Waist circumference is associated with major adverse cardiovascular events in male but not female patients with type-2 diabetes mellitus

Glycemic variability evaluated by HbA1c rather than fasting plasma glucose is associated with adverse cardiovascular events

Background

Although studies have shown that glycemic variability is positively associated with an increased risk of cardiovascular disease, few studies have compared hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG) variability with adverse cardiovascular events in patients with type 2 diabetes mellitus (T2DM).

Methods

This was a post hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study. Cox proportional hazards models were used to explore the relationship between HbA1c or FPG variability and the incidence of major adverse cardiovascular events (MACEs).

Results

In total, 9,547 patients with T2DM were enrolled in this study. During the median 4.6 ± 1.5 years follow-up period, 907 patients developed MACEs. The risk of MACEs increased in the HbA1c variability group in each higher quartile of HbA1c variability (P < 0.01). Compared with those in the first quartile of HbA1c variability, patients in the fourth quartile had a hazard ratio of 1.37 (Model 2, 95% confidence interval: 1.13-1.67) for MACEs. Higher FPG variability was not associated with a higher risk of MACEs in patients with T2DM (P for trend=0.28). A U-shaped relationship was observed between HbA1c and FPG variability, and MACEs. Glucose control therapy modified the relationship between HbA1c and MACEs; participants with higher HbA1c variability receiving intensive glucose control were more likely to develop MACEs (P for interaction <0.01).

Conclusion

In adults with T2DM, the relationship between glycemic variability evaluated using HbA1c and FPG was U-shaped, and an increase in HbA1c variability rather than FPG variability was significantly associated with MACEs. The relationship between HbA1c variability and MACEs was affected by the glucose control strategy, and a higher HbA1c variability was more strongly associated with MACEs in patients receiving an intensive glucose control strategy.

Predicted lean body mass, fat mass, and heart failure in patients with type 2 diabetes mellitus

BACKGROUND

High body mass index (BMI) is associated with a higher risk of heart failure (HF) in patients with new-onset type 2 diabetes mellitus (T2DM). However, limited studies have investigated the independent association between fat mass or lean body mass and HF risk among T2DM patients with cardiovascular disease (CVD) or high CVD risk.

OBJECTIVES

To investigate the association between fat mass index (FMI, kg/m²) or lean BMI (LBMI, kg/m²) and HF risk.

METHODS

This was a post hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study. Cox proportional-hazards models were applied to evaluate the association of FMI, LBMI, and BMI with HF risk. Discordant analysis was performed to compare the magnitude of this associations.

RESULTS

HF occurred in 356 participants (3.7%). After adjusting for confounding factors, higher FMI values were independently associated with HF risk (HR: 1.72, 95% CI: 1.15-2.57, each 1 SD increase in FMI); LBMI was a protective risk factor for HF (HR: 0.58, 95% CI: 0.38-0.87,). After further adjusting for FMI, the association between BMI and HF risk (HR, 0.97; 95% CI, 0.67-1.42) disappeared. Compared with concordant values below the medians, discordant FMI above the median with BMI below yielded an HR of 1.78 (95% CI: 1.14-2.78) for HF. In contrast, BMI above the median with FMI below was not associated with HF risk (HR: 1.09, 95% CI: 0.57-2.09).

CONCLUSIONS

The risk of HF conferred by higher BMI was primarily driven by the association between FMI and HF. After adjusting for BMI, LBMI played a protective role.

Neck circumference for predicting the occurrence of future cardiovascular events: A 7.6-year longitudinal study

BACKGROUND & AIMS

This study aimed to investigate whether neck circumference (NC) could be used to predict future cardiovascular (CV) events in a community-based Chinese cohort.

