Background::Spinal injuries are an urgent public health priority; nevertheless, no China-wide studies of these injuries exist. This study measured the incidence, prevalence, causes, regional distribution, and annual trends of spinal injuries in China from 1990 to 2019.Methods::We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 to estimate the incidence and prevalence of spinal injuries in China. The data of 33 provincial-level administrative regions (excluding Taiwan, China) provided by the National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention (CDC) were use to systematically analyze the provincial etiology, geographical distribution, and annual trends of spinal injuries. The Bayesian meta-regression tool DisMod-MR 2.1 was used to ensure the consistency among incidence, prevalence, and mortality rates in each case.Results::From 1990 to 2019, the number of living patients with spinal injuries in China increased by 138.32%, from 2.14 million to 5.10 million, while the corresponding age-standardized prevalence increased from 0.20% (95% uncertainty interval [UI]: 0.18-0.21%) to 0.27% (95% UI: 0.26-0.29%). The incidence of spinal injuries in China increased by 89.91% (95% UI: 72.39-107.66%), and the prevalence increased by 98.20% (95% UI: 89.56-106.82%), both the most significant increases among the G20 countries; 71.00% of the increase could be explained by age-specific prevalence. In 2019, the incidence was 16.47 (95% UI: 12.08-22.00, per 100,000 population), and the prevalence was 358.30 (95% UI: 333.96-386.62, per 100,000 population). Based on the data of 33 provincial-level administrative regions provided by CDC, age-standardized incidence and prevalence were both highest in developed provinces in Eastern China. The primary causes were falls and road injuries; however, the prevalence and specific causes differed across provinces.Conclusions::In China, the overall disease burden of spinal injuries increased significantly during the past three decades but varied considerably according to geographical location. The primary causes were falls and road injuries; however, the prevalence and specific causes differed across provinces.

Objective:To investigate and analyse the current status of screening and management of diabetic kidney disease (DKD) in six provinces and cities in China.Methods:The qualitative research method of focus group interview was adopted, based on the semi-structured interview outline, the clinical medical and disease control personnel in Tianjin, Chongqing, Gansu, Hubei, Heilongjiang, and Guangdong were interviewed. The interview transcripts were analyzed using thematic analysis, and MAXQDA analysis software was used for data management and analysis.Results:A total of 6 interviews were conducted with 49 interviewees. Forty respondents (81.6%) claimed that DKD screening was critical; 53.1% think that it was not easy for patients to obtain DKD screening services; 40.8%, 26.5% and 14.3% of the people believed that the technology of DKD screening services was moderate, simple or very simple, respectively. Of the respondents,16.3% thought that the cost of DKD screening service was relatively expensive, while 83.7% thought that the cost was inexpensive; 75.5% of the respondents believed that the patients could receive early DKD screening service. The factors of fully implementing medical reform policies, changing concepts and actively serving patients, and integrating external resources in medical and health institutions at all levels and of all types were conducive to the development of DKD screening and management services. The lack of technology and personnel for DKD screening services at the grassroots level, the lack of trust in the service capabilities of grassroots medical institutions by patients, the low level of patient awareness, and the novel coronavirus infection epidemic had an adverse impact on the development of DKD screening and management services.Conclusion:The screening and management services for DKD are relatively limited in China, and there is a significant fragmentation in the management and care of diabetes and DKD.

