Independent and interactive associations of heart rate and body mass index or blood pressure with type 2 diabetes mellitus incidence: A prospective cohort study

Independent and interactive associations of heart rate and obesity with type 2 diabetes mellites: A population-based study

BACKGROUND

Although obesity and heart rate (HR) were closely related to the prevalence and development of type 2 diabetes mllitus (T2DM), few studies have shown a co-association effect of them on T2DM. We aimed at assessing the interactive effects of HR and obesity with prevalence of T2DM in Chinese population, providing the exact cutpoint of the risk threshold for blood glucose with high HR.

MATERIALS AND METHODS

In the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal study (REACTION) cohorts (N = 8398), the relationship between HR and T2DM was explored by linear regression, logistic regression, and restricted cubic spline, and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Interaction terms between HR and body mass index (BMI) and HR and waist circumference (WC) were introduced into the logistic regression model.

RESULTS

In those with HR > 88.0 beats/min, fasting plasma glucose and oral glucose tolerance tests were significantly correlated with HR, and the prevalence of T2DM was highly correlated with HR (all p < .05). There were interactive associations of HR and obesity in patients with T2DM with HR < 74 beats/min.

CONCLUSION

High HR was in interaction with obesity, associating with prevalence of T2DM. The newly subdivided risk threshold for HR with T2DM might be HR > 88 beats/minute.

Diabetes mellitus early warning and factor analysis using ensemble Bayesian networks with SMOTE-ENN and Boruta

Diabetes mellitus (DM) has become the third chronic non-infectious disease affecting patients after tumor, cardiovascular and cerebrovascular diseases, becoming one of the major public health issues worldwide. Detection of early warning risk factors for DM is key to the prevention of DM, which has been the focus of some previous studies. Therefore, from the perspective of residents' self-management and prevention, this study constructed Bayesian networks (BNs) combining feature screening and multiple resampling techniques for DM monitoring data with a class imbalance in Shanxi Province, China, to detect risk factors in chronic disease monitoring programs and predict the risk of DM. First, univariate analysis and Boruta feature selection algorithm were employed to conduct the preliminary screening of all included risk factors. Then, three resampling techniques, SMOTE, Borderline-SMOTE (BL-SMOTE) and SMOTE-ENN, were adopted to deal with data imbalance. Finally, BNs developed by three algorithms (Tabu, Hill-climbing and MMHC) were constructed using the processed data to find the warning factors that strongly correlate with DM. The results showed that the accuracy of DM classification is significantly improved by the BNs constructed by processed data. In particular, the BNs combined with the SMOTE-ENN resampling improved the most, and the BNs constructed by the Tabu algorithm obtained the best classification performance compared with the hill-climbing and MMHC algorithms. The best-performing joint Boruta-SMOTE-ENN-Tabu model showed that the risk factors of DM included family history, age, central obesity, hyperlipidemia, salt reduction, occupation, heart rate, and BMI.

Association between initial in-hospital heart rate and glycemic control in patients with acute ischemic stroke and diabetes mellitus

BACKGROUND

A high resting heart rate (HR) has been associated with an increased risk of diabetes mellitus. This study explored the association between initial in-hospital HR and glycemic control in patients with acute ischemic stroke (AIS) and diabetes mellitus.

METHODS

We analyzed data from 4,715 patients with AIS and type 2 diabetes mellitus enrolled in the Chang Gung Research Database between January 2010 and September 2018. The study outcome was unfavorable glycemic control, defined as glycated hemoglobin (HbA1c) ≥ 7%. In statistical analyses, the mean initial in-hospital HR was used as both a continuous and categorical variable. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression analysis. The associations between the HR subgroups and HbA1c levels were analyzed using a generalized linear model.

RESULTS

Compared with the reference group (HR < 60 bpm), the adjusted ORs for unfavorable glycemic control were 1.093 (95% CI 0.786-1.519) for an HR of 60-69 bpm, 1.370 (95% CI 0.991-1.892) for an HR of 70-79 bpm, and 1.608 (95% CI 1.145-2.257) for an HR of ≥ 80 bpm. Even after adjusting for possible confounders, the HbA1c levels after admission and discharge among diabetic stroke patients increased significantly in the subgroups with higher HRs (p < 0.001).

CONCLUSIONS

High initial in-hospital HR is associated with unfavorable glycemic control in patients with AIS and diabetes mellitus, particularly in those with an HR of ≥ 80 bpm, compared with those with an HR of < 60 bpm.

Downregulation of ALDH6A1 is a New Marker of Muscle Insulin Resistance in Type 2 Diabetes Mellitus

Purpose

Skeletal muscle insulin resistance (IR) is an important etiology of type 2 diabetes mellitus (T2DM); however, its molecular mechanism is yet to be fully defined. This study attempted to identify the gene expression patterns and molecular disorders in T2DM patients’ skeletal muscle samples.

