Cross-Sectional and Longitudinal Associations between Forearm Bone Mineral Density and Anthropometry in Adult Japanese Men and Women.

BACKGROUND: No consensus exists regarding which anthropometric measurements are related to bone mineral density (BMD), and this relationship may vary according to sex and age. A large Japanese cohort was analyzed to provide an understanding of the relationship between BMD and anthropometry while adjusting for known confounding factors. METHODS: Our cohort included 10,827 participants who underwent multiple medical checkups including distal forearm BMD scans. Participants were stratified into four groups according to age (≥50 years or <50 years) and sex. The BMD values were adjusted for confounding factors, after which single and partial correlation analyses were performed. The prevalence of osteopenia was plotted for each weight index (weight or body mass index [BMI]) class. RESULTS: Cross-sectional studies revealed that weight was more favorably correlated than BMI in the older group (R=0.278 and 0.212 in men and R=0.304 and 0.220 in women, respectively), whereas weight and BMI were weakly correlated in the younger age groups. The prevalence of osteopenia exhibited a negative linear relationship with weight among older women ≥50 years of age, and an accelerated increase was observed with decreasing weight in older men weighing <50 kg and younger women weighing <60 kg. When weight was replaced with BMI, the prevalence was low in most subgroups classified by weight. CONCLUSIONS: Weight, rather than BMI, was the most important indicator of osteopenia but it might not be predictive of future bone loss.

Association between screen time, including that for smartphones, and overweight/obesity among children in Japan: NICE EVIDENCE Study 4.

The association between screen time (ST), including that for smartphones, and overweight/obesity in children was examined separately for boys and girls, considering the influence of lifestyle factors. A cross-sectional study was conducted in 2,242 Japanese children (1,278 girls) aged 10-14 years. Overweight/obesity was defined by the International Obesity Task Force. Logistic regression analysis showed that only for girls, total ST (≥4 h), smartphone ST (≥3 h), and non-smartphone ST (≥2 h) were all independently and significantly associated with overweight/obesity compared to <2 h total ST, non-use of smartphones, and <1 h non-smartphone ST. Thus, smartphone ST ≥3 h and non-smartphone ST ≥2 h were additively associated with overweight/obesity in girls only. Girls having smartphone ST ≥3 h and non-smartphone ST ≥2 h were 6.79 times (95% CI: 3.11-14.81) more likely to have overweight/obesity than girls with less usage of both. In girls, when total ST was ≥4 < 5 h or smartphone ST was ≥2 h, the significant association with overweight/obesity disappeared when physical activity was ≥60 min/day and sleep time was ≥8.5 h. In addition, none of these associations was significant in boys. In Japanese girls, smartphone ST, non-smartphone ST, and total ST were all significantly associated with overweight/obesity. To avoid overweight/obesity, it is suggested to keep smartphone ST, non-smartphone ST, and total ST to <3 h, <2 h, and <4 h, respectively, and to engage in sufficient physical activity and sleep time.

Usefulness of New Criteria for Metabolic Syndrome Optimized for Prediction of Cardiovascular Diseases in Japanese.

AIMS: We attempted to clarify whether the multiple criteria for metabolic syndrome (MetS) can sufficiently predict cardiovascular disease, whether waist circumference (WC) should be required, and whether sex-specific thresholds for each component are necessary. Only a few large-scale studies among East Asians have addressed the ability of MetS to predict cardiovascular disease. METHODS: We analyzed the data of 330,051 men and 235,028 women aged 18-74 years with no history of coronary artery disease (CAD) or cerebrovascular disease (CVD) from a nationwide Japanese claims database accumulated during 2008-2016. The association of each MetS component with CAD or CVD (CAD/CVD), MetS associated with CAD/CVD according to various criteria, and utility of modified criteria with more specific optimal values for each component were examined using multivariate Cox regression and receiver operating characteristic (ROC) analysis. RESULTS: During the study, 3,934 men (1.19%) and 893 women (0.38%) developed CAD/CVD. For each current MetS criteria, there was a 1.3- to 2.9-fold increased risk of CAD/CVD. Optimal thresholds for predicting CAD/CVD were WCs of 83 and 77 cm, triglycerides levels of 130 and 90 mg/dl, high-density lipoprotein cholesterol levels of 50 and 65 mg/dl, blood pressures of 130/80 and 120/80 mmHg, and fasting plasma glucose levels of 100 and 90 mg/dl for men and women, respectively. The existing MetS criteria and modified criteria were not significantly different in predicting CAD/CVD, but using the modified criteria markedly increased the prevalence of MetS and percentage of people with MetS developing CAD/CVD. CONCLUSIONS: Although various criteria for MetS similarly predicted CAD/CVD, the new criteria greatly reduced the number of high-risk individuals, especially women, overlooked by the current criteria.

