Salt reduction behavior of adults in Anhui province in 2019: a cross-sectional survey of 3,378 participants.

Objective: A high-sodium diet is an important risk factor for hypertension in the Chinese population, which can increase the risk of cardiovascular and cerebrovascular diseases. Although a large number of related studies have been carried out in Anhui province, clear, effective salt reduction interventions and policies that can be widely promoted have not yet been formed. This study sought to understand the prevalence and precise measures of salt reduction behavior, the variables affecting salt reduction behavior, and the reasons why salt reduction behavior was not practiced in Anhui Province, China. Methods: The total number of participants in the study was 3,378. Using a multi-stage stratified cluster random sampling method, residents between the ages of 18 and 69 years in 10 counties and districts were selected from March to October 2019. A survey questionnaire and physical measurements were given to each participant. The influencing factors of residents' salt reduction behavior were examined using a multi-factor unconditional logistic regression analysis. The chi-squared (χ2) test was used to analyze the implementation of salt reduction behaviors among different age groups and gender, the factors influencing the implementation of salt reduction measures, and the reasons for not implementing salt reduction measures. Results: A history of hypertension was associated with salt reduction strategies (P = 0.014). Patients with hypertension were more likely to adopt salt reduction behaviors than those without hypertension (OR = 1.218, P = 0.040). The influence of eating out on the adoption of salt-reduction measures varied by age group (χ2 = 50.463, P < 0.001) and gender (χ2 = 81.348, P < 0.001). Conclusion: In summary, residents of the Anhui Province are not very knowledgeable about salt reduction. Age, gender, education level, hypertension, and marital status are the main determinants. Our findings have significant implications for policymakers who want to devise salt reduction strategies.

Glycemic control and its influencing factors in type 2 diabetes patients in Anhui, China.

Objective: To investigate the status of glycemic control and analyze its influencing factors in patients with type 2 diabetes (T2D) in Anhui, China. Methods: 1,715 T2D patients aged 18-75 years old were selected from 4 counties or districts in Anhui Province in 2018, using a convenience sampling method. All patients have undergone a questionnaire survey, physical examination, and a glycosylated hemoglobin (HbA1c) test. According to the 2022 American Diabetes Association criteria, HbA1c was used to evaluate the glycemic control status of patients, and HbA1c < 7.0% was defined as good glycemic control. The influencing factors of glycemic control were analyzed by multivariate unconditional logistic regression. Results: The prevalence of good glycemic control among people with T2D in the Anhui Province was low (22.97%). On univariate analysis, gender, education level, occupation, region, smoking, drinking, waist circumference and disease duration (all P < 0.05) were significantly associated with glycemic control. The factors associated with pool glycemic control were female gender [OR = 0.67, 95%CI (0.52, 0.86), P = 0.001], higher level of education [OR = 0.47, 95%CI (0.27, 0.83), P = 0.001], living in rural areas [OR = 1.77, 95%CI (1.39, 2.26), P < 0.001], central obesity [OR = 1.58, 95%CI (1.19, 2.09), P = 0.001] and longer duration of disease [OR = 2.66, 95%CI (1.91, 3.69), P < 0.001]. Conclusions: The prevalence of good glycemic control in people with T2D in Anhui Province was relatively low, and gender, region, education level, central obesity and course of the disease were influencing factors. The publicity and education on the importance of glycemic control should be further strengthened in T2D patients, and targeted intervention measures should be carried out for risk groups.

The detection rate and influencing factors of high-risk groups of cardiovascular disease in Anhui, China: A cross-sectional study of 99,821 residents.

Objective: To investigate the detection rate and influencing factors of high-risk population of cardiovascular disease in Anhui province. Methods: From March 2017 to August 2019, the residents aged 35-75 years old were selected using the multi-stage stratified cluster sampling method in 8 counties and districts of Anhui Province, and questionnaire survey, anthropometric measurement, and collection of biological samples were carried out among them. Results: A total of 99,821 residents in Anhui Province were finally investigated, and among them 21,426 residents were detected to be high-risk groups of cardiovascular disease. The detection rate of high-risk groups was 21.46%. According to the high-risk types, the high-risk groups can be clustered. 74.57% of them had only one high-risk type, 22.57% of them had two high-risk types, and 2.86% had three or more high-risk types. The results of Generalized Linear Mixed Model (GLMM) showed that male, age ≥45 years old, not married, occupation as a farmer, annual family income <25,000 yuan, drinking, overweight and obesity, pre-central obesity and central obesity, snoring, feeling fatigued, sleepiness, and self-reported history of diabetes were more likely to be risk factors of cardiovascular disease (all P value < 0.05). Conclusion: The detection rate of high-risk groups of cardiovascular disease in Anhui Province is relatively high. Individualized intervention measures as well as comprehensive prevention and control strategies should be adopted focusing on the distribution characteristics of risk factors of high-risk groups.

