While these studies differ somewhat

While these studies differ somewhat in terms of their health measures and population samples, they all overlook a more fundamental backdrop: the changing nature of educational and health inequalities across the twentieth century. In the United States, high school and college education changed greatly in curricular content and economic value during this time, and postsecondary education became more common in later decades (Hout, 2012). Meanwhile, patterns of health, disease and longevity became more unequal by educational attainment (Lynch 2003; Masters, Hummer, & Powers, 2012). Finally, the gender gap in obtaining a college education closed by the 1980s, and across the twentieth century men and women have shown distinct resources for and returns to educational attainment (DiPrete & Buchmann, 2013; Hout 2012; Masters et al., 2012). Despite these fundamental historical shifts, it remains unclear whether the presence or strength of resource substitution or cumulative (dis)advantage depends upon gender or cohort. Here, I draw on national US data to analyze these further contingencies in health returns to education.
Data and methods
Results
Discussion Parental SES lays a foundation for life-course health (Johnson & Schoeni, 2011). While most existing studies find that health returns to education are strongest among those who come from disadvantaged ptc124 (consistent with resource substitution), other studies instead find health returns to be highest among individuals from privileged or advantaged families (consistent with cumulative (dis)advantage). While these mixed findings may be due in part to the differing samples or health outcomes across studies, they overlook fundamental historical shifts in education and health. The economic value of obtaining education varied widely across the twentieth century, while educational attainment and returns to education differed markedly by gender as well (DiPrete & Buchmann, 2013; Hout, 2012). In this study, I tested the importance of gender and cohort to life-course health disparities. These findings suggest that Bauldry′s (2014) findings may be gender- or life-course-dependent. They may also reflect the use of a propensity scoring methodology, which examines effect heterogeneity across a vector of pre-educational factors rather than parental SES in particular, and focuses on returns to a four-year college degree specifically. Increasingly researchers are examining the measurement properties of self-rated health. Population subgroups defined by gender or race may differ systematically in terms of the cognitive thresholds they carry for thinking about and self-assigning subjective health (Grol-Prokopczyk, Freese, & Hauser, 2011). In contrast, the results for mortality supported resource substitution, for women only. Education did not significantly buffer mortality among women from relatively advantaged families, whereas men showed educational mortality buffering regardless of family origins. Prior work similarly finds that educational mortality buffering is strongest among those who are least likely to complete college (Schafer et al., 2013). However, this work had not tested for heterogeneity by gender. Further models also examined the roles of cohort and age, demonstrating that relatively disadvantaged families show increasing educational disparities in mortality in more recent cohorts and decreased mortality protection with age. This importantly adds to prior work documenting the roles of cohort and age in educational mortality buffering (e.g., Masters et al., 2012; Ross et al., 2012), by showing that cohort and age variation in educational returns may be concentrated among those from disadvantaged families. Overall, health measures in this study reveal differing socioeconomic interaction patterns, and, from a policy standpoint, suggest that education may help reduce the deleterious effects of early childhood deprivation when it comes to preventing premature death specifically.