Better identification of individuals at high risk for type 2 diabetes mellitus (T2DM) requires risk-prediction models incorporating novel predictors. Accordingly, this study aimed to evaluate the merits of including long-term systolic blood pressure variability (SBPV) in predicting T2DM incidence in a Japanese cohort of 3017 participants (2446 men, 571 women; age, 36-65 years) in 2007, who were followed up until March 2019. Consecutive SBP values, recorded between 2003 and 2007, were regressed annually for each participant. The slope and root-mean-square error of the regression line were calculated for each individual to represent SBPV. The significance of SBPV was examined by adding it to a multivariate Cox model incorporating age, sex, smoking status, regular exercise, family history of diabetes, body mass index, blood levels of triglycerides, high-density lipoprotein cholesterol, and fasting blood glucose. The c-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to compare the performance of the prediction models without (Model 1) and with (Model 2) SBPV. During the 9.8-year follow-up period, 135 participants developed T2DM. Although a statistically significant difference in c-index between Model 1 (0.785) and Model 2 (0.786) was not found, the NRI (8.312% [p < 0.001]) and IDI (0.700% [p = 0.012]) demonstrated that the performance of Model 2 improved compared with Model 1. In conclusion, results suggested that long-term SBPV slightly improved predictive utility for T2DM when added to a conventional prediction model. The study was registered at University Hospital Medical Information Network Clinical Trial registry (UMIN000052544, https://www.umin.ac.jp/).

Background:Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from hospitals and self-reported physician diagnoses or typical schizophrenia symptoms. These approaches are likely to underestimate the true prevalence owing to stigma, poor insight, or lack of access to health care among respondents. To address these issues, we previously developed an artificial neural network (ANN)-based schizophrenia classification model (SZ classifier) using data from a large-scale Japanese web-based survey to enhance the comprehensiveness of schizophrenia case identification in the general population. In addition, we also plan to introduce a population-based survey to collect general information and sample participants matching the population's demographic structure, thereby achieving a precise estimate of the prevalence of schizophrenia in Japan. Objective:This study aimed to estimate the prevalence of schizophrenia by applying the SZ classifier to random samples from the Japanese population. Methods:We randomly selected a sample of 750 participants where the age, sex, and regional distributions were similar to Japan's demographic structure from a large-scale Japanese web-based survey. Demographic data, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities were collected and applied to the SZ classifier, as this information was also used for developing the SZ classifier. The crude prevalence of schizophrenia was calculated through the proportion of positive cases detected by the SZ classifier. The crude estimate was further refined by excluding false-positive cases and including false-negative cases to determine the actual prevalence of schizophrenia. Results:Out of 750 participants, 62 were classified as schizophrenia cases by the SZ classifier, resulting in a crude prevalence of schizophrenia in the general population of Japan of 8.3% (95% CI 6.6%-10.1%). Among these 62 cases, 53 were presumed to be false positives, and 3 were presumed to be false negatives. After adjustment, the actual prevalence of schizophrenia in the general population was estimated to be 1.6% (95% CI 0.7%-2.5%). Conclusions:This estimated prevalence was slightly higher than that reported in previous studies, possibly due to a more comprehensive disease classification methodology or, conversely, model limitations. This study demonstrates the capability of an ANN-based model to improve the estimation of schizophrenia prevalence in the general population, offering a novel approach to public health analysis.

Purpose The aim of this study is to evaluate the prevalence, severity, and risk factors of cancer-related fatigue among currently working cancer survivors. Methods We searched the PubMed, Embase, Scopus, CINAHL, Cochrane Library, and ICHUSHI databases. The risk of bias was evaluated independently using the Risk of Bias Assessment Tool for Non-randomized Studies (RoBANS). A meta-analysis was conducted to determine the prevalence, severity, and related factors associated with cancer-related fatigue among currently working cancer survivors. Results Our meta-analysis included 18 studies and revealed that 42.2% of currently working cancer survivors experience cancer-related fatigue. The fatigue severity in this group was significantly higher than that in workers without cancer (absolute standardized mean difference (SMD) = 0.67), but lower than that in cancer survivors who had previously worked and were not currently working (absolute SMD = 0.72). Distress was identified as a potential risk factor for cancer-related fatigue in working cancer survivors (partial correlation coefficient = 0.38). Conclusions The high prevalence of cancer-related fatigue among employed cancer survivors underscores the need for targeted workplace interventions and fatigue management strategies. While the severity of fatigue is less than that seen in non-working survivors, the comparison with the general working population highlights a significant health disparity. The association between distress and fatigue suggests the necessity for a holistic approach to fatigue management that considers both physical and mental factors in working cancer survivors. Implications for Cancer Survivors Our findings highlight the critical need for healthcare professionals and employers to monitor fatigue levels among working cancer survivors and offer appropriate support.

