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Chapter 2 Education and Health: Evaluating Theories and Evidence David M. Cutler and Adriana Lleras-Muney T here is a well-known large and persistent association between education and health. This relationship has been observed in many countries and time periods , and for a wide variety of health measures.1 The differences between the more and the less educated are significant: in 1999, the age-adjusted mortality rate of high school dropouts ages twenty-eight to sixty-four was more than twice as large as the mortality rate of those with some college (Lyert et al. 2001, table 26). Substantial attention has been paid to these “health inequalities.” Gradients in health by education are now systematically monitored in many countries (the United States includes them as part of its Healthy People 2010 goals). Countries such as the United Kingdom have target goals of reducing health disparities specifically through education or factors correlated with education.2 Through understanding the possible causal relationships between education and health and the mechanisms behind them, we can assess the extent to which education policies can or should be thought of as health policies. We note at the outset that this is a controversial topic. A number of authors have written about education-related health inequalities, and the conclusions frequently differ. To some extent, this is a result of data limitations. Many of the data sets that we and others employ use health measures that are self-reported. In addition to true differences in health, there are also some differences related to knowledge of existing conditions, which may itself be related to education. It is also very important, however, that work on the mechanisms underlying the link between health and education has not been conclusive. Not all relevant theories have been tested, and, when they have, studies often conflict with each other. We highlight the discrepancies as best we can. We do not resolve the differences here—that is an enormous task, and is not doable with current information. Noting the points of disagreement is important in its own right, however. Along the way, we indicate where more research would be particularly valuable. / 29 THE RELATIONSHIP BETWEEN HEALTH AND EDUCATION To document the basic correlations between education and health, we estimate the following regression: Hi = c + βEi + Xiδ + εi (2.1) where Hi is a measure of individual i’s health or health behavior, Ei stands for i’s years of completed education, Xi is a vector of individual characteristics that includes race, gender, and single year of age dummies, c is a constant term, and ε is the error term. The coefficient on education β (also referred to as the education gradient ) is the object of interest, and it measures the effect of one more year of education on the particular measure of health. We focus on individuals who are twenty-five and older because they have most likely already completed their education . Education is included either in years (as in the labor literature), or using dummies for each year of education, to be as flexible as possible. We first report results for the entire sample, and then for different demographic groups. We estimate linear models for continuous variables. For dichotomous variables we estimate logit probability models and report the marginal effects. The data we employ are from various years of the National Health Interview Survey (NHIS) in the United States.3 We use the NHIS because it has a large number of health outcomes and behaviors. Generally, results from the NHIS match other surveys with self-reports (Cutler and Glaeser 2005) and even physical assessments , though clearly there are exceptions such as weight and height. We note possible reporting issues as we present the results. Table 2.1 reports the coefficient on years of schooling in explaining various measures of health. The first outcome we look at is whether an individual died within five years of the interview. In the NHIS this is determined by matching individual information to death certificates through the National Death Index (see appendix for more details). Then we look at gradients in the self-report of a past acute or chronic disease diagnosis. Most of these diseases are very serious (cancer or heart disease, for example), and people would certainly know if they had been diagnosed with them. (Although it is possible that conditional on having the disease, the more educated are more likely to know about it. If that is the case, then the gradients we report for these diseases...

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