INTRODUCTION: Degenerative mitral stenosis (DMS) is frequently cited as increasing in prevalence in the developed world, although comparatively little is known about DMS in comparison to rheumatic mitral stenosis (RMS). METHOD: A retrospective observational study was conducted on 745 cases of native-valve mitral stenosis (MS) with median follow-up time of 7.25 years. Clinical and echocardiographic parameters were compared. Univariate and multivariate Cox regression analyses were performed for a composite of all-cause mortality and heart failure hospitalisation. RESULTS: Patients with DMS compared to RMS were older (age, mean ± standard deviation: 69.6 ± 12.3 versus [vs] 51.6 ± 14.3 years, respectively; P<0.001) and a greater proportion had medical comorbidities such as diabetes mellitus (78 [41.9%] vs 112 [20.0%], P<0.001). The proportion of cases of degenerative aetiology increased from 1.1% in 1991-1995 to 41.0% in 2016-2017. In multivariate analysis for the composite outcome, age (hazard ratio [HR] 95% confidence interval [CI] of 1.032 [1.020-1.044]; P<0.001), diabetes mellitus (HR 1.443, 95% CI 1.068-1.948; P=0.017), chronic kidney disease (HR 2.043, 95% CI 1.470-2.841; P<0.001) and pulmonary artery systolic pressure (HR 1.019, 95% CI 1.010- 1.027; P<0.001) demonstrated significant indepen-dent associations. The aetiology of MS was not independently associated with the composite outcome. CONCLUSION DMS is becoming an increasingly common cause of native-valve MS. Despite numerous clinical differences between RMS and DMS, the aetiology of MS did not independently influence a composite of mortality or heart failure hospitalisation.
Humans ; Mitral Valve Stenosis/etiology* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Rheumatic Heart Disease/mortality* ; Echocardiography ; Hospitalization/statistics & numerical data* ; Heart Failure/epidemiology* ; Singapore/epidemiology* ; Proportional Hazards Models ; Diabetes Mellitus/epidemiology*

BACKGROUND: The global rise in diabetes prevalence is a pressing concern. Despite initiatives like "The Healthy Beijing Action 2020-2030" advocating for increased awareness, treatment, and control, the specific situation in Beijing remains unexplored. This study aimed to analyze the trends in diabetes prevalence, awareness, treatment, and control among Beijing adults. METHODS: Through a stratified multistage probability cluster sampling method, a series of representative cross-sectional surveys were conducted in Beijing from 2005 to 2022, targeting adults aged 18-79 years. A face-to-face questionnaire, along with body measurements and laboratory tests, were administered to 111,943 participants. Data from all survey were age- and/or gender-standardized based on the 2020 Beijing census population. Annual percentage rate change (APC) or average annual percentage rate change (AAPC) was calculated to determine prevalence trends over time. Complex sampling logistic regression models were employed to explore the relationship between various characteristics and diabetes. RESULTS: From 2005 to 2022, the total prevalence of diabetes among Beijing adults aged 18-79 years increased from 9.6% (95% CI: 8.8-10.4%) to 13.9% (95% CI: 13.1-14.7%), with an APC/AAPC of 2.1% (95% CI: 1.1-3.2%, P <0.05). Significant increases were observed among adults aged 18-39 years and rural residents. Undiagnosed diabetes rose from 3.5% (95% CI: 3.2-4.0%) to 7.2% (95% CI: 6.6-7.9%) with an APC/AAPC of 4.1% (95% CI: 0.5-7.3%, P <0.05). However, diabetes awareness and treatment rates showed annual declines of 1.4% (95% CI: -3.0% to -0.2%, P <0.05) and 1.3% (95% CI: -2.6% to -0.2%, P <0.05), respectively. The diabetes control rate decreased from 21.5% to 19.1%, although not statistically significant (APC/AAPC = -1.5%, 95% CI: -5.6% to 1.9%). Overweight and obesity were identified as risk factors for diabetes, with ORs of 1.65 (95% CI: 1.38-1.98) and 2.48 (95% CI: 2.07-2.99), respectively. CONCLUSIONS The prevalence of diabetes in Beijing has significantly increased between 2005 and 2022, particularly among young adults and rural residents. Meanwhile, there has been a concerning decrease in diabetes awareness and treatment rates, while control rates have remained stagnant. Regular blood glucose testing, especially among adults aged 18-59 years, should be warranted. Furthermore, being male, elderly, overweight, or obese was associated with higher diabetes risk, suggesting the needs for targeted management strategies.
Humans ; Adult ; Middle Aged ; Male ; Female ; Aged ; Adolescent ; Young Adult ; Cross-Sectional Studies ; Diabetes Mellitus/epidemiology* ; Beijing/epidemiology* ; Prevalence ; China/epidemiology* ; Surveys and Questionnaires

