Alexis Bolio Galvis, Osama Hamdy, Miguel Escalante Pulido, Victoria Alejandra Rajme Haje, Hugo Antonio Laviada Molina, Mario Eduardo Martínez Sánchez, David González Bárcena, Teresita Huici y de Yta, Albert Marchetti, Refaat A Hegazi and Jeffrey I Mechanick
In Mexico, Type 2 Diabetes (T2D), dyslipidemia, hypertension, and associated Cardiovascular Disease (CVD) have replaced infectious diseases as primary causes of morbidity and mortality. In less than four decades, T2D has become the foremost health problem of this middle income nation, affecting nearly one sixth of the adult population, more than 10 million people. Dyslipidemia is also problematic and widespread, with a national prevalence among the worlds highest. Contributing to these troubles, are alarming rates of weight disorders. Mexico now has one of the most overweight and obese populations in the world, where 66% of men and 72% of women over age 20 are overweight or obese. Additionally, Mexico has emerged as the country with the highest percentage of overweight and obese youth -26% of young children and 32% of teens. Among city children with weight disorders, hypertension has become more frequent, adding to the already high prevalence of hypertension in the country and contributing yet another dimension to an already complex problem with enormously detrimental clinical and economic consequences. These problems can be mitigated through lifestyle modifications that are vital components of comprehensive care for metabolic disorders and mandated in Clinical Practice Guidelines (CPG) for T2D. Unfortunately, CPG can be complicated and often lack portability. Simplification and transculturalization can enhance applicability and implementation. The transcultural Diabetes Nutrition Algorithm (tDNA) programmatically addresses these needs and concerns through an evidence-based patient-algorithm template that is amenable to cultural adaptation. Food choices, dietary practices, physical activities, and healthcare practices in Mexico were considered for the Mexican adaptation. The resultant algorithm and its underlying recommendations are herein presented and explained.