Methods

First, the difference in genetic expression among GSE25462 data was analyzed. Next, PPI network analysis of differential genes was carried out, after which the maladjustment module was identified. Then, an enrichment analysis and gene set enrichment analysis (GSEA) were carried out. Finally, the transcription factors that regulate the modular genes by raid were predicted.

Results

Most differentially expressed genes were found to be able to form an interaction network and cluster into 9 modules. These modular genes were shown to possess a significant correlation with immune inflammation and metabolic response. Importantly, the top 15 genes of area under receiver operating characteristic curve (AUC) were identified, and the expression of 10 genes by GSE12643, GSE18732 and GSE29221 was confirmed. The expression and AUC value of ALDH6A1 were then verified according to three sets of data, where ALDH6A1 was found to be negatively correlated with follicular helper T cells. However, among the predicted transcription regulators, HDAC was shown to have a better regulatory effect.

Conclusion

The findings highlight that the dysregulation of ALDH6A1 expression in IR of T2DM may serve as a potential therapeutic target. ALDH6A1 is involved in the immune inflammation and metabolic pathways.

Salidroside Affects Gut Microbiota Structure in db/db Mice by Affecting Insulin, Blood Glucose and Body Weight

PURPOSE

The purpose of this study was to investigate the regulatory effect of salidroside on the intestinal flora of mice with type 2 diabetes (T2DM) and its protective effect in the body.

PATIENTS AND METHODS

We acclimated 8-week-old mice for 7 days, divided them into 4 groups, and continued dosing for 8 weeks. We recorded weekly blood glucose levels and body weight for each mouse. After the completion of the feeding cycle, the 16S rRNA of the intestinal flora in the mice was sequenced, and the insulin and C-peptide levels in each group of mice were measured. Four samples were taken from each group for liver and kidney section staining.

RESULTS

Our results showed that gut microbiota diversity and function were significantly different between the diabetic mice and healthy mice and that insulin levels, body weight, and blood glucose levels could significantly influence gut microbiota changes at the genus level. The gut microbiota diversity and function of db/db mice were also altered after salidroside administration. Salidroside could attenuate inflammatory damage, lipid accumulation and inflammatory changes in the diabetic liver, as well as diabetic kidney damage. Candidatus arthromitus and Odoribacter are important species of the microbiota during diabetes and may serve as potential therapeutic targets.

CONCLUSION

Our investigation of the associated pathological conditions and fecal microbiota in db/db mice provides new insights into the pathogenesis of T2DM and provides implications for the diagnosis and treatment of T2DM.

The causal association between body mass index and type 2 diabetes mellitus-evidence based on regression discontinuity design

OBJECTIVE

This study aimed to investigate and determine the precise causal association between body mass index (BMI) and type 2 diabetes mellitus (T2DM) using a regression discontinuity design (RDD).

METHODS

The cross-sectional data of 8550 participants were from the China Health and Nutrition Survey (CHNS) in 2015. Influencing factors with statistically significant were selected with logistic regression analysis, and a risk prediction model was established to obtain the risk of individuals suffering from T2DM. RDD was performed with BMI as the grouping variable and the risk of individuals suffering from T2DM as the outcome variable.

RESULTS

The predictive factors in the T2DM risk prediction model were age, gender, BMI, habitation, education, physical activity level, preference for sugary beverages, walking, self-evaluation health status and history of hypertension. The AUC (area under receiver operating characteristic curve) of the T2DM risk prediction model was 0.849 (95% CI: 0.833, 0.866). BMI was an independent risk factor for T2DM (OR = 1.109, p < 0.001); at BMI = 31 kg/m² , the risk of T2DM increased sharply by 5.03% (p = 0.006).

CONCLUSIONS

There was a positive causal association between BMI and T2DM; when BMI = 31 kg/m² , the risk of individuals suffering from T2DM was sharply increased.

Dependence of Heart Rate Variability Indices on the Mean Heart Rate in Women with Well-Controlled Type 2 Diabetes

Heart rate variability (HRV) is a method used to evaluate the presence of cardiac autonomic neuropathy (CAN) because it is usually attributed to oscillations in cardiac autonomic nerve activity. Recent studies in other pathologies suggest that HRV indices are strongly related to mean heart rate, and this does not depend on autonomic activity only. This study aimed to evaluate the correlation between the mean heart rate and the HRV indices in women patients with well-controlled T2DM and a control group. HRV was evaluated in 19 T2DM women and 44 healthy women during basal supine position and two maneuvers: active standing and rhythmic breathing. Time-domain (SDNN, RMSSD, pNN20) and frequency-domain (LF, HF, LF/HF) indices were obtained. Our results show that meanNN, age, and the maneuvers are the main predictors of most HRV indices, while the diabetic condition was a predictor only for pNN20. Given the known reduced HRV in patients with T2DM, it is clinically important that much of the HRV indices are dependent on heart rate irrespective of the presence of T2DM. Moreover, the multiple regression analyses evidenced the multifactorial etiology of HRV.