Introduction: Stress responses to work-related stressors often manifest in non-specific physical complaints, by monitoring it may provide early indications of underlying health issues. Hypothesis: We hypothesized that there is a significant association between non-specific physical complaints and the subsequent incidence of cardiovascular diseases (CVD) in middle-aged Japanese. Methods: A cohort of 4820 Japanese workers (3876 male, 944 female) ages 35 to 65 years were followed from 2007 to 2019 for CVD incidence (stroke and acute coronary artery diseases). Non-specific physical complaints were assessed as a domain of stress response in the 57-item brief job stress questionnaire and consisted of 11 items: felt dizzy; experienced joint pains; experienced headaches; had stiff neck or shoulders; had lower back pain; had eyestrain; had heart palpitations or shortness of breath; had stomach or intestine problems; lost appetite; had diarrhea or constipation; couldn’t sleep well. Each item had four possible responses from never, sometimes, often, to always, corresponding scores of which are 1, 2, 3, and 4, respectively. The presence of non-specific physical complaints was defined as a sum score of 27-44 for males and 30-44 for females according to the recommended standard values. Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) of non-specific physical complaints for CVD were estimated and adjusted for age, sex, smoking status, alcohol consumption, regular exercise, sleep duration, body mass index, systolic blood pressure, total cholesterol, and histories of hypertension, hyperlipidemia, and diabetes. Results: During a median of 10.4 years of follow-up, 90 CVD cases were identified. The presence of non-specific physical complaints was significantly associated with the incidence of CVD independent of confounding variables (HR: 2.04, 95% CI: 1.02-4.07). Conclusion: The present study revealed that the presence of non-specific physical complaints was associated with a higher risk of developing CVD.

Aim: Several studies have shown that dairy consumption in old age is effective in preventing frailty. However, there is a lack of evidence regarding the association between milk consumption during middle age and the development of frailty in old age. Therefore, we carried out an investigation to explore the association between milk consumption during middle age and development of frailty examined after over 15 years of follow up in a long-term cohort study in Japan. Methods: We studied 265 participants aged 60-79 years (212 men and 53 women) in 2018, who participated in both the baseline survey in 2002 and the frailty assessment in 2018. The amount of milk consumption (g/day) at baseline was age- and energy-adjusted, and classified into three categories (no, low and high consumption: 0 g/day, <= 135.86 g/day, >135.86 g/day in men and 0 g/day, <= 126.44 g/day, >126.44 g/day in women). Odds ratios (OR) and 95% confidence intervals (CI) for prefrailty/frailty after adjusting for lifestyles at baseline, stratified by sex, were estimated using logistic regression analysis. Results: The prevalence of prefrailty/frailty in 2018 was 37.7% and 28.3% in men and women, respectively. Milk consumption categories were inversely associated with the prevalence of prefrailty/frailty in men (OR 0.34, 95% CI 0.14-0.84 in low consumption; OR 0.31, 95% CI 0.10-0.95 in high consumption; P < 0.05), but not in women (OR 0.53, 95% CI 0.11-2.65; P = 0.44). Conclusions: In this study, milk intake in middle-aged men was inversely associated with the prevalence of prefrailty/frailty later in life. Geriatr Gerontol Int 2024; center dot center dot: center dot center dot-center dot center dot.

Background: The term "nonrestorative sleep (NRS)" refers to unrefreshed feeling at wake-up and is a domain of poor sleep quality. Previous researches have demonstrated that NRS is linked to a number of diseases and adverse health outcomes, but less is known regarding the link between NRS and diabetes, particularly in Japanese. Methods: We studied 3665 middle-aged male participants of the Aichi Workers' Cohort Study who were followed -up from 2002 to 2019. Cox proportional hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) of incident type 2 diabetes mellitus (T2DM) in relation to NRS adjusted for potential confounding variables. Results: During a median follow-up of 14.6 years, 421 type 2 diabetes cases were identified. Participants with NRS had a higher crude incidence rate of T2DM (11.2/1,000 person -years), compared to participants without NRS (9.3/1,000 personyears). In the fully adjusted model, individuals who reported having NRS had a significantly higher risk of developing T2DM (HR: 1.36, 95% CI: 1.10-1.67). The association was observed only in participants under 50 years old (HR: 1.82, 95% CI: 1.36-2.43), not in the older (50 years or older) participants (P for interaction =0.025). In contrast, stratified analyses by the presence of shift work, obesity or sleep duration showed similar associations in all the strata. Conclusions: NRS was associated with higher risk of T2DM in middle-aged Japanese male workers independent of a variety of lifestyle factors and other sleep problems.