Lifestyle Intervention With Smartphone App and isCGM for People at High Risk of Type 2 Diabetes: Randomized Trial.

AIMS: Although conventional interventions for people at high risk of developing type 2 diabetes are usually conducted face-to-face, such interventions are burdensome for health care providers. We developed a lifestyle intervention program combining lifestyle coaching via a smartphone application augmented by intermittently scanned continuous glucose monitoring without burdening health care providers. Its effectiveness for glycemic control and body weight reduction in people at risk of type 2 diabetes was investigated. MATERIALS AND METHODS: For this 12-week randomized unblinded trial with offline recruitment, participants with a hemoglobin A1c level of 5.6% to 6.4% or a fasting blood glucose of 110 to 125 mg/dL and body mass index (BMI) >23 kg/m2 but <40 kg/m2 were randomly assigned to the intervention group (App) and control group (C). The primary endpoint was the difference in time in range of blood glucose between 70 and 140 mg/dL (3.9-7.8 mmol/L) before and after the study period between the 2 groups. RESULTS: Among 168 patients (mean age, 48.1 years; mean BMI, 26.6 kg/m2; and male, 80.4%), 82 and 86 were assigned to the App group and C group, respectively. After 12 weeks, time in range of blood glucose at 70 to 140 mg/dL significantly improved in the App group compared with the C group (-2.6 minutes/day vs +31.5 minutes/day, P = .03). Changes in time above range did not differ, whereas time below range (blood glucose <70 mg/dL; +23.5 minutes/day vs -8.9 minutes/day, P = .02) improved in the App group. BMI (-0.26 vs -0.59, P = .017) was reduced in the App group compared with the C group. CONCLUSION: Intervention with a smartphone app and intermittently scanned continuous glucose monitoring increased glycemic control accompanied by decreased carbohydrate intake and weight loss. Further trials are needed to confirm whether these interventions can reduce incident type 2 diabetes.

Associations among metabolic health, weight status, and various physical fitness components in Japanese adolescents: a cross-sectional study (NICE EVIDENCE study- Agano 3).

Aim was to examine associations among metabolic health, weight status, and various physical fitness (PF) components in 1744 Japanese adolescents aged 13-14. Anthropometric measurements and PF tests (20 m shuttle run test [20mSRT], handgrip strength/body mass [HG], standing long jump [SLJ], and sit ups [SU]) were administered. The bottom sex-specific quintile of PF indicated "low fit". Participants were classified as non-overweight (non-OW) or overweight/obese (OW) according to the International Obesity Task Force. Clustered metabolic risk was defined as the sum of Z scores for mean arterial pressure, non-high-density lipoprotein cholesterol, and HbA1c, divided by three, and ≥ 1 SD. Combination of weight status and scores for HG or SU were additively associated with clustered metabolic risk. Compared with the non-OW-moderate-high fit group, the OW-low HG group was 3.05 (95%CI: 1.88-4.97) times more likely to have clustered metabolic risk although risk was not significantly elevated in the OW-moderate-high HG group (1.52 [95%CI: 0.88-2.62]). A similar association was observed between OW and low SU scores but not between OW and low 20mSRT or SLJ scores. Adolescents with OW and moderate-high HG or SU scores had a lower prevalence of an unfavourable metabolic state than those with OW and low HG or SU results.

Machine learning approach to predict body weight in adults.