METHODS AND RESULTS

We enrolled 1435 participants aged 50-80 years (men, 43.62%) from communities in Shanghai. High NC was defined as NC ≥ 38.5 cm in men and NC ≥ 34.5 cm in women. Kaplan-Meier analysis and Cox proportional hazards regression were performed to explore the association between NC and CV events. During a mean follow-up period of 7.6 years, 148 CV events (10.31%) occurred. The incidence of CV events was higher in men than in women (83 (13.26%) vs. 65 (8.03%), P = 0.002). Multivariable-adjusted Cox regression analysis showed that for every 1-SD increase in NC in the whole population, the hazard ratio (HR) of CV events was 1.45 (95% confidence interval [CI], 1.15-1.83). The dose-response association between NC and CV events was significant in men (HR, 1.37, 95% CI, 1.10-1.71) but not in women (HR, 1.19, 95% CI, 0.94-1.52). In comparison with participants showing low baseline NC, those with high baseline NC showed a significantly higher risk of CV events (HR, 1.59, 95% CI, 1.14-2.22). Further stratified by sex, the positive association remained significant in men (HR, 1.90, 95% CI, 1.21-2.98) but not in women (HR, 1.25, 95% CI, 0.75-2.07).

CONCLUSION

NC was significantly associated with the risk of future CV events in middle-aged and elderly populations in the community and was a better predictor in men.

Effect of Dietary-Based Lifestyle Modification Approaches on Anthropometric Indices and Dietary Intake Parameters in Women with Breast Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

This systematic review and meta-analysis aimed to investigate the effect of dietary-based lifestyle modification interventions ("diet," or "diet + exercise," or "diet + exercise + behavioral" intervention) on the measures of anthropometric and dietary intake parameters in women with breas cancer (BC). Databases were searched until June 2021. Inclusion criteria were randomized controlled trials that enrolled only women with BC. Studies that used exercise or behavioral interventions alone were not included. Mean ± SD changes were extracted for each outcome, and pooled using a random-effects model; 7315 studies were identified. Fifty-one studies (n = 7743) were included. The median ± SD duration of treatment was 24 ± 16.65 wk. Dietary-based interventions significantly reduced body weight [45 studies (n = 7239), weighted mean difference (WMD) (95% CI): -2.6 (-3.2, -2.1) kg], BMI [31 studies (n = 5384); WMD (95% CI): -1.0 (-1.3, -0.7) kg/m2], lean body mass [15 studies (n = 1194); WMD (95% CI): -0.6(-0.7, -0.4) kg], fat mass [11 studies (n = 913); WMD (95% CI): -2.6 (-3.3, -1.8) kg], fat percentage [17 studies (n = 897); WMD (95% CI): -1.5 (-1.9, -1.3)%], hip circumference [9 studies (n = 489); WMD (95% CI): -2.43 (-3.34, -1.54) cm], and waist circumference [7 studies (n = 309); WMD (95% CI): 0.02 (-0.03, -0.005) cm]. Significant reductions in energy intakes [20 studies (n = 4608), WMD (95% CI): -162 (-220, 104) kcal/d] and fat intakes [7 studies (n = 4316), WMD (95% CI): -7.5 (-7.8, -7.2)% of energy/d], and an increase in fiber intakes [11 studies (n = 4241), WMD (95% CI): 2.4 (0.7, 4.1) g/d] were observed. No significant changes were seen in protein, carbohydrate, and fruit and vegetable intakes. Subgroup analyses showed that changes in anthropometric and dietary intake indices were significant in studies that enrolled patients with both obesity and normal weight, studies that used diet therapy in combination with exercise and behavioral therapy, and studies that started the intervention during the treatment period. Overall, a multimodal dietary-based lifestyle intervention had significant effects on anthropometric and dietary intake parameters in women with BC, specifically when started as early as the diagnosis. This meta-analysis was registered at PROSPERO as CRD42021291488.

Risk for Cardiovascular Death Associated With Waist Circumference and Diabetes: A 9-Year Prospective Study in the Wan Shou Lu Cohort

Background

It has been reported that obesity and diabetes are both risk factors for the development of cardiovascular diseases (CVDs). However, recent articles reported that compared with body mass index, waist circumference (WC) can better reflect obesity, more closely related to visceral fat tissue which is positively associated with an increased risk of cardiovascular death. Moreover, few studies have investigated the prognostic value of both WC and diabetes during a long-term follow-up. We aimed to investigate whether the higher level of WC measurements and diabetes were able to predict cardiovascular mortality in the general population.

