Explaining Divergent Levels of Longevity in High-Income Countries (2011) / Chapter Skim
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9 The Role of Inequality
9 The Role of Inequality
Pages 117-141
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From page 117... ...
. The fundamental cause idea emphasizes that fact that there are many mechanisms through which social status creates social inequality in health.
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From page 118... ...
MEASURING THE ASSOCIATION BETWEEN SOCIOECONOMIC INEQUALITY AND MORTALITY The association between indicators of socioeconomic status, such as income and education, and mortality implies that the distribution of socioeconomic status within a country could affect mortality -- in particular, that two countries with the same average income or education could have differences in health and mortality if income or education were differentially distributed. For instance, a country with greater income inequality -- with more wealthy but also more poor people -- may have worse average health and greater average mortality because the health benefits to the wealthy from their extra income are outweighed by the health deficits experienced by the poor.
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From page 119... ...
. Identifying the causal paths linking socioeconomic status to health and mortality remains an important objective for determining appropriate policy to address differentials in health and mortality, but this objective is beyond the scope of this volume (for extended discussion, see Kawachi et al., 2010)
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From page 120... ...
RELATIONSHIP BETWEEN OBSERVED SOCIOECONOMIC INEQUALITY AND HEALTH AND MORTALITY Many studies have looked at the relationship between socioeconomic status and health and mortality in either one or a number of countries. They have almost invariably found that people at lower socioeconomic levels have poorer health on many dimensions (see the review in Elo, 2009)
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From page 121... ...
Specific causes of mortality also have been linked to socioeconomic status. For example, one massive study looked at mortality from ischemic heart disease in millions of people in 10 Western European populations.
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From page 122... ...
. Because racial differences in mortality reflect largely socioeconomic differences and because more data are available in the United States by race than by socioeconomic status, an
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From page 123... ...
In addition, even though there appears to have been a growing inequality in mortality in the United States by socioeconomic status in recent years, this does not appear to be due to a widening of inequality by race. The findings of two recent studies of mortality trends reinforce these conclusions.
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From page 124... ...
124 Relative Index of Inequality 5.0 4.5 4.0 3.5 3.0 Male 2.5 Female 2.0 1.5 1.0 0.5 France Poland Finland USA all Estonia Norway Sweden Belgium England Hungary Slovenia Denmark Lithuania USA whites USA blacks Switzerland Czech Republic FIGURE 9-1 U.S. life expectancy at age 50 by race and gender, 1980-2006.
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From page 125... ...
An examination of self-reported health and mortality versus socioeconomic status in 22 European countries found that in almost every country, lower socioeconomic status was associated with poorer health and higher mortality. However, the size of the differences varied greatly from country to country.
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From page 126... ...
. From the early 1960s to the late 1980s, Japan had the narrowest income differentials among all industrialized countries, and it has been suggested that smaller differentials in health by socioeconomic status in Japan may have resulted from this low level of inequality (Marmot and Davey Smith, 1989; Shibuya et al., 2002; Wilkinson, 1994)
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From page 127... ...
men in the highest education group is higher than that in the European countries, while life expectancy in the lowest education group is identical. Women in each educational grouping in the United States have lower life expectancy than the average for European TABLE 9-2 Life Expectancy at Age 65 (Years)
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From page 128... ...
Educational level was used as a measure of socioeconomic status. The authors chose to use education as the basic index of socioeconomic status because it is relatively easy to measure, it can be made closely comparable from country to country, and it is much less susceptible to the problem of reverse causation than income or wealth.
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From page 129... ...