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

BACKGROUND: Studies on the impact of blood glucose indicators on metabolism remain relatively scarce. The aim of this study was to investigate the associations between blood glucose indicators and metabolic disorders in China. METHODS: Data were from the Thyroid disorders, Iodine status and Diabetes Epidemiological survey (TIDE survey), which randomly selected 31 cities from 31 provinces in the Chinese mainland. A total of 68,383 participants without preexisting diabetes and have complete data on blood glucose, lipids, and blood pressure were included in the analysis. The diabetic population was divided into seven groups based on different types of elevated blood glucose levels, including fasting plasma glucose (FPG), postprandial glucose (PPG), and hemoglobin A1c (HbA1c): FPG ≥7 mmol/L; PPG ≥11.1 mmol/L; HbA1c ≥6.5%; FPG ≥7 mmol/L and PPG ≥11.1 mmol/L; FPG ≥7 mmol/L and HbA1c ≥6.5%; PPG ≥11.1 mmol/L and HbA1c ≥6.5%; FPG ≥7 mmol/L, PPG ≥11.1 mmol/L, and HbA1c ≥6.5%. The effects of each blood glucose indicator on metabolism were investigated separately. Weighted calculation was applied during the analysis, with the weighting coefficient based on the number of people corresponding to the population characteristics of each sample in the 2010 Chinese Census. A logistic regression model with restricted cubic splines (RCS) was employed to characterize the nonlinear associations of age and body mass index (BMI) with the risk of diabetes subtypes defined by distinct blood glucose indicators elevations, as well as the relationships between different blood glucose indicators (FPG, PPG, HbA1c) and the risk of metabolic disorders such as hypertension, hypertriglyceridemia, hypercholesterolemia, high low-density lipoprotein cholesterol (high LDL-C) and low high-density lipoprotein cholesterol (low HDL-C). RESULTS: Among individuals with diabetes, elevated PPG alone was the most common abnormality, affecting 26.96% (1382/5127) of the population. Among the seven groups with only one elevated blood glucose indicator, individuals with elevated PPG alone exhibited the highest mean levels of triglycerides (TG) at 2.11 mmol/L (95% confidence interval [CI]: 1.97-2.25 mmol/L, P = 0.004), total cholesterol (TC) at 5.26 mmol/L (95% CI: 5.18-5.33 mmol/L, P <0.001), and low-density lipoprotein cholesterol (LDL-C) at 3.12 mmol/L, (95% CI: 3.06-3.19 mmol/L, P = 0.001). Individuals with elevated PPG alone showed a high prevalence of hypertension (806/1382, 58.32%), hypertriglyceridemia (676/1382, 48.91%), hypercholesterolemia (694/1382, 50.22%), High LDL-C (525/1382, 37.94%), and Low HDL-C (364/1382, 26.34%). The association of age and BMI with the risk of diabetes revealed that the older the patient, the steeper the RCS curve for the odds ratio (OR) of diabetes with elevated PPG alone (age = 60, OR = 2.79, 95% CI [2.49-3.12], P <0.01). Similarly, as BMI increased, the RCS curve for the OR of diabetes with elevated HbA1c alone also steepened (BMI = 35, OR = 3.75, 95% CI [3.23-4.35], P <0.001). Additionally, the RCS yielded a positive association between blood glucose indicators and metabolic diseases risk. In individuals with diabetes, RCS for both the ORs of metabolic diseases (hypertension, hypertriglyceridemia, hypercholesterolemia, high LDL-C, low HDL-C) and the levels of metabolic indicators (TG, TC, LDL-C, HDL-C) revealed some inflection points within the ranges of FPG 5-6 mmol/L, PPG 6-8 mmol/L, and HbA1c 5.5-6.0%. CONCLUSIONS PPG is more closely related to metabolic disorders than FPG and HbA1c in people with diabetes. For patients with diabetes and metabolic disorders, it may be necessary to monitor blood glucose fluctuations within specific ranges (FPG 5-6 mmol/L, PPG 6-8 mmol/L, and HbA1c 5.5-6.0%).
Humans ; Female ; Cross-Sectional Studies ; Male ; Blood Glucose/metabolism* ; Middle Aged ; Glycated Hemoglobin/metabolism* ; Adult ; Metabolic Diseases/epidemiology* ; Aged ; China ; Diabetes Mellitus/blood* ; East Asian People