Background: Associations of major risk factors for stroke with total and each type of stroke, as well as subtypes of ischemic stroke, and their population attributable fractions had not been examined comprehensively. Methods: Participants of the Japan Public Health Center-based prospective (JPHC) Study Cohort II without histories of cardiovascular disease and cancer (n = 14,797) were followed from 1993 through 2012. Associations of current smoking, hypertension, diabetes, overweight (body mass index ≥25 kg/m2), non-high-density lipoprotein cholesterol (non-HDLC) categories, low HDLC (<40 mg/dL), urine protein, and history of arrhythmia were examined in a mutually-adjusted Cox regression model that included age and sex. Population attributable fractions (PAFs) were estimated using the hazard ratios and the prevalence of risk factors among cases. Results: Subjects with hypertension were 1.63 to 1.84 times more likely to develop any type of stroke. Diabetes, low HDLC, current smoking, overweight, urine protein, and arrhythmia were associated with risk of overall and ischemic stroke. Hypertension and urine protein were associated with risk of intracerebral hemorrhage, while current smoking, hypertension, and low non-HDLC were associated with subarachnoid hemorrhage. Hypertension alone accounted for more than a quarter of stroke incidence, followed by current smoking and diabetes. High non-HDLC, current smoking, low HDLC, and overweight contributed mostly to large-artery occlusive stroke. Arrhythmia explained 13.2% of embolic stroke. Combined PAFs of all the modifiable risk factors for total, ischemic, and large-artery occlusive strokes were 36.7%, 44.5%, and 61.5%, respectively. Conclusion: Although there are differences according to subtypes, hypertension could be regarded as the most crucial target for preventing strokes in Japan.

Objectives　We evaluated the number of hospitalizations among public assistance recipients for each major classification according to the International Classification of Diseases 10th Revision (ICD-10), adjusting for sex and age differences in the general Japanese population. This study aimed to provide a comprehensive assessment of hospitalization patterns among public assistance recipients by disease category.Methods　We used indirect methods to adjust for sex and age, with public assistance recipients and the entire Japanese population as the observation and reference groups, respectively. We calculated the standardized hospitalization ratios (SHRs) for each major classification based on the ICD-10. We only used publicly available government statistics, including data from the 2020 Patient Survey, for hospitalization rates according to sex, age, and major classification. Additionally, we used data from the 2020 National Survey on Public Assistance Recipients conducted for the number of public assistance recipients by sex and age groups and data from the 2020 Survey on the Actual Status of Medical Assistance conducted for the number of hospitalizations by major classification.Results　After adjusting for age, the overall SHR was 1.49. The major classifications with the high SHRs for men and women were "V. Mental and behavioural disorders" (SHR for men; 4.06, women; 3.45) and "IV. Endocrine, nutritional, and metabolic diseases" (SHR for men; 2.40, women; 1.47). Conversely, the major classifications with low SHRs were "XVI. Certain conditions originating in the perinatal period" (SHR; 0.43) and "VII. Diseases of the eye and adnexa" (SHR; 0.44) for men. For women, these were "XV. Pregnancy, childbirth, and the puerperium" (SHR; 0.17) and "VII. Diseases of the eye and adnexa" (SHR; 0.27).Conclusion　After adjusting for age, hospitalization status among public assistance recipients was higher overall than in the general Japanese population. However, if divided based on major classifications, higher and lower rates were observed compared with the general population. In assessing the status of medical assistance for public assistance recipients, research should be conducted by disease classification, considering the significant differences in age composition between public assistance recipients and the general Japanese population.

