001, male life
expectancy for U.S.-born blacks and whites was 67.5
and 74.8 years, respectively. Life expectancy for U.S.born Hispanic males (75.2 years) was greater than
for non-Hispanic whites and was greater still for
U.S.-born Asian/Pacific Islanders (78.9 years). The
same pattern is shown for women. For both men and
women, the health advantage of Hispanic and Asians
compared to U.S.-born whites is even greater for recent immigrants in these groups (see Foreign-Born
Populations box).
Intersection of SES and Race/Ethnicity
Some definitions limit disparities to those associated
with race/ethnicity. This focus has been fostered both
by relative availability of data as described above
and by social equity concerns based on current and
historical racism and discrimination. Such a limitation can be problematic, however, given marked differences in the distribution of racial/ethnic groups
across levels of education, income, occupation, and
wealth.29,56 Examining race/ethnicity without simultaneously considering socioeconomic position
can attribute too much influence to race/ethnicity per
se, and may inadvertently foster an emphasis on biological differences. This point is forcefully made by
Isaacs & Schroeder,52 who argue that social class is
the “ignored determinant” of health in the United
States.
Researchers are increasingly looking at how SES
and race/ethnicity function jointly and independently to affect health. Socioeconomic measures often
account for a large part of racial/ethnic differences,
although independent effects of race/ethnicity on
health outcomes also exist, depending on what outcome is examined. Adequate control for SES across
racial/ethnic groups may be difficult to achieve.54
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FOREIGN-BORN POPULATIONS
Place of birth is a critical and frequently ignored component of socioeconomic and racial/ethnic disparities.
To the extent that first-generation immigrants make up
a substantial proportion of a given group’s population
in the United States, immigrants’ health advantage may
contribute to differences between groups. For most
health outcomes (notable exceptions are stomach cancer and liver disease), foreign-born individuals in the
United States have lower rates of disease than do their
native-born peers. Controlling for demographic and socioeconomic factors, immigrant men and women 25
years of age and older had mortality rates 18% and
13% lower, respectively, than did nonimmigrants.95
Immigrants as a group lived 3.4 years longer on average than did those born in the United States in 19992001, an increase over a gap of 2.3 years two decades
earlier.94 The gap was largest for native-born vs. immigrant blacks and Hispanics.
Most analyses of health disparities do not include
birth place and do not account for the generally lower
rates of disease among foreign-born individuals.79 U.S.
Hispanics as a group have lower all-cause mortality
rates than do non-Hispanic blacks or non-Hispanic
whites; a difference that becomes even greater after
controlling for household income. The relatively lower
rates of all-cause mortality among Hispanics as compared with non-Hispanics in the United States have
been well documented, and a large literature investigating the substantive and potentially artifactual reasons for this has emerged (although no clear consensus
has been reached yet).79 Asian Americans, too, show favorable health profiles, with the lowest prevalence of a
number of diseases and the lowest all-cause mortality
rate of any major racial/ethnic group, and the role of
migration processes in these disparities is also an area
of active research.
SES indicators may have different meanings for
different groups. For example, at the same income
level, the amount of wealth and debt differ substantially by racial/ethnic group; Hispanics and
African Americans have lower wealth than nonHispanic whites and Asians at a given income
level.14,24 Similarly, at any given educational level,
these groups have lower incomes than do whites.14
Although some studies “control” for SES by adjusting for an indicator such as education or income,
this adjustment is insufficient given evidence for independent effects of the different domains of SES.
Controlling for a single measure is unlikely to capture the effects of social class per se, and residual
confounding may be erroneously interpreted as
racial/ethnic differences.14,54
Descriptive Findings
A descriptive understanding of socioeconomic and
racial/ethnic disparities is important for (a) understanding both long- and short-term trends in health
disparities, (b) informing causal investigations of
health disparities, (c) targeting resources for prevention and treatments to reduce disparities in specific
diseases, and (d) increasing public awareness of the
existence and characteristics of health disparities.
Below we briefly consider descriptive data regarding
mortality disparities, cause-specific disparities, geographic variation in disparities, and time trends in
these disparities.
