Introduction: Stroke remains a major cause of death and disability in Japan and worldwide. Detecting individuals at high risk for stroke to apply preventive approaches is recommended. This study aimed to develop a stroke risk prediction model among urban Japanese using cardiovascular risk factors. Methods: We followed 6,641 participants aged 30–79 years with neither a history of stroke nor coronary heart disease. The Cox proportional hazard model estimated the risk of stroke incidence adjusted for potential confounders at the baseline survey. The model’s performance was assessed using the receiver operating characteristic curve and the Hosmer-Lemeshow statistics. The internal validity of the risk model was tested using derivation and validation samples. Regression coefficients were used for score calculation. Results: During a median follow-up duration of 17.1 years, 372 participants developed stroke. A risk model including older age, current smoking, increased blood pressure, impaired fasting blood glucose and diabetes, chronic kidney disease, and atrial fibrillation predicted stroke incidence with an area under the curve = 0.76 and p value of the goodness of fit = 0.21. This risk model was shown to be internally valid (p value of the goodness of fit in the validation sample = 0.64). On a risk score from 0 to 26, the incidence of stroke for the categories 0–5, 6–7, 8–9, 10–11, 12–13, 14–15, and 16–26 was 1.1%, 2.1%, 5.4%, 8.2%, 9.0%, 13.5%, and 18.6%, respectively. Conclusion: We developed a new stroke risk model for the urban general population in Japan. Further research to determine the clinical practicality of this model is required.
Aim: Weight change could have many health outcomes. This study aimed to investigate the association between weight change and mortality risk due to total cardiovascular disease (CVD), ischemic heart disease (IHD), and stroke among Japanese. Methods: We used Suita Study data from 4,746 people aged 30-79 years in this prospective cohort study. Weight change was defined as the difference between baseline weight and weight at age 20. We used Cox proportional hazards models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) of total CVD, IHD, and stroke mortality for 1) participants with a weight change (>10, 5 to 10, -5 to -10, and <-10 kg) compared to those with stable weight (-4.9 to 4.9 kg) and 2) participants who moved from one body mass index category (underweight, normal weight, or overweight) to another compared to those with normal weight at age 20 and baseline. Results: Within a median follow-up period of 19.9 years, the numbers of total CVD, IHD, and stroke mortality were 268, 132, and 79, respectively. Weight loss of >10 kg was associated with the increased risk of total CVD mortality 2.07 (1.29, 3.32) and stroke mortality 3.02 (1.40, 6.52). Moving from normal weight at age 20 to underweight at baseline was associated with the increased risk of total CVD, IHD, and stroke mortality: 1.76 (1.12, 2.77), 2.10 (1.13, 3.92), and 2.25 (1.05, 4.83), respectively. Conclusion: Weight loss, especially when moving from normal to underweight, was associated with the increased risk of CVD mortality.
A prospective cohort study in a Japanese urban general population was performed to investigate whether triglyceride (TG) and its related indices were associated with the risk for the incidence of ischemic cardiovascular disease (CVD) after the adjustment for low-density lipoprotein cholesterol (LDL-C) in Asian community dwellers.Methods: A 15.1-year prospective cohort study was performed in 6,684 Japanese community dwellers aged 30-79 years without a history of CVD and whose fasting TG levels were 400 mg/dL. After adjusting for covariates, including LDL-C, the multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of the deciles (D) of TG and those of 1-standard deviation (SD) increment of log-transformed TG (1-SD of TG) according to LDL-C level (≥ 140 and 140 mg/dL) for ischemic CVD incidence were estimated. The multivariable-adjusted HRs and 95%CIs of the quintiles (Q) of TG, TG/HDL-C, and the cardiometabolic index (CMI) for ischemic CVD were also estimated. Results:In 101,230 person-years, 464 ischemic CVD cases occurred. For D10 of TG, the HR (95%CI) was 1.56 (1.05-2.32), and for 1-SD of TG, it was 1.30 (1.00-1.70) in participants with LDL-C 140 mg/dL and 1.07 (0.77-1.50) in those with LDL-C ≥ 140 mg/dL. For Q5 of the CMI, the multivariable-adjusted HR was higher than those of TG and TG/HDL-C. Conclusions:Fasting TG was an independent predictor for ischemic CVD incidence after adjusting for LDL-C in Japanese community dwellers with TG 400 mg/dL. Among TG, TG/HDL-C, and the CMI, the CMI could be the most powerful predictor for ischemic CVD. coronary artery disease (CAD) 1) and stroke 2) . Furthermore, elevated TG levels appear to be associated with a residual risk of atherosclerotic cardiovascular diseases (CVDs), despite the use of lowdensity lipoprotein cholesterol (LDL-C)-lowering Copyright©2021 Japan Atherosclerosis Society This article is distributed under the terms of the latest version of CC BY-NC-SA defined by the Creative Commons Attribution License.
Aims-Perfluoroalkyl substances (PFAS) are environmentally and biologically persistent synthetic environmental contaminants linked to adverse health outcomes. Though null to modest inverse relationships between PFAS and coronary heart disease (CHD) have been reported, studies regarding relationships in high risk populations such as those with diabetes are sparse. We investigated the relationship of PFAS with CHD in persons with diabetes. Methods-Data on 5,270 adults, aged ≥20 years, with diabetes were obtained from the C8 Health Project. Four PFAS were investigated separately: perfluorohexane sulfonate (PFHxS), perfluoroctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and perfluoronanaoic acid (PFNA). Results-In logistic regression analyses adjusting for age, sex, diabetes duration, BMI, smoking, lipids, WBC, CRP, eGFR, uric acid, hemoglobin and iron, all PFAS were inversely associated with CHD, ORs (95% CIs
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