Methods

In this prospective cohort study, a total of 1,521 consecutive subjects free of clinical CVD were included. The endpoint was cardiovascular death. The Kaplan–Meier method and Cox regression models were used to evaluate the cumulative risk of the outcome at different WC levels with or without diabetes.

Results

During a median follow-up of 9.2 years, 265 patients died due to cardiovascular conditions. Kaplan–Meier survival estimates indicated that the patients with higher levels of WC (WC &gt; 94 cm) coexisted with diabetes had a significantly increased risk of cardiovascular death (log-rank p &lt; 0.05). After adjustment for potential confounders, multiple COX regression models showed that the incidence of cardiovascular death was significantly higher when patients with high WC coexisted with diabetes mellitus (hazard ratio: 3.78; 95% CI: 3.35–3.98; p &lt; 0.001).

Conclusion

Patients with high WC and diabetes represent a high-risk population for cardiovascular death. WC and diabetes may provide incremental prognostic value beyond traditional risks factors.

Prevalence of overweight and obesity amongst patients with diabetes and their non-diabetic family members in Senwabarwana, Limpopo province, South Africa

Background

Diabetes remains a public health concern and the second cause of mortality in South Africa. Family history of diabetes increases risk of developing diabetes. Obesity amongst patients is associated with comorbidity, whilst amongst non-diabetic family members it is associated with developing diabetes. This study aimed at determining prevalence of overweight and obesity amongst patients with diabetes and non-diabetic family members.

Methods

A quantitative, cross-sectional descriptive study was conducted on 200 patients and 200 non-diabetic family members were selected using systematic random sampling from rural clinics of Senwabarwana. Data were collected using close-ended questionnaires and anthropometric measurements. Body mass index (BMI) and waist circumference were measured and interpreted according to World Health Organization guidelines. Data were analysed using Statistical Package for Social Sciences, using both descriptive and inferential statistics. Chi-square test was used to calculate associations at 95% confidence interval where a p-value of < 0.05 was considered statistically significant.

Results

Most patients (75.5%) had comorbidities and hypertension was most prevalent (89.0%). Over half of the patients (57.0%) and 38.0% of family members were obese. Most patients (75.0%) and 58.0% of family members had abdominal obesity.

Conclusion

Patients with diabetes suffer from comorbidities are overweight and obese whilst evidence from various studies suggest that non-diabetic family members are at added risk of developing diabetes because of higher BMI and abdominal obesity. There is an urgent need to create a conducive environment that discourages sedentary behaviours through lifestyle modifications using the family centred approach, and involve family members in the care of patients.

Obesity is associated with greater cognitive function in patients with type 2 diabetes mellitus

BACKGROUND

The impact of obesity on cognitive function in patients with type 2 diabetes mellitus (T2DM) remains controversial. This study aimed to evaluate whether obesity, assessed by body mass index (BMI) was associated with cognitive function among T2DM patients and whether the effect of obesity on cognitive function was through brain structure.

METHODS

This was a post-hoc analysis of the Action to Control Cardiovascular Risk in Diabetes-Memory in Diabetes (ACCORD-MIND) study. The cognitive test battery included the Digit Symbol Substitution Test (DSST), Mini-Mental State Exam (MMSE), Rey Auditory Verbal Learning Test (RAVLT), and STROOP test, which were administered at baseline, and at 20, 40, and 80 months. A subgroup (n = 614) of the ACCORD-MIND study underwent MRI scanning at baseline and at 40 and 80 months. The total brain volume (TBV), abnormal white matter volume (AWM), abnormal gray matter volume (AGM), and abnormal basal ganglia volume (ABG) were estimated. The outcomes of this study were cognitive function and brain structure.

RESULTS

In the adjusted analyses, BMI was positively associated with the MMSE (β:0.08, 95%CI,0.01-0.16, per standard deviation [SD] increase) and RAVLT scores (β:0.09, 95%CI,0.01-0.18). It was also associated with a greater TBV (β:7.48, 95%CI,0.29-14.67). BMI was not associated with the DSST or STROOP scores, and AWM, AGM, ABG. Mediation analysis found that the effect of BMI on MMSE/RAVLT was mediated through TBV.

CONCLUSION

Obesity may be associated with greater cognitive function and the effect of BMI on cognitive function may be mediated by TBV among patients with T2DM.

