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etween SES and health is a dose-response relationship, and not a relationship described by a thresholdeffect where the worse-off have poor health while everyone else has good health.The gradient has been found using different measures of SES and of health (Berkman & Kawachi,2000). Health indicators consist of mortality (all-cause and disease-specific mortality, infant mortality andlife expectancy), morbidity, and self-rated health, including quality of life indicators. In the U.S., the healthgradient was first reported by Kitagawa and Hauser (1973) (Kitagawa & Hauser, 1973) who mergedCensus and death records and found a relationship between mortality and SES, whether income,education or occupation was used as the indicator of SES. The inverse association between SES andmortality was reported in several U.S. communities, for example Evans County Georgia (Tyroler et al.,1984), Washington County, Maryland (Comstock & Tonasica, 1977), Alameda County, California (Haan M.et al., 1987), and Tecumseh, Michigan (Williams D. R., 1986). More recently, Backlund, Sorlie, & Johnson(1996) (Backlund et al., 1996) and Sorlie, Backlund, & Keller (1995) (Sorlie et al., 1995) used the NationalLongitudinal Mortality Study surveys, which represent approximately 500,000 personal or telephoneinterviews and 40,000 deaths, to describe the relationship between income and mortality. An incomebasedgradient with declining mortality associated with increasing income exists in all age groups for bothmales and females, though it is steeper in working-age groups and for males. The gradient flattens butremains when controlling for household size, education, marital status and employment status, indicatingthat income has an independent effect on health.An SES gradient in morbidity, impairments, and disability is also apparent (Williams D. R., 1990).Rates of chronic illness are higher among the disadvantaged (Haan M. N. & Kaplan, 1986; Lerner, 1975;Newacheck et al., 1980). The mortality and morbidity gradient is present with other socioeconomicvariables such as wealth, employment grade or social class. For example, a gradient was found in theclassic Whitehall study of civil servants in the United Kingdom (Marmot M. G., 1986). The top gradeadministrative civil servants had a 10-year cumulative mortality rate half that of the next gradeprofessional/executive civil servants, three times lower than the next grade clerical civil servants, and fourtimes lower than civil servants in the lowest grade. The gradient holds for many, but not all, healthoutcomes, including cause-specific mortality, morbidity or self-reported health. The SES based healthgradient is a fairly universal phenomenon. Differences in health by SES have been reported in Norway,Denmark, Finland, Germany, the Netherlands, Australia, New Zealand, Canada, Japan and severaldeveloping countries (Haan M. N. & Kaplan, 1986; Marmot M. et al., 1987; Williams D. R., 1990; WolfsonM. et al., 1993).SES is usually measured by income, education, occupational status, social class or a combinationof these factors. Among these measures, education stands out as the most basic SES component since itshapes future occupational opportunities and earning potential (Adler & Newman, 2002). Education isconsidered the primary and core status dimension that influences all other dimensions of statusthroughout the lifetime (Mirowsky & Ross, 2003). Education provides life skills that allow educated peopleto gain access to resources that promote health and to use these resources more effectively. Bettereducated people are more likely to be employed, to be working in well-paying jobs, to be in moreprestigious occupations, and to have more control, autonomy, creativity and authority on the job (Mirowsky& Ross, 2003). Education is the antecedent to all other measures of SES as it comes early in life andinfluences all other measures of SES.The association between SES and health becomes more robust when SES is measured byeducation (Fuchs V. R., 1979; Kitagawa & Hauser, 1973; Lebowitz, 1977; Liberatos et al., 1988; WilliamsD. R., 1990). Winkleby and colleagues, in an attempt to untangle the relative effect of education, incomeand occupation, found that only education remained a significant predictor of cardiovascular disease wheneducation, income and occupation were all included (Winkleby et al., 1992). These results taken togetherhave lead researchers to conclude that education is the best SES predictor of health status (Williams D.R., 1990).E-27