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

Non-obstructive azoospermia is a common condition associated with significant health risks, including increased mortality, cancer, and chronic diseases such as metabolic and cardiovascular disorders. This review aims to highlight the potential health challenges faced by men with this condition compared to fertile counterparts. Through a comprehensive bibliographic search on PubMed, using the following algorithm: ("infertility, male" [MeSH Terms] OR "azoospermia" [MeSH Terms]) AND ("mortality" [MeSH Terms] OR "neoplasms" [MeSH Terms] OR "chronic disease" [MeSH Terms] OR "diabetes mellitus" [MeSH Terms] OR "heart diseases" [MeSH Terms]), we analyzed existing literature to explore the associations between infertility, specifically azoospermia, and adverse health outcomes. Findings indicate that infertile men are at a higher risk of death, various cancers (particularly testicular cancer), metabolic syndrome, diabetes, hypogonadism, and cardiovascular disease. Although research specifically addressing azoospermia is limited, available studies support the notion that men with this condition may experience heightened health vulnerabilities. Given these risks, it is imperative for healthcare professionals, especially urologists, to conduct thorough health assessments for men diagnosed with azoospermia. Informing patients of these potential health issues and integrating comprehensive evaluations into their care can facilitate early detection and intervention for life-threatening conditions. Ultimately, men with azoospermia should receive ongoing monitoring to address their specific health concerns, thus improving their long-term health outcomes.
Humans ; Male ; Azoospermia/epidemiology* ; Cardiovascular Diseases/etiology* ; Metabolic Syndrome/epidemiology* ; Infertility, Male/complications* ; Testicular Neoplasms/epidemiology* ; Hypogonadism/epidemiology* ; Diabetes Mellitus/epidemiology* ; Risk Factors ; Neoplasms/epidemiology*

OBJECTIVES: To analyze the multimorbidity patterns and core diseases among hospitalized patients in different age groups and to explore the impacts of multimorbidity patterns on hospitalization costs. METHODS: Electronic medical records of adult inpatients (aged ≥18 years) from Ningbo Medical Center Lihuili Hospital between January 1, 2018, and June 30, 2023 were collected. The multimorbidity status involving 53 specific diseases was analyzed across different age groups. Association rule mining was used to identify common multimorbidity patterns. Complex network analysis was used to identify core diseases within the multimorbidity networks. Generalized estimating equations (GEE) were used to analyze the impact of different multimorbidity patterns on hospitalization costs. RESULTS: The prevalence of multimorbidity among the 359 402 adult inpatients was 38.51%, with higher rates observed in males (43.60%) and elderly patients (58.29%). Association rule mining identified 15 common multimorbidity patterns, which exhibited differences across age groups. The most prevalent multimorbidity pattern overall was "diabetes→hypertension" (support=7.04%, confidence=62.17%, lift=2.17). In the young adult group, the most prevalent pattern was "dyslipidemia→chronic liver disease" (support=1.19%, confidence=53.17%, lift=6.04). In the middle-aged group, it was "diabetes→hypertension" (support=4.84%, confidence=50.28%, lift=2.15). In the elderly group, it was "coronary heart disease, diabetes→hypertension" (support=2.38%, confidence=77.43%, lift=1.63). Complex network analysis revealed that the core diseases within multimorbidity networks differed across age groups. The core disease identified in the young adult group was chronic liver disease (degree centrality=50, betweenness centrality=0.055, closeness centrality=0.963). Core diseases in the middle-aged group included hypertension, chronic liver disease, and diabetes (all with degree centrality=52, betweenness centrality=0.022, closeness centrality=1.000). Core diseases in the elderly group comprised hypertension, diabetes, malignant tumors, chronic liver disease, thyroid disease, anemia, and arrhythmia (all with degree centrality=52, betweenness centrality=0.009, closeness centrality=1.000). Generalized estimating equations analysis indicated that, most multimorbidity patterns were significantly associated with increased hospitalization costs. However, the magnitude of cost increase varied across different multimorbidity patterns. Specifically, hospitalization costs for patients with patterns such as "heart failure→hypertension", "stroke→hypertension", "malignant tumor, diabetes→hypertension", "stroke, diabetes→hypertension", and "diabetes, heart failure→hypertension" were more than double those of patients without any target diseases. CONCLUSIONS Multimorbidity patterns and core diseases among hospitalized patients differ significantly across age groups, and different patterns exert varying impacts on hospitalization costs. These findings underscore the necessity for age-stratified and multimorbidity pattern specific management strategies.
Humans ; Multimorbidity ; Male ; Hospitalization/economics* ; Female ; Aged ; Middle Aged ; Adult ; Age Factors ; Young Adult ; Adolescent ; Diabetes Mellitus/epidemiology* ; Electronic Health Records ; Aged, 80 and over ; Hospital Costs ; China/epidemiology* ; Hypertension/economics* ; Liver Diseases/epidemiology*

