A study of factors affecting the physical health of urban residents based on Pearson's correlation analysis

Abstract

Over the years, the prevalence of chronic diseases has continued to rise in China, posing a great threat to people's health. In order to better understand the prevalence of chronic diseases and the factors affecting them, according to the Dietary Guidelines for Chinese Residents issued by the Chinese Nutrition Society, combined with the data from the Epidemiological Questionnaire on Chronic Non-Communicable Diseases and their Associated Factors, we used stratified sampling to select samples from people in different regions, ages and genders, and applied person correlation analysis and neural network analysis to construct a standardized healthy life evaluation model and a chronic disease-related degree model. methods, and constructed a standardized healthy life evaluation model and a chronic disease-related degree model. The degree of influence of living habits and dietary habits on physical health was analyzed, and the correlation between diet, living habits, age, gender, marital status, education level, occupation and other factors and the prevalence of chronic diseases was studied. Through modeling analysis, the risk of chronic diseases can be more accurately assessed, providing a scientific basis for prevention and treatment. Through the implementation of these recommendations, people can effectively reduce the risk of chronic diseases and improve the quality of life.