We aimed to estimate the future burden of coronary heart disease (CHD) and stroke mortalities by sex and all 47 prefectures of Japan until 2040 while accounting for effects of age, period, and cohort and integrating them to be at the national level to account for regional differences among prefectures. We estimated future CHD and stroke mortality projections, developing Bayesian age-period-cohort (BAPC) models in population and the number of CHD and stroke by age, sex, and all 47 prefectures observed from 1995 to 2019; then applying these to official future population estimates until 2040. The present participants were all men and women aged over 30 years and were residents of Japan. In the BAPC models, the predicted number of national-level cardiovascular deaths from 2020 to 2040 would decrease (39,600 [95% credible interval: 32,200-47,900] to 36,200 [21,500-58,900] CHD deaths in men, and 27,400 [22,000-34,000] to 23,600 [12,700-43,800] in women; and 50,400 [41,900-60,200] to 40,800 [25,200-67,800] stroke deaths in men, and 52,200 [43,100-62,800] to 47,400 [26,800-87,200] in women). After adjusting these factors, future CHD and stroke deaths will decline until 2040 at the national level and in most prefectures. This research was supported by the Intramural Research Fund of Cardiovascular Diseases of the National Cerebral and Cardiovascular Center (21-1-6, 21-6-8), JSPS KAKENHI Grant Number JP22K17821, and the Ministry of Health, Labour and Welfare Comprehensive Research on Life-Style Related (Diseases Cardiovascular Diseases and Diabetes Mellitus Program), Grant Number 22FA1015.

We aimed to quantify contributions of changes in risks and uptake of evidence-based treatment to coronary heart disease (CHD) mortality trends in Japan between 1980 and 2012. We conducted a modelling study for the general population of Japan aged 35 to 84 years using the validated IMPACT model incorporating data sources like Vital Statistics. The main outcome was difference in the number of observed and expected CHD deaths in 2012. From 1980 to 2012, age-adjusted CHD mortality rates in Japan fell by 61%, resulting in 75,700 fewer CHD deaths in 2012 than if the age and sex-specific mortality rates had remained unchanged. Approximately 56% (95% uncertainty interval [UI]: 54-59%) of the CHD mortality decrease, corresponding to 42,300 (40,900-44,700) fewer CHD deaths, was attributable to medical and surgical treatments. Approximately 35% (28-41%) of the mortality fall corresponding to 26,300 (21,200-31,000) fewer CHD deaths, was attributable to risk factor changes in the population, 24% (20-29%) corresponding to 18,400 (15,100-21,900) fewer and 11% (8-14%) corresponding to 8400 (60,500-10,600) fewer from decreased systolic blood pressure (8.87 mm Hg) and smoking prevalence (14.0%). However, increased levels of cholesterol (0.28 mmol/L), body mass index (BMI) (0.68 kg/m2), and diabetes prevalence (1.6%) attenuated the decrease in mortality by 2% (1-3%), 3% (2-3%), and 4% (1-6%), respectively. Japan should continue their control policies for blood pressure and tobacco, and build a strategy to control BMI, diabetes, and cholesterol levels to prevent further CHD deaths.

Background: Although the 2018 revised International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification was proposed recently, until now, no reports have been made comparing the association of renal prognosis between the 2018 revised ISN/RPS classification and the 2003 ISN/RPS classification. The present study aimed to assess the usefulness, especially of activity and chronicity assessment, of the 2018 revised ISN/RPS classification for lupus nephritis (LN) in terms of renal prognosis compared to the classification in 2003. Methods: We retrospectively collected medical records of 170 LN patients from the database of renal biopsy at Fujita Health University from January 2003 to April 2019. Each renal biopsy specimen was reevaluated according to both the 2003 ISN/RPS classification and the 2018 revised ISN/RPS classification. Renal endpoint was defined as a 30% decline of estimated glomerular filtration rate (eGFR). Results: A total of 129 patients were class III/IV±V (class III, 44 patients; class IV, 35 patients; class III/IV+V, 50 patients). The mean age was 42 years, 88% were female, and the median observation period was 50.5 months. Renal prognosis was significantly different among the classes and significantly poor in the patients with higher modified National Institute of Health (mNIH) chronicity index (C index, ≥ 4) by a log-rank test (p = 0.05 and p = 0.02, respectively). By Cox proportional hazard models, only the C index was significantly associated with renal outcome (hazard ratio 1.32, 95% CI 1.11–1.56, p ≤ 0.01), while the classes, the 2003 activity and chronicity subdivision, and the mNIH activity index had no significant association with renal outcome. Each component of the C index was significantly associated with renal outcome in different models. Conclusion: This study demonstrates that the 2018 revised ISN/RPS classification was more useful in terms of association with renal prognosis compared to the 2003 ISN/RPS classification.