Background: Obesity is an established risk factor for non-communicable diseases such as type 2 diabetes mellitus, hypertension and cardiovascular disease. Thus, weight control is a key factor in the prevention of non-communicable diseases. A simple and quick method to predict weight change over a few years could be helpful for weight management in clinical settings. Methods: We examined the ability of a machine learning model that we constructed to predict changes in future body weight over 3 years using big data. Input in the machine learning model were three-year data on 50,000 Japanese persons (32,977 men) aged 19-91 years who underwent annual health examinations. The predictive formulas that used heterogeneous mixture learning technology (HMLT) to predict body weight in the subsequent 3 years were validated for 5,000 persons. The root mean square error (RMSE) was used to evaluate accuracy compared with multiple regression. Results: The machine learning model utilizing HMLT automatically generated five predictive formulas. The influence of lifestyle on body weight was found to be large in people with a high body mass index (BMI) at baseline (BMI ≥29.93 kg/m2) and in young people (<24 years) with a low BMI (BMI <23.44 kg/m2). The RMSE was 1.914 in the validation set which reflects ability comparable to that of the multiple regression model of 1.890 (p = 0.323). Conclusion: The HMLT-based machine learning model could successfully predict weight change over 3 years. Our model could automatically identify groups whose lifestyle profoundly impacted weight loss and factors the influenced body weight change in individuals. Although this model must be validated in other populations, including other ethnic groups, before being widely implemented in global clinical settings, results suggested that this machine learning model could contribute to individualized weight management.

Utility of a Physical Fitness Score in Screening for Chronic Diseases.

We developed a new Physical Score (PS) consisting of comprehensive physical fitness indicators and elucidated the association between the resultant PS and metabolic diseases, i.e., diabetes, hypertension, dyslipidemia, fatty liver, and metabolic syndrome (MetS), among Japanese. Analyzed were 49,850 persons (30,039 men) aged 30 to 69 y who underwent physical fitness tests. Principal component analysis was performed on the correlation matrix of the physical fitness test results (relative grip strength, single-leg balance with eyes closed, and forward bending) according to sex and age. We defined the PS as the first principal component score. A formula was developed for various age groups comprised of men and women from 30 to 69 years of age from which the PS for each age and sex was calculated. The PS for both men and women was normally distributed with a value of 0 ± 1.15-1.16. Multivariate logistic regression analysis showed that the risk of metabolic diseases increased approximately 1.1-1.6 times per each 1-point reduction in the PS. The association between PS and MetS was particularly strong in that a 1-point reduction in the PS increased the risk of MetS by 1.54 times (95% confidence interval 1.46 to 1.62) in men and by 1.21 times (1.15 to 1.28) in women. The association between a lower PS and disease risk was stronger in younger men for fatty liver and in older men for MetS. Conversely, in women, the association between a lower PS and disease risk was stronger in older women for fatty liver and in younger women for MetS. For diabetes, hypertension, and dyslipidemia, the change in the impact of PS reductions across age groups was small. The PS is a useful and simple non-invasive tool for screening Japanese people for metabolic diseases.

Combined effects of blood pressure and glycemic status on risk of heart failure: a population-based study.

AIMS: To investigate the combined effects of blood pressure (BP) and glycemic status on the risk of heart failure. METHODS: Examined was a Japanese claims database from 2008 to 2019 on 589 621 individuals. Cox proportional hazards model identified the incidence of heart failure among five levels of SBP/DBP according to glucose status. RESULTS: Mean follow-up period was 5.6 years. The incidence of heart failure per 1000 person-years in the normoglycemia, borderline glycemia, and diabetes groups were 0.10, 0.18, and 0.80, respectively. In normoglycemia, a linear trend was observed between both SBP and DBP categories and hazard ratios for heart failure ( P for linearity <0.001). In borderline glycemia, J-shaped association was observed between DBP categories and hazard ratios, although the liner trend was significant ( P  < 0.001). In diabetes, the linear trend for the relationship between DBP categories and hazard ratios was not significant ( P  = 0.09) and the J-shaped association in relation to the hazard ratios was observed between SBP categories and heart failure risk. In the lowest SBP category (i.e. SBP < 120 mmHg), patients with diabetes had more than five-fold heart failure risk [hazard ratio (95% confidence interval), 5.10 (3.19-8.15)], compared with those with normoglycemia and SBP less than 120 mmHg. CONCLUSION: The association between SBP/DBP and heart failure risk weakened with worsening of glucose metabolism, suggesting strict BP control accompanied by excessively lowered DBP should be cautious in prevent heart failure in abnormal glycemic status. Particularly in diabetes, comprehensive management of risk factors other than BP may be essential to prevent heart failure. Further trials are needed to support these suggestions and apply them to clinical practice.

Association of the estimated glomerular filtration rate (eGFR) and/or proteinuria to predict the risk of initiation of dialysis in people with and without diabetes.

