Abstract
A focus in recent decades has involved examining the potential causal impact of educational attainment (schooling years) on a variety of disease and life-expectancy outcomes. Numerous studies have broadly revealed a link suggesting that as years of formal schooling increase so too does health and wellbeing; however, it is unclear whether the associations are causal. Here we use Mendelian randomization, an instrumental variables technique, with a two-sample design, to probe whether more years of schooling are causally linked to type 2 diabetes (T2D) and 10 of its attendant risk factors. The results revealed a protective effect of more schooling years against T2D (odds ratio = 0.39; 95% confidence interval: 0.26, 0.58; P = 3.89 × 10–06), which in turn might be partly mediated by more years of schooling being protective against the following: having a father with T2D, being overweight, having higher blood pressure and higher levels of circulating triglycerides, and having lower levels of HDL cholesterol. More schooling years had no effect on risk for gestational diabetes or polycystic ovarian syndrome and was associated with a decreased likelihood of moderate physical activity. These findings imply that strategies to retain adults in higher education may help reduce the risk for a major source of metabolic morbidity and mortality.
Highlights
Tacit to most epidemiological research is a desire to infer whether an environmental exposure impacts some disease or health outcome in a causal fashion
Scholars have begun utilizing data gleaned from large genomic consortia and publicly available genome wide association (GWA) studies to construct instrumental variables comprised of trait-relevant singlenucleotide polymorphisms (SNPs)
A strong protective effect against type 2 diabetes (T2D) is observed for more Education Years
Summary
Tacit to most epidemiological research is a desire to infer whether an environmental exposure impacts some disease or health outcome in a causal fashion. Educational attainment has been associated (in a protective sense) with diverse mental and physical health outcomes, including depression, cancer incidence, heart disease, and d iabetes[1]. Entangled in this line of inquiry—and much of social science research, —is a concern about the degree of causal inference open to scholars[3]. When certain assumptions (discussed below) are satisfied in the data, it is possible to investigate whether some type of modifiable risk or protective factor causally impacts some o utcome[4]. We apply MR modeling strategies to zoom in on whether educational attainment plays a causal role in the prevention of one of society’s most pressing public-health challenges: type 2 diabetes (T2D) and 10 of its risk factors
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