BACKGROUND: Studies have shown that married couples often share similar lifestyles, as well as lifestyle-associated conditions such as diabetes, hypertension, and hyperlipidemia. This study aims to prospectively investigate the association between an individual's development of a non-communicable disease and the subsequent development of the same condition in their spouse. METHODS: This population-based cohort study utilized 12 waves of annual prospective surveys from 2005 onwards in Japan, with a discrete-time design. A total of 9,417 middle-aged couples (18,834 participants; discrete-time observations = 118,876) were included. Each participant whose spouse had developed one of six conditions was propensity score-matched with five controls whose spouses had not been diagnosed with the condition: diabetes [n = 1374 vs n = 6870], hypertension [n = 2657 vs n = 13285], hypercholesterolemia [n = 3321 vs n = 16605], stroke [n = 567 vs n = 2835], coronary heart disease (CHD) [n = 1093 vs n = 5465] or cancer [n = 923 vs n = 4615]. Using conditional logistic regression, we assessed participants' development of the same condition within three years following their spouse's diagnosis. RESULTS: Participants whose spouses had developed diabetes, hypertension, hypercholesterolemia, or CHD were more likely to develop the same condition within three years. The odds ratios (ORs) and 95% confidence intervals (CIs) were: 1.96 (1.53-2.50), 1.20 (1.06-1.36), 1.63 (1.47-1.81) and 1.43 (1.05-1.95), respectively. No significant associations were observed in stroke [1.69 (0.80-3.58)] or cancer [1.08 (0.75-1.54)]. CONCLUSION Spouses of individuals recently diagnosed with certain metabolic conditions are at a higher risk of developing those conditions themselves. These findings may provide valuable guidance for targeting and personalizing chronic disease screening and prevention efforts.
Humans ; Spouses/statistics & numerical data* ; Male ; Female ; Middle Aged ; Aged ; Japan/epidemiology* ; Longitudinal Studies ; Noncommunicable Diseases/epidemiology* ; Prospective Studies ; Neoplasms/epidemiology* ; Diabetes Mellitus/epidemiology* ; Risk Factors ; Aged, 80 and over ; Adult ; Hypertension/epidemiology*

BACKGROUND: High visceral fat mass (FM) is associated with a high risk of cardiometabolic morbidity. Meanwhile, loss of skeletal muscle (lean mass, LM) has been suggested to contribute to metabolic diseases. METHODS: We investigated associations between cardiometabolic diseases and dual energy X-ray absorptiometry (DXA)-measured body composition indices, including the FM index (FM/height²), percent body fat, trunk-to-appendicular fat ratio (TAR), trunk-to-leg fat ratio (TLR), LM index (LM/height²) and FM-to-LM ratio in 595 community-dwelling elderly Japanese men (mean age, 74 years; standard deviation, 6; range, 65 to 94). Hypertension was identified as high blood pressure and/or the use of antihypertensive drugs. Diabetes was identified as high hemoglobin A1c and/or the use of antidiabetic drugs. The ability of DXA-based indices to discriminate between the presence and absence of cardiometabolic diseases was evaluated using area under the curve (AUC) calculated by receiver operating characteristic curve analysis. RESULTS: Body mass index, FM index, percent body fat, TAR, TLR and FM-to-LM ratio were significantly associated with hypertension (P < 0.05). TAR and TLR, but not body mass index, FM index, percent body fat, LM index and FM-to-LM ratio, showed significant positive associations with diabetes. The AUC for the LM index was significantly lower than those for the FM index, percent body fat and FM-to-LM ratio. No associations were observed between the LM index and hypertension, dyslipidemia and diabetes. CONCLUSION The association between cardiometabolic function and LM, which includes skeletal muscle, may not be as pronounced or stronger than associations between cardiometabolic function and FM. Further detailed studies are needed to clarify how skeletal muscle contributes to cardiometabolic disease.
Humans ; Male ; Absorptiometry, Photon ; Aged ; Japan/epidemiology* ; Body Composition ; Aged, 80 and over ; Hypertension/epidemiology* ; Cardiovascular Diseases/epidemiology* ; Body Mass Index ; Muscle, Skeletal ; Osteoporosis/epidemiology* ; Diabetes Mellitus/epidemiology* ; Risk Factors ; East Asian People