Aims: To determine the associations between combined urinary protein (UP) and a reduced estimated glomerular filtration rate (eGFR) and the risk of starting dialysis with or without diabetes mellitus (DM). Methods: A nationwide database with claims data on 335,778 people with and without DM aged 19-72 years in Japan was used to elucidate the impact of the severities of UP and eGFR on starting dialysis. Initiation of dialysis was determined from claims using ICD-10 codes and medical procedures. Using multivariate Cox modeling, we investigated the severities of UP and eGFR to predict the initiation of dialysis with and without DM. Results: Both eGFR < 60 and UP(+) were independent predictors for starting dialysis with and without DM, and their values exhibited a synergistic risk of dialysis. eGFR < 60 presented a nearly twofold risk for starting dialysis compared to UP(+) regardless of DM. Risk of starting dialysis was increased with UP(+) and eGFR ≥ 60 accompanied by DM although this association was not observed without DM. Those who had UP(-) and eGFR < 60 had a high risk of starting dialysis regardless of DM. Compared with DM(-)UP(-)eGFR ≥ 60, HRs for starting dialysis for DM(+)UP(+)eGFR ≥ 60, DM(+)UP(-)eGFR < 60 and DM(+)UP(+)eGFR < 60 significantly increased 17.7 (10.6-29.7), 25.5 (13.8-47.1) and 358.1 (239.1-536.5) times, respectively. Conclusions: eGFR < 60 and UP(+) together presented an extremely high risk of dialysis especially with DM. UP( +) increased the risk of starting dialysis regardless of the eGFR with DM. Both patient education and a treatment strategy by physicians might be helpful to avoid the progression of renal failure.

Network meta-analysis of glucose-lowering drug treatment regimens with the potential risk of hypoglycemia in patients with type 2 diabetes mellitus in terms of glycemic control and severe hypoglycemia.

Insulin and its secretagogues are essential for some patients with type 2 diabetes (T2D) to maintain good glycemic control (GC), but severe hypoglycemia (SH) is a concern. This network meta-analysis aimed to find optimal glucose-lowering drug treatment regimens in terms of GC and SH in T2D patients. MEDLINE and EMBASE were used to identify trials that compared two or more treatments including insulins and/or sulfonylurea or glinides and that examined both GC and SH. Treatment hierarchy was expressed as the surface under the cumulative ranking curve (SUCRA) probabilities. We identified 137 eligible trials comprising 42 treatments. The use of insulins and non-insulin glucose-lowering agents except for sulfonylurea or glinide had a higher SUCRA than insulins only for hemoglobin A1c (A1C) (p = 0.01) changes and achievement of A1C < 7.0% (p = 0.02) or A1C ≤ 6.5% (p = 0.002). The use of sulfonylurea or glinide and other non-insulin glucose-lowering agents resulted in a lower SUCRA for SH than insulins only when trials were analyzed for A1C change (p = 0.06) and achievement of A1C < 7.0% (p = 0.004) or A1C ≤ 6.5% (p = 0.004). Cluster analysis indicated that premixed insulin plus glucagon-like peptide-1 receptor agonist (Mix-ins + GLP1) belonged to the high-efficacy category for GC and glinide plus thiazolidinedione (glinide + TZD) belonged to the relatively high-efficacy category for GC among several high-safety categories regarding SH. In T2D patients, clinicians should consider appropriate combinations of non-insulin glucose-lowering agents (especially glinide + TZD) for reducing SH risk before switching to insulin therapies. If switching, they should be willing to add non-insulin glucose-lowering agents (especially, Mix-ins + GLP1) to insulins to further improve GC.

Fast walking and physical activity are independent contributors to improved physical function.

BACKGROUND AND OBJECTIVES: To clarify whether the presence or absence of fast walking and habitual physical activity are independently associated with the incidence of functional disability. METHODS: This historical cohort study was comprised of 9,652 (4,412 men, mean age 65 years) individuals aged 39-98 years without functional disability at baseline. Functional disability was determined based on the Japanese long-term care insurance system, which specified requirements for assistance in the activities of daily living. The impact of fast walking and habitual physical activity on the incidence of functional disability was analysed by Cox proportional hazards models. RESULTS: The follow-up period was a median of 3.7 years during which 165 patients were newly certified as having functional disability. In the multivariate analysis, baseline age in 5-year increments (hazard ratio 2.42 [95% confidence interval 2.18-2.69]), no habitual physical activity (1.56 [1.07-2.27]), and not fast walking (1.89 [1.32-2.69]) significantly increased the risk of functional disability after adjustment for covariates. The stratified analysis showed that compared with physical activity (+), the impact of physical activity (-) on the incidence of functional disability was observed in those aged ≥75 years regardless of fast walking (+). Fast walking (-) significantly increased the risk of disability compared with fast walking (+) in those aged <75 years regardless of a physical activity habit. CONCLUSION: In Japanese, slow walking speed and lack of a physical activity habit were shown to be independent risk factors for incident functional disability, with their impact differing according to age.