Multiple 24-hour urine collections are necessary to adequately assess sodium and potassium intake. Here, we assessed kidney function decline for four years after baseline in relation to seven-time averaged 24-hour urinary sodium and potassium excretion (UNaV, UKV), their UNaV/UKV ratio, and their categorical combination in outpatients with chronic kidney disease (CKD). This retrospective cohort study was based on 240 outpatients with baseline CKD stages 3-5, baseline age 20 years or more (median age 72.0 years), and a median follow-up (with interquartile range) of 2.9 (1.4-4.0) years. Outcome was the percentage change in annual slope of estimated glomerular filtration rate (delta eGFR per year). In linear mixed models, percentage changes in delta eGFR per year were -3.26% (95% confidence interval -5.85 to -0.60), +5.20% (2.34 to 8.14), and -5.20% (-7.64 to -2.69), respectively, per one standard deviation increase in the seven-time averaged UNaV and UKV, and their UNaV/UKV ratio. Additionally, percentage changes per year in delta eGFR per year were -16.27% (-23.57 to -8.27) in the middle-to-high UNaV and low UKV group, compared with the low UNaV and middle-to high UKV group. Thus, our study reinforces the observation of opposite associations between GFR decline and urinary excretion rates of sodium (positive) and potassium (negative), respectively. Whether changes in dietary sodium and potassium intake slow GFR decline still requires further study.

Background: Few previous studies used information on changes in fasting plasma glucose ( FPG ) assessed at multiple points in time in relationship to cardiovascular disease ( CVD ) incidence. The present study aimed to identify subgroups of FPG trajectories with assessing CVD incidence. Methods and Results: The present study was based on the Suita study, a population‐based cohort study in Japan. The primary outcome was incidence of the first CVD events consisting of stroke and coronary heart diseases between 1989 and 2013. The main exposure was FPG assessed every 2 years. We used joint latent class mixed models to derive FPG trajectories over time while evaluating cumulative incidence of CVD , and categorized participants into several subgroups based on those trajectories and cumulative incidence. We observed 356 and 243 CVD events during the median follow‐up of 17.2 and 20.2 years among 3120 men and 3482 women, respectively. The joint latent mixed models found 3 subgroups in men and 2 subgroups in women. Of the 3 subgroups in men, 1 subgroup had FPG levels that increased sharply (96.5–205.0 mg/dL from aged 40 to 80 years) and higher CVD cumulative incidence. Of the 2 subgroups in women, 1 subgroup had FPG levels that increased sharply (97.7–190.5 mg/dL from aged 40 to 80 years) and tended to have slightly higher CVD incidence compared with the other subgroup. Conclusion: It can be important to manage CVD risk factors especially for people whose FPG trajectories sharply increased to prevent CVD .

In-home monitoring systems have been used to detect cognitive decline in older adults by allowing continuous monitoring of routine activities. In this study, we investigated whether unobtrusive in-house power monitoring technologies could be used to predict cognitive impairment. A total of 94 older adults aged ≥65 years were enrolled in this study. Generalized linear mixed models with subject-specific random intercepts were used to evaluate differences in the usage time of home appliances between people with and without cognitive impairment. Three independent power monitoring parameters representing activity behavior were found to be associated with cognitive impairment. Representative values of mean differences between those with cognitive impairment relative to those without were −13.5 min for induction heating in the spring, −1.80 min for microwave oven in the winter, and −0.82 h for air conditioner in the winter. We developed two prediction models for cognitive impairment, one with power monitoring data and the other without, and found that the former had better predictive ability (accuracy, 0.82; sensitivity, 0.48; specificity, 0.96) compared to the latter (accuracy, 0.76; sensitivity, 0.30; specificity, 0.95). In summary, in-house power monitoring technologies can be used to detect cognitive impairment.