BACKGROUND: Approximately 40% of individuals with diabetes worldwide are at risk of developing diabetic kidney disease (DKD), which is not only the leading cause of kidney failure, but also significantly increases the risk of cardiovascular disease, causing significant societal health and financial burdens. This study aimed to describe the burden of DKD and explore its cross-country epidemiological status, predict development trends, and assess its risk factors and sociodemographic transitions. METHODS: Based on the Global Burden of Diseases (GBD) Study 2021, data on DKD due to type 1 diabetes (DKD-T1DM) and type 2 diabetes (DKD-T2DM) were analyzed by sex, age, year, and location. Numbers and age-standardized rates were used to compare the disease burden between DKD-T1DM and DKD-T2DM among locations. Decomposition analysis was used to assess the potential drivers. Locally weighted scatter plot smoothing and Frontier analysis were used to estimate sociodemographic transitions of DKD disability-adjusted life years (DALYs). RESULTS: The DALYs due to DKD increased markedly from 1990 to 2021, with a 74.0% (from 2,227,518 to 3,875,628) and 173.6% (from 4,122,919 to 11,278,935) increase for DKD-T1DM and DKD-T2DM, respectively. In 2030, the estimated DALYs for DKD-T1DM surpassed 4.4 million, with that of DKD-T2DM exceeding 14.6 million. Notably, middle-sociodemographic index (SDI) quintile was responsible for the most significant DALYs. Decomposition analysis revealed that population growth and aging were major drivers for the increased DKD DALYs in most regions. Interestingly, the most pronounced effect of positive DALYs change from 1990 to 2021 was presented in high-SDI quintile, while in low-SDI quintile, DALYs for DKD-T1DM and DKD-T2DM presented a decreasing trend over the past years. Frontiers analysis revealed that there was a negative association between SDI quintiles and age-standardized DALY rates (ASDRs) in DKD-T1DM and DKD-T2DM. Countries with middle-SDI shouldered disproportionately high DKD burden. Kidney dysfunction (nearly 100.0% for DKD-T1DM and DKD-T2DM), high fasting plasma glucose (70.8% for DKD-T1DM and 87.4% for DKD-T2DM), and non-optimal temperatures (low and high, 5.0% for DKD-T1DM and 5.1% for DKD-T2DM) were common risk factors for age-standardized DALYs in T1DM-DKD and T2DM-DKD. There were other specific risk factors for DKD-T2DM such as high body mass index (38.2%), high systolic blood pressure (10.2%), dietary risks (17.8%), low physical activity (6.2%), lead exposure (1.2%), and other environmental risks. CONCLUSIONS DKD markedly increased and varied significantly across regions, contributing to a substantial disease burden, especially in middle-SDI countries. The rise in DKD is primarily driven by population growth, aging, and key risk factors such as high fasting plasma glucose and kidney dysfunction, with projections suggesting continued escalation of the burden by 2030.
Humans ; Global Burden of Disease ; Risk Factors ; Male ; Female ; Disability-Adjusted Life Years ; Diabetic Nephropathies/epidemiology* ; Middle Aged ; Diabetes Mellitus, Type 2/epidemiology* ; Adult ; Diabetes Mellitus, Type 1/complications* ; Aged ; Adolescent ; Young Adult ; Quality-Adjusted Life Years