Background: The association between obesity and cardiovascular disease (CVD) remains unclear, particularly for those with established CVD risk factors. We analyzed follow-up data from the Aichi Workers' Cohort Study. We studied the association between the degree of obesity and risk of CVD and its subtypes specifically among individuals with hypertension, hyper-low-density lipoprotein (LDL)-cholesterolemia, or diabetes. Methods: Pooled data of 8972 adults (7076 men and 1896 women) who were recruited between 2002 and 2008 were used in the current analysis. We used multivariable Cox proportional hazard model to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between the degree of obesity assessed with body mass index (BMI) and the risk of CVD and its subtypes, i.e., coronary heart disease (CHD) and stroke. Results: During a median of 12 years, there were 197 CVDs (80 CHDs and 117 strokes). BMI >= 27.5 compared to 21.0-22.9 kg/m(2 )was positively and significantly associated with the risks of CVD, CHD, and total stroke. Hypertension, hyper-LDL-cholesterolemia, and diabetes mediated 15.9%, 5.8%, and 8.7% of obesity-CVD associations, respectively, and 28.3% by their combination. In the stratified analyses by the presence of risk factors, BMI >= 25.0 (overweight/obesity) compared to BMI < 25 kg/m(2) was associated with a higher risk of CVD in those with and without hypertension, but only with hyper-LDL-cholesterolemia, and without diabetes. Conclusions: Overweight/obesity was associated with the risk of CVD and its subtypes. About 30% of the risk was explained by hypertension, hyper-LDL-cholesterolemia, and diabetes, of which hypertension accounted for approximately the half of the explained risk. However, overweight/obesity increased the risk of CVD even in those without hypertension. These findings highlight the importance of controlling and preventing overweight/ obesity regardless of chronic disease status.

Background and Objective: Excellent generalizability is the precondition for the widespread practical implementation of machine learning models. In our previous study, we developed the schizophrenia classification model (SZ classifier) to identify potential schizophrenia patients in the Japanese population. The SZ classifier has exhibited impressive performance during internal validation. However, ensuring the robustness and generalizability of the SZ classifier requires external validation across independent sample sets. In this study, we aimed to present an external validation of the SZ classifier using outpatient data. Methods: The SZ classifier was trained by using online survey data, which incorporate demographic, health-related, and social comorbidity features. External validation was conducted using an outpatient sample set which is independent from the sample set during the model development phase. The model performance was assessed based on the sensitivity and misclassification rates for schizophrenia, bipolar disorder, and major depression patients. Results: The SZ classifier demonstrated a sensitivity of 0.75 when applied to schizophrenia patients. The misclassification rates were 59% and 55% for bipolar disorder and major depression patients, respectively. Conclusions: The SZ classifier currently encounters challenges in accurately determining the presence or absence of schizophrenia at the individual level. Prior to widespread practical implementation, enhancements are necessary to bolster the accuracy and diminish the misclassification rates. Despite the current limitations of the model, such as poor specificity for certain psychiatric disorders, there is potential for improvement if including multiple types of psychiatric disorders during model development.

The association between chronotype and leisure-time physical activity (LTPA) remains unclear. We investigated the difference in regular LTPA and for a sufficient duration between those with evening-type (ET) and morning-type chronotypes (MT). We conducted a cross-sectional analysis using the data of the Aichi Workers’ Cohort Study. It included 3,221 men (mean [standard deviation] age: 45.0 [11.6] years) and 1,294 women (39.8 [11.2] years). Chronotypes were determined with the reduced version of the Morningness-Eveningness Questionnaire. We calculated the metabolic equivalents (METs) consumed per week based on the four types of LTPA: strolling, brisk walking, light- and moderate-intensity PA, and vigorous-intensity PA. Regular LTPA and for a sufficient duration was defined as doing once or more per week and for 30 min or longer per session, respectively. Logistic regression analysis was conducted separately by sex to calculate odds ratios of ET for regular LTPA and for a sufficient duration, adjusted for age and other factors, for each type of LTPA. ET men consumed fewer total METs per week than MT men (p < .001), although this pattern is not found in women. Compared to MT men, ET men were less likely to be engaged in regular LTPA in all types of LTPA (prevalence and adjusted odds ratio [95

