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Abstract Anemia and chronic kidney disease (CKD), which worsen bidirectionally, are associated with mortality in older adults. This study aimed to examine the association between CKD and the type of anemia and its impact on mortality in the general population. Data from a nationwide database of 203,280 individuals who participated in the annual “Specific Health Check and Guidance in Japan” evaluation between 2008 and 2011 were used. Over a follow-up period of 4 years, 2,819 all-cause, 1,595 cancer-related, 523 cardiovascular, and 128 infectious disease deaths were recorded. Macrocytic anemia was detected in 2.3% of participants. The prevalence of normocytic and macrocytic anemia increased with advancing CKD stage. Multivariate Cox proportional hazards regression analysis revealed significant associations between macrocytic anemia and the all-cause, cancer, and cardiovascular mortality rates. Including the anemia type improved the prediction accuracy for all-cause deaths. The participants were divided into eight groups based on the anemia type and CKD. Macrocytic anemia of CKD had the highest hazard ratio for all-cause mortality in the general population. A correlation was observed between macrocytic anemia and CKD. Macrocytic anemia predicted mortality in the general population, suggesting that it could serve as an early indicator of premature death in high-risk individuals.

Abstract A higher heart rate is recognized as an independent risk factor for all-cause mortality and cardiovascular events in the general population. However, the association between elevated heart rate and clinical adverse outcomes in patients with non-dialysis-dependent chronic kidney disease (CKD) has not been sufficiently investigated. A total of 1353 participants enrolled in the Fukushima CKD Cohort Study were examined to investigate associations between resting heart rate and clinical adverse outcomes using Cox proportional hazards analysis. The primary outcome of the present study was all-cause mortality, with cardiovascular events as the secondary outcome. Participants were stratified into four groups based on resting heart rate levels at baseline (heart rate

Abstract Predicting the transition of kidney function in chronic kidney disease is difficult as specific symptoms are lacking and often overlooked, and progress occurs due to complicating factors. In this study, we applied time-series cluster analysis and a light gradient boosting machine to predict the trajectories of kidney function in non-dialysis dependent chronic kidney disease patients with baseline estimated glomerular filtration rate (GFR) ≥ 45 mL/min/1.73 m2. Based on 5-year changes in estimated GFR, participants were stratified into groups with similar trajectories by cluster analysis. Next, we applied the light gradient boosting machine algorithm and Shapley addictive explanation to develop a prediction model for clusters and identify important parameters for prediction. Data from 780 participants were available for analysis. Participants were classified into five classes (Class 1: n = 78, mean [± standard deviation] estimated GFR 100 ± 19.3 mL/min/1.73 m2; Class 2: n = 176, 76.0 ± 9.3 mL/min/1.73 m2; Class 3: n = 191, 59.8 ± 5.9 mL/min/1.73 m2; Class 4: n = 261, 52.7 ± 4.6 mL/min/1.73 m2; and Class 5: n = 74, 53.5 ± 12.0 mL/min/1.73 m2). Declines in estimated GFR were 8.9% in Class 1, 12.2% in Class 2, 4.9% in Class 3, 12.0% in Class 4, and 45.1% in Class 5 during the 5-year period. The accuracy of prediction was 0.675, and the top three most important Shapley addictive explanation values were 1.61 for baseline estimated GFR, 0.12 for hemoglobin, and 0.11 for body mass index. The estimated GFR transition of patients with preserved chronic kidney disease mostly depended on baseline estimated GFR, and the borderline for estimated GFR trajectory was nearly 50 mL/min/1.73 m2.

