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.

Impact of a history of cardiovascular disease and physical activity habits on the incidence of functional disability.

We examined the impact of a history of coronary artery disease (CAD) or cerebrovascular disease (CVD) and physical activity habits on functional disability among community-dwelling Japanese adults. This population-based retrospective cohort study included 10,661 people aged 39-98 years in Japan (5054, men). Median follow-up was 3.7 years. During the study period, 209 functional disabilities occurred in the overall study population. In multivariable analysis, a history of CVD (hazard ratio [HR] 1.57 [95% CI: 1.00-2.45]) and no physical activity habit (HR 1.74 [1.27-2.39]) presented increased risks for functional disability. HRs for functional disability among patients with a CVD history with and without a physical activity habit were 1.68 (0.75-3.74) and 2.65 (1.49-4.71), respectively, compared with individuals without a history of CVD with a physical activity habit. Similar results were observed for CAD. We found no significant difference in the incidence of functional disability between the group with a history of CAD or CVD and physical activity habits and the group with no history of CAD or CVD and without physical activity habits. Physical activity habits had a favorable influence on avoiding functional disability regardless of a history of CAD or CVD. Future prospective studies are needed to clarify these associations.

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.

Retrospective cohort study to examine the association between serum amylase and the incidence of type 2 diabetes mellitus, Toranomon Hospital Health Management Center Study 23 (TOPICS 23).

INTRODUCTION: Low serum amylase values are cross-sectionally associated with the prevalence of type 2 diabetes mellitus (T2DM) but have not been shown to be longitudinally associated with its incidence. This retrospective cohort (ie, historical cohort) study aimed to examine the association of previously lowered levels of serum amylase with incident T2DM. RESEARCH DESIGN AND METHODS: Examined were 8316 individuals who had annual health examinations for 6 years (ie, 7 times) at the Toranomon Hospital Health Management Center. The trajectory of serum amylase as the study exposure was classified into two elements: (1) serum amylase level at entry and (2) change in serum amylase, which was expressed as the annual change rate. The annual change rate was calculated by dividing the change in the amylase values according to follow-up periods. Regression analyses were performed to examine the association between low and decreased levels of serum amylase and the incidence of T2DM. RESULTS: Analyzed were 6917 individuals who had not developed T2DM within 1 year after cohort entry. T2DM thereafter occurred in 1021 patients. Cox regression indicated that the adjusted HR (95% CI) for incident T2DM for amylase ≤57 IU/L (quintile (Q) 1) was 0.97 (0.84 to 1.13) compared with amylase ≥58 IU/L (Q2-Q5). Logistic regression indicated that the adjusted OR (95% CI) for an annual change rate of amylase ≤-2.0% (Q1) vs ≥-1.9% (Q2-Q5) was 3.53 (3.00 to 4.16). The adjusted ORs were consistently significant throughout sensitivity analyses according to baseline amylase and the combination of age, body mass index, and hemoglobin A1c. CONCLUSIONS: Results showed that not low but previously decreased serum amylase was a risk factor for T2DM, suggesting the significance of periodic examinations of serum amylase values to detect individuals at high risk of T2DM.

Relationship between the magnitude of body mass index reductions and remission in patients with type 2 diabetes in real world settings: Analysis of nationwide patient registry in Japan (JDDM74).

AIMS: To determine the association between the magnitude of weight loss and incidence of remission according to baseline characteristics in patients with diabetes in clinical settings. METHODS: In total, 39 676 Japanese patients with type 2 diabetes aged ≥18 years with glycated haemoglobin (HbA1c) ≥6.5% and/or glucose-lowering drug prescription were identified from databases of specialists' clinics from 1989 and followed until September 2022. Remission was diagnosed as maintaining HbA1c <6.5% at least 3 months after cessation of a glucose-lowering drug. Factors associated with remission were evaluated by logistic regression analysis according to weight change in 1 year (i.e. ≥10%, 7.0-9.9%, 3.0-6.9% reduction, <3% change and ≥3.0% increase). RESULTS: During the study period, 3454 remissions occurred. The rates of remission were higher in the group with the greatest reduction of body mass index (BMI) in any category examined (i.e. baseline BMI, HbA1c, duration of diabetes and treatment). The incidences of remission per 1000 person-years were about 25 and 50, respectively, for those with BMI ≥22.5 and reductions in BMI of 7.0-9.9% and ≥10% in 1 year. Remissions per 1000 person-years were 99.2 and 91.8, respectively, for those with baseline HbA1c of 6.5-6.9 and a 10% BMI reduction and those not taking glucose-lowering drugs accompanied by a 10% BMI reduction. CONCLUSIONS: Modest weight losses of 3.0-7.9% were significantly associated with remission, but a minimum of 10% weight loss would be required in addition to an early diagnosis to achieve a 10% remission rate in clinical settings. Our results implied that remission may be expected with a relatively lower BMI in an Asian population compared with that was reported in Western populations if accompanied by weight loss.

Incidence and predictors of remission and relapse of type 2 diabetes mellitus in Japan: Analysis of a nationwide patient registry (JDDM73).