All-cause mortality. The first U.S. study with a
sample size sufficient to allow the examination of
socioeconomic disparities within race/ethnicity based
on individual-level data was done by Kitigawa &
Hauser,58 although data constraints limited comparisons to whites and nonwhites. Using data from
the 1960 matched records of persons age 25 and
over, they documented that compared with whites,
age-adjusted all-cause mortality rates for nonwhites
were 34% higher for females and 20% higher for
males, correcting for net census undercount. They
also examined mortality by education, occupation,
income, and geographical location. For white men
and women ages 25-64 mortality was respectively
64% and 105% higher for the least compared with
the most educated. For nonwhite men and women
the comparable difference in mortality by education
was 31% and 70%, respectively. Pappas et al.81 revisited this work, with data from 1986, showing a
relatively sharper decrease in mortality over this time
period for higher-income and more-educated individuals, thus creating greater relative disparities by
income and education overall and within racial/
ethnic groups over time. This and other work also
highlights the importance of disparities based on social class for both women and men, despite some
earlier work that suggested smaller social class disparities among women.72
In addition to dichotomizing race into white and
nonwhite, earlier U.S. research generally dichotomized income into below versus above the poverty
line. Publication of the Whitehall study inspired researchers to see if SES formed a graded association
with health in the United States, as it did in England.
Multiple studies have now demonstrated SES gradients by income and by education for a range of
health outcomes including mortality, incidence of
cardiovascular disease, arthritis, diabetes, asthma,
cervical cancer, depression, and disability in children, adolescents, and both younger and older
adults.4,22,43,76 Although these associations occur
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across the distribution, they are generally stronger
at the lowest levels of income and education.8,33,91
Cause-specific mortality. Studies uniformly find
higher all-cause mortality for blacks than for whites
under age 65, but within this overall trend there is
heterogeneity by cause of death. For example, data
from the National Longitudinal Mortality Study
(NLMS) of 1.3 million persons89 reveal a racial/
ethnic difference for mortality from many but not
all diseases. Black and white men under age 65 had
approximately the same standardized mortality ratio
(SMR) for ischemic heart disease, whereas (in order
of magnitude of difference) black men had substantially higher SMRs than did whites for homicide, hypertensive heart disease, esophageal cancer, and
pulmonary circulation but had relatively lower SMRs
for aortic aneurysm, suicide, leukemia, and chronic
obstructive pulmonary disease (COPD). Black
women had substantially higher rates of homicide,
hypertensive heart disease, diseases of pulmonary circulation, nephritis, and stomach cancer than did
white women, with comparatively lower levels of
suicide, COPD, and leukemia.
Howard et al.51 also used data from the NLMS
and found that SES accounted for different amounts
of black-white mortality differences depending on
the cause of death. For men, SES accounted for 30%55% of the black-white mortality differences for accidents, lung cancer, stomach cancer, stroke, and
homicide, but less than 17% of the differences for
prostate cancer, pulmonary disease, and hypertension. For women, SES accounted for 37%-67% of
differences for accidents, ischemic heart disease, diabetes, and homicide, but less than 17% for hypertension, infections, and stomach cancers. However,
only income and education were used as SES controls, which could underestimate the contribution of
SES to black-white mortality differences. Kington &
Smith57 found that with more complete demographic
controls including wealth, racial/ethnic differences
in functional limitation in health of older individuals
were eliminated, although differences remain for
other chronic diseases.
Wong et al.106 also studied the contribution of
education and race/ethnicity to different causes of
death. Whereas many causes of death contributed in
a similar way to both racial/ethnic and educational
disparities in mortality (e.g., cardiovascular disease,
liver disease), other causes were responsible for
greater educational differentials (e.g., cancer, lung
disease) or greater black-white differences (e.g., hypertension, lung disease, homicide).The data from
these studies show that although the direction of disparities is fairly consistent, the extent of socioeco-
19
nomic and racial/ethnic disparities and their interactions differ substantially by cause.
Geographic variation. Although marked differences in mortality rates across the United States
have been noted, the extent to which socioeconomic
factors and race/ethnicity explain these variations
had not been adequately studied. However, data
from within metropolitan areas reveal a geographic
variation that can be substantially explained by considering these factors. These data also suggest that
differences in local socioeconomic conditions have a
greater impact on African American mortality than
white mortality, resulting in an interaction between
socioeconomic factors and race/ethnicity with respect
to geography.23,98 This is consistent with data from
the NLMS89 showing that the locations with the lowest mortality rates for whites and for blacks were at
an equivalent level, even as overall rates were higher
for blacks. These studies of geographic differences
show the importance of area context for disparities
and note that relationships among race/ethnicity,
class, and health are not fixed, even within the United
States during a given time period.
