FRBSF Economic Letter
98-29; October 2, 1998
Income Inequality and Mortality Risk in the United States:
Is There a Link?
Rapid growth in income inequality in the United States over the past
20 years has raised numerous concerns among policymakers. One of the more
disturbing is the possible link between income inequality and mortality.
The U.S. income distribution is currently among the most unequal in the
industrialized world, and life expectancy in the U.S. lags behind that
of any developed countries. Recent research suggests that these two occurrences
may be linked--that the unequal distribution of income in the U.S. affects
the health of the populace.
This Economic Letter discusses the mechanisms by which inequality
may affect life expectancy, reviews briefly the empirical literature on
income inequality and mortality, and reports on recent research by Daly,
Duncan, Kaplan, and Lynch (hereafter DDKL), which highlights the importance
of using disaggregated measures of income inequality and comparisons over
time to describe fully the link between income inequality and health in
the United States.
Although the literature on this topic is relatively new, a few patterns
have emerged. Overall, the evidence suggests that there is an association
between inequality and mortality across states in the U.S. However, data
that follow states over time indicate that the association may be weaker
than is indicated by point-in-time estimates. In addition, the correlation
appears to be based almost entirely on inequality induced by deterioration
at the bottom of the income distribution rather than by improvements at
Why income inequality might affect life expectancy
Repeated examinations of empirical evidence have shown that an association
exists between the level of inequality in the distribution of society's
resources and the mortality risk in that society. However, the reasons
for this association are not at all certain.
For the most part, the explanations for the observed association fall
into two categories: economic and psychosocial. The economic explanations
rest on the premise that at the individual level, the relationship between
mortality and income is nonlinear; that is, if inequality in the income
distribution produces unequal access to commodities--such as education,
health care, and police protection--the negative effects on those at the
bottom of the distribution will not be offset by positive outcomes for
those at the top of the distribution. Moreover, the negative health outcomes
of an unequal income distribution may not be limited to the portion of
the population with fewer resources. Differential access to resources
and services may result in less effective preventive health care (e.g.,
childhood vaccinations), more costly disease control (e.g., tuberculosis
treatments), or higher crime rates, affecting the health and mortality
risk of the entire population.
The psychosocial hypothesis suggests that it is relative income position
itself that matters for life expectancy. Under this hypothesis, income
inequality and mortality risk are linked through the effects of emotional
and psychological stress on health. The theory posits that levels of depression,
isolation, insecurity, and anxiety, which are known correlates of mortality,
are associated with relative economic position. In addition, some argue,
the psychology of inequality damps many of the behaviors that may reduce
stress and anxiety, such as participation in voluntary organizations or
community groups and investment in ongoing education and training.
Which of these two pathways, if either, connects aggregate income inequality
to individual health outcomes is an empirical question that researchers
are only beginning to investigate. To date, empirical research on mortality
and inequality has been focused less on identifying the causal pathways
and more on establishing a basic relationship between the two.
Empirical evidence of an association
The potential connection between income inequality and mortality is best
known from the work of Richard Wilkinson. In a series of papers he related
income inequality to life expectancy across OECD countries and found striking
negative associations that persisted even after controlling for cross-country
differences in median income (e.g., Wilkinson 1996). Following Wilkinson,
a number of scholars (Kaplan, et al., 1996, Kennedy, et al., 1996, and
Lynch, et al., 1998) documented significant associations between mortality
rates and inequality across states and metropolitan areas within the U.S.
Like Wilkinson, these researchers found significant associations between
income inequality and health even after controlling for income level.
Although the results from these studies point to a strong link between
income inequality and mortality risk, a number of unanswered questions
remain. One of the most important is whether researchers have successfully
isolated an independent effect of income inequality. Although cross-sectional
correlations typically include controls for population characteristics,
such as average household size, per capita income, and racial composition,
there are many more potentially important variables that are not easily
measured or easily included in the analysis. If these important variables
are omitted from the analysis, cross-sectional correlations may overstate
the linkage between inequality and mortality. One way to control for these
unmeasured factors is to estimate a "fixed effects" model in which changes
in inequality within states are related to changes in mortality within
those states. Models of this type difference out effects of persistent
characteristics (both measurable and unmeasurable) that may lead to spurious
Another important question is whether increases in inequality reduce
life expectancy even if the inequality increase is due to the "rich getting
richer" rather than the "poor getting poorer." For example, in theory,
increasing the affluence of the rich could have either detrimental or
beneficial health consequences for the remainder of the population. Beneficial
consequences could arise from positive externalities created by wealthy
individuals, such as advanced medical technology, better schooling, or
more crime prevention. In contrast, increasing the wealth of richer families
could negatively affect health outcomes by increasing economic segregation
and crowding out the concerns of the poor. Given that most of the recent
increase in inequality in the United States has been associated with income
growth among the middle and upper levels of the income distribution, rather
than with income losses among the poor, documenting how and when income
inequality affects mortality is important.
