OBJECTIVE: This study aimed to estimate spatiotemporal variations of global heat-related cardiovascular disease (CVD) burden from 1990 to 2019. METHODS: Data on the burden of heat-related CVD were derived from the Global Burden of Disease Study 2019. Deaths and disability-adjusted life years (DALYs) were used to quantify heat-induced CVD burden. We calculated the age-standardized mortality rate (ASMR) and DALY rate (ASDR) per 100,000 population to compare this burden across regions. Generalized linear models were applied to evaluate estimated annual percentage changes (EAPC) for temporal trends from 1990 to 2019. The correlation between the socio-demographic index (SDI) and age-standardized rate was measured using the Spearman rank test. RESULTS: Heat-induced CVD caused approximately 90 thousand deaths worldwide in 2019. Global ASMR and ASDR of heat-related CVD in 2019 were 1.17 [95% confidence interval ( CI): 0.13-1.98] and 25.59 (95% CI: 2.07-44.17) per 100,000 population, respectively. The burden was significantly increased in middle and low-SDI regions and slightly decreased in high-SDI regions from 1990 to 2019. ASMR showed an upward trend, with the most considerable increase in low-latitude countries. We observed a negative correlation between SDI and EAPC in ASMR ( r _s = -0.57, P < 0.01) and ASDR ( r _s = -0.59, P < 0.01) among 204 countries. CONCLUSION Heat-attributable CVD burden substantially increased in most developing countries and tropical regions.
Humans ; Quality-Adjusted Life Years ; Cardiovascular Diseases/etiology* ; Hot Temperature ; Temperature ; Global Health ; Global Burden of Disease

BACKGROUND: Sex- and age-specific impacts of cardiovascular risk factors on the development of dementia have not been well evaluated. We investigated these impacts of smoking, overweight/obesity, hypertension, and diabetes mellitus on the risk of disabling dementia. METHODS: The study participants were 25,029 (10,134 men and 14,895 women) Japanese aged 40-74 years without disabling dementia at baseline (2008-2013). They were assessed on smoking status (non-current or current), overweight/obesity (body mass index ≥25 kg/m² and ≥30 kg/m², respectively), hypertension (systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg or any antihypertensive medication use), and diabetes mellitus (a fasting serum glucose ≥126 mg/dL, non-fasting glucose ≥200 mg/dL, hemoglobin A1c ≥6.5% by the National Glycohemoglobin Standardization Program or glucose-lowering medication use) at baseline. Disabling dementia was identified as the level of care required ≥1 and cognitive disability grade ≥IIa according to the National Long-term Care Insurance Database. We used a Cox proportional regression model to estimate hazard ratios and 95% confidence intervals (95% CIs) of disabling dementia according to the cardiovascular risk factors and calculated the population attributable fractions (PAFs). RESULTS: During a median follow-up of 9.1 years, 1,322 (606 men and 716 women) developed disabling dementia. Current smoking and hypertension were associated with a higher risk of disabling dementia in both sexes, whereas overweight or obesity was not associated with the risk in either sex. Diabetes mellitus was associated with a higher risk only in women (p for sex interaction = 0.04). The significant PAFs were 13% for smoking and 14% for hypertension in men and 3% for smoking, 12% for hypertension, and 5% for diabetes mellitus in women. The total PAFs of the significant risk factors were 28% in men and 20% in women. When stratified by age, hypertension in midlife (40-64 years) was associated with the increased risk in men, while diabetes mellitus in later-life (65-74 years) was so in women. CONCLUSIONS A substantial burden of disabling dementia was attributable to smoking, and hypertension in both sexes and diabetes mellitus in women, which may require the management of these cardiovascular risk factors to prevent dementia.
Male ; Humans ; Female ; Adult ; Middle Aged ; Overweight/complications* ; East Asian People ; Cardiovascular Diseases/epidemiology* ; Hypertension/etiology* ; Diabetes Mellitus/etiology* ; Obesity/etiology* ; Smoking/epidemiology* ; Risk Factors ; Age Factors ; Dementia/etiology*