Relationship between changes in blood pressure from summer to winter and estimated 24-hour salt excretion using spot urine: the Niigata Wellness Study.

A convenient way to determine salt intake is salt excretion using spot urine (e-NaCl). We measured e-NaCl at health checkups and compared results with seasonal changes in blood pressure. Among 19,732 examinees who underwent health checkups from Aug. 2012 to Mar. 2013, age, body weight and e-NaCl were measured and compared to monthly mean systolic blood pressure (SBP). Excluded were those taking antihypertensive drugs and with creatinine levels higher than 2.0 mg/dL. Also examined was salt intake (i-NaCl) by an interview survey from Aug. to Dec. 2012. Correlations with SBP were R = 0.7718 for age, R = 0.5996 for body weight, R = 0.2498 for i-NaCl and R = 0.9335 for e-NaCl. e-NaCl decreased in summer. It was presumed that the reduced burden on the kidney of salt excretion due to sweating may be related to decreases in blood pressure in summer.

Impact of metabolic syndrome and metabolic dysfunction-associated fatty liver disease on cardiovascular risk by the presence or absence of type 2 diabetes and according to sex.

BACKGROUND: To determine the impact of metabolic syndrome (MetS) and/or metabolic dysfunction-associated fatty liver disease (MAFLD), which are pathophysiologically similar and include insulin resistance, on the development of new-onset cardiovascular disease with and without type 2 diabetes and according to sex. METHODS: This study included 570,426 individuals without a history of cardiovascular disease who were enrolled in a nationwide claims database from 2008 to 2016 and were classified by the presence or absence of MetS and/or MAFLD stratified by the presence or absence of type 2 diabetes and sex. The fatty liver index was used to determine the presence or absence of fatty liver that required a diagnosis of MAFLD. Risks of developing coronary artery disease (CAD) and cerebrovascular disease (CVD) in each category were analyzed using a multivariate Cox proportional hazard model. RESULTS: During a median follow-up of 5.2 years, 2252 CAD and 3128 CVD events occurred. Without type 2 diabetes the hazard ratio (HR) (95% CI) for CAD/CVD compared with neither MAFLD nor MetS was 1.32 (1.17-1.50)/1.41(1.28-1.57) for MAFLD only (without MetS), 1.78 (1.22-2.58)/1.66 (1.34-2.06) for MetS only (without MAFLD), and 2.10 (1.84-2.39)/1.73 (1.54-1.95) for MAFLD + MetS. For those with type 2 diabetes, the HR for CAD for MAFLD only (compared with neither MAFLD nor MetS) was 1.29 (1.06-1.58), for MetS only 1.34 (0.84-2.13), and for MAFLD + MetS 1.22 (1.02-1.47). For CVD, there was a significant increase in HR only in MAFLD + MetS [1.44 (1.18-1.76)]. The results of the analysis stratified by sex showed that MAFLD had a greater impact in men, and MetS had a greater impact in women regarding the development of CAD. CONCLUSIONS: Distinguishing between MetS and/or MAFLD in the presence or absence of type 2 diabetes and according to sex may aid in accurately identifying patients at high risk of cardiovascular disease.

EGF Downregulates Presynaptic Maturation and Suppresses Synapse Formation In Vitro and In Vivo.

Neuronal differentiation, maturation, and synapse formation are regulated by various growth factors. Here we show that epidermal growth factor (EGF) negatively regulates presynaptic maturation and synapse formation. In cortical neurons, EGF maintained axon elongation and reduced the sizes of growth cones in culture. Furthermore, EGF decreased the levels of presynaptic molecules and number of presynaptic puncta, suggesting that EGF inhibits neuronal maturation. The reduction of synaptic sites is confirmed by the decreased frequencies of miniature EPSCs. In vivo analysis revealed that while peripherally administrated EGF decreased the levels of presynaptic molecules and numbers of synaptophysin-positive puncta in the prefrontal cortices of neonatal rats, EGF receptor inhibitors upregulated these indexes, suggesting that endogenous EGF receptor ligands suppress presynaptic maturation. Electron microscopy further revealed that EGF decreased the numbers, but not the sizes, of synaptic structures in vivo. These findings suggest that endogenous EGF and/or other EGF receptor ligands negatively modulates presynaptic maturation and synapse formation.