Changes in disparities over time. The magnitude of disparities in mortality by race/ethnicity and
by SES have changed over time, providing further
evidence that these disparities are changeable and
preventable. Preston & Ilo86 confirmed Pappas’s
finding of increasing education gradients for all-cause
mortality for men since 1960 but also found that education differentials in mortality declined for women
25-64 and remained stationary for women 65-74.
Ward et al.104 examined disparities in cancer mortality by race/ethnicity 1975-2000. Prior to 1980 investigators saw no black/white disparities in breast
cancer mortality among women and saw slightly
higher rates of colorectal cancer mortality among
white as compared with black men. But this changed,
and by 2000, black women had higher breast cancer
mortality than did white women and black men had
higher colorectal cancer mortality than did white
men. The black-white gap in overall life expectancy
decreased from 1975 to1984, increased from 1984 to
1992-1994, then decreased again through 2004.48
Most of these changes stemmed from relative improvements for blacks in specific causes of death
(e.g., relatively greater decreases from 1994 to 2004
in homicide and unintentional injuries for both sexes
and for HIV for men and heart disease for women).
Disparities in risk factors for disease have also
changed over time. For example, Zhang & Wang108
examined obesity rates among U.S. women 20-60
years old from 1971 to 2000 using data from the
National Health and Nutrition Examination Survey
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CHAPTER 1 HEALTH OUTCOMES
(NHANES). Owing to rapid increases in obesity
prevalence among all educational groups, education
disparities actually decreased, although all groups
were worse off. These results highlight the importance of overall population trends for assessing
progress in reducing health disparities.
Changes in disparities over the life course. The
extent and nature of health disparities changes over
the life course. Substantial disparities begin at birth;
babies born to mothers who are poor, have lower education, and/or are African American are smaller at
birth and are more likely to die within the first year
of life. Disparities are smallest during childhood, adolescence, and early adulthood and greatest in middle
age, becoming weaker again in older populations.5
The primary explanation for diminished disparities
in older populations is that the least healthy individuals are no longer in the population, and mortality
will eventually be experienced by all regardless of socioeconomic status and race/ethnicity. Although selection over time can produce artifactual population
patterns,102 the proportion of the narrowing of disparities explained by selection is unclear. There may
also be etiologic reasons, including the provision of
safety net supports such as Social Security and
Medicare, which are available to older adults and
may reduce and/or buffer the effects of disadvantage.
Variation by measure of SES. Occupation, income, and education have different associations with
health outcomes.58,89 As currently operationalized,
education and income are generally more strongly associated with health in U.S. data than are measures of
occupation other than employed versus nonemployed.
However, weaker associations with occupation may be
due to the use of standard U.S. occupational measures.14 Using a classification based on the new U.K.
national statistics social class measure—which categorizes individuals as managers/professionals, intermediate, small employers and self employed, lower
supervisory and technology, and semiroutine/routine
or not in labor force—Barbeau et al.9 found occupational associations with current smoking status as
strong as those with education or income. Variations
by SES measure used speak to the frequent recommendation of using discrete measures of SES such as
education or income rather than a composite.32 In addition to empirical reasons, use of specific SES measures clarifies intervention possibilities.
UNDERSTANDING THE NATURE AND
CAUSES OF DISPARITIES
General patterns of disparities over the late twentieth century in the United States are similar: Those
with fewer resources have worse health outcomes for
a number of different causes. But variations by health
outcome, place, time, and age point to the fact that
these associations are not fixed or immutable, and
that this heterogeneity should be used to better understand the causes of disparities. Kunitz63 places
links between distribution of resources and health
within particular historical, socioeconomic, and cultural contexts. Given these variations, a deeper understanding of off-diagonals may be informative
about the nature of disparities. This analysis would
include diseases that do not show disparities or are
more prevalent in more advantaged groups (e.g.,
black-white differences in kidney function and socioeconomic differences in breast cancer). It would
also include those who do not show expected patterns such as immigrants, low-SES individuals in
good health, and high-SES individuals in poor
health. Finally, international comparisons of socioeconomic disparities highlight the importance of
national contexts for understanding the nature of
health disparities.