Abstract The red blood cell distribution width–albumin ratio (RAR) is a prognostic factor for adverse outcomes in various populations. However, whether RAR is associated with renal outcomes remains unclear. Therefore, we aimed to investigate the impact of RAR on the prognosis in patients with chronic kidney disease (CKD). We conducted a retrospective cohort study using 997 CKD patients who were enrolled in the Fukushima Cohort Study. Patients were categorized into tertiles (T1-3) according to the baseline RAR. The associations of RAR with end-stage kidney disease (ESKD) were assessed using Kaplan–Meier curves and multivariable cox regression analyses. Receiver operating characteristic (ROC) curves were performed to test whether significant differences were present between red cell distribution width (RDW) and RAR. The median age was 66, 57% were men, the median eGFR was 47.8 ml/min/1.73 m2, and the median value of RAR was 3.5. The higher RAR group showed an increased risk for ESKD in the Kaplan–Meier curve analysis. Compared to the lowest RAR group, higher RAR groups had a higher risk of ESKD (hazard ratio [HR] 1.37, 95% CI 0.68–2.78 and 2.92, 95% CI 1.44–5.94) for T2 and T3 groups, respectively. ROC curve analysis proved that the discriminating ability of RAR for ESKD was superior to RDW. A higher RAR value was associated with worse renal outcomes in patients with CKD. RAR could be a convenient and useful prognostic marker for renal prognosis.

Abstract Lifestyle factors, including smoking habit, diet, and physical activity, affect the prognosis of various diseases. We elucidated the effect of lifestyle factors and health status on deaths from respiratory diseases in the general Japanese population using data from a community health examination database. Data of the nationwide screening program of the Specific Health Check-up and Guidance System (Tokutei-Kenshin), targeting the general population in Japan, from 2008 to 2010 were analyzed. The underlying causes of death were coded according to the International Classification of Diseases (ICD)-10. The hazard ratios of the incidence of mortality associated with respiratory disease were estimated using the Cox regression model. This study included 664,926 participants aged 40–74 years, who were followed up for 7 years. There were 8051 deaths, including 1263 (15.69%) deaths from respiratory diseases. The independent risk factors of mortality associated with respiratory diseases were male sex, older age, low body mass index, no exercise habit, slow walking speed, no drinking habit, smoking history, history of cerebrovascular diseases, high hemoglobin A1c and uric acid levels, low low-density lipoprotein cholesterol level, and proteinuria. Aging and decline of physical activity are significant risk factors for mortality associated with respiratory diseases, regardless of the smoking status.

Abstract Height loss is caused by osteoporosis, vertebral fractures, disc reduction, postural changes, and kyphosis. Marked long-term height loss is reportedly associated with cardiovascular disease and mortality in the elderly. The present study investigated the relationship between short-term height loss and the risk of mortality using the longitudinal cohort data of the Japan Specific Health Checkup Study (J-SHC). Included individuals were aged 40 years or older and received periodic health checkups in 2008 and 2010. The exposure of interest was height loss over the 2 years, and the outcome was all-cause mortality over subsequent follow up. Cox proportional hazard models were used to examine the association between height loss and all-cause mortality. Of the 222,392 individuals (88,285 men, 134,107 women) included in this study, 1436 died during the observation period (mean 4.8 ± 1.1 years). The subjects were divided into two groups based on a cut-off value of height loss of 0.5 cm over 2 years. The adjusted hazard ratio (95% confidence interval) was 1.26 (1.13–1.41) for exposure to height loss ≥ 0.5 cm compared to height loss

Abstract The transtheoretical model (TTM) is a commonly used model of health-related behavioral change. However, the practical effect of using this model for chronic kidney disease (CKD) self-management remains unclear. This study aimed to investigate the association between stages of change for lifestyle behavior and the incidence of CKD in the general Japanese population. A retrospective cohort study was conducted among 178,780 non-CKD participants aged 40–74 years who underwent annual health check-ups for two consecutive years between 2008 and 2009. Health behavior change was determined using questionnaires based on the TTM, which consists of five stages of change (precontemplation, contemplation, preparation, action, and maintenance). The exposure of interest was the change in stages between two years. Participants were categorized into 3 groups ‘improved’, ‘unchanged’, or ‘deteriorated’. The association between the change in stages and the incidence of CKD was examined using logistic regression analysis. After one year of follow-up, 20.0% of participants developed CKD. Participants in the deteriorated group showed a significantly higher risk of CKD incidence than in the improved group. Promoting the stage of change for healthy lifestyle behaviors evaluated by the TTM was associated with a risk reduction for the incidence of CKD.