BACKGROUND: The epidemiological pattern and disease burden of type 2 diabetes have been shifting in China over the past decades. This analysis described the epidemiological transition of type 2 diabetes in the past three decades and projected the trend in the future three decades in China. METHODS: Age-, sex-, and year-specific incidence, prevalence, death, and disability-adjusted life years (DALYs) for people with 15 years or older and diabetes or high fasting glucose in China and related countries from 1990 to 2021 were obtained from the Global Burden of Disease. We obtained the trends of age-, sex-, and year-specific rates and absolute numbers of incidence, prevalence, deaths, and DALYs attributable to type 2 diabetes in China from 1990 to 2021. Using the Lee-Carter model, we projected the incidence, prevalence, death, and DALYs attributable to type 2 diabetes to 2050 stratified by age and sex. RESULTS: The age-standardized incidence of type 2 diabetes was 341.5 per 100,000 persons (1.6 times in 1990) and the age-standardized prevalence was 9.96% (9960.0 per 100,000 persons, 2.5 times in 1990) in China 2021. In 2021, there were 0.9 million deaths and 26.8 million DALYs due to type 2 diabetes or hyperglycemia, as 2.9 and 2.7 times the data in 1990, respectively. The age-standardized rates of type 2 diabetes and hyperglycemia were projected to raise to 449.5 per 100,000 persons for incidence, 18.17% for prevalence, 244.6 per 100,000 persons for death, and 4720.2 per 100,000 persons for DALYs by 2050. The incidence of type 2 diabetes kept growing among individuals under the age of 20 years in the past three decades (128.7 per 100,000 persons in 1990 and 439.9 per 100,000 persons in 2021) and estimating 1870.8 per 100,000 in 2050. CONCLUSIONS The incidence, prevalence, and disease burden of type 2 diabetes grew rapidly in China in the past three decades. The prevention of type 2 diabetes in young people and the care for elder adults will be the greatest challenge for the country.
Humans ; Diabetes Mellitus, Type 2/mortality* ; China/epidemiology* ; Prevalence ; Female ; Male ; Incidence ; Middle Aged ; Adult ; Aged ; Adolescent ; Young Adult ; Disability-Adjusted Life Years ; Aged, 80 and over

Child ; Humans ; China/epidemiology* ; Diabetes Mellitus, Type 2/epidemiology* ; Hypoglycemic Agents/therapeutic use* ; Insulin/therapeutic use* ; Insulin Resistance

BACKGROUND: Prior studies have shown that drivers with type 2 diabetes are more likely to be involved in motor vehicle collisions (MVCs) compared to the general population. Certain meteorological factors have been increasingly recognized as contributors to MVC risk. This study aims to examine the association of MVCs with temperature, rainfall, wind speed, and sunshine duration among drivers with type 2 diabetes. METHODS: Using Taiwan's National Health Insurance data (2019-2021), we identified individuals diagnosed with type 2 diabetes and linked their records to the Police-Reported Traffic Accident Registry to obtain daily MVC counts. Meteorological data were sourced from the Central Weather Administration. Associations between daily weather conditions and MVCs were assessed using a Distributed Lag Non-Linear Model. RESULTS: Over the 1,096-day study period, 170,468 MVC events involving drivers with type 2 diabetes were recorded. A U-shaped association was observed between same-day temperature and MVC rates. Compared with the reference temperature of 17.5 °C, both lower temperatures (≤15 °C; rate ratio [RR] = 1.014-1.053) and higher temperatures (≥30 °C; RR = 1.062) were associated with increased MVC risk. Rainfall showed an inverse relationship with MVCs. Compared with 70 mm of rainfall, the lowest MVC rate occurred at 129 mm (RR = 0.873), while the highest was on rain-free days (0 mm; RR = 1.068). Stronger effects were observed when lag periods up to 14 days were considered. Wind speed and sunshine duration were not significantly associated with MVC risk. CONCLUSIONS These findings suggest that drivers with type 2 diabetes should exercise greater caution on days with extreme temperatures or in days with lesser rainfall, as these conditions may elevate MVC risk.
Humans ; Diabetes Mellitus, Type 2/epidemiology* ; Taiwan/epidemiology* ; Accidents, Traffic/statistics & numerical data* ; Male ; Middle Aged ; Female ; Weather ; Aged ; Adult ; Temperature ; Risk Factors

OBJECTIVE: This study aimed to investigate the impact of glycemic control and diabetes duration on subsequent myocardial infarction (MI) in patients with both coronary heart disease (CHD) and type 2 diabetes (T2D). METHODS: We conducted a retrospective cohort study of 33,238 patients with both CHD and T2D in Shenzhen, China. Patients were categorized into 6 groups based on baseline fasting plasma glucose (FPG) levels and diabetes duration (from the date of diabetes diagnosis to the baseline date) to examine their combined effects on subsequent MI. Cox proportional hazards regression models were used, with further stratification by age, sex, and comorbidities to assess potential interactions. RESULTS: Over a median follow-up of 2.4 years, 2,110 patients experienced MI. Compared to those with optimal glycemic control (FPG < 6.1 mmol/L) and shorter diabetes duration (< 10 years), the fully-adjusted hazard ratio ( HR) (95% Confidence Interval [95% CI]) for those with a diabetes duration of ≥ 10 years and FPG > 8.0 mmol/L was 1.93 (95% CI: 1.59, 2.36). The combined effects of FPG and diabetes duration on MI were largely similar across different age, sex, and comorbidity groups, although the excess risk of MI associated with long-term diabetes appeared to be more pronounced among those with atrial fibrillation. CONCLUSION Our study indicates that glycemic control and diabetes duration significant influence the subsequent occurrence of MI in patients with both CHD and T2D. Tailored management strategies emphasizing strict glycemic control may be particularly beneficial for patients with longer diabetes duration and atrial fibrillation.
Humans ; Diabetes Mellitus, Type 2/blood* ; Male ; Female ; Middle Aged ; Aged ; Coronary Disease/complications* ; Myocardial Infarction/etiology* ; Retrospective Studies ; China/epidemiology* ; Glycemic Control ; Blood Glucose ; Adult ; Risk Factors ; Time Factors