BACKGROUND: Previous cardiovascular risk prediction models in Japan have utilized prospective cohort studies with concise data. As the health information including health check-up records and administrative claims becomes digitalized and publicly available, application of large datasets based on such real-world data can achieve prediction accuracy and support social implementation of cardiovascular disease risk prediction models in preventive and clinical practice. In this study, classical regression and machine learning methods were explored to develop ischemic heart disease (IHD) and stroke prognostic models using real-world data. METHODS: IQVIA Japan Claims Database was searched to include 691,160 individuals (predominantly corporate employees and their families working in secondary and tertiary industries) with at least one annual health check-up record during the identification period (April 2013-December 2018). The primary outcome of the study was the first recorded IHD or stroke event. Predictors were annual health check-up records at the index year-month, comprising demographic characteristics, laboratory tests, and questionnaire features. Four prediction models (Cox, Elnet-Cox, XGBoost, and Ensemble) were assessed in the present study to develop a cardiovascular disease risk prediction model for Japan. RESULTS: The analysis cohort consisted of 572,971 invididuals. All prediction models showed similarly good performance. The Harrell's C-index was close to 0.9 for all IHD models, and above 0.7 for stroke models. In IHD models, age, sex, high-density lipoprotein, low-density lipoprotein, cholesterol, and systolic blood pressure had higher importance, while in stroke models systolic blood pressure and age had higher importance. CONCLUSION Our study analyzed classical regression and machine learning algorithms to develop cardiovascular disease risk prediction models for IHD and stroke in Japan that can be applied to practical use in a large population with predictive accuracy.
Humans ; Cardiovascular Diseases/epidemiology* ; Prognosis ; Prospective Studies ; Japan/epidemiology* ; Stroke/etiology* ; Myocardial Ischemia/epidemiology* ; Risk Assessment/methods*

OBJECTIVE: The main aim of this study is to investigate whether acupuncture could be an effective complementary treatment for reducing the risk of macrovascular complications in diabetic patients currently taking antidiabetic medications using a nationwide population-based database. METHODS: We conducted a retrospective cohort study to assess the efficacy of acupuncture on cardiovascular complications in diabetic patients using data from patients between 40 and 79 years of age, newly diagnosed with diabetes between 2003 and 2006, found in the National Health Insurance Service-National Sample Cohort (NHIS-NSC) in Korea. From the data, we identified 21,232 diabetic patients who were taking antidiabetic medication between 2003 and 2006. The selected patients were divided into two groups-those who received acupuncture at least three times and those who received no acupuncture (non-acupuncture) in the year following their diagnosis of diabetes. After 1:1 propensity score matching (PSM), each group had 3350 patients, and the observation ceased at the occurrence of a major adverse cardiovascular event (MACE), which was defined as either myocardial infarction, stroke, or death due to cardiovascular cause. RESULTS: After PSM, the acupuncture group had a lower incidence of MACE (hazard ratio [HR]: 0.87; 95% confidence interval [CI]: 0.81-0.94; P = 0.0003) and all-cause mortality (HR: 0.77; 95% CI: 0.70-0.84; P < 0.0001) than the non-acupuncture group; the HRs for stroke-related mortality (HR: 0.75; 95% CI: 0.56-1.00; P = 0.0485), ischemic heart disease mortality (HR: 0.53; 95% CI: 0.34-0.84; P = 0.006) and circulatory system disease mortality (HR: 0.67; 95% CI: 0.55-0.82; P < 0.0001) were lower in the acupuncture group than in the non-acupuncture group in the secondary analysis. CONCLUSION Our results indicate that diabetic patients receiving acupuncture treatment might have a lower risk of MACE, all-cause mortality and cardiovascular mortality. This population-based retrospective study suggests beneficial effects of acupuncture in preventing macrovascular complications associated with diabetes. These findings call for further prospective cohort or experimental studies on acupuncture treatment for cardiovascular complications of diabetes. Please cite this article as: Jung H, Won T, Kim GY, Jang J, Yeo S, Lim S. Efficacy of acupuncture on cardiovascular complications in patients with diabetes mellitus in Korea: A nationwide retrospective cohort. J Integr Med. 2023; 21(2): 176-183.
Humans ; Retrospective Studies ; Cardiovascular Diseases/etiology* ; Diabetes Mellitus, Type 2/drug therapy* ; Hypoglycemic Agents/therapeutic use* ; Stroke/complications* ; Acupuncture Therapy ; Republic of Korea/epidemiology*

Humans ; Cardiovascular Diseases ; Risk Factors ; Myocardial Infarction/complications* ; Coronary Disease/etiology* ; Heart Disease Risk Factors