Mortality and Disease Burden of Injuries from 2008 to 2017 in Anhui Province, China.

OBJECTIVE: To investigate the temporal trends in mortality and disease burden of injuries in Anhui province from 2008 to 2017, so as to provide reference for injury control and prevention. METHODS: Data of mortality were collected from 9 national surveillance points in Anhui province during 2008-2017 in the Information System for Death Cause Register and Management. The surveillance data were analyzed by using crude mortality, standardized mortality rate (SMR), potential year of life lost (PYLL), PYLL rate (PYLLR), and average of year life lost (AYLL). RESULTS: There were a total of 44855 people died from injury, accounted for 9.44% of the all-cause mortality, ranked as the fifth leading cause of deaths in the whole population, and denoted the first leading cause of deaths in the 0-44 year's group. The leading causes of injury deaths were road traffic accidents, suicide, accidental falls, drowning, and poisoning. Road traffic accidents was the primary cause of injury deaths among the male population, while suicide was the dominate cause of injury deaths among the female population. Drowning, traffic accidents, and suicide accounted for the most injury deaths among the population aged 0-14 years, 15-64 years, and above 60 years, respectively. The road traffic accidents accounted for the largest proportion of injury PYLL and PYLLR, and drowning caused the highest AYLL among injury deaths. CONCLUSION: In Anhui province, road traffic accidents, suicide, accidental falls, drowning, and poisoning were the top five causes of injury deaths that harm the health of local residents; corresponding injury prevention strategies should be formulated.

[Association between mortality rate of hepatic carcinoma and the distance from Suihe River in Lingbi county, Anhui province].

OBJECTIVE: To explore the association between mortality rate of hepatic carcinoma and the distance from Suihe River in Lingbi county, Suzhou, Anhui province. METHODS: Using the disease mapping and spatial statistical analysis techniques,we described the spatial distributions of the mortality rate of hepatic carcinoma from 2005 to 2010 in Lingbi county. Taking the distance between villages and polluted rivers as proxy variable of environmental exposure, mortality rate of hepatic carcinoma in each village as dependant variable, and using the Glimmix model and Bayesian spatial model (BYM) to undertake the univariate and multivariate analysis, we investigatived the association between mortality rate of hepatic carcinoma and the water pollution of Suihe River in Lingbi county. RESULTS: Obvious clustering of high mortality rate of hepatic carcinoma along the polluted river was observed in Lingbi county. Results of Glimmix model showed that whether spatial autocorrelation was considered or not, closer to the polluted river has higher mortality rate of hepatic carcinoma. Results of univariate analysis of the BYM model showed that, compared with the villages far from the polluted river more than 12 km (the mortality rate of hepatic carcinoma was 33.12/100 000(1068/3 224 562) ), the RR values of the hepatic carcinoma mortality was 1.38(95%CI:1.06-1.82) for the villages apart from the polluted river within 6 km (the mortality rate of hepatic carcinoma was 42.48/100 000(777/1 829 064)), and 1.13 (95%CI:0.92-1.39) for villages apart from the river between 6 and 12 km (the mortality rate of hepatic carcinoma was 35.65/100 000(651/1 825 848)). In the BYM model multivariate analysis, adding the volume of fertilizer and pesticides used per cultivated area, GDP per capita to do multivariate analysis were, the relation between mortality rate of hepatic carcinoma and distance from polluted rivers remains unchanged. CONCLUSION: The mortality rate of hepatic carcinoma was associated with the exposure to the polluted river in Lingbi county. The polluted river may increase the hepatic carcinoma mortality of nearby residents.