Objective:To determine the priority of diabetes prevention and control measures in the perspective of the economy and importance, and provide theoretical support for guiding relevant departments to implement measures based on actual economic level.Methods:An online survey was conducted on the importance, feasibility and implementation of major chronic disease prevention and control measures in 488 national demonstration areas for comprehensive chronic disease prevention and control. The content of the survey was divided into individual and group levels, with 10 dimensions and 44 measures, to obtain the scores of the economy and importance. IPA model was used to divide the dimension index of diabetes prevention and control into quadrants. The standardized factor load coefficient of the second-order confirmatory factor analysis was used to determine the priority of dimension index in the same quadrant. The priority of prevention and control measures in each dimension was determined by the discriminant parameter of project response theory.Results:The mean scores of economy and importance were 66.50 and 89.94, respectively, and the matrix was divided into four quadrants. The first quadrant was the "highest priority" with high importance and economy, including medical insurance and family doctors, health education, high-risk detection and intervention, patient management and community action. The second quadrant was characterized as high importance but low economy, which was the priority for improvement, including only one dimension of complication screening. The third quadrant was the lowest priority due to low importance and economy, including personal health service evaluation and follow-up, environmental support, diabetes co-infection prevention and glycemic policy. The last quadrant had low importance but high economy, which was the second improvement level. The priority measures in different quadrants were: (1) the highest priority: blood lipid control, occupational site, prevention and control work plan, blood glucose testing, family doctor contract service; (2) the priority improvement: annual neuropathy screening; (3)the lowest priority: universal access to risk scoring, healthy eating, healthy dining innovations and tuberculosis screening.Conclusion:IPA model can be used to construct a decision-making model for diabetes prevention and control and determine the priority of corresponding measures.

Objective:To determine the priority of diabetes prevention and control measures in the perspective of the economy and importance, and provide theoretical support for guiding relevant departments to implement measures based on actual economic level.Methods:An online survey was conducted on the importance, feasibility and implementation of major chronic disease prevention and control measures in 488 national demonstration areas for comprehensive chronic disease prevention and control. The content of the survey was divided into individual and group levels, with 10 dimensions and 44 measures, to obtain the scores of the economy and importance. IPA model was used to divide the dimension index of diabetes prevention and control into quadrants. The standardized factor load coefficient of the second-order confirmatory factor analysis was used to determine the priority of dimension index in the same quadrant. The priority of prevention and control measures in each dimension was determined by the discriminant parameter of project response theory.Results:The mean scores of economy and importance were 66.50 and 89.94, respectively, and the matrix was divided into four quadrants. The first quadrant was the "highest priority" with high importance and economy, including medical insurance and family doctors, health education, high-risk detection and intervention, patient management and community action. The second quadrant was characterized as high importance but low economy, which was the priority for improvement, including only one dimension of complication screening. The third quadrant was the lowest priority due to low importance and economy, including personal health service evaluation and follow-up, environmental support, diabetes co-infection prevention and glycemic policy. The last quadrant had low importance but high economy, which was the second improvement level. The priority measures in different quadrants were: (1) the highest priority: blood lipid control, occupational site, prevention and control work plan, blood glucose testing, family doctor contract service; (2) the priority improvement: annual neuropathy screening; (3)the lowest priority: universal access to risk scoring, healthy eating, healthy dining innovations and tuberculosis screening.Conclusion:IPA model can be used to construct a decision-making model for diabetes prevention and control and determine the priority of corresponding measures.