Recent decades have seen the remarkable development of China in medical accessibility and quality index, and the application of a number of new advanced cardiovascular technologies benefits more patients. However, according to the Annual Report on Cardiovascular Health and Diseases in China published in this article, which was organized and summarized by National Center for Cardiovascular Diseases, there is still a huge population living with risk factors of cardiovascular diseases (CVD), and the morbidity and mortality of CVD are increasing. It is estimated that there are around 330 million patients suffering from CVD currently, including 245 million of hypertension, 13 million of stroke, 45.3 million of peripheral artery disease, 11.39 million of coronary heart disease (CHD), 8.9 million of heart failure, 5 million of pulmonary heart disease, 4.87 million of atrial fibrillation, 2.5 million of rheumatic heart disease, and 2 million of congenital heart disease. Tobacco use, diet and nutrition factors, physical activity, overweight and obesity, and psychological factors are what affect cardiovascular health, while hypertension, dyslipidemia, diabetes, chronic kidney disease, metabolic syndrome, and air pollution are the risk factors for CVD. In this article, in addition to risk factors for CVD, we also report the epidemiological trends of CVD, including CHD, cerebrovascular disease, arrhythmias, valvular heart disease, congenital heart disease, cardiomyopathy, heart failure, pulmonary vascular disease and venous thromboembolism, and aortic and peripheral artery diseases, as well as the basic research and medical device development in CVD. In a word, China has entered a new stage of transforming from high-speed development focusing on scale growth to high-quality development emphasizing on strategic and key technological development to curb the trend of increasing incidence and mortality of CVD.
Humans ; Cardiovascular Diseases/etiology* ; Hypertension/complications* ; Risk Factors ; Cardiomyopathies ; Heart Failure/complications* ; Heart Defects, Congenital/complications* ; Coronary Disease ; Atrial Fibrillation/complications*

OBJECTIVE: To develop and validate a three-year risk prediction model for new-onset cardiovascular diseases (CVD) among female patients with breast cancer. METHODS: Based on the data from Inner Mongolia Regional Healthcare Information Platform, female breast cancer patients over 18 years old who had received anti-tumor treatments were included. The candidate predictors were selected by Lasso regression after being included according to the results of the multivariate Fine & Gray model. Cox proportional hazard model, Logistic regression model, Fine & Gray model, random forest model, and XGBoost model were trained on the training set, and the model performance was evaluated on the testing set. The discrimination was evaluated by the area under the curve (AUC) of the receiver operator characteristic curve (ROC), and the calibration was evaluated by the calibration curve. RESULTS: A total of 19 325 breast cancer patients were identified, with an average age of (52.76±10.44) years. The median follow-up was 1.18 [interquartile range (IQR): 2.71] years. In the study, 7 856 patients (40.65%) developed CVD within 3 years after the diagnosis of breast cancer. The final selected variables included age at diagnosis of breast cancer, gross domestic product (GDP) of residence, tumor stage, history of hypertension, ischemic heart disease, and cerebrovascular disease, type of surgery, type of chemotherapy and radiotherapy. In terms of model discrimination, when not considering survival time, the AUC of the XGBoost model was significantly higher than that of the random forest model [0.660 (95%CI: 0.644-0.675) vs. 0.608 (95%CI: 0.591-0.624), P < 0.001] and Logistic regression model [0.609 (95%CI: 0.593-0.625), P < 0.001]. The Logistic regression model and the XGBoost model showed better calibration. When considering survival time, Cox proportional hazard model and Fine & Gray model showed no significant difference for AUC [0.600 (95%CI: 0.584-0.616) vs. 0.615 (95%CI: 0.599-0.631), P=0.188], but Fine & Gray model showed better calibration. CONCLUSION It is feasible to develop a risk prediction model for new-onset CVD of breast cancer based on regional medical data in China. When not considering survival time, the XGBoost model and the Logistic regression model both showed better performance; Fine & Gray model showed better performance in consideration of survival time.
Humans ; Female ; Adult ; Middle Aged ; Adolescent ; Breast Neoplasms/epidemiology* ; Cardiovascular Diseases/etiology* ; Proportional Hazards Models ; Logistic Models ; China/epidemiology*

