Background Metabolic syndrome (MetS), a condition of metabolic disorders, is now causing large disease burden around the world. This study aimed to update the prevalence of MetS in Jiangsu Province of China and evaluate the predicting value of five anthropometric measures including waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI) and body roundness index (BRI) in MetS. Methods 8040 participants from 12 survey sites were enrolled into this cross-sectional study by multi-stage stratified cluster random sampling method from 2014 nutrition and diet investigation project in Jiangsu Province. The transformation of sex-specific z-score made the comparison meaningful when conducting the logistic analysis between anthropometric indices and MetS. The abilities of anthropometric indices to predict MetS were evaluated by the receiver operating characteristic curve (ROC). Delong test was applied to compare area under different ROC curves. Results The prevalence of MetS in Jiangsu Province was 35.2% and the standardized prevalence was 34.8%. WC, BMI, WHtR, ABSI and BRI z-scores were positively related to MetS and its components. WC, WHtR and BRI z-score had stronger associations with MetS than BMI and ABSI in both male and female population. WC, WHtR and BRI had larger area under ROC curve than BMI and ABSI in male and female. WC in men had the largest area under the ROC curve, significantly higher than the other four measures of BMI, WHtR, ABSI and BRI (Z value = 9.08, 2.88, 16.73, 2.75 respectively). Among women, WC, WHtR and BRI had larger area under the ROC curve than BMI and ABSI, but the area under the WC, WHtR and BRI curve were not significantly different after the pairwise comparison by the Delong test. The optimal cut-off values of WC, WHtR and BRI for predicting MetS was 85.25 cm, 0.52 and 3.61 in male, 80.05 cm, 0.51 and 3.83 in female. Conclusion MetS has become one of the major chronic diseases in Jiangsu Province. WC was better than other four indices in predicting MetS among male population in Jiangsu. WC, WHtR and BRI had superior abilities than BMI/ABSI in predicting MetS among female population.

Background: Stroke is the leading cause of death in China, and its burdens are rapidly increasing. The prevalence and control of stroke risk factors among stroke patients in China are unknown. Objective: We investigated the stroke risk factors of stroke patients in China. Design: We examined stroke risk factors in 6580 stroke patients aged 18 years or older in the China National Chronic Diseases and Nutrition Surveillance of Adults (2015–2017). With regard to the basic characteristics of the study participants, categorical variables were described as frequency (percent). The chi-square test was used to analyze the difference between men and women. The multivariate logistic regression model was used in the multivariate analysis. Results: Among the 6580 stroke patients, hypertension was the most common stroke risk factor identified in most cases (78.51%), followed by overweight or obesity (61.58%), dyslipidemia (54.38%), smoking (24.04%), diabetes (21.75%), family history of stroke (17.43%), lack of exercise (16.35%), and atrial fibrillation (4.47%). Drinking stroke patients had a lower rate of hypertension, diabetes, and dyslipidemia. Patients with hyperuricemia had a higher rate of hypertension and dyslipidemia than no-hyperuricemia patients. The hypertension awareness, treatment, and control rates among hypertension stroke patients were 73.62%, 70.19%, and 17.79%, respectively. The diabetes awareness, treatment, and control rates among diabetes patients were 69.74%, 65.83%, and 34.59%, respectively. The dyslipidemia awareness, treatment, and control rates among dyslipidemia patients were 42.37%, 29.4%, and 20.07%, respectively. Among treated hypertension patients, the rates of taking medicine as medically advised, controlled diet, increased exercise, and blood pressure monitoring were 91.31%, 58.88%, 45.78%, and 73.99%, respectively. Among treated diabetes patients, the rates of oral antidiabetic medications, insulin injection, diet control, and blood glucose monitoring were 78.24%, 34.71%, 85.77%, and 78.24%, respectively. Among treated dyslipidemic patients, the rate of taking medicine as medical advice, controlled diet, increased exercise, and regular blood lipid monitoring was 80.61%, 77.57%, 56.46%, and 40.3%, respectively. Conclusions: The most common risk factors for community stroke patients in China are hypertension, dyslipidemia, and overweight or obesity. The stroke community patients’ suboptimal awareness and treatment of hypertension, and suboptimal awareness, treatment, and control of diabetes, and dyslipidemia are significant problems in China.

The aim of this study was to examine the association between dietary patterns and high blood glucose in Jiangsu province of China by using structural equation modelling (SEqM). Methods: Participants in this cross-sectional study were recruited through the 2015 Chinese Adult Chronic Disease and Nutrition Surveillance Program in Jiangsu province using a multistage stratified cluster random sampling method. Dietary patterns were defined by exploratory factor analysis (EFA). Confirmatory factor analysis (CFA) was used to test the fitness of EFA. SEqM was used to investigate the association between dietary patterns and high blood glucose. Results: After exclusion, 3137 participants with complete information were analysed for this study. The prevalence of high blood glucose was 9.3% and 8.1% in males and females, respectively. Two dietary patterns: the modern dietary pattern (i.e., high in red meats and its products, vegetables, seafood, condiments, fungi and algae, main grains and poultry; low in other grains, tubers and preserves), and the fruit–milk dietary pattern (i.e., high in milk and its products, fruits, eggs, nuts and seeds and pastry snacks, but low in vegetable oils) were established. Modern dietary pattern was found to be positively associated with high blood glucose in adults in Jiangsu province (multivariate logistic regression: OR = 1.561, 95% CI: 1.025~2.379; SEqM: β = 0.127, p < 0.05). Conclusion: The modern dietary pattern—high intake of red meats—was significantly associated with high blood glucose among adults in Jiangsu province of China, while the fruit–milk dietary pattern was not significantly associated with high blood glucose.

The present study was conducted to investigate the nutrition status of dietary patterns and the association between dietary patterns and the risk of poor glycemic control in Chinese diabetics. The relevant data was collected from the China Nutrition and Health Surveillance 2015–2017 survey, which is a national cross-sectional surveillance program. A total of 2031 participants were included in the present statistical analysis. Food consumption was assessed through a validated and standard food frequency questionnaire. Dietary patterns were derived with reduced rank regression using hemoglobin A1c. Diabetes was diagnosed by medical institutions, glycemic control was defined as hemoglobin A1c less than 7%, poor glycemic control was defined as hemoglobin A1c greater than 7%. A multiple-variable-adjusted logistic regression, including age, living area, income level, educational attainment, body mass index, occupational physical activity, energy intake, current smoking status, current drinking status, diabetic medication use, insulin use, following diabetic diets, increased exercise, and glucose monitoring, was adjusted to explore the association between dietary patterns and the risk of poor glycemic control in diabetes. Two gender-specific dietary patterns have an increased risk of poor glycemic control and are characterized by a low intake of freshwater fish, poultry, and fruits. For male participants, the dietary pattern was characterized by a high intake of wheat and its products, a low intake of vegetables, corn and its products, shrimp and crab, and beans (Q4 vs. Q1, OR = 2.69, 95% CI: 1.76 to 4.10). For female participants, the dietary pattern was characterized by a low intake of snacks and nuts, and algae and mushroom (Q4 vs. Q1, OR = 2.18, 95% CI: 1.48 to 3.20).