OBJECTIVE: This study aimed to identify high-risk areas for type 2 diabetes mellitus (T2DM) mortality to provide relevant evidence for interventions in emerging economies. METHODS: Empirical Bayesian Kriging and a discrete Poisson space-time scan statistic were applied to identify the spatiotemporal clusters of T2DM mortality. The relationships between economic factors, air pollutants, and the mortality risk of T2DM were assessed using regression analysis and the Poisson Log-linear Model. RESULTS: A coastal district in East Guangdong, China, had the highest risk (Relative Risk [RR] = 4.58, P < 0.01), followed by the 10 coastal districts/counties in West Guangdong, China (RR = 2.88, P < 0.01). The coastal county in the Pearl River Delta, China (RR = 2.24, P < 0.01), had the third-highest risk. The remaining risk areas were two coastal counties in East Guangdong, 16 districts/counties in the Pearl River Delta, and two counties in North Guangdong, China. Mortality due to T2DM was associated with gross domestic product per capita (GDP per capita). In pilot assessments, T2DM mortality was significantly associated with carbon monoxide. CONCLUSION High mortality from T2DM occurred in the coastal areas of East and West Guangdong, especially where the economy was progressing towards the upper middle-income level.
Diabetes Mellitus, Type 2/epidemiology* ; China/epidemiology* ; Humans ; Risk Factors ; Spatio-Temporal Analysis ; Air Pollutants/analysis* ; Socioeconomic Factors ; Bayes Theorem ; Female ; Male ; Middle Aged

OBJECTIVE: This study aimed to explore the interplay between the life-course body mass index (BMI) trajectories and insulin resistance (IR) on incident diabetes. METHODS: This longitudinal cohort included 2,336 participants who had BMI repeatedly measured 3-8 times between 1989 and 2009, as well as glucose and insulin measured in 2009. BMI trajectories were identified using a latent class growth mixed model. The interplay between BMI trajectories and IR on diabetes was explored using the four-way effect decomposition method. Logistic regression and mediation models were used to estimate the interaction and mediation effects, respectively. RESULTS: Three distinct BMI trajectory groups were identified: low-stable ( n = 1,625), medium-increasing ( n = 613), and high-increasing ( n = 98). Both interaction and mediation effects of BMI trajectories and IR on incident diabetes were significant ( P < 0.05). The proportion of incident diabetes was higher in the IR-obesity than in the insulin-sensitivity (IS) obesity group (18.9% vs. 5.8%, P < 0.001). After adjusting for covariates, the odds ratios (95% confidence intervals) of the IR, IS-obesity, and IR-obesity groups vs. the normal group were 3.22 (2.05, 5.16), 2.05 (1.00, 3.97), and 7.98 (5.19, 12.62), respectively. IR mediated 10.7% of the total effect of BMI trajectories on incident diabetes ( P < 0.001). CONCLUSION We found strong interactions and weak mediation effects of IR on the relationship between life-course BMI trajectories and incident diabetes. IS-obesity is associated with a lower risk of incident diabetes than IR-obesity.
Humans ; Insulin Resistance ; Body Mass Index ; Male ; Female ; Middle Aged ; China/epidemiology* ; Adult ; Longitudinal Studies ; Incidence ; Diabetes Mellitus/epidemiology* ; Aged ; Obesity/epidemiology* ; Diabetes Mellitus, Type 2/epidemiology* ; East Asian People