CLINICAL TRIAL REGISTRATION

http://www.clinicaltrials.gov, identifier NCT00000620.

Waist-to-height ratio has a stronger association with cardiovascular risks than waist circumference, waist-hip ratio and body mass index in type 2 diabetes

AIMS

To compare the associations between four anthropometric indices including waist-to-height ratio (WHtR), waist circumference (WC), waist-hip-ratio (WHR) and body mass index (BMI) and cardio-cerebrovascular events (CCBVEs) in Chinese T2DM patients.

METHODS

The associations of four anthropometric measures with CCBVEs and metabolic syndrome (MetS) were compared by multiple regression model in 3108 T2DM patients. CCBVEs was defined as a history of myocardial infarction, angina, angioplasty, coronary artery bypass surgery, transient ischemic attack, ischemic or hemorrhagic stroke.

RESULTS

After controlling for age, sex and diabetes duration, the prevalence of CCBVEs and MetS significantly increased across the WHtR, WC, WHR and BMI quartiles in T2DM patients, respectively. However, when controlling for these four anthropometric measurements together, although four anthropometric measures were closely associated with MetS prevalence, only WHtR quartile was significantly associated with CCBVEs prevalence (6.5%, 13.8%, 16.9% and 21.3%, p < 0.001 for trend). After adjusting for multiple confounders including four anthropometric parameters, a regression analysis revealed that only WHtR was independently and positively associated with the presence of CCBVEs (p = 0.029).

CONCLUSIONS

Compared with WC, WHR and BMI, WHtR have a stronger association with CCBVEs in T2DM subjects. WHtR maybe a better indicator than other anthropometric measurements for evaluating cardiovascular risks in T2DM.

Association between body mass index and short-term mortality in patients with intra-abdominal infections: a retrospective, single-centre cohort study using the Medical Information Mart for Intensive Care database

OBJECTIVES

This study aimed to determine the relationship between the body mass index (BMI) and short-term mortality of patients with intra-abdominal infection (IAI) using the Medical Information Mart for Intensive Care (MIMIC-III) database.

DESIGN

Retrospective cohort study.

SETTING

Adult intensive care units (ICUs) at a tertiary hospital in the USA .

PARTICIPANTS

Adult IAI ICU patients from 2001 to 2012 in the MIMIC-III database.

INTERVENTIONS

In univariate analysis, we compared the differences in the characteristics of patients in each BMI group. Cox regression models were used to evaluate the relationships between BMI and short-term prognosis.

PRIMARY AND SECONDARY OUTCOME MEASURES

90-day survival.

RESULTS

In total, 1161 patients with IAI were included. There were 399 (34.4%) patients with a normal BMI (<25 kg/m²), 357 (30.8%) overweight patients (25-30 kg/m²) and 405 (34.9%) obese patients (>30 kg/m²) who tended to be younger (p<0.001) and had higher Sequential Organ Failure Assessment scores (p<0.05). The mortality of obese patients at 90 days was lower than that of patients with a normal BMI (20.74% vs 23.25%, p<0.05), but their length of stay in the ICU was higher (4.9 days vs 3.6 days, p<0.001); however, their rate of mechanical ventilation utilisation was higher (61.48% vs 56.86%, p<0.05). In the Cox regression model, we also confirmed that BMI was a protective factor in patients with IAIs, and the adjusted mortality rate of patients with a higher BMI was 0.97 times lower than that of patients with a lower BMI (p<0.001, HR=0.97, 95% CI 0.96 to 0.99).

CONCLUSIONS

IAI patients with an overweight or obese status might have lower 90-day mortality than patients with a normal BMI.