Establishing Causality
There are clearly documented associations of SES
and health outcomes, but the causal link is still debated. Some questions are methodological, dealing
with alternative explanations for the associations.
Others are concerned with the nature of the mechanisms by which these upstream factors influence
health. SES is unlikely to affect health directly (e.g.,
having more dollars in one’s pocket is not health protective). Rather, it shapes life conditions that, in turn,
influence health. In this section we first consider the
methodological challenges to understanding causes
of health disparities and then consider potential
mechanisms by which SES may affect morbidity and
mortality.
Methodological challenges—alternative explanations. When asserting that a measure of SES leads
to sub-optimal health and premature mortality, researchers must address possible alternative explanations for the associations that are found.42,45 The
first possibility is that associations result from random chance; this possibility can be assessed by specifying confidence intervals around the effect estimate
or p-values. Second, associations may be due to conditioning on an effect of the exposure and outcome
occurring either through the selection of the sample
(i.e., selection bias) or through use of inappropriate
control variables.42,50 Avoiding this possibility requires using a causal understanding of the process
that created the data to inform sample selection and
an appropriate choice of control covariates.
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A third challenge is that the presumed health
outcome may cause the exposure (reverse causation
or health selection bias).58,96 For example, illness
may prompt individuals to decrease work hours,
change to less demanding and lucrative jobs, or leave
the labor force entirely. Using data from the Health
and Retirement Study of individuals over the age of
50, Smith96 found that wealth decreased by $17,000,
and earnings by $2,600 per year with the onset of
major disease. Collecting measures of income that
predate the health assessment through longitudinal
designs, data linkage or retrospective earnings recall
can decrease reverse causation potential between income and health. Using a lagged approach with longitudinal data, McDonough et al.71 found little
difference in predicting all-cause mortality between
a one-year lag and a five-year lag, thus questioning
the importance of reverse causation for explaining
the mortality associations. Using another approach
to account for health selection, Benzeval & Judge10
controlled for initial health status in addition to using
measures of income prior to disease onset, and the associations between income and health outcomes
remained.
There is less reason for concern about reverse
causation between education and health. Generally
the temporal lag between education exposure and
adult health outcomes argues against adult health
impacting education.58 However, childhood illnesses
and low birth weight may contribute to lower educational attainment.18,25 These factors are themselves
a function of SES. Haas46 demonstrated that disadvantaged social background led to sub-optimal
health in childhood, which made a subsequent impact on adult social class.
Overall, although health can affect SES, SES significantly affects health. The extent of reciprocal influence for specific outcomes is generally not
understood. Longitudinal data with health, education, income, labor force participation, and wealth
measures over time can more accurately model the
process of social stratification and the extent to
which causation and selection impact specific health
outcomes at different points in the life course.
A fourth concern is whether associations result
from the joint association of SES and health with a
common underlying cause such as genetic factors,
time preferences/delayed gratification,39 or cognitive
ability. 44 As with reverse causation, these confounders may themselves reflect SES. Early family
environments affected by parents’ education and income may shape all three of these potential confounders, including the extent to which genetic
potential is realized through epigenetic processes. As
evidence of the importance of SES and child envi-
21
ronments for adult health increases, rather than viewing these factors as undermining evidence for the importance of socioeconomic factors on health, they
should be viewed as part of the dynamic process between SES and health over the life course.
Data structure and methods. In addition to collecting appropriate data to control for potential alternative explanations in regression models, several
types of data structures can also facilitate better determination of causal relationships and help rule out
alternative explanations for observed correlations.
True experiments are rare because individuals cannot
easily be randomly assigned to levels of education, income, or occupation. However, experimental trials of
interventions that modify some aspect of SES or factors associated with it are informative. Researchers
have also taken advantage of natural experiments to
assess the effects of economic or policy changes that
affect an individual’s SES but are not due to his or her
own characteristics or behaviors. These reduce confounding and allow for a more easily conceptualized
counterfactual.45 Relevant examples include using
German reunification to estimate the effects of income on health,38 changes in the Earned Income Tax
Credit to estimate the effects of household income
on children’s test scores,28 enactment of schooling
laws to estimate the effects of education on mortality,66 and changes in legislation affecting Social
Security benefits to estimate the effects of income on
mortality in an older population.97 With the exception of the Social Security payments, these studies
confirm the effects from observational studies of socioeconomic factors to health.
Data with repeated measures on individuals over
time also provide some strength for making causal
claims.87 Repeated measures allow observation of
the temporal sequence of cause and effect. Birth cohorts provide particularly rich data for modeling
early life confounders and exposures of interest.
Three British studies of representative samples of
children born in 1946, 1958, and 1970 have provided critical data about the causes of health disparities and have shown the impact on adult health and
behaviors of early life exposures and socioeconomic
position at different points in life.84,103 Using data
from the 1958 cohort, Power at al.85 found a number of causes of health inequalities at age 33, including class at birth, socioemotional adjustment,
educational level, and psychosocial job strain. In the
absence of a birth cohort, follow-up of members of
completed studies of children and adolescents can
provide some of the same advantages.41
Analytic approaches. In addition to the design
approaches described above, new analytic methods
are facilitating a better understanding of the causes
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CHAPTER 1 HEALTH OUTCOMES
of health disparities. Five methods that may be particularly useful are propensity score matching, instrumental variables, time-series analysis, causal
structural equation modeling, and marginal structural models.
Propensity scores provide an analytical method
for balancing factors associated with being in either of the analytical comparison groups of interest
in a particular study (e.g., high versus low education). If assumptions are met it allows for unbiased
causal estimates of the exposure under study.27,90
They have been used to identify the effects of gun violence exposure on subsequent violent activity,11
neighborhood characteristics on dropping out of
high school,47 and neighborhood socioeconomic environment on cardiovascular mortality.30 This approach is based on the same principle as adjusting
for confounders in a regression model and similarly
requires all confounders be measured. However,
they facilitate assessment of whether overlap of confounding variables actually allows one to compare
the analytic groups of interest appropriately, and
they also provide power to control for a larger number of confounding covariates.
Instrumental variables (IV) offer advantages
when analyzing data from natural experiments or
similar designs. The crucial assumption is the availability of a variable (the instrument) that does not directly affect the outcome but is only associated with
the predictor of interest, and where the exposure (instrument) is not itself influenced by known confounders.7 This approach has been used to show
causal effects of income on health outcomes34 and to
demonstrate the effect of years of schooling on allcause mortality.66
Time-series analyses are particularly helpful for
evaluating policy changes or other population exposures by analyzing the variation in health outcomes
over time, while allowing investigators to identify
and remove temporal autocorrelation and also account for lag effects between exposure and outcome.
Particularly useful are data from multiple locations
with different temporal ordering of the exposure to
remove more general temporal trends. This approach
has been used to demonstrate the effects of unemployment on alcohol abuse19 and on very low birth
weight20 and to examine trends in black-white disparities over time.65
Structural equation models have been used extensively in the social sciences to understand complex
relations between variables and to test relationships
among hypothesized causes, mediators, and outcomes. Despite controversy, work over the past two
decades by Pearland others82,83 has clarified the con-
ditions under which the models may be used to represent cause. A significant innovation for gaining this
understanding is the use of directed acyclic graphs
(DAGs), a graphical language for describing causal
relations. These form a framework for representing
assumptions about elements of the causal pathways
from social exposures to outcomes and information
about possible confounders. Explicit delineation of
the proposed causal structures through DAGs allows
other researchers to evaluate the assumptions made
and to build on the proposed structures. These models facilitate identification of valid empirical tests of
proposed causal models.31 This is helpful in testing
proposed mediators between social class and
health.55 A causal structural modeling approach
using DAGs is also mathematically equivalent to
marginal structural models,82 which allow (when assumptions are met) a determination of the overall
causal effect of an exposure within a framework
based on treating unobserved counterfactuals as
missing data.101
Chandola et al.21 used this approach with data
from the 1958 British Birth Cohort to examine the
relative contributions of six different pathways connecting education and health. The structural model
included factors at age 7 (cognitive ability, father’s social class), age 16 (adolescent health), age 23 (education), age 33 (adult social class, sense of control,
healthy behaviors), and age 42 (adult health). It
showed no direct effect of education on adult health
but showed significant effects through adult social
class, control, and behaviors, with differences by gender in the strength of pathways.21 A similar approach
was taken by Mulatu & Schooler77 in examining the
relative strength of behavioral and psychosocial pathways between SES and health.
