[Analysis on cardio-metabolic related risk factors in farmers of 15 provinces in China].

Objective: To analyze the prevalence and co-prevalence of cardio-metabolic related risk factors in farmers aged ≥18 years in China, to explore the influence of population economic factors on them. Methods: A total of 3 367 farmers, including fishermen or hunters, aged ≥18 years were selected as study subjects from the database of Nutritional Status and Health Transition of Chinese Residents Project in 2015. Basic information (age, gender), data on anthropometric (body height, weight and waist size), blood biochemical and socioeconomic (occupation, income, education level and living area) were included. According to the definition of the metabolic syndrome released by the International Diabetes Federation (IDF) in 2005, five cardio-metabolic risk factors appeared as central obesity, increased triglycerides, decreased HDL-C, increased blood pressure and increased plasma glucose. Co-prevalence of risk factors was defined as detecting 2 or more risk factors in a person at the same time. Multivariate logistic regression model was used to analyze the relationship between socioeconomic factors and metabolic risk factors. Results: In 3 367 framers of 15 provinces (autonomous region and municipality), the prevalence rates of central obesity, increased blood pressure, increased plasma glucose, increased triglycerides and decreased HDL-C were 51.8 % , 59.0 % , 17.0 % , 25.5 % and 38.7 % respectively. Multivariate logistic regression analysis showed that the risks for central obesity ( OR =3.69, 95 %CI : 3.17-4.28) and decreased HDL-C ( OR =3.28, 95 %CI : 2.81- 3.82) were higher in women than in men, and the risks for increased blood pressure ( OR =0.73, 95 %CI : 0.63-0.84), increased blood glucose ( OR =0.80, 95 %CI : 0.67-0.97) were lower in women than in men. Age was positively correlated with the prevalence or co-prevalence of metabolic risk factors (trend P <0.05). Framers in western China had obviously lower risk for central obesity compared with farmers in central China. No significant correlation was found between farmers' income level, education level or the prevalence of metabolic risk factors. Conclusion: In 15 provinces of China, the prevalence of at least 1 kind of cardio-metabolic risk factor was found in 85.5 % of the farmers, and the co-prevalence of cardio-metabolic risk factor was found in 60 % of farmers. The prevalence and co-prevalence of cardio-metabolic risk factors were significantly associated with age and gender. It is suggested to take targeted nutritional intervention and health education according to the distribution characteristics of prevalence and co-prevalence of cardio-metabolic factors and strengthen the early prevention and control programs of the diseases.