BACKGROUND

There is an increasing population of elderly patients with diabetes. Malnutrition has been associated to higher morbidity and mortality among these patients. Currently, there are limited data on malnutrition and its risk factors among elderly patients with diabetes in the Philippines.

This study determined the prevalence, clinical profile and risk factors associated with malnutrition and identify the association of malnutrition with glycemic status and insulin resistance among elderly patients with diabetes.

This is a cross-sectional study involving 117 elderly patients with diabetes seen at a tertiary hospital in Manila, Philippines. Demographic, anthropometric, and clinical data were collected. Mini-Nutritional Assessment-Short form (MNA-SF), Simple FRAIL questionnaire and Mini-cog assessment were administered. Patients were categorized into normal, at risk for malnutrition, and malnourished using the MNA-SF. Comparative and logistic regression analyses were performed to identify the clinical profile and possible risk factors.

The prevalence of malnutrition was 1.71% with 29.06% at risk for malnutrition. There was no significant difference in demographic, anthropometric and biochemical parameters between the different nutrition statuses. High BMI, central obesity, and increased insulin resistance were observed across all nutrition status. Frail patients had almost five times increased likelihood (OR=4.94, p=0.043) of developing malnutrition. Good glycemic control had two-fold decreased likelihood (OR=0.44, p=0.050) of malnutrition. Insulin resistance was not associated with malnutrition.

Malnutrition is prevalent among elderly patients with diabetes. Frailty and poor glycemic control increased the risk of malnutrition. Therefore, malnutrition screening should be routinely performed among these patients. Diabetes management among elderly patients should include maintaining good glycemic control and preventing frailty and its complications.

BACKGROUND: It is crucial to understand the seasonal variation of Metabolic Syndrome (MetS) for the detection and management of MetS. Previous studies have demonstrated the seasonal variations in MetS prevalence and its markers, but their methods are not robust. To clarify the concrete seasonal variations in the MetS prevalence and its markers, we utilized a powerful method called Seasonal Trend Decomposition Procedure based on LOESS (STL) and a big dataset of health checkups. METHODS: A total of 1,819,214 records of health checkups (759,839 records for men and 1,059,375 records for women) between April 2012 and December 2017 were included in this study. We examined the seasonal variations in the MetS prevalence and its markers using 5 years and 9 months health checkup data and STL analysis. MetS markers consisted of waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG). RESULTS: We found that the MetS prevalence was high in winter and somewhat high in August. Among men, MetS prevalence was 2.64 ± 0.42 (mean ± SD) % higher in the highest month (January) than in the lowest month (June). Among women, MetS prevalence was 0.53 ± 0.24% higher in the highest month (January) than in the lowest month (June). Additionally, SBP, DBP, and HDL-C exhibited simple variations, being higher in winter and lower in summer, while WC, TG, and FPG displayed more complex variations. CONCLUSIONS This finding, complex seasonal variations of MetS prevalence, WC, TG, and FPG, could not be derived from previous studies using just the mean values in spring, summer, autumn and winter or the cosinor analysis. More attention should be paid to factors affecting seasonal variations of central obesity, dyslipidemia and insulin resistance.
Male ; Female ; Humans ; Metabolic Syndrome/epidemiology* ; Seasons ; Prevalence ; Climate ; Insulin Resistance ; Triglycerides

Objective: To compare insulin surrogate indices with the homeostasis model assessment of insulin resistance (HOMA-IR) in Thai people with type 2 diabetes (T2D). Methodology: A cross-sectional study of 97 individuals with T2D was done to determine the association between HOMA-IR and seven surrogate indices for insulin resistance. IR was defined as HOMA-IR ≥2.0. The indices included Waist Circumference (WC), Waist-to-Hip Ratio (WHR), Waist-to-Height Ratio (WHtR), Triglyceride-Glucose (TyG) index, estimated Glucose Disposal Rate (eGDR) calculated by WC, BMI, and WHR. Results: A total of 97 subjects with T2D (36.1% female, mean age 61.7 ± 12.0 years, BMI 26.4 ± 3.7 kg/m2, A1C 6.9 ± 1.2%) were studied. The TyG index showed a positive association with HOMA-IR, while eGDR exhibited a negative association. TyG index had the strongest correlation with IR (r = 0.49), while various eGDR formulas showed weaker negative correlations (r = 0.12-0.25). However, subgroup analysis in individuals with T2D and coronary artery disease (CAD) showed that only eGDR-WC and eGDR-BMI demonstrated a significant correlation with triple vessel disease. Conclusion The TyG index was a useful and simple marker for identifying the presence of IR in Thai people with T2D. Future longitudinal studies are warranted to demonstrate the prediction value of cardiovascular outcomes.
Insulin Resistance ; Surrogate Markers ; Biomarkers