Impact of Medication Adherence and Glycemic Control on the Risk of Micro- and Macrovascular Diseases in Patients with Diabetes.

PURPOSE: Our purpose in the research was to clarify the impact of medication adherence to oral hypoglycemic agents during a 1-year period and subsequent glycemic control on the risk of micro- and macrovascular diseases. METHODS: Examined was a nationwide claims database on 13,256 individuals with diabetic eye disease without requiring prior treatment, 7,862 without prior initiation of dialysis, 15,556 without prior coronary artery disease, 16,243 without prior cerebrovascular disease, and 19,386 without prior heart failure from 2008 to 2016 in Japan. Medication adherence was evaluated by the proportion of days covered. Patients were considered to have poor adherence if the proportion of days covered was <80%. Multivariate Cox regression model identified risks of micro- and macrovascular diseases. RESULTS: In each group, mean age was 53 to 54 years, HbA1c was 7.1% to 7.2%, and median follow-up period was 4.6 to 5.1 years, and the percentage of poor adherence was approximately 30%. During the study period, 532 treatment-requiring diabetic eye disease, 75 dialysis, 389 coronary artery disease, 316 cerebrovascular disease, and 144 heart failure events occurred. Multivariate Cox regression model revealed that the hazard ratio (95% confidence interval) of dialysis in the poor adherence group was 2.04 (1.27-3.30) compared with the good adherence group. The hazard ratios in the poor adherence/poor glycemic control group were 3.34 (2.63-4.24) for treatment-requiring diabetic eye disease, 4.23 (2.17-8.26) for dialysis, 1.69 (1.23-2.31) for coronary artery disease, and 2.08 (1.25-3.48) for heart failure compared with the good adherence/good glycemic control group. CONCLUSIONS: Poor medication adherence was an independent risk factor for the initiation of dialysis, suggesting that clinicians must pay close attention to these patients.

Impact of prior cerebrovascular disease and glucose status on incident cerebrovascular disease in Japanese.

BACKGROUND: Although both a history of cerebrovascular disease (CVD) and glucose abnormality are risk factors for CVD, few large studies have examined their association with subsequent CVD in the same cohort. Thus, we compared the impact of prior CVD, glucose status, and their combinations on subsequent CVD using real-world data. METHODS: This is a retrospective cohort study including 363,627 men aged 18-72 years followed for ≥ 3 years between 2008 and 2016. Participants were classified as normoglycemia, borderline glycemia, or diabetes defined by fasting plasma glucose, HbA1c, and antidiabetic drug prescription. Prior and subsequent CVD (i.e. ischemic stroke, transient ischemic attack, and non-traumatic intracerebral hemorrhage) were identified according to claims using ICD-10 codes, medical procedures, and questionnaires. RESULTS: Participants' mean age was 46.1 ± 9.3, and median follow up was 5.2 (4.2, 6.7) years. Cox regression analysis showed that prior CVD + conferred excess risk for CVD regardless of glucose status (normoglycemia: hazard ratio (HR), 8.77; 95% CI 6.96-11.05; borderline glycemia: HR, 7.40, 95% CI 5.97-9.17; diabetes: HR, 5.73, 95% CI 4.52-7.25). Compared with normoglycemia, borderline glycemia did not influence risk of CVD, whereas diabetes affected subsequent CVD in those with CVD- (HR, 1.50, 95% CI 1.34-1.68). In CVD-/diabetes, age, current smoking, systolic blood pressure, high-density lipoprotein cholesterol, and HbA1c were associated with risk of CVD, but only systolic blood pressure was related to CVD risk in CVD + /diabetes. CONCLUSIONS: Prior CVD had a greater impact on the risk of CVD than glucose tolerance and glycemic control. In participants with diabetes and prior CVD, systolic blood pressure was a stronger risk factor than HbA1c. Individualized treatment strategies should consider glucose tolerance status and prior CVD.

Associations of Systolic Blood Pressure and Diastolic Blood Pressure With the Incidence of Coronary Artery Disease or Cerebrovascular Disease According to Glucose Status.

