The Impact of Education and Age on Metabolic Disorders - Stephens, Christopher R.; Easton, Jonathan F.; Robles-Cabrera, Adriana; Fossion, Ruben; de la Cruz, Lizbeth; Martínez-Tapia, Ricardo; Barajas-Martínez, Antonio; Hernández-Chávez, Alejandro; López-Rivera, Juan Antonio; Rivera, Ana Leonor (Frontiers in Public Health, 2020)
Metabolic disorders, such as obesity, elevated blood pressure, dyslipidemias, insulin resistance, hyperglycemia, and hyperuricemia have all been identified as risk factors for an epidemic of important and widespread chronic-degenerative diseases, such as type 2 diabetes and cardiovascular disease, that constitute some of the world’s most important public health challenges. Their increasing prevalence can be associated with an ageing population and to lifestyles within an obesogenic environment. Age is not a controllable variable; however, lifestyle is, hence, behavioral interventions may be devised to improve health. Taking educational level as a proxy for lifestyle, and using both logistic and linear regressions, we study the relation between a wide set of metabolic variables, educational level, body mass index (BMI), age and sex in a population of 1,073 students, academic and non-academic staff at Mexico's largest university (UNAM). We use the corresponding risk profiles to classify metabolic disorders. The heterogeneity of the profiles indicates different aetiologies and, importantly, the need for targeted population-specific interventions that distinguish between education-susceptible and non-education-susceptible factors, as well as between different age groups. Controlling for BMI and sex we consider educational level and age as complementary measures - degree and duration - of exposure to metabolic insults. Young adults have a quite distinct metabolic risk profile when compared to older adults. Analyzing the role of education across a wide spectrum of educational levels (from primary school to doctoral degree), we show that higher education correlates to significantly better health outcomes when compared to lower levels and is associated with significantly less risk for waist circumference, systolic blood pressure, glucose, glycosylated hemoglobin, triglycerides, high density lipoprotein and metabolic syndrome; but not for diastolic blood pressure, basal insulin, uric acid, low density lipoprotein, and total cholesterol. There are variables strongly linked to educational level, which therefore are candidates for lifestyle change interventions. Thus, public policy efforts should be focused on education-susceptible variables, prone to modification by exposure to information, while adopting a different approach for education-non- susceptible variables which are poor targets for educational campaigns.