BackgroundIn Japan, challenges were reported in accurately estimating the prevalence of schizophrenia among the general population. Retrieving previous studies, we investigated that patients with schizophrenia were more likely to experience poor subjective well-being and various physical, psychiatric, and social comorbidities. These factors might have great potential for precisely classifying schizophrenia cases in order to estimate the prevalence. Machine learning has shown a positive impact on many fields, including epidemiology, due to its high-precision modeling capability. It has been applied in research on mental disorders. However, few studies have applied machine learning technology to the precise classification of schizophrenia cases by variables of demographic and health-related backgrounds, especially using large-scale web-based surveys. ObjectiveThe aim of the study is to construct an artificial neural network (ANN) model that can accurately classify schizophrenia cases from large-scale Japanese web-based survey data and to verify the generalizability of the model. MethodsData were obtained from a large Japanese internet research pooled panel (Rakuten Insight, Inc) in 2021. A total of 223 individuals, aged 20-75 years, having schizophrenia, and 1776 healthy controls were included. Answers to the questions in a web-based survey were formatted as 1 response variable (self-report diagnosed with schizophrenia) and multiple feature variables (demographic, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities). An ANN was applied to construct a model for classifying schizophrenia cases. Logistic regression (LR) was used as a reference. The performances of the models and algorithms were then compared. ResultsThe model trained by the ANN performed better than LR in terms of area under the receiver operating characteristic curve (0.86 vs 0.78), accuracy (0.93 vs 0.91), and specificity (0.96 vs 0.94), while the model trained by LR showed better sensitivity (0.63 vs 0.56). Comparing the performances of the ANN and LR, the ANN was better in terms of area under the receiver operating characteristic curve (bootstrapping: 0.847 vs 0.773 and cross-validation: 0.81 vs 0.72), while LR performed better in terms of accuracy (0.894 vs 0.856). Sleep medication use, age, household income, and employment type were the top 4 variables in terms of importance. ConclusionsThis study constructed an ANN model to classify schizophrenia cases using web-based survey data. Our model showed a high internal validity. The findings are expected to provide evidence for estimating the prevalence of schizophrenia in the Japanese population and informing future epidemiological studies.

Objective: This study examined the longitudinal association of perceived stress, ikigai, and having someone one can count on in middle age with the advanced-level functional competency in older age, which is crucial for the maintenance of independent life among older adults. The issue is especially relevant in super-aged countries like contemporary Japan, where more and more older people live in a household consisting only of older people.Methods: Data were collected in 2019 from a total of 1692 retirees of the Aichi Workers' Cohort Study participants in which baseline survey including psychological factors was conducted during their employment in 2002. Japan Science and Technology Agency Index of Competence (JST-IC) was used to measure the advanced-level functional competency. Multivariable-adjusted odds ratios (ORs) were obtained for having low JST-IC in later life by the degrees of psychological factors reported in the middle age adjusting for the presence of depressive mood in 2019.Results: Those who were not sure about ikigai (OR: 2.02, 95 % CI: 1.33 to 3.08) and who have no one to count on (OR: 2.19, 95 % CI: 1.52 to 3.16) in the middle age were significantly associated with low JST-IC after retirement. Having much stress was significantly inversely associated with a low JST-IC (OR: 0.69, 95 % CI: 0.50 to 0.97).Conclusion: Having ikigai and someone reliable, and stress during middle age might play a role in preventing impaired advanced-level functional competency. Improved ikigai and increased social interaction and support might improve functional competency. Further research might explore avenues for improving ikigai.

Objective: The associations between body mass index (BMI) and stroke subtypes, particularly intracerebral hemorrhage, have not been consistent. Such inconsistencies may be due to differences in the age at which BMI was obtained. We examined the possible age modifications in the association between BMI and stroke risk. Materials and Methods: We followed 88,754 participants, aged 40-69 years at baseline (1990-1994), of the Japan Public Health Center-based prospective (JPHC) study for stroke incidence. BMI was obtained using self-reported body weight and height, which were categorized using the following cut-off points: 18.5, 21, 23, 25, 27.5, and 30 kg/m2. Time-dependent Cox proportional hazards models that updated BMI and covariates using 5-and 10-year questionnaire responses were used to estimate hazard ratios and 95 % confidence intervals. The analyses were stratified by age group (40-59 and >= 60 years) and the age of the individuals was updated.Results: During the median follow-up period of 19 years, we documented 4,690 strokes, including 2,781 ischemic strokes and 1,358 intracerebral hemorrhages. After adjusting for sex, age, smoking, alcohol consumption, leisure time physical activity, history of hypertension, dyslipidemia, and diabetes mellitus, we observed a positive linear association between BMI and ischemic stroke (linear trend, p < 0.001) in both age groups (interaction p>0.05). In contrast, a curvilinear association between BMI and intracerebral hemorrhage was observed in both the middle (curvilinear trend, p=0.017) and the older group (curvilinear trend, p=0.098) (interaction p>0.05).Conclusion: BMI and stroke associations did not vary significantly with age, although the association may differ according to subtype.