Abstract Early detection and treatment of diseases through health checkups are effective in improving life expectancy. In this study, we compared the predictive ability for 5-year mortality between two machine learning-based models (gradient boosting decision tree [XGBoost] and neural network) and a conventional logistic regression model in 116,749 health checkup participants. We built prediction models using a training dataset consisting of 85,361 participants in 2008 and evaluated the models using a test dataset consisting of 31,388 participants from 2009 to 2014. The predictive ability was evaluated by the values of the area under the receiver operating characteristic curve (AUC) in the test dataset. The AUC values were 0.811 for XGBoost, 0.774 for neural network, and 0.772 for logistic regression models, indicating that the predictive ability of XGBoost was the highest. The importance rating of each explanatory variable was evaluated using the SHapley Additive exPlanations (SHAP) values, which were similar among these models. This study showed that the machine learning-based model has a higher predictive ability than the conventional logistic regression model and may be useful for risk assessment and health guidance for health checkup participants.

Abstract Growing evidence has demonstrated an association between nondialysis chronic kidney disease and cancer incidence, although the association between trace proteinuria and cancer death remains unclear. The aim of this study was to investigate the association between trace proteinuria and cancer death in a community-based population in Japan. This was a prospective cohort study of 377,202 adults who participated in the Japanese Specific Health Check and Guidance System from 2008 to 2011. Exposure was dipstick proteinuria categorized as − (negative), ± (trace), 1 + (mild), or ≥ 2 + (moderate to heavy). Outcome was cancer death based on information from the national database of death certificates. Adjusted Cox hazard regression model was used to evaluate the associations between trace proteinuria and cancer death. During median follow-up of 3.7 years, 3056 cancer deaths occurred, corresponding to overall cancer death rate of 21.7/10,000 person-years. In the fully adjusted model, risk of cancer death increased significantly in each successive category of proteinuria: hazard ratio (HR) (95% confidence interval [95% CI]) for risk of cancer death was 1.16 (1.03–1.31), 1.47 (1.27–1.70), and 1.61 (1.33–1.96) for trace, mild, and moderate to heavy proteinuria, respectively. Sensitivity analyses revealed a similar association between trace proteinuria and cancer death, and participants with trace proteinuria had greater risk of mortality from hematological cancers (HR: 1.59 [95% CI: 1.09–2.31]). Both mild to heavy and trace proteinuria were significantly associated with risk of mortality from cancer in a general population.

Abstract Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) may be linked to development of chronic kidney diseases (CKD). The FIB4 index, a noninvasive liver fibrosis score, has been reported to predict CKD in non-diabetic patients, but there are no reports yet in diabetic cases. Therefore, we evaluated the prognostic impact of FIB4 index on the risk of developing diabetic kidney disease (DKD) in Japanese patients with type 2 diabetes in a retrospective cohort study. We assessed patients with type 2 diabetes with an eGFR ≥ 60 mL/min/1.73 m2 and without dipstick positive proteinuria (≥ 1 +) at their first visit to our department. Participants were divided into two groups based on the FIB4 index at their first visit: FIB4 index > 1.3 and FIB4 index ≤ 1.3. The primary endpoint was defined as a decrease in eGFR 1.3 (32.0%) and the median observation period was 6.0 (3.8–11.0) years. Kaplan–Meier survival analysis indicated that the risks of developing DKD, eGFR 1.3 patients than in FIB4 ≤ 1.3 patients. In the Cox regression analysis, an FIB4 index > 1.3 was a significant predictor for onset of DKD (HR 1.54, 95% CI 1.15–2.08) and proteinuria (HR 1.55, 95% CI 1.08–2.23), but not for an eGFR 1.3 has a prognostic impact on the development of CKD and proteinuria in type 2 diabetic patients. This warrants further investigation of the prognostic impact of the development of DKD or proteinuria.