Objective:To explore the relationship between body mass index (BMI), waist circumference (WC) and the risk for ischemic stroke in adults in China.Methods:A total of 36 632 adults were selected from 60 surveillance areas (25 urban surveillance areas and 35 rural surveillance areas) in China Chronic Disease Surveillance Project in 2010 for a follow up study from 2016 to 2017 based on the baseline data in 2010. The follow up was completed for 27 762 adults. Cox proportional hazard regression model was used to analyze the association of body mass index and waist circumference with the risk for ischemic stroke in different populations. The death and hypercholesterolemia cases were excluded by sensitivity analysis.Results:A total of 26 907 adults were included in the analysis. During the follow up period, 1 128 ischemic stroke events were observed (491 in men and 637 in women). After adjusting the related confounding factors and taking normal BMI/normal WC group as the reference, the risk for ischemic stroke increased by 50% in normal BMI/abdominal obesity group ( HR=1.50, 95% CI:1.07-2.08), 51% in overweight/abdominal obesity group ( HR=1.51, 95% CI:1.20-1.91), 46% in obesity/abdominal obesity group ( HR=1.46, 95% CI:1.09-1.96), and 63% in normal BMI/abdominal obesity group ( HR=1.63, 95% CI:1.12-2.38), 56% in overweight/abdominal obesity group ( HR=1.56, 95% CI: 1.20-2.03) and 45% in obesity/abdominal obesity group ( HR=1.45, 95% CI: 1.05-2.01) respectively in men and in men with CVD risk factors. There was no increased risks in the overweight/normal WC group. The risk increased by 40% in overweight/abdominal obesity group ( HR=1.40, 95% CI:1.15-1.72) and 46% in obesity/abdominal obesity group ( HR=1.46, 95% CI:1.16-1.83), and 35% in overweight/abdominal obesity group ( HR=1.35, 95% CI:1.08-1.69) and 30% in obesity/abdominal obesity group ( HR=1.30, 95% CI:1.01-1.67) respectively in women and women with CVD risk factors. There were no risk increases in overweight/normal WC group and normal BMI/abdominal obesity group. Sensitivity analysis results showed no change. Conclusion:Overweight/obesity with abdominal obesity or abdominal obesity alone could increase the risk for stroke in men, and overweight/obesity with abdominal obesity could increase the risk for ischemic stroke in women; suggesting that BMI and WC should be used jointly to evaluate obesity in population for weight control to prevent ischemic stroke.

Objective:To analyze the association between waist-to-height ratio and the overall and type specific incidence of stroke in adults in China.Methods:A total of 36 632 people were selected from 60 surveillance sites (25 in urban area and 35 in rural area) in China Chronic Disease Surveillance Project in 2010. The China Chronic Disease Surveillance Project data in 2010 were used as baseline data. A total of 27 762 people were followed up from 2016 to 2017. Cox proportional risk regression model was used to analyze the risk ratio of waist-to-height ratio for the overall and type specific incidence of stroke. Subgroup analyses were performed based on baseline characteristics such as age and sex, and sensitivity analysis was performed by excluding those who died and those with diabetes at baseline survey.Results:A total of 27 112 subjects were included in the stroke analysis, and 1 333 stroke events were observed. A total of 26 907 subjects were included in the ischemic stroke analysis, and 1 128 ischemic stroke events were observed. A total of 25 984 subjects were included in the hemorrhagic stroke analysis, and 205 cases of hemorrhagic stroke were observed. After adjusting for relevant confounders and taking group with waist-to-height ratio of 0-0.45 as a reference, the stroke analysis indicated that in groups with waist-to-height ratio of 0.46-0.49, 0.50-0.54 and ≥0.55 the risk for stroke increased by 21% ( HR=1.21, 95% CI:1.00-1.46), 26% ( HR=1.26, 95% CI:1.04-1.53) and 60% ( HR=1.60, 95% CI:1.29-1.99) respectively. Subgroup analysis revealed that age specific waist-to-height ratio had modification effect on the risk for stroke (interaction P=0.001). Ischemic stroke analysis indicated that in groups with waist-to-height ratio of 0.46-0.49, 0.50-0.54 and ≥0.55 the risk for ischemic stroke increased by 30% ( HR=1.30, 95% CI: 1.05-1.60), 33% ( HR=1.33, 95% CI: 1.07-1.64) and 61% ( HR=1.61, 95% CI: 1.26-2.05) respectively. Subgroup analysis revealed that age specific waist-to-height ratio had modification effect on the risk for ischemic stroke (interaction P=0.024). Hemorrhagic stroke analysis indicated that in group with waist-to-height ratio of ≥0.55 the risk for hemorrhagic stroke increased by 73% ( HR=1.73, 95% CI: 1.02-2.94), but the differences in the risk increase in groups with waist-to-height ratio of 0.46-0.49 and 0.50-0.54 were not significant. The sensitivity analysis showed no changes. Conclusions:In the prevention and control of stroke by body weight control, it is necessary to take waist to height ratio as one of the indicators of body weight control. Particular attention needed to be paid to the people aged <50 years with waist-to-height ratio of ≥0.55 as well as those with waist-to-height ratio of <0.5 (i.e., 0.46-0.49).