Background: Better identification of high-risk individuals of type 2 diabetes mellitus (T2DM) for focused delivery of preventive measures requires risk prediction models using novel predictors. We evaluated the predictive value of long-term variability of systolic blood pressure (SBPV), which was recently reported to be associated with T2DM incidence, if added to a model with conventional T2DM predictors in a Japanese cohort study. Methods: A cohort of 3017 Japanese individuals (2446 male, 571 female) ages 36-65 years were followed from 2007 to 2019. Root-mean-square error (RMSE) and slope of systolic blood pressure (SBP) change regressed on year were calculated per individual using SBP values obtained consecutively from 2003 to 2007 to represent SBPV. An initial Cox model included age, sex, smoking status, regular exercise, family history of diabetes, body mass index (BMI), baseline SBP, blood levels of triglycerides (TG), high-density lipoprotein cholesterol (HDLC) and fasting blood glucose (FBG), and backward elimination was used for variable selection. The c-statistics, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to compare the performance of prediction models without (Model 1) and with SBPV (Model 2). Results: During 9.8-year (median) follow-up, 135 developed T2DM. We confirmed that RMSE was significantly associated with T2DM incidence independent of other variables used in a conventional model. Backwards elimination procedure selected BMI, TG, HDLC, FBG, SBP RMSE, and SBP slope for the final model (Table 1). Although the c-indices were not statistically different between Model 1 (0.77) and Model 2 (0.78) as well as the NRI (7.1%), the IDI was statistically significant (0.8%, p<0.05). Conclusions: The present study revealed that long-term variability of SBP slightly improved the predictive value of T2DM if added to a conventional prediction model.

The physical, psychiatric, and social comorbidities interfere with the everyday activities of community-dwelling individuals with schizophrenia and increase the risk of their readmission. However, these comorbidities have not been investigated comprehensively in Japan. We conducted a self-reported internet survey in February 2022 to identify individuals aged 20–75 years with and without schizophrenia using a prevalence case-control study. The survey compared physical comorbidities such as being overweight, hypertension, and diabetes; psychiatric comorbidities such as depressive symptoms and sleep disturbances; social comorbidities such as employment status, household income, and social support between participants with and without schizophrenia. A total of 223 participants with schizophrenia and 1776 participants without schizophrenia were identified. Participants with schizophrenia were more likely to be overweight and had a higher prevalence of hypertension, diabetes, and dyslipidemia than participants without schizophrenia. Additionally, depressive symptoms, unemployment, and non-regular employment were more prevalent in participants with schizophrenia than those without schizophrenia. These results highlight the necessity of comprehensive support and interventions addressing physical, psychiatric, and social comorbidities in individuals with schizophrenia in the community. In conclusion, effective interventions for managing comorbidities in individuals with schizophrenia are necessary to enable them to continue to live in the community.

Introduction: Low density lipoprotein cholesterol (LDL-C) is an established causal factor for coronary heart disease (CHD) and ischemic stroke. A positive linear association between LDL-C and risk of CHD or ischemic stroke was reported from western populations but among Japanese the evidence still insufficient especially on the risk of ischemic stroke. This study used a longitudinal data from the Aichi Worker’s Cohort Study to explore the associations of LDL-C levels with the incidence of CHD, and stroke subtypes. Methods: Pooled data of 6325 adults (5001 men and 1324 women) who responded to the second (2002) and third (2007) wave surveys of the study were used for the current analysis. Propensity scores for LDL-C categories were generated using multinomial logistic regression that included age, sex, smoking, alcohol drinking, physical activity, body mass index, high-density lipoprotein cholesterol, triglycerides, history of diabetes and hypertension, antihypertensive medication, taking dyslipidemia medication and survey year. Hazard ratios (HRs) and the 95% confidence intervals (95% CIs) were estimated from inverse probability weighted (IPW) cox proportional hazards model for LDL-C categories associations with risks of CHD, stroke and its subtypes, and CVD. We also used restricted cubic spline to examine the possible nonlinear relationship. Results: During a median of 14 years of follow-up, 73 strokes (40 ischemic stroke, 30 hemorrhagic stroke and 3 unknown) and 60 CHD were observed. In comparison with LDL-C < 120 mg/ dl, LDL-C ≥160 mg/dl was significantly associated with the increased risk of CVD (HR 1.79, 95% CI: 1.12-2.86) and CHD (HR 3.82, 95% CI: 1.80-8.06), but not with stroke (HR 1.05, 95% CI: 0.54-2.06), hemorrhagic stroke (HR 0.47, 95% CI: 0.13-1.67) or ischemic stroke (HR 1.56, 95% CI: 0.66-3.68). The results of restricted cubic spline analysis showed that the risks of CVD and CHD gradually increased from LDL-C of 120 mg/dl. On the other hand, the risk of ischemic stroke was flat until around LDL-C of 160 mg/dl and then increased afterward. The risk of hemorrhagic stroke was flat from LDL-C of 120 mg/dl or above, but showed an increased risk trend towards lower levels of LDL-C. Conclusions: Based on this recent, long-term prospective study among middle-aged Japanese workers and by applying the IPW method to adjust for several confounding variables, we found that LDL-C was linearly and positively associated with CHD incidence while higher LDL-C levels tended to be at an increased risk of ischemic stroke, though non-significant.

