The fasting serum triglyceride levels of elderly population with different progression stages of diabetes mellitus in China

From normal population to prediabetes and diabetes: study of influencing factors and prediction models

Objective

The purpose of this study is to investigate the independent influencing factors of the transition from normal population to prediabetes, and from prediabetes to diabetes, and to further construct clinical prediction models to provide a basis for the prevention and management of prediabetes and diabetes.

Materials and methods

The data for this study were based on clinical information of participants from the Health Management Center of Peking University Shenzhen Hospital. Participants were classified into normal group, prediabetes group, and diabetes group according to their functional status of glucose metabolism. Spearman's correlation coefficients were calculated for the variables, and a matrix diagram was plotted. Further, univariate and multivariate logistic regression analysis were conducted to explore the independent influencing factors. The independent influencing factors were used as predictors to construct the full-variable prediction model (Full.model) and simplified prediction model (Simplified.model).

Results

This study included a total of 5310 subjects and 22 variables, among which there were 1593(30%) in the normal group, 3150(59.3%) in the prediabetes group, and 567(10.7%) in the diabetes group. The results of the multivariable logistic regression analysis showed that there were significant differences in 9 variables between the normal group and the prediabetes group, including age(Age), body mass index(BMI), systolic blood pressure(SBP), urinary glucose(U.GLU), urinary protein(PRO), total protein(TP), globulin(GLB), alanine aminotransferase(ALT), and high-density lipoprotein cholesterol(HDL-C). There were significant differences in 7 variables between the prediabetes group and the diabetes group, including Age, BMI, SBP, U.GLU, PRO, triglycerides(TG), and HDL.C. The Full.model and Simplified.model constructed based on the above influencing factors had moderate discriminative power in both the training set and the test set.

Conclusion

Age, BMI, SBP, U.GLU, PRO, TP, and ALT are independent risk factors, while GLB and HDL.C are independent protective factors for the development of prediabetes in the normal population. Age, BMI, SBP, U.GLU, PRO, and TG are independent risk factors, while HDL.C is an independent protective factor for the progression from prediabetes to diabetes. The Full.model and Simplified.model developed based on these influencing factors have moderate discriminative power.

Triglyceride/Glucose Index (TyG Index) as a marker of glucose status conversion among reproductive-aged women in Jakarta, Indonesia: The Bogor cohort study (2011-2016)

BACKGROUND AND AIMS

Reproductive-aged women are prone to type 2 diabetes mellitus. This study aims to evaluate the optimal cut off point of Triglyceride/Glucose Index for predicting glucose status conversion among women of reproductive age.

METHODS

This study involved normoglycemic and prediabetes women aged 20-49 years from the Bogor Non-Communicable Diseases Cohort Study (West Java, Indonesia) conducted from 2011 to 2016. Statistical analysis was performed using Receiver Operating Characteristics curve analysis with STATA version 15.

RESULTS

Among prediabetes subjects (n = 371), the cut-off point of TyG index for regression from prediabetes to normoglycemic subjects was <4.51 [sensitivity, specificity, AUC (95%CI) 83.9%, 80.1%, 0.913 (0.875-0.943), respectively] and the cut-off point for progression from prediabetes to diabetes was >4.54 [80.0%, 73.1%, 0.858 (0.807-0.900)]. Among normoglycemic subjects (n = 1300), the cut-off point of TyG index for progression to prediabetes and diabetes were >4.44 [80.1%, 71.1%, 0.834 (0.812-0.854)] and >4.47 [80.6%, 80.8%, 0.909 (0.890-0.926)] respectively.

CONCLUSION

Based on sample of subjects evaluated between 2011 and 2016, TyG index appears to be a promising marker for glucose status conversion among reproductive-aged women in Jakarta, Indonesia.

Association of adiposity with diabetes: A national research among Chinese adults

BACKGROUND

Adiposity is an established risk factor for diabetes. The different measurements of adiposity for predicting diabetes have been compared in recent studies in Western countries. However, similar researches among Chinese adults are limited.

METHODS

Data were collected from a national survey conducted during September 2014 and May 2015 Among Chinese adults aged 40 years and older across 30 China's provinces. Multilevel model analysis was performed to examine the impacts of different obesity indices [body mass index (BMI), waist circumference (WC), lipid accumulation product index (LAP), visceral adiposity index (VAI), and body adiposity index (BAI)] on the risk of diabetes.

RESULTS

A total of 162 880 participants were included in this study. Of them, 54.47% were female. With an increase in BMI, WC, LAP, VAI, and BAI, the prevalence of diabetes significantly grew (P < 0.001). The multilevel model analysis showed that WC has the strongest impact on diabetes prevalence, while BAI was the weakest. For one SD increment in BMI, WC, LAP, VAI, and BAI, the prevalence of diabetes increased by 27.0% (Odds Ratio (OR) = 1.270, 95% Confidence interval (CI) = 1.251-1.289), 37.4% (OR = 1.374, 95% CI = 1.346-1.401), 28.1% (OR = 1.281, 95% CI = 1.266-1.297), 22.0% (OR = 1.220, 95% CI = 1.204-1.236), and 17.4% (OR = 1.174, 95% CI = 1.151-1.192), respectively.

CONCLUSION

Obesity indicators of BMI, WC, LAP, VAI, and BAI have significant positive relationships with the risk of diabetes. WC has the strongest impact on diabetes, while BAI has the weakest.

Diagnostic values and appropriate cutoff points of lipid ratios in patients with abnormal glucose tolerance status: a cross-sectional study

BACKGROUND

Lipid ratios, for example total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C) and triglyceride/high-density lipoprotein cholesterol (TG/HDL-C), are associated with type 2 diabetes mellitus (T2DM). However, the predictive values of lipid ratios in prediabetes remain unclear. The aims of this study were: 1) to investigate the association between lipid ratios and abnormal glucose tolerance; 2) to compare the predictive significance of lipid ratios with commonly used indicators of lipid variables in clinical practice in a Chinese population.

METHODS

The cross-sectional study enrolled 2680 participants from the Health Promotion Center of the First Affiliated Hospital of Nanjing Medical University. All participants received a 75 g oral glucose tolerance test. Blood samples were obtained at baseline and 120 min after glucose ingestion. Participants were classified as normal glucose tolerance (NGT), impaired glucose regulation (IGR), and T2DM. The odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression model. The receiver operating characteristic (ROC) curve was used to identify the cutoff points of lipid and lipid ratios. The area under the receiver operating characteristic curve (AUROC), sensitivity and specificity were calculated to estimate their diagnostic values.

RESULTS

TC, TG, TC/HDL-C, TG/HDL-C and non-HDL-C were significantly correlated with both prediabetes and T2DM after adjustment for other risk factors such as blood glucose, whereas LDL-C was only positively correlated with prediabetes. TG and TG/HDL-C showed higher diagnostic values for prediabetes and T2DM than TC, LDL-C, HDL-C, TC/HDL-C and non-HDL-C, with the AUC values over 0.70. For predicting prediabetes, the optimal cutoff point was 1.36 mmol/l for TG and 1.13 for TG/HDL-C. For predicting T2DM, the optimal cutoff point was 1.46 mmol/l for TG and 1.22 for TG/HDL-C.

CONCLUSIONS

Both TG and TG/HDL-C are promising biomarkers for distinguishing individuals with abnormal glucose tolerance, and can be used to predict prediabetes and T2DM in Chinese population.

Intestinal microorganisms involved in colorectal cancer complicated with dyslipidosis

BACKGROUND

Abnormal lipid metabolism is considered to be one of main promoters of colorectal cancer (CRC), and intestinal microorganisms may be involved in CRC in patients with abnormal lipid metabolism.