OBJECTIVES

Pre-impaired glucose tolerance (pre-IGT) is a prediabetes stage characterized by normoglycemia and compensatory hyperinsulinemia due to insulin resistance. Hyperinsulinemia increases cardiovascular disease (CVD) risk, especially, endothelial dysfunction (ED). However, there is paucity of studies on ED with hyperinsulinemia alone, particularly in individuals with pre-IGT. This study aimed to determine the presence of ED using brachial artery flow-mediated dilatation (FMD) among adult participants with pre-IGT and its correlation with insulin levels and other related clinical parameters.

This is a cross-sectional analytical study. We screened adult patients with risk factors for developing diabetes (first-degree relative with type 2 diabetes mellitus, obesity, history of gestational diabetes and polycystic ovary syndrome). Brachial artery FMD was performed among participants with pre-IGT and findings were correlated with CVD risk factors using Pearson’s correlation and linear regression.

Of the 23 pre-IGT patients, 5 (21.74%) had decreased FMD values with significant associations with serum insulin and HbA1c. It was further observed that for every 1-unit increase in second-hour serum insulin and in HbA1c, there was a decrease in FMD values by 0.38% and 0.50%, respectively. Serum insulin was elevated, while other biochemical parameters were normal. Moreover, participants with low FMD were older, with higher BMI and had higher HBA1c, total cholesterol and low-density lipoprotein (LDL) cholesterol.

As early as the pre-IGT stage, endothelial dysfunction using the FMD test is already present, with red flags on other CVD risk factors already developing.

Objective To explore the roles of different insulin resistance indexes[triglyceride-glucose (TyG),triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C),and metabolic score for insulin resistance (METS-IR)]and combinations of two indexes in predicting diabetes risk in hypertensive population. Methods The survey of hypertension was conducted for the residents in Wuyuan county,Jiangxi province from March to August in 2018.The basic information of hypertensive residents was collected by interview.Blood was drawn on an empty stomach in the morning and physical measurements were carried out.Logistic regression model was employed to analyze the relationship between different insulin resistance indexes and diabetes,and the area under the receiver operating characteristic curve was used for evaluating the predictive effects of each index on diabetes risk. Results A total of 14 222 hypertensive patients with an average age of (63.8±9.4) years old were included in this study,including 2616 diabetic patients.The diabetic hypertensive population had higher TyG (t=50.323,P<0.001),TG/HDL-C (Z=17.325,P<0.001),and METS-IR (t=28.839,P<0.001) than the non-diabetic hypertensive population.Multivariate analysis showed that each insulin resistance index was positively correlated with diabetes risk.The area under curve of each insulin index was in a descending order of TyG (0.770)> METS-IR (0.673)> TG/HDL-C (0.620).The difference in the area under curve between two indexes was statistically significant[TyG vs.TG/HDL-C (Z=42.325,P<0.001);TyG vs.METS-IR(Z=17.517,P<0.001);METS-IR vs.TG/HDL-C (Z=10.502,P<0.001)]. Conclusions Elevated insulin resistance indexes can increase the risk of diabetes.TyG and the combination of indexes outperform TG/HDL-C and METS-IR in the prediction of diabetes.
Humans ; Middle Aged ; Aged ; Insulin Resistance ; Blood Glucose/metabolism* ; Biomarkers ; Diabetes Mellitus ; Hypertension ; Glucose ; Triglycerides ; Cholesterol, HDL

Objective To explore the relationship between insulin resistance (IR) indexes and hyperuricemia (HUA) among the people with hypertension. Methods From July to August in 2018,hypertension screening was carried out in Wuyuan county,Jiangxi province,and the data were collected through questionnaire survey,physical measurement,and biochemical test.Logistic regression was performed to analyze the relationship between HUA and IR indexes including metabolic score for IR (METS-IR),triglyceride-glucose (TyG) index,TyG-body mass index (BMI),TyG-waist circumference (WC),visceral adiposity index (VAI),triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C),and lipid accumulation product (LAP).The penalty spline method was used for the curve fitting between IR indexes and HUA.The area under the receiver operating characteristic curve (AUC) was employed to reveal the correlation between each index and HUA. Results The 14 220 hypertension patients included 6 713 males and 7 507 females,with the average age of (63.8±9.4) years old,the average uric acid level of (418.9±120.6) mmol/L,and the HUA detection rate of 44.4%.The HUA group had higher proportions of males,current drinking,current smoking,diabetes,and using antihypertensive drugs,older age,higher diastolic blood pressure,WC,BMI,homocysteine,total cholesterol,TG,low-density lipoprotein cholesterol,blood urea nitrogen,creatinine,aspartate aminotransferase,alanine aminotransferase,total protein,albumin,total bilirubin,direct bilirubin, METS-IR, TyG, TyG-BMI, TyG-WC, VAI, TG/HDL-C, and LAP, and lower systolic blood pressure and HDL-C than the normal uric acid group (all P<0.05).Multivariate Logistic regression showed that METS-IR (OR=1.049,95%CI=1.038-1.060, P<0.001), TyG (OR=1.639,95%CI=1.496-1.797, P<0.001), TyG-BMI (OR=1.008,95%CI=1.006-1.010, P<0.001), TyG-WC (OR=1.003,95%CI=1.002-1.004, P<0.001), lnVAI (OR=1.850, 95%CI=1.735-1.973, P<0.001), ln(TG/HDL-C) (OR=1.862,95%CI=1.692-2.048, P<0.001),and lnLAP (OR=1.503,95%CI=1.401-1.613,P<0.001) were associated with the risk of HUA.Curve fitting indicated that METS-IR,TyG,TYG-BMI,TYG-WC,lnVAI,ln(TG/HDL-C),and lnLAP were positively correlated with HUA (all P<0.001),and the AUC of TyG index was higher than that of other IR indexes (all P<0.05). Conclusion Increased IR indexes,especially TyG,were associated with the risk of HUA among people with hypertension.
Male ; Female ; Humans ; Middle Aged ; Aged ; Insulin Resistance ; Hyperuricemia ; Uric Acid ; Hypertension/complications* ; Glucose ; Obesity, Abdominal/epidemiology* ; Triglycerides ; Bilirubin ; Cholesterol ; Blood Glucose/metabolism*

This study aimed to explore the effects and mechanisms of total flavones of Abelmoschus manihot(TFA), the extracts from traditional Chinese medicine indicated for kidney diseases, on insulin resistance(IR) and podocyte epithelial-mesenchymal transition(EMT) in diabetic kidney disease(DKD), and further to reveal the scientific connotation. Thirty-two rats were randomly divided into a normal group, a model group, a TFA group, and a rosiglitazone(ROS) group. The modified DKD model was induced in rats by methods including high-fat diet feeding, unilateral nephrectomy, and streptozotocin(STZ) intraperitoneal injection. After modeling, the rats in the four groups were given double-distilled water, TFA suspension, and ROS suspension correspondingly by gavage every day. At the end of the 8th week of drug administration, all rats were sacrificed, and the samples of urine, blood, and kidney tissues were collected. The parameters and indicators related to IR and podocyte EMT in the DKD model rats were examined and observed, including the general condition, body weight(BW) and kidney weight(KW), the biochemical parameters and IR indicators, the protein expression levels of the key signaling molecules and structural molecules of slit diaphragm in the renal insulin receptor substrate(IRS) 1/phosphatidylinositol 3-kinase(PI3K)/serine-threonine kinase(Akt) pathway, foot process form and glomerular basement membrane(GBM) thickness, the expression of the marked molecules and structural molecules of slit diaphragm in podocyte EMT, and glomerular histomorphological characteristics. The results showed that for the DKD model rats, both TFA and ROS could improve the general condition, some biochemical parameters, renal appearance, and KW. The ameliorative effects of TFA and ROS were equivalent on BW, urinary albumin(UAlb)/urinary creatinine(UCr), serum creatinine(Scr), triglyceride(TG), and KW. Secondly, they could both improve IR indicators, and ROS was superior to TFA in improving fast insulin(FIN) and homeostasis model assessment of insulin resistance(HOMA-IR). Thirdly, they could both improve the protein expression levels of the key signaling molecules in the IRS1/PI3K/Akt pathway and glomerulosclerosis in varying degrees, and their ameliorative effects were similar. Finally, both could improve podocyte injury and EMT, and TFA was superior to ROS. In conclusion, this study suggested that podocyte EMT and glomerulosclerosis could be induced by IR and the decreased activation of the IRS1/PI3K/Akt pathway in the kidney in DKD. Similar to ROS, the effects of TFA in inhibiting podocyte EMT in DKD were related to inducing the activation of the IRS1/PI3K/Akt pathway and improving IR, which could be one of the scientific connotations of TFA against DKD. This study provides preliminary pharmacological evidence for the development and application of TFA in the field of diabetic complications.
Rats ; Animals ; Diabetic Nephropathies/drug therapy* ; Proto-Oncogene Proteins c-akt/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Abelmoschus/chemistry* ; Podocytes ; Rats, Sprague-Dawley ; Epithelial-Mesenchymal Transition ; Flavones/pharmacology* ; Insulin Resistance ; Reactive Oxygen Species ; Diabetes Mellitus