[Bivariate heritability estimation of resting heart rate and common chronic disease based on extended pedigrees]

OBJECTIVE

To estimate the univariate heritability of resting heart rate and common chronic disease such as hypertension, diabetes, and dyslipidemia based on extended pedigrees in Fujian Tulou area and to explore bivariate heritability to test for the genetic correlation between resting heart rate and other relative phenotypes.

METHODS

The study was conducted in Tulou area of Nanjing County, Fujian Province from August 2015 to December 2017. The participants were residents with Zhang surname and their relatives from Taxia Village, Qujiang Village, and Nanou Village or residents with Chen surname and their relatives from Caoban Village, Tumei Village, and Beiling Village. The baseline survey recruited 1 563 family members from 452 extended pedigrees. The pedigree reconstruction was based on the family information registration and the genealogy booklet. Univariate and bivariate heritability was estimated using variance component models for continuous variables, and susceptibility-threshold model for binary variables.

RESULTS

The pedigree reconstruction identified 1 seven-generation pedigree, 2 five-generation pedigrees, 23 four-generation pedigrees, 186 three-generation pedigrees, and 240 two-generation pedigrees. The mean age of the participants was 57.2 years and the males accounted for 39.4%. The prevalence of hypertension, diabetes, dyslipidemia in this population was 49.2%, 10.0%, and 45.2%, respectively. The univariate heritability estimation of resting heart rate, hypertension, and dyslipidemia was 0.263 (95%CI: 0.120－0.407), 0.404 (95%CI: 0.135－0.673), and 0.799 (95%CI: 0.590－1), respectively. The heritability of systolic blood pressure, diastolic blood pressure, fasting glucose, total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol was 0.379, 0.306, 0.393, 0.452, 0.568, 0.852, and 0.387, respectively. In bivariate analysis, there were phenotypic correlations between resting heart rate with hypertension, diabetes, diastolic blood pressure, fasting glucose, and triglyceride. After taking resting heart rate into account, there were strong genetic correlations between resting heart rate with fasting glucose (genetic correlation 0.485, 95%CI: 0.120－1, P<0.05) and diabetes (genetic correlation 0.795, 95%CI: 0.181－0.788, P<0.05).

CONCLUSION

Resting heart rate was a heritable trait and correlated with several common chronic diseases and related traits. There was strong genetic correlation between resting heart rate with fasting glucose and diabetes, suggesting that they may share common genetic risk factors.

Abnormal Glucose Metabolism and Associated Risk Factors Among Adults in Mekelle City, Ethiopia

BACKGROUND

In the past decade, the prevalence of diabetes has grown more rapidly in low- and middle-income countries than in high-income countries. In 2019, Ethiopia is the fourth highest contributor to cases with diabetes in Africa with 1.7 million total cases. The present study was aimed to determine the prevalence of abnormal glucose metabolism and associated factors in Mekelle city, Northern Ethiopia.

METHODS AND MATERIALS

Community-based cross-sectional study was conducted among 321 randomly selected participants aged 20 years and above. Sociodemographic, lifestyle, clinical, and anthropometric data were collected in accordance with the STEPwise approach as recommended by the World Health Organization (WHO) for non-communicable disease (NCDs) surveillance. Blood glucose and lipid profiles were determined using a fasting venous blood sample. Bivariate and multivariable logistic regression analysis was used to identify factors associated with abnormal glucose metabolism. The level of statistical significance was set at p ≤0.05.

RESULTS

More than half (54.8%) of the participants were women with an overall mean (±SD) age of 39.0 (±14.2) years. The overall prevalence of pre-diabetes and diabetes was 12.5% and 9.3%, respectively, with a mean (±SD) fasting blood glucose of 97.42 (±38.03) mg/dL. More than two-thirds (70.0%) of adults with diabetes were not aware of being diabetes. Advanced age, hypercholesterolemia, medium and high rank of heart rate, and raised waist to height ratio were significantly associated with a higher risk of pre-diabetes, whereas having house servant, systolic hypertension, and hypercholesterolemia were significantly associated with diabetes.

CONCLUSION

We found a high prevalence of prediabetes and diabetes with more than two-thirds (70.0%) of newly diagnosed adults with diabetes, which showed a lack of awareness in the community. Awareness creation together with access to basic diagnostics in the primary health-care settings should therefore be a top priority to prevent its progression and complication.