The SMART Framework: Selection of Machine learning Algorithms with ReplicaTions - a Case Study on the Microvascular Complications of Diabetes

Over 34 million people in the US have diabetes, a major cause of blindness, renal failure, and amputations. Machine learning (ML) models can predict high-risk patients to help prevent adverse outcomes. Selecting the 'best' prediction model for a given disease, population, and clinical application is challenging due to the hundreds of health-related ML models in the literature and the increasing availability of ML methodologies. To support this decision process, we developed the Selection of Machine-learning Algorithms with ReplicaTions (SMART) Framework that integrates building and selecting ML models with decision theory. We build ML models and estimate performance for multiple plausible future populations with a replicated nested cross-validation technique. We rank ML models by simulating decision-maker priorities, using a range of accuracy measures (e.g., AUC) and robustness metrics from decision theory (e.g., minimax Regret). We present the SMART Framework through a case study on the microvascular complications of diabetes using data from the ACCORD clinical trial. We compare selections made by risk-averse, -neutral, and -seeking decision-makers, finding agreement in 80% of the risk-averse and risk-neutral selections, with the risk-averse selections showing consistency for a given complication. We also found that the models that best predicted outcomes in the validation set were those with low performance variance on the testing set, indicating a risk-averse approach in model selection is ideal when there is a potential for high population feature variability. The SMART Framework is a powerful, interactive tool that incorporates various ML algorithms and stakeholder preferences, generalizable to new data and technological advancements.

The prediction of Metabolic Syndrome alterations is improved by combining waist circumference and handgrip strength measurements compared to either alone

Background

Adiposity is a major component of the metabolic syndrome (MetS), low muscle strength has also been identified as a risk factor for MetS and for cardiovascular disease. We describe the prevalence of MetS and evaluate the relationship between muscle strength, anthropometric measures of adiposity, and associations with the cluster of the components of MetS, in a middle-income country.

Methods

MetS was defined by the International Diabetes Federation criteria. To assess the association between anthropometric variables (waist circumference (WC), waist-to-hip ratio (W/H), body mass index (BMI)), strength (handgrip/kg bodyweight (HGS/BW)) and the cluster of MetS, we created a MetS score. For each alteration (high triglycerides, low HDLc, dysglycemia, or high blood pressure) one point was conferred. To evaluate the association an index of fat:muscle and MetS score, participants were divided into 9 groups based on combinations of sex-specific tertiles of WC and HGS/BW.

Results

The overall prevalence of MetS in the 5,026 participants (64% women; mean age 51.2 years) was 42%. Lower HGS/BW, and higher WC, BMI, and W/H were associated with a higher MetS score. Amongst the 9 HGS/BW:WC groups, participants in the lowest tertile of HGS/BW and the highest tertile of WC had a higher MetS score (OR = 4.69 in women and OR = 8.25 in men;p < 0.01) compared to those in the highest tertile of HGS/BW and in the lowest tertile of WC.

Conclusion

WC was the principal risk factor for a high MetS score and an inverse association between HGS/BW and MetS score was found. Combining these anthropometric measures improved the prediction of metabolic alterations over either alone.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01256-z.

Body roundness index is a superior indicator to associate with the cardio-metabolic risk: evidence from a cross-sectional study with 17,000 Eastern-China adults

Background

To investigate the ability of body shape index (ABSI), body roundness index (BRI), waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body adiposity index (BAI) for predicting non-adipose cardio-metabolic risk.

Methods

A total of 17,360 Chinese subjects aged 18–95 years old who escaped cardiovascular disease (CVD) or diabetes were recruited in the cross-sectional study. Anthropometric and biochemical parameters were assessed. Receiver operating characteristic curve (ROC) and multinomial logistic regression were conducted to examine the association of anthropometric indicators with cardio-metabolic risk factors.

Results

The mean age of subjects were 53.7(13.1) years, 41.6 % were males. The areas under the curve (AUC) demonstrated that WC, BMI, WHR, WHtR and BRI were able to predict high cardio-metabolic risk (AUC > 0.70). Meanwhile, multinomial logistic regression showed BRI was significantly associated with high cardio-metabolic risk (OR 3.27, 95% CI 3.01–3.55). The optimal cut-off values of BRI for high cardio-metabolic risk were (< 60 y: 3.49 vs. ≥60 y: 3.46) in males and (< 60 y: 3.47 vs. ≥60 y: 3.60) in females.

Conclusions

WC, BMI WHR, and WHtR were potential obesity indicators in discriminating high cardio-metabolic risk, while BAI or ABSI was not. Moreover, BRI revealed superior predictive capacity and significant association with accumulated cardio-metabolic risk factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-01905-x.