Objective: The present study investigates the association between long-term systolic blood pressure (SBP) variability and the risk of type 2 diabetes mellitus (T2DM) by using different indicators of the variability including standard deviation (SD), coefficient of variation (CV), maximum and minimum difference (MMD), root mean square error (RMSE), variability independent of the mean (VIM), and average real variability (ARV). Design and method: A cohort of 3017 Japanese individuals (2446 male, 571 female) aged 36 to 65 was followed from 2007 through 2019. SD, CV, MMD, RMSE, VIM, and ARV of long term SBP changes were calculated per individual using SBP values obtained consecutively from 2003 to 2007. A multivariable Cox proportional model was applied to estimate hazard ratio (HR) and the corresponding 95% confidence interval (CI) for tertiles of the each variability measure, SD, CV, MMD, RMSE, VIM, and ARV, adjusted for age, sex, smoking status, regular exercise, family history of diabetes, sleep disorders, sodium intake, body mass index (BMI), BMI slope, fasting blood glucose (FBG), and 2007 SBP. Results: Of the variability measures examined, the highest RMSE tertile compared to the lowest was significantly associated with T2DM incidence (multivariable-adjusted HR: 1.79, 95% CI: 1.15–2.78). Also, the highest ARV tertile compared to the lowest was associated with T2DM incidence (multivariable-adjusted HR: 1.54, 95% CI: 1.00–2.35). The SD, CV, MMD and VIM were not significantly associated with T2DM incidence independent of the covariates. Conclusion: This study revealed that long-term SBP variability is possibly an independent risk factor for the future occurrence of T2DM, and such property can only be measured by either RMSE or ARV.

Objectives:Despite the high incidence of urinary dysfunction (UD) after rectal surgery, it remains questionable whether UD causes future chronic kidney disease (CKD). This study aimed to clarify the long-term trends in renal function and risk factors for future CKD after rectal resection.Methods:For comparison, patients who underwent rectal resection (n = 129) and colectomy (n = 127) between 2006 and 2017 were identified. The estimated glomerular filtration rate (eGFR) ratio was calculated as the ratio to the baseline. "eGFR ratio < 0.75 at 3-year" was adopted as a surrogate indicator of future CKD.Results:eGFR ratio significantly decreased in the rectal cohort compared with the colon cohort at 1.5 years (0.9 vs. 0.95, p = 0.008) and at 3 years (0.85 vs. 0.94, p < 0.001). Although the preoperative prevalence of CKD was lower in the rectal than the colon cohort (13.9% vs. 23.6%, p = 0.055), it was similar at 3 years (29.5% vs. 30.7%). In multivariate analysis, females, and cT4 were independent risk factors for future CKD, but UD itself was not.Conclusions:Postoperative eGFR significantly decreased after rectal cancer surgery compared to colectomy. The prevalence of CKD more than doubled at 3 years after rectal resection. The female sex and cT4 tumor, instead of the UD, were independent risk factors for future CKD.

Importance Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US. Objective To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes. Design, Setting, and Participants Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021. Exposures The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR). Main Outcomes and Measures The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses. Results Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m 2 (SD, 22 mL/min/1.73 m 2 ) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m 2 (SD, 22 mL/min/1.73 m 2 ) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m 2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m 2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years]). Conclusions and Relevance In this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations.