In the education literature there is on going debate about

In the education literature, there is on-going debate about the mechanisms to explain the relationship between education and health. There are many theorized mechanisms to explain the relationship between education and health. Some argue the effect of education on health arises through credentialing or “sheepskin” effects. According to the credential model, education confers degrees, which are symbolic in nature. Education impacts health because employers use degrees to screen and hire their employees. Higher education has been associated with full-time employment, higher incomes, and less exposure to occupational hazards (Kawachi, Adler, & Dow, 2010). Using this model, each additional year of education has no added value unless it leads to a degree (Ross & Mirowsky, 1999; Ross & Wu, 1995). Another hypothesized mechanism described by the quantity model is that education confers skills and knowledge (Ross & Mirowsky, 1999). Under the quantity model, more years of schooling leads to more human capital acquisition. Education may help develop foundational analytic skills such as the ability to observe, experiment, synthesize, and classify. Education introduces people to the process of gathering and interpreting information and solving problems (Ross & Mirowsky, 1999), and these abilities can serve people well in their daily lives. Some research suggests both may be operating. In examining national education and adult mortality patterns, a linear decline in mortality risk was found from 0–11 years of schooling, followed by a step change in mortality risk once a high school diploma is achieved, and then a steeper linear endopeptidase in mortality risk with increasing schooling after high-school (Montez, Hummer, & Hayward, 2012). In this paper, we focused on testing the quantity model and assessed the extent to which the effects of education depressive symptoms are mediated through one important skill acquired through schooling, viz., literacy. This was an observational study, so residual and unmeasured confounding remained a reasonable threat. One potential confounder of this relationship is early life intelligence. A concern is that our literacy measure could reflect a combination of literacy (reading ability) and general intelligence. HRS does not have an early life measure of cognitive function or intelligence. Although cognitive function was measured later in life, basal body measure may be affected by the respondents’ educational attainment and/or literacy level. As a result, late life cognitive function may partially mediate the relationship between education, literacy, and depressive symptoms. Lack of an early life measure of cognitive function is a limitation of our study. However, previous research indicate educational attainment influences cognitive function (Stevenson, Chen, & Booth, 1990) independent of intelligence (Herd, 2010; Link, Phelan, Miech, & Westin, 2008). A related concern is whether our vocabulary measure is influenced by cognitive decline. In this study, we also used vocabulary assessments from the 1995/6 and 1998 interview waves and treated our mediator as a time-constant variable. Thus, any cognitive decline after baseline would not be influenced by our vocabulary measure. The literature has demonstrated that literacy is stable over time even in the presence of early dementia (Manly, Schupf, Tang, & Stern, 2005). The Pearson correlation between the vocabulary score and change in memory score (difference between 2000 and 1998) score is -0.06. The correlation between our vocabulary score and age is -0.09. In comparison, the correlation between memory function and age was -0.69. Thus, consistent with prior literature, age has a very weak influence on literacy, compared to a large and consistent impact of age on memory function. Furthermore, reverse causation may be a potential threat. There is some evidence that depression can influence educational attainment (Fletcher, 2008, 2010). Milder forms of depression may have less of an impact on education. In addition, most previous research suggests the predominant direction is educational attainment influencing depressive symptoms (McFarland & Wagner, 2015; Mezuk, Myers, & Kendler, 2013). In this study, we assessed literacy using a brief test. While correlation between the validated WRAT and our measure of literacy was moderately high (r = 0.75), there persists the possibility of measurement error in our proposed mediator. This suggests we likely underestimated the role of literacy in mediating effects of education on mental health.