Schisandra chinensis, a traditional Chinese medicinal herb, is rich in chemical constituents, including lignans, triterpenes, polysaccharides, and volatile oils. Clinically, it is commonly used to treat cardiovascular, cerebrovascular, liver, gastrointestinal, and respiratory diseases. Modern pharmacological studies have shown that S. chinensis extract and monomers have multiple pharmacological activities in lowering liver fat, alleviating insulin resistance, and resisting oxidative stress, and have good application prospects in alleviating nonalcoholic fatty liver disease(NAFLD). Therefore, this study reviewed the research progress on chemical constituents of S. chinensis and its effect on NAFLD in recent years to provide references for the research on S. chinensis in the treatment of NAFLD.
Non-alcoholic Fatty Liver Disease ; Schisandra ; Insulin Resistance ; Lignans

Ten alkaloids(1-10) were isolated from the ethyl acetate extract of the fruit of Lycium chinense var. potaninii by silica gel, ODS, and preparative high performance liquid chromatography(HPLC), and identified by NMR and MS as methyl(2S)-[2-formyl-5-(hydroxymethyl)-1H-pyrrol-1-yl]-3-(phenyl)propanoate(1), methyl(2R)-[2-formyl-5-(methoxymethyl)-1H-pyrrol-1-yl]-3-(phenyl)propanoate(2), 3-hydroxy-4-ethyl ketone pyridine(3), indolyl-3-carbaldehyde(4),(R)-4-isobutyl-3-oxo-3,4-dihydro-1H-pyrrolo[2,1-c][1,4]oxazine-6-carbaldehyde(5),(R)-4-isopropyl-3-oxo-3,4-dihydro-1H-pyrrolo[2,1-c][1,4]oxazine-6-car-baldehyde(6), methyl(2R)-[2-formyl-5-(methoxymethyl)-1H-pyrrol-1-yl]-3-(4-hydroxyphenyl)propanoate(7), dimethyl(2R)-[2-formyl-5-(methoxymethyl)-1H-pyrrol-1-yl]butanedioate(8), 4-[formyl-5-(methoxymethyl)-1H-pyrrol-1-yl]butanoate(9), 4-[2-formyl-5-(methoxymethyl)-1H-pyrrol-1-yl]butanoic acid(10). All the compounds were isolated from the plant for the first time. Among them, compounds 1-3 were new compounds. Compounds 1-9 were evaluated for hypoglycemic activity in vitro with the palmitic acid-induced insulin resistance in HepG2 cells. At 10 μmol·L~(-1), compounds 4, 6, 7, and 9 can promote the glucose consumption of HepG2 cells with insulin resistance.
Lycium/chemistry* ; Fruit/chemistry* ; Insulin Resistance ; Propionates ; Alkaloids/pharmacology*

Most information used to evaluate diabetic statuses is collected at a special time-point, such as taking fasting plasma glucose test and providing a limited view of individual's health and disease risk. As a new parameter for continuously evaluating personal clinical statuses, the newly developed technique "continuous glucose monitoring" (CGM) can characterize glucose dynamics. By calculating the complexity of glucose time series index (CGI) with refined composite multi-scale entropy analysis of the CGM data, the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes (P for trend < 0.01). Furthermore, CGI was significantly associated with various parameters such as insulin sensitivity/secretion (all P < 0.01), and multiple linear stepwise regression showed that the disposition index, which reflects β-cell function after adjusting for insulin sensitivity, was the only independent factor correlated with CGI (P < 0.01). Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.
Humans ; Glucose ; Blood Glucose ; Insulin Resistance/physiology* ; Diabetes Mellitus, Type 2/diagnosis* ; Blood Glucose Self-Monitoring ; Time Factors ; Insulin