Capacity Strengthening Undertaking-Farm Organized Response of Workers against Risk for Diabetes: (C.S.U.-F.O.R.W.A.R.D. with Cal Poly)-A Concept Approach to Tackling Diabetes in Vulnerable and Underserved Farmworkers in California

• Published in: Sensors (Basel, Switzerland) Switzerland), 2022-10, Vol.22 (21), p.8299
• Main Authors: Sikalidis, Angelos K, Kristo, Aleksandra S, Reaves, Scott K, Kurfess, Franz J, DeLay, Ann M, Vasilaky, Kathryn, Donegan, Lorraine
• Format: Article
• Language: English
• Subjects: Acculturation; Adult learning; Adult students; agriculture; Anthropometry; Artificial intelligence; artificial intelligence (AI); California; Cardiovascular diseases; Chronic illnesses; Circadian rhythms; Concept Paper; Costs; Diabetes; Diabetes mellitus; Diabetes Mellitus, Type 2 - prevention & control; Didacticism; Disease control; Education; Empowerment; Exercise; Expenditures; Experiential learning; farm workers; Farmers; Farms; Farmworkers; Gender differences; Glucose; Hispanic culture; Hispanic people; Humans; Lifestyles; Machine learning; Medical research; Medicine, Experimental; Methods; nutrition; Nutrition research; Physical fitness; Political activists; Poly A; Population; Reformers; Risk analysis; Risk factors; Risk management; Signs and symptoms; Social reformers; Telemedicine; Training; Type 2 diabetes; type 2 diabetes mellitus (T2DM); Workers
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22218299

In our project herein, we use the case of farmworkers, an underserved and understudied population at high risk for Type-2 Diabetes Mellitus (T2DM), as a paradigm of an integrated action-oriented research, education and extension approach involving the development of long-term equitable strategies providing empowerment and tailored-made solutions that support practical decision-making aiming to reduce risk of T2DM and ensuing cardiovascular disease (CVD). A Technology-based Empowerment Didactic module (TEDm) and an Informed Decision-Making enhancer (IDMe) coupled in a smart application (app) for farmworkers aiming to teach, set goals, monitor, and support in terms of nutrition, hydration, physical activity, sleep, and circadian rhythm towards lowering T2DM risk, is to be developed and implemented considering the particular characteristics of the population and setting. In parallel, anthropometric, biochemical, and clinical assessments will be utilized to monitor risk parameters for T2DM and compliance to dietary and wellness plans. The app incorporating anthropometric/clinical/biochemical parameters, dietary/lifestyle behavior, and extent of goal achievement can be continuously refined and improved through machine learning and re-programming. The app can function as a programmable tool constantly learning, adapting, and tailoring its services to user needs helping optimization of practical informed decision-making towards mitigating disease symptoms and associated risk factors. This work can benefit apart from the direct beneficiaries being farmworkers, the stakeholders who will be gaining a healthier, more vibrant workforce, and in turn the local communities.