OBJECTIVE: To investigate the association between long-term exposure to ambient fine particulate matter (PM _2.5) and its constituents and the risk of incident type 2 diabetes mellitus (T2DM), and to examine the modification roles of overweight status. METHODS: This prospective study included 27,507 adults living in rural China. The annual mean residential exposure to PM _2.5 and its constituents was estimated using a satellite-based statistical model. Cox models were used to estimate the risk of T2DM associated with PM _2.5 and its constituents. Stratified analysis quantified the role of overweight status in the association between PM _2.5 constituents and T2DM. RESULTS: Over a median follow-up of 9.4 years, 3,001 new T2DM cases were identified. The hazard ratio ( HR) for a 10 μg/m ³ increase in ambient PM _2.5 was 1.30 (95% confidence interval [ CI]: 1.17, 1.45). Among the constituents, the strongest association was observed with black carbon. Being overweight significantly modified the association between certain constituents and the risk of T2DM. Participants who were overweight and exposed to the highest quartile of PM _2.5 constituents had the highest risk of T2DM ( HR: 2.46, 95% CI: 2.04, 2.97). CONCLUSIONS Our findings indicate that PM _2.5 was associated with an increased risk of T2DM, with black carbon potentially being the primary contributor. Being overweight appeared to enhance the association between PM _2.5 and T2DM. This suggests that controlling both PM _2.5 exposure and overweight status may reduce the burden of T2DM.
Humans ; Diabetes Mellitus, Type 2/chemically induced* ; China/epidemiology* ; Particulate Matter/analysis* ; Overweight/epidemiology* ; Female ; Male ; Middle Aged ; Rural Population ; Air Pollutants/analysis* ; Adult ; Prospective Studies ; Environmental Exposure/adverse effects* ; Aged ; Risk Factors

BACKGROUND: Management of gastric leak after sleeve gastrectomy (SG) is challenging due to its unpredictable outcomes. We aimed to summarize the characteristics of SG leaks and analyze interventions and corresponding outcomes in a real-world setting. METHODS: To retrospectively review of 15,721 SG procedures from 2010 to 2020 based on a national registry. A cumulative sum analysis was used to identify a fitting curve of gastric leak rate. The Kaplan-Meier method and log-rank tests were performed to calculate and compare the probabilities of relevant outcomes. The logistic regression analysis was conducted to determine the predictors of acute leaks. RESULTS: A total of 78 cases of SG leaks were collected with an incidence of 0.5% (78/15,721) from this registry (6 patients who had the primary SG in non-participating centers). After accumulating 260 cases in a bariatric surgery center, the leak rate decreased to a stably low value of under 1.17%. The significant differences presented in sex, waist circumference, and the proportion of hypoproteinemia and type 2 diabetes at baseline between patients with SG leak and the whole registry population ( P = 0.005, = 0.026, <0.001, and = 0.001, respectively). Moreover, 83.1% (59/71) of the leakage was near the esophagogastric junction region. Leakage healed in 64 (88.9%, 64/72) patients. The median healing time of acute and non-acute leaks was 5.93 months and 8.12 months, respectively. Acute leak (38/72, 52.8%) was the predominant type with a cumulative reoperation rate >50%, whereas the cumulative healing probability in the patients who required surgical treatment was significantly lower than those requring non-surgical treatment ( P = 0.013). Precise dissection in the His angle area was independently associated with a lower acute leak rate, whereas preservation ≥2 cm distance from the His angle area was an independent risk factor. CONCLUSIONS Male sex, elevated waist circumference, hypoproteinaemia, and type 2 diabetes are risk factors of gastric leaks after SG. Optimizing surgical techniques, including precise dissection of His angle area and preservation of smaller gastric fundus, should be suggested to prevent acute leaks.
Humans ; Male ; Retrospective Studies ; Diabetes Mellitus, Type 2/complications* ; Obesity, Morbid ; Anastomotic Leak/epidemiology* ; Gastrectomy/methods* ; Reoperation/methods* ; Registries ; Laparoscopy/methods* ; Treatment Outcome

Humans ; Diabetes Mellitus, Type 2/epidemiology* ; Air Pollution/adverse effects* ; Air Pollutants/toxicity* ; Risk Assessment ; Particulate Matter ; Environmental Exposure