Vascular endothelium formulates the basic defense against cardiovascular diseases. Multiple factors such as inflammatory factors, oxidative stress and biological factors can cause endothelial dysfunction and be involved in the formation and development of cardiovascular diseases. In studies of recent years, accumulated evidences showed that periodontitis was an independent risk factor for cardiovascular events, and was related to vascular endothelial dysfunction. Periodontal therapy could improve the vascular endothelial function. In this paper, the epidemiological evidences of associations between periodontitis and vascular endothelial dysfunction in recent years were listed, and the possible mechanisms of periodontitis aggravating endothelial dysfunction were analyzed. The importance of periodontal intervention in improving endothelial function was emphasized. This will provide new ideas for further study about the relationship between periodontitis and cardiovascular diseases and for the prevention and treatment strategies.
Cardiovascular Diseases/etiology* ; Endothelium, Vascular ; Humans ; Oxidative Stress ; Periodontitis/complications* ; Risk Factors

OBJECTIVE: This study aims to investigate the association of metabolic phenotypes that are jointly determined by body mass index (BMI) or fat mass percentage and metabolic health status with the ten-year risk of cardiovascular disease (CVD) among Chinese adults. METHODS: Data were obtained from a cross-sectional study. BMI and body fat mass percentage (FMP) combined with the metabolic status were used to define metabolic phenotypes. Multiple linear regression and logistic regression were used to examine the effects of metabolic phenotypes on CVD risk. RESULTS: A total of 13,239 adults aged 34-75 years were included in this study. Compared with the metabolically healthy non-obese (MHNO) phenotype, the metabolically unhealthy non-obese (MUNO) and metabolically unhealthy obese (MUO) phenotypes defined by BMI showed a higher CVD risk [odds ratio, OR (95% confidence interval, CI): 2.34 (1.89-2.89), 3.45 (2.50-4.75), respectively], after adjusting for the covariates. The MUNO and MUO phenotypes defined by FMP showed a higher CVD risk [ OR (95% CI): 2.31 (1.85-2.88), 2.63 (1.98-3.48), respectively] than the MHNO phenotype. The metabolically healthy obese phenotype, regardless of being defined by BMI or FMP, showed no CVD risk compared with the MHNO phenotype. CONCLUSION General obesity without central obesity does not increase CVD risk in metabolically healthy individuals. FMP might be a more meaningful factor for the evaluation of the association of obesity with CVD risk. Obesity and metabolic status have a synergistic effect on CVD risk.
Adipose Tissue/anatomy & histology* ; Adult ; Aged ; Body Mass Index ; Cardiovascular Diseases/etiology* ; China/epidemiology* ; Cross-Sectional Studies ; Female ; Humans ; Male ; Metabolic Diseases/etiology* ; Middle Aged ; Obesity/complications* ; Phenotype ; Regression Analysis ; Risk Factors

OBJECTIVE: This study aimed to examine the associations of daytime napping with incident risks of cardiovascular diseases (CVDs) and hypertension (HTN). METHODS: Data for napping and CVD outcomes in 25 provinces were collected from baseline (2010) and three waves of follow-up (2012-2017) investigations of the China Family Panel Studies. Cox frailty models with random intercepts for the surveyed provinces were used to assess the longitudinal effects of daytime napping on CVD and HTN. RESULTS: Compared with non-nappers, 30+ min nappers had higher risks of CVD and HTN, while no significant associations were observed among < 30 min nappers. Incident risks among 30- to < 60-min nappers increased by 22% [hazard ratio (HR) 1.22, 95% confidence interval ( CI) 1.08-1.39] for CVD and 21% (1.21, 1.04-1.41) for HTN, respectively, with corresponding HRs of CVD and HTN of 1.27 (1.09-1.47) and 1.38 (1.16-1.65) among ≥ 60 min nappers. Nap-associated CVD risks varied by subgroups, with stronger associations in participants with lower body mass index (< 24 kg/m ²), physically inactive persons, smokers, and participants with longer nighttime sleep (≥ 7 h/night). Significant effects of daytime napping were observed on rural and northern residents only, highlighting great regional variations in CVD risks associated with napping habits. CONCLUSIONS This cohort study revealed strong evidence that long daytime napping (≥ 30 min) is associated with an increased incidence of cardiovascular events.
Adult ; Cardiovascular Diseases/etiology* ; China/epidemiology* ; Cohort Studies ; Female ; Humans ; Hypertension/etiology* ; Incidence ; Longitudinal Studies ; Male ; Middle Aged ; Risk Factors ; Sleep/physiology* ; Time Factors