Abstract Hyperuricaemia is a risk for premature death. This study evaluated the burden of hyperuricaemia (serum urate > 7 mg/dL) for all-cause and cardiovascular mortality in 515,979 health checkup participants using an index of population attributable fraction (PAF). Prevalence of hyperuricaemia at baseline was 10.8% in total subjects (21.8% for men and 2.5% for women). During 9-year follow-up, 5952 deaths were noted, including 1164 cardiovascular deaths. In the Cox proportional hazard analysis adjusted for confounding factors, hyperuricaemia was independently associated with all-cause and cardiovascular mortality (adjusted hazard ratios [95% confidence interval]; 1.36 [1.25–1.49] and 1.69 [1.41–2.01], respectively). Adjusted PAFs of hyperuricaemia for all-cause and cardiovascular deaths were 2.9% and 4.4% (approximately 1 in 34 all-cause deaths and 1 in 23 cardiovascular deaths), respectively. In the subgroup analysis, the association between hyperuricaemia and death was stronger in men, smokers, and subjects with renal insufficiency. Adjusted PAFs for all-cause and cardiovascular deaths were 5.3% and 8.1% in men; 5.8% and 7.5% in smokers; and 5.5% and 7.3% in subjects with renal insufficiency. These results disclosed that a substantial number of all-cause and cardiovascular deaths were statistically relevant to hyperuricaemia in the community-based population, especially men, smokers, and subjects with renal insufficiency.

Abstract Based on questionnaires from 197,825 non-diabetic participants in a large Japanese cohort, we determined impact of (1) habit of exercise, (2) habit of active physical activity (PA) and (3) walking pace on new-onset of type 2 diabetes mellitus. Unadjusted and multivariable-adjusted logistic regression models were used to determine the odds ratio of new-onset diabetes mellitus incidence in a 3-year follow-up. There were two major findings. First, habits of exercise and active PA were positively associated with incidence of diabetes mellitus. Second, fast walking, even after adjusting for multiple covariates, was associated with low incidence of diabetes mellitus. In the subgroup analysis, the association was also observed in participants aged ≥ 65 years, in men, and in those with a body mass index ≥ 25. Results suggest that fast walking is a simple and independent preventive factor for new-onset of diabetes mellitus in the health check-up and guidance system in Japan. Future studies may be warranted to verify whether interventions involving walking pace can reduce the onset of diabetes in a nation-wide scale.

Abstract As previous studies have reported finding an association between hyperuricemia and the development of cardiovascular and chronic kidney disease, hyperuricemia is thought to be an independent risk factor for hypertension and diabetic mellitus. However, we have not been able to determine whether the use of xanthine oxidase inhibitors can reduce cardiovascular disease. The present study used the longitudinal data of the Fukushima Cohort Study to investigate the relationship between the use of xanthine oxidase inhibitors and cardiovascular events in patients with cardiovascular risks. During the 3-year period between 2012 and 2014, a total of 2724 subjects were enrolled in the study and followed. A total of 2501 subjects had hypertension, diabetic mellitus, dyslipidemia, or chronic kidney disease, and were identified as having cardiovascular risks. The effects of xanthine oxidase inhibitor use on the development of cardiovascular events was evaluated in these patients using a time to event analysis. During the observational periods (median 2.7 years), the incidence of cardiovascular events was 20.7 in subjects with xanthine oxidase inhibitor and 11.2 (/1000 person-years, respectively) in those without. Although a univariate Cox regression analysis showed that the risk of cardiovascular events was significantly higher in subjects administered xanthine oxidase inhibitors (HR = 1.87, 95% CI 1.19–2.94, p = 0.007), the risk was significantly lower in subjects administered a xanthine oxidase inhibitor after adjustment for covariates (HR = 0.48, 95% CI 0.26–0.91; p = 0.024) compared to those without. Xanthine oxidase inhibitor use was associated with reduced risk of cardiovascular disease in patients with cardiovascular risk factors.