Modeling of Chronic Disease Prevention and Nutritional Intervention for the Elderly Based on Big Data Analysis

To explore the level of chronic disease prevention and control literacy of the elderly and to provide a basis for the development of chronic disease prevention and control and health promotion strategies suitable for the elderly. In this paper, we first applied the Logistic model to mine the data related to the prevention and control of chronic diseases in the elderly from three aspects: chronic disease prevention and control literacy and health status of the elderly, the accuracy of the chronic disease prevention and control literacy assessment questions of the elderly, and the factors influencing the prevention and control literacy. Then, the nutritional intervention method was designed, and the Soc model was established to analyze the nutritional intervention for elderly chronic disease patients. The results of data mining showed that the level of chronic disease prevention and treatment among the elderly was higher in urban than in rural areas, higher in the East than in the center and the West, higher literacy than lower literacy, and higher in good health than in poor health. There were significant differences between the nutrition intervention group and the control group (P<0.05) in terms of compliance behavior, coping style, hope level, nutritional status, self-care ability, comfort, and quality of life enhancement, and all of them were better than the control group, which achieved a direct and significant effect of the nutrition intervention, and facilitated the prevention and treatment of chronic diseases of the elderly in the progress of a better direction.