High Ed. Overall Rate % Low % Middle % High PAFc United States, all 1,840 1,339 885 1,379 20 54 26 39 United States, whites 1,779 1,316 876 1,334 19 54 27 38 United States, blacks 2,264 1,658 1,198 1,903 32 55 14 39 Finland 1,700 1,410 942 1,528 49 30 22 41 Sweden 1,151 953 706 1,026 40 43 16 33 Norway 1,498 1,194 873 1,272 30 48 22 33 Denmark 1,659 1,400 982 1,508 43 38 19 37 England/Walesd 1,128 786 652 1,074 83 7 10 39 Belgium 1,590 1,264 999 1,480 61 22 17 32 Switzerland 1,477 1,123 831 1,165 20 56 24 30 France 1,285 955 624 1,132 50 37 13 51 aRates are directly standardized to the U.S.
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From page 130... ...
High Ed. Overall Rate % Low % Middle % High PAFc United States, all 1,142 839 588 888 20 61 19 36 United States, whites 1,099 818 583 856 18 62 20 34 United States, blacks 1,399 1,091 765 1,197 30 57 13 39 Finland 794 631 528 735 51 29 20 26 Sweden 657 534 402 589 41 40 19 32 Norway 801 616 484 697 36 47 17 31 Denmark 1,037 814 664 960 53 28 19 29 England/Walesd 670 472 394 652 87 8 5 40 Belgium 801 628 582 766 67 19 14 22 Switzerland 657 523 472 591 40 53 7 19 France 530 387 334 492 62 28 10 31 aRates are directly standardized to the U.S.
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From page 131... ...
In short, among the most highly educated people, white men in the United States had mortality rates that compared favorably with those of men in some countries in Western Europe, while white women had rates that were higher than those of women in most of the Western European countries, and blacks had mortality rates worse than all of the comparable groups in Western Europe (Avendano et al., 2010)
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A second way of describing the effect of socioeconomic status on a country's mortality rates is to calculate the population attributable factor (PAF)
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WHAT CAN BE LEARNED FROM GEOGRAPHIC INEQUALITY? The discussion in the previous section provides evidence for evaluating the role of differences in socioeconomic status as a source of the gap in life expectancy between the United States and other countries.
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From page 134... ...
These studies suggest rising geographic inequality in mortality in recent decades, again particularly for women, but their results include mortality across the age range, and they do not compare changes in the United States with those in other countries. In a paper prepared for the panel, Wilmoth and colleagues (2010)
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From page 135... ...
Male life expectancy at age e 50 by State FIGURE 9-4 Geographic variation in life expectancy at age 50 in the contiguous Fig 9-4b.eps United States, 2000. SOURCE: Wilmoth et al.
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Female Female 30 30 25 25 Male Male 20 20 1940 1950 1960 1970 1980 1990 2000 1940 1950 1960 1970 1980 1990 2000 Year Year FIGURE 9-5 Trends in the average value of life expectancy at age 50 within Fig 9-5c.eps quintiles of geographic distribution, United States compared with Canada, France, Fig9-5d.eps Japan, and Western Europe, 1940-2005. NOTE: Each line represents the trend for one quintile; the spread of the lines represents the inequality across quintiles.
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From page 137... ...
WHAT EXPLAINS INCREASES IN INEQUALITY IN MORTALITY? As indicated at the beginning of this chapter, socioeconomic status can be considered a fundamental cause of differentials in health and mortality and one that works through many mechanisms.
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138 TABLE 9-5 Smoking and Obesity by Education: Proportion Who Currently Smoke, Ever Smoked, or Are Obese by Years of Education and Ratio of Lowest Education Group (≤ years) to Highest (≤16 years)
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, 2004; for Japan, Nihon University Japanese Longitudinal Study of Aging (NUJLSOA) , 2006; for Canada, Canadian Community Health Survey (CCHS)
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. Furthermore, a large number of people in the United States, especially at lower levels of socioeconomic status, have no health insurance, while most Western European countries have national health care coverage programs.
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From page 141... ...
women is somewhat different: mortality rates are higher than in most Northern and Western European countries among both those who are highly educated and the least educated. This generalization for women is similar to that noted for geographic differences, with states in the United States faring relatively poorly compared with OECD countries at comparable points in their respective educational distributions.
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