AIMS: To determine the incidence of remission and 1-year relapse from remission and associated factors in patients with type 2 diabetes. MATERIALS AND METHODS: A total of 48 320 Japanese patients with type 2 diabetes aged ≥18 years, with glycated haemoglobin (HbA1c) levels ≥48 mmol/mol (6.5%) and/or glucose-lowering drug prescription, were identified from databases of specialist clinics from 1989 and followed until September 2022. Remission was defined as HbA1c <48 mmol/mol at least 3 months after cessation of a glucose-lowering drug. Relapse was defined as failure to maintain remission for 1 year. Factors associated with remission and relapse were evaluated by logistic regression analysis. RESULTS: The overall incidence of remissions per 1000 person-years was 10.5, and for those with HbA1c levels of 48 to 53 mmol/mol (6.5% to 6.9%), those taking no glucose-lowering drugs at baseline, and those with a ≥10% body mass index (BMI) reduction in 1 year, it was 27.8, 21.7 and 48.2, respectively. Shorter duration, lower baseline HbA1c, higher baseline BMI, higher BMI reduction at 1 year, and no glucose-lowering drugs at baseline were significantly associated with remission. Among 3677 persons with remission, approximately two-thirds (2490) relapsed within 1 year. Longer duration, lower BMI at baseline, and lower BMI reduction at 1 year were significantly associated with relapse. CONCLUSIONS: The results showed that the incidence of remission and predictors of relapse, especially baseline BMI, might differ greatly between East Asian and Western populations. Furthermore, the relationships of BMI reduction with remission and relapse may be greater in East Asian than in Western populations, implying ethnic differences in returning from overt hyperglycaemia to nearly normal glucose levels.

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.

Machine Learning Approach to Drug Treatment Strategy for Diabetes Care.

Globally, the number of people with diabetes mellitus has quadrupled in the past three decades, and approximately one in 11 adults worldwide have diabetes mellitus. Since both microvascular and macrovascular diseases in patients with diabetes predispose them to a lower quality of life as well as higher rates of mortality, managing blood glucose levels is of clinical relevance in diabetes care. Many classes of antihyperglycemic drugs are currently approved to treat hyperglycemia in patients with type 2 diabetes mellitus, with several new drugs having been developed during the last decade. Diabetes-related complications have been reduced substantially worldwide. Prioritization of therapeutic agents varies according to national guidelines. However, since the characteristics of participants in clinical trials differ from patients in actual clinical practice, it is difficult to apply the results of such trials to clinical practice. Machine learning approaches became highly topical issues in medicine along with rapid technological innovations in the fields of information and communication in the 1990s. However, adopting these technologies to support decision-making regarding drug treatment strategies for diabetes care has been slow. This review summarizes data from recent studies on the choice of drugs for type 2 diabetes mellitus focusing on machine learning approaches.

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.

Effect of heat-moisture treated brown rice crackers on postprandial flow-mediated dilation in adults with mild endothelial dysfunction.

Background: Endothelial dysfunction is an early pathophysiological feature and independent predictor of a poor prognosis in most forms of cardiovascular disease. We evaluated the effect of brown rice crackers (BR-C) on endothelial function. Methods: Effect of heat-moisture treated (HMT) -BR-C on postprandial flow-mediated dilation (FMD) in adults with mild endothelial dysfunction was compared with that of BR-C and white rice crackers (WR-C) in 12 adults with mild endothelial dysfunction (less than 7.0% of FMD) by a randomized, single-blind, three-treatment three-period crossover trial (UMIN 000034898). Since we considered that the FMD increase was associated with the treatment of HMT-BR-C, we examined the effect of three possible factors: postprandial glucose levels, polyphenol content, and polyphenol release from the food matrix. Results: Mean pre-intake baseline FMD values of HMT-BR-C, BR-C, and WR-C were 4.9%, 5.1%, and 4.9%, respectively, and those values 1 h post-intake were 6.3%, 5.1%, and 4.8%, respectively. There was no difference in intergroup comparisons of FMD using Dunnett's multiple comparison test. There was a significant increase in FMD only in HMT-BR-C in intragroup comparisons (P = 0.042 by paired-t test). In comparison with BR-C, no significant difference was noted in the postprandial glucose level nor in the content of total polyphenols and ferulic acid derivatives in HMT-BR-C. However, the 70% ethanol extracted from HMT-BR-C contained a significantly larger amount of free and bound ferulic acids than from BR-C. Conclusion: HMT-BR-C intake increased the postprandial FMD response.

Association between Obesity and Intake of Different Food Groups among Japanese with Type 2 Diabetes Mellitus-Japan Diabetes Clinical Data Management Study (JDDM68).

BACKGROUND: We investigated the association between various food groups and obesity in Japanese patients with type 2 diabetes. METHODS: 2070 patients with type 2 diabetes who attended 26 diabetes clinics throughout Japan were analyzed and were divided into obese and non-obese groups. Intakes of food groups determined by a food frequency questionnaire were compared. Odds ratios for obesity for quartiles of individual food groups were calculated using a logistic regression model. RESULTS: Non-obese patients consumed a larger variety of food groups than obese patients, with the diets of non-obese individuals closer to the traditional Japanese diet characterized by fish, seaweed, and soybeans/soy products. Among 21 food groups, low vegetable intake and high sweets intake were the most strongly associated with obesity in both men and women. Low intake of both fruits and vegetables and the combination of high intake of sweets and low intake of fruits were associated with obesity. CONCLUSIONS: Food groups and their combinations that were strongly associated with obesity in Japanese patients with type 2 diabetes were identified. Our findings also suggested an inverse association between the traditional Japanese diet and obesity.