Objective:To explore the relationship between sedentary time and the incidence of type 2 diabetes in adults in China.Methods:Data collected from the Chinese Chronic Disease and Risk Factor Surveillance (CCDRFS) in 2010 were used as baseline data. Eight provinces where CCDRFS were conducted in 2010 were selected, and two surveillance spots (one in urban area and another one in rural area) of each provinces were further selected for the follow-up studies. After excluding diagnosed diabetes patients according to baseline data, a total of 8 625 of subjects were recruited as participants. In the follow up carried out from 2016 to 2017, a total of 5 991 people received complete follow up. Cox proportional hazards models were used to analyze the relationship between sedentary time and the incidence of type 2 diabetes, and subgroup analysis was conducted based on variables such as gender, geographic area, and urban area or rural areas.Results:A total of 5 782 subjects were included in final analysis. During an average 6.4 years of follow up (36 927.0 person-years), 592 participants developed type 2 diabetes, the incidence rate was 16.0 per 1 000 person years. Multivariate Cox regression analysis showed that after adjustment for possible confounders, compared with the 0.0-h/d group, the risk of diabetes incidence increased by 33% ( HR=1.33, 95 %CI: 1.05-1.68) for those who had sedentary time for more than 6.0 h every day. The subgroup analysis showed that the significant association was only observed in those who were men, current smokers, central obese, had family history of diabetes, had rural residency, and lived in eastern and central areas of China. Conclusions:Longer sedentary time can increase the risk of type 2 diabetes. Lifestyle intervention should be strengthened to reduce sedentary time, especially for people who had sedentary time for more than 6.0 h every day.

Harmful drinking causes serious consequences to social security as well as physical and mental health of the general public. The Global Burden of Disease Study (2017) showed that the number of alcohol-related deaths in China in 2017 was 1.82 times higher than that in 1990, and the population attributable fraction increased by 44.13%. The burden of disease caused by drinking alcohol had been increasing. By comparing with the comprehensive intervention strategy of restricting harmful drinking put forward by the World Health Organization, we suggest that the current interventions that need to be improved in China should include several aspects below: (1) strengthening the control of alcohol production, marketing and circulation, (2) restricting the availability of alcohol products for minors through enterprise self-discipline, laws and regulations, parents and school health education, (3) bridging gaps in appropriate techniques and services for alcohol restriction/abstinence in the health care system, (4) providing services such as rapid screening of alcohol dependence and short abstinence interventions, (5) strengthening restrictions on alcohol advertising especially in new media (e.g., online and social media) marketing practices for alcohol products, (6) conducting scientific research and evaluation on alcohol tax-related issues, and (7) regularly reviewing alcohol prices related to inflation and income levels.

Harmful drinking causes serious consequences to social security as well as physical and mental health of the general public. The Global Burden of Disease Study (2017) showed that the number of alcohol-related deaths in China in 2017 was 1.82 times higher than that in 1990, and the population attributable fraction increased by 44.13%. The burden of disease caused by drinking alcohol had been increasing. By comparing with the comprehensive intervention strategy of restricting harmful drinking put forward by the World Health Organization, we suggest that the current interventions that need to be improved in China should include several aspects below: (1) strengthening the control of alcohol production, marketing and circulation, (2) restricting the availability of alcohol products for minors through enterprise self-discipline, laws and regulations, parents and school health education, (3) bridging gaps in appropriate techniques and services for alcohol restriction/abstinence in the health care system, (4) providing services such as rapid screening of alcohol dependence and short abstinence interventions, (5) strengthening restrictions on alcohol advertising especially in new media (e.g., online and social media) marketing practices for alcohol products, (6) conducting scientific research and evaluation on alcohol tax-related issues, and (7) regularly reviewing alcohol prices related to inflation and income levels.