OBJECTIVE: To determine associations of systolic blood pressure (SBP) and diastolic blood pressure (DBP) with new-onset coronary artery disease (CAD) or cerebrovascular disease (CVD) according to glucose status. RESEARCH DESIGN AND METHODS: Examined was a nationwide claims database from 2008 to 2016 on 593,196 individuals. A Cox proportional hazards model identified risks of CAD and CVD events among five levels of SBP and DBP. RESULTS: During the study period 2,240 CAD and 3,207 CVD events occurred. Compared with SBP ≤119 mmHg, which was the lowest quintile of SBP, hazard ratios (95% CI) for CAD/CVD in the 4 higher quintiles (120-129, 130-139, 140-149, ≥150 mmHg) gradually increased from 2.10 (1.73-2.56)/1.46 (1.27-1.68) in quintile 2 to 3.21 (2.37-4.34)/4.76 (3.94-5.75) in quintile 5 for normoglycemia, from 1.39 (1.14-1.69)/1.70 (1.44-2.01) in quintile 2 to 2.52 (1.95-3.26)/4.12 (3.38-5.02) in quintile 5 for borderline glycemia, and from 1.50 (1.19-1.90)/1.72 (1.31-2.26) in quintile 2 to 2.52 (1.95-3.26)/3.54 (2.66-4.70) in quintile 5 for diabetes. A similar trend was observed for DBP across 4 quintiles (75-79, 80-84, 85-89, and ≥90 mmHg) compared with ≥74 mmHg, which was the lowest quintile. CONCLUSIONS: Results indicated that cardiovascular risks gradually increased with increases in SBP and DBP regardless of the presence of and degree of a glucose abnormality. Further interventional trials are required to apply findings from this cohort study to clinical practice.

Rates and risk factors for amputation in people with diabetes in Japan: a historical cohort study using a nationwide claims database.

BACKGROUND: The prevalence of diabetes is rising, and diabetes develops at a younger age in East Asia. Although lower limb amputation negatively affects quality of life and increases the risk of cardiovascular events, little is known about the rates and predictors of amputation among persons with diabetes from young adults to those in the "young-old" category (50-72 y). METHODS: We analyzed data from a nationwide claims database in Japan accumulated from 2008 to 2016 involving 17,288 people with diabetes aged 18-72 y (mean age 50.2 y, HbA1c 7.2%). Amputation occurrence was determined according to information from the claims database. Cox regression model identified variables related to lower limb amputation. RESULTS: The mean follow-up time was 5.3 years, during which time 16 amputations occurred (0.17/1000 person-years). Multivariate Cox regression analysis showed that age (hazard ratio [HR] 1.09 [95% confidence intervals] 1.02-1.16, p = 0.01) and HbA1c (HR 1.46 [1.17-1.81], p < 0.01) were independently associated with amputations. Compared with those aged < 60 years with HbA1c < 8.0%, the HR for amputation was 27.81 (6.54-118.23) in those aged ≥60 years and HbA1c ≥8.0%. CONCLUSIONS: Age and HbA1c were associated with amputations among diabetic individuals, and the rates of amputation were significantly greater in those ≥60 years old and with HbA1c ≥8.0%.

Association of estimated plasma volume and weight loss after long-term administration and subsequent discontinuation of the sodium-glucose cotransporter-2 inhibitor tofogliflozin.

Sodium-glucose cotransporter-2 inhibitors (SGLT2) are drugs that have been reported to have several effects through the regulation of plasma volume, for example, antihypertensive effects. This study aimed to clarify the impact of long-term administration and subsequent discontinuation of the SGLT2 inhibitor tofogliflozin on estimated plasma volume (ePV), brain natriuretic peptide (BNP) and the relationship between changes in ePV, BNP and body weight (BW). Data from 157 participants with type 2 diabetes receiving tofogliflozin monotherapy in a phase 3 study were analysed. Changes in variables or correlations among them during a 52-week administration and a 2-week post-treatment period were investigated. Percent change in ePV was calculated using the Strauss formula. Significant decreases in BW, ePV and ln-transformed BNP (ln-BNP) were noted by week 52. %ΔBW was not significantly correlated with %ΔePV and Δln-BNP, while %ΔePV was significantly correlated with Δln-BNP. Two weeks after discontinuation of tofogliflozin, BW, ePV and ln-BNP were significantly increased. %ΔBW was significantly correlated with %ΔePV and Δln-BNP. Furthermore, ePV and BNP were significantly higher than baseline levels.