Recent research on the inequality-mortality
Recent research by DDKL provides evidence on the relevance of these issues
in evaluating the mortality-inequality linkage. DDKL, like others, examine
correlations between state-level income inequality and mortality using
data from the National Center for Health Statistics Compressed Mortality
File and the 1980 and 1990 decennial censuses. All analyses are age-adjusted
and control for the median level of household income in the state. As
a measure of overall income inequality, DDKL compute the ratio of the
90th to 10th percentiles of state household income. The goal of the analysis
is to document the difference between state-level correlations obtained
from point-in-time versus over-time estimation, as well as from overall
measures of inequality versus disaggregated ones. The remainder of the
Letter summarizes their results.
Isolating the effect of inequality
In keeping with previous research, DDKL find a strong correlation between
state-level income inequality and age-adjusted state mortality rates in
both 1980 and 1990. The average correlation for these two years is shown
in the first bar of Figure 1.
However, as noted previously, these simple point-in-time estimates may
not accurately reflect the independent role of income inequality. A stricter
test of the inequality-mortality association is represented by the second
bar which reports the correlation between changes in inequality
and mortality, by state, from 1980 to 1990. As the figure indicates, controlling
for potentially unmeasured state-specific characteristics reduces the
correlation between income inequality and mortality by about one-third.
This suggests that some portion of the inequality-mortality association
captured in the cross-sectional analysis most likely is attributable to
a third factor, such as industrial structure, for which inequality is
a good proxy.
To decompose the effect of overall inequality into inequality associated
with deprivation at the bottom versus affluence at the top, DDKL use two
detailed measures of dispersion. The first is an affluence-sensitive indicator
that measures inequality at the high end of the income distribution as
the ratio of the 90th percentile to the 50th percentile of state household
income. The second detailed measure is a poverty-sensitive indicator and
is computed as the ratio of the 50th percentile to the 10th percentile.
The remaining two bars in the figure report the results of over-time
estimates of the correlation between changes in state-level mortality
and changes in the disaggregated measures of household income inequality.
Comparing the last two bars in the figure indicates that the strength
of the association between income inequality and mortality is driven by
income dispersion in the lower half of the income distribution. The poverty
sensitive measure of income inequality is strongly associated with higher
state mortality rates, implying that the deeper the poverty in a state,
the higher the state mortality rate. In contrast, the affluence-sensitive
measure shows that dispersion in the upper half of the income distribution
has almost no association with state mortality rates.
In general, these results support the economic hypothesis of the link
between income inequality and mortality. The fact that mortality correlations
are stronger for measures that stress the depth of poverty rather than
the height of affluence suggests that actual deprivation, not relative
economic position, determines the relationship. However, these results
do not imply that the effects of prolonged inequality are confined to
those in the lower part of the income distribution. In fact, these findings
support theories that emphasize spillover effects of increased poverty--for
example, if the health care system becomes overburdened or if the general
health of the population is affected by increased anti-social behavior
that might accompany the deepening poverty.
Rapid growth in income inequality in the United States over the past
two decades has prompted many to question the wisdom of allowing an unequal
income distribution to persist in an industrialized nation. A growing
literature on the links between income inequality and mortality has enhanced
such concerns. Although more research is required to understand fully
how income inequality affects mortality, the results presented here suggest
that policies targeted at increasing the incomes of the poor are likely
to have a larger effect on mortality risk than policies designed to reduce
inequality more generally.
Mary C. Daly
Professor of Education and Social Policy
Daly, M.C., G. Duncan, G.A. Kaplan, and J.W. Lynch. 1998. "Macro-to-Micro
Linkages in the Relationship between Income Inequality and Mortality."
Milbank Quarterly 76, pp. 315-339.
Kaplan, G.A., E.R. Pamuk, J.W. Lynch, R.D. Cohen, and J.L. Balfour. 1996.
"Inequality in Income and Mortality in the United States: Analysis of
Mortality and Potential Pathways." British Medical Journal 312,
Kennedy, B., I. Kawachi, and D. Prothrow-Stith. 1996. "Income Distribution
and Mortality: Cross Sectional Ecological Study of the Robin Hood Index
in the United States." British Medical Journal 312, pp. 1,004-1,007.
Lynch, J.W., G.A. Kaplan, E.R. Pamuk, R.D. Cohen, K.E. Heck, J.L. Balfour,
I.H. Yen. 1998. "Income Inequality and Mortality in Metropolitan Areas
of the United States." American Journal of Public Health 88 (7)
July, pp. 1,074-1,080.
Wilkinson, R.G. 1996. Unhealthy Societies:The Afflictions of Inequality.
Opinions expressed in this newsletter do not necessarily reflect
the views of the management of the Federal Reserve Bank of San Francisco
or of the Board of Governors of the Federal Reserve System. Editorial
comments may be addressed to the editor or to the author. Mail comments
Federal Reserve Bank of San Francisco
P.O. Box 7702
San Francisco, CA 94120