Pathways and Mechanisms
Much recent research has attempted to explicate the
pathways and the mechanisms by which SES influences health. Although few studies have explicitly
tested these through structural equation models, the
studies provide many candidates. Physical and social environments, including a person’s home, school,
work, neighborhood, and community, vary by SES
and affect the likelihood of individuals’ exposure to
both health-damaging conditions and healthprotecting resources. Health-damaging exposures
within these pathways include early life conditions,
inadequate nutrition, poor housing, exposure to lead
and other toxins, inadequate healthcare, unsafe
working conditions, uncontrollable stressors, social
exclusion, and discrimination.5,6,105
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Some of the exposures listed above have direct
effects on health, whereas others may influence psychological dispositions and behaviors that have
health consequences. A vast literature demonstrates
the contribution of psychosocial and behavioral
factors to morbidity and mortality. These factors
include cognition and emotion (e.g., depression,
hopelessness, hostility, and lack of control) and behavior (e.g., use of cigarettes, alcohol, and other
substances). Gallo & Matthews40 observed that
substantial evidence links negative emotions with
many health outcomes and links SES with negative
emotions, but few studies have analyzed these pathways together. For example, hostility and hopelessness are strongly predicted by childhood
socioeconomic position49 and are linked, in turn, to
poorer health.12,37,40 However, the extent to which
the links between childhood SES and adult health
are accounted for by hostility and hopelessness has
not been determined.
The few studies that have considered mediation
by psychosocial factors provide supportive findings,
but these have used regression rather than structural
equation models. For example, Marmot et al.67 examined the role of sense of control over one’s work
in explaining health disparities within the Whitehall
sample. The higher the grade of the civil servants,
the more control they experienced in relation to their
work conditions. Consistent with hypothesized mediation, the association of occupational grade with
health was substantially reduced when adjusted for
sense of control.
A common element in many of the proposed
mechanisms linking SES to health is differential exposure to stress. Disadvantaged environments expose individuals to greater uncertainty, conflict, and
threats for which there are often inadequate resources to respond effectively. These experiences cumulate to create chronic stress. Until recently, stress
research focused primarily on acute stress, which is
more easily modeled in the lab, and was based on a
model of homeostasis. The development of the model
of “allostatic load” (AL)73 provided a major conceptual advancement to understand health disparities. This model posits that the body does not simply
reestablish homeostasis after experiencing a perturbation associated with a stressor. Rather, with repeated exposures, set points for various systems
involved in the stress response, including the endocrine, metabolic, cardiovascular, and immune systems, may shift. Although the body may be in
balance, the systems become burdened and dysregulated by the costs of the repeated adaptation cycles.74
Precise ways to assess AL are still being developed,
23
but early findings suggest that it is a useful approach.
Seeman et al.92,93 assessed AL in terms of 10 dysregulation indicators in a sample of older adults who
had no major diseases at baseline. AL scores were
higher in those with less education and predicted
subsequent decline in physical and cognitive functioning, new cardiovascular disease, and seven-year
mortality. Using data from the Normative Aging
Study, Kubzanksy et al.62 also found higher AL
among those with less education and further found
evidence that the effect was partially mediated by
hostility.
Although the effects of chronic stress cumulate
over time, the biological manifestations may be seen
relatively early in life. Evans35 found that children
from disadvantaged environments had higher AL
than did children from more affluent backgrounds,
and one indicator of AL was found in structural
equation models to mediate the impact of poorer
housing conditions on illness-related school
absences.53
These examples are a few of thousands of studies on a variety of potential mechanisms and pathways. Most of these have not been linked
specifically with health disparities but provide detailed information on different levels of cause that
could result in disparities. Data sets with adequate
measures of socioeconomic factors and race/
ethnicity, potential psychosocial and biological
mechanisms, and health outcomes are necessary to
best understand pathways. These then can be analyzed using techniques such as causal structural
models that allow modeling and testing of multiple
direct and indirect pathways to health outcomes
that are the bases of disparities.
CONCLUSION
Substantial health disparities exist in the United
States by social class and race/ethnicity. It would,
of course, be preferable to eliminate disparities by
addressing the root causes, changing the inequitable resource distribution that now accompanies SES and race/ethnicity as well as other bases of
disparity. For effective policy development...
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