OBJECTIVE

To investigate lipid metabolism in CRC patients and explore the role of intestinal microorganisms in CRC complicated with abnormal lipid metabolism.

METHODS

Overall, 150 CRC patients in Huzhou Central Hospital from January 2016 to September 2017 were recruited in the present study. Basic patient information and clinical serological indicators were investigated and analyzed. Twenty-one stool samples were collected from patients after receiving informed consent. Next-generation sequencing technology was used to sequence bacterial 16S ribosomal RNA. Bioinformatics analysis was used to profile the microbial composition and screen distinctive bacteria in patients with CRC complicated with abnormal lipid metabolism.

RESULTS

Apo B and FFA levels were higher in patients with stage I disease than in patients with other stages. HDL, LDL, Apo B and FFA levels were higher in female patients than in male patients. FFA level was higher in rectal cancer patients than in colon cancer patients. These differences were statistically significant (p < 0.05). The proportion of Escherichia/Shigella was increased in CRC patients with hyperlipoidaemia and hypercholesteremia; the abundance of Streptococcus was increased in CRC patients with hyperlipoidaemia; the abundance of Clostridium XIVa was reduced in CRC patients with hyperlipoidaemia and hypercholesteremia; and the abundance of Ruminococcaceae was reduced in CRC patients with hypercholesteremia. Bilophila and Butyricicoccus were closely related to CRC patients without hyperlipoidaemia or hypercholesteremia, and Selenomonas, Clostridium, Bacteroidetes Slackia, Burkholderiales and Veillonellaceae were closely related to CRC patients with hyperlipoidaemia. Some pathways, including secretion system, chaperones and folding catalysts, amino sugar and nucleotide sugar metabolism, arginine and proline metabolism, glycine, serine and threonine metabolism, histidine metabolism, pores and ion channels, nitrogen metabolism and sporulation, may be involved in lipid metabolism abnormality in CRC patients.

CONCLUSIONS

Many CRC patients have abnormal lipid metabolism, and the intestinal microbiota is altered in these CRC patients.

Analysis on influencing factors of abnormal renal function in elderly patients with type 2 diabetes mellitus

BACKGROUND

To investigate the related influencing factors of abnormal renal function in elderly in patients with type 2 diabetes mellitus (T2DM) and their clinical significance.

METHODS

The clinical data of elderly T2DM patients hospitalized in Beijing Luhe Hospital from January 2013 to June 2016 were retrospectively analyzed. According to their glomerular filtration rate (GFR) levels, these patients were divided into GFR≥90 mL/min/1.73 m2 group (group A), GFR =60-90 mL/min/1.73 m2 group (group B), and GFR <60 mL/min/1.73 m2 group (group C, i.e., abnormal renal function group). Clinical and laboratory indicators were compared among each group.

RESULTS

A total of 614 elderly T2DM patients were collected and divided into group A (N.=186), group B (N.=280) and group C (N.=148, 24.10%). Among them, patients clinically diagnosed with diabetic nephropathy (DN) accounted for 13.68%, and those complicated with high blood pressure (HBP) accounted for 61.40%. In Group C, DN accounted for only 29.73%. In elderly T2DM patients, HBP course, systolic blood pressure (SBP), diastolic blood pressure (DBP), 2h postprandial blood glucose (2hPBG), serum total cholesterol (TC) and blood uric acid (BUA) were independent influencing factors associated with abnormal renal function, among which HBP had a more significant impact on abnormal renal function. With the increase of blood pressure (BP) level, the extension in the course of DM, the increase in urinary albumin/creatinine (Alb/Cr) and the decrease in GFR, the incidence rate of abnormal renal function was increased.

CONCLUSIONS

HBP course, SBP, DBP, 2hPBG, TC and BUA are independent risk factors for abnormal renal function in elderly patients with T2DM. Well-controlled BP and blood glucose are protective factors, and a comprehensive treatment targeting to the above influencing factors has important clinical significance in preventing and delaying the occurrence and development of abnormal renal function.