Low sensitivity of the metabolic syndrome to identify adolescents with impaired glucose tolerance: an analysis of NHANES 1999-2010

Clustering of cardio-metabolic risk factors and pre-diabetes among U.S. adolescents

Few studies have assessed the association between clustering of cardio-metabolic risk factors (CMRFs) and pre-diabetes in children or adolescents. We aimed to examine the association between clustering of CMRFs and pre-diabetes among U.S. adolescents. Data were available for 5,633 U.S. adolescents aged 12-19 years from the National Health and Nutrition Examination Surveys 1999-2014. Pre-diabetes was defined as impaired fasting glucose (IFG) (fasting plasma glucose 100-125 mg/dL), impaired glucose tolerance (IGT) (2-h plasma glucose 140-199 mg/dL) or elevated hemoglobin A1c (HbA1c) (HbA1c 5.7-6.4%). The individual CMRFs considered in the present study were as follows: waist-to-height ratio, blood pressure, triglycerides, and high-density lipoprotein cholesterol. CMRFs were defined based on the modified National Cholesterol Education Program (NCEP) criteria or the modified International Diabetes Federation (IDF) criteria. Logistic regression analysis was used to examine the association between clustering of CMRFs and pre-diabetes with adjustment for potential covariates. Among 5633 adolescents, 11.4% had IFG, 4.7% had IGT, 4.5% had elevated HbA1c and 16.1% had pre-diabetes. Compared with adolescents with no CMRFs, the odds ratios (ORs) with 95% confidence intervals (CIs) for pre-diabetes across the clustering of CMRFs (i.e., 1, 2, 3, and 4) were 1.32 (1.03-1.68), 2.07 (1.55-2.76), 2.52 (1.69-3.76), and 5.41 (3.14-9.32), respectively, based on the modified NCEP criteria. The corresponding ORs with 95% CIs were 1.16 (0.89-1.51), 1.78 (1.35-2.36), 3.07 (1.89-4.98) and 12.20 (3.93-37.89), respectively, based on the modified IDF criteria. The present study suggests that the clustering of CMRFs is associated with increased pre-diabetes among U.S. adolescents. It might be necessary for effective strategies and measures targeting adolescents with clustering of CMRFs, including those with less than 3 risk factors.

Prevalence of Metabolic Syndrome and Impaired Glucose Metabolism among 10- to 17-Year-Old Overweight and Obese Lithuanian Children and Adolescents

BACKGROUND

Overweight (Ow) and obesity among adults and children increases the risk of metabolic consequences. Metabolic syndrome (MS) and impaired glucose metabolism are well-known risk factors for cardiovascular diseases and type 2 diabetes. The aim of this study was to evaluate the prevalence of MS and impaired glucose metabolism among Ow and obese (Ob) children and adolescents (aged 10-17 years) in Lithuania, and to evaluate the associations between insulin resistance (IR) indices and anthropometric parameters as well as metabolic disturbances.

METHODS

The study population consisted of 344 OwOb children and adolescents of all pubertal stages. Oral glucose tolerance tests (OGTTs), IR and β cell function indices, lipid profile, and anthropometric parameters of all subjects were analyzed. MS was defined according to the International Diabetes Federation consensus guidelines.

RESULTS

MS was found in 21.3% of the OwOb children and adolescents, and 12.1% had impaired glucose metabolism (6.9% with impaired fasting glucose, 4.5% with impaired glucose tolerance, and 0.6% with type 2 diabetes). IR was directly related to body mass index and waist circumference, waist-to-height and waist-to-hip ratios, and sum of skin-fold thicknesses. Children with MS were more insulin-resistant, had higher odds ratio for prediabetes and had a more disturbed lipid profile than subjects without MS. Moreover, total cholesterol and low-density lipoprotein cholesterol levels were significantly lower in the more mature OwOb adolescents.

CONCLUSION

MS and lipid profile disturbances are common in OwOb children and adolescents. MS is directly associated with IR. Therefore, OwOb children and adolescents should be carefully followed up for metabolic abnormalities during late childhood as these can persist into adulthood.

Association Between Metabolic Syndrome and Parameters of Subclinical Target Organ Damage in Urban Subjects Without Documented Cardiovascular Disease

Background: Identification of subclinical target organ damage (TOD) at early stage is important for the reduction in cardiovascular risk. This study was performed to assess the association between metabolic syndrome (MetS) and several types of TOD in urban people. Methods: Data from 958 Korean subjects without cardiovascular disease, living in Seoul city (mean age, 55.2 years, 47.6% males), were extracted from the prospective cohort database. All participants underwent extensive evaluation of TOD parameters, including left ventricular mass index (LVMI), E/e', brachial-ankle pulse wave velocity (baPWV), estimated glomerular filtration rate (eGFR), ankle-brachial index (ABI), carotid intima-media thickness (IMT), and obstructive coronary artery disease. Results: MetS and ≥1 TOD were detected in 494 (51.5%) and 329 (34.3%) subjects, respectively. There were no significant differences in the prevalence of ≥1 TOD according to the presence of MetS (P > 0.05). Among MetS components, only high blood pressure was associated with ≥1 TOD (69.6% vs. 59.9%, P = 0.004). There was a positive association between ≥1 TOD and the number of MetS traits (P = 0.034). There were significant linear correlations of Z-score of MetS with baPWV (r = 0.241, P < 0.001) and eGFR (r = -0.173, P < 0.001) but not with LVMI, E/e', ABI, and carotid IMT (P > 0.05 for each). Conclusions: In urban Korean population without cardiovascular disease, TOD is more closely related to the number of risk factors meeting MetS criteria and high blood pressure than the presence of MetS itself.

Severity of the metabolic syndrome as a predictor of prediabetes and type 2 diabetes in first degree relatives of type 2 diabetic patients: A 15-year prospective cohort study

BACKGROUND

Type 2 diabetes mellitus (T2DM) has high morbidity and mortality worldwide, therefore there is of paramount importance to identify the risk factors in the populations at risk early in the course of illness. A strong correlation between severity of metabolic syndrome (MetS) and HbA1c, fasting insulin and insulin resistance has been reported. Accordingly, the MetS severity score (or MestS Z-score) can potentially be used to predict the risk of T2DM progression over time.

AIM

To evaluate the association the of MestS Z-score in first degree relatives (FDRs) of T2DM with the risk of prediabetes and type 2 diabetes in future.

METHODS

A prospective open cohort study was conducted between 2003-2018. At baseline, the sample comprised of 1766 FDRs of patients with T2DM who had a normal glucose tolerance test. Relative risk (RR) and 95% confidence interval were calculated based on logistic regression. The receiver-operator characteristic analysis and area under the curve based on MetS Z-score were used to evaluate the risk of prediabetes and diabetes among the FDR population.

RESULTS

Baseline MetS Z-scores were associated with the its latest values (P < 0.0001). Compared with individuals who were T2DM free at the end of follow up, those who developed T2DM had higher MetS Z-score at baseline (P < 0.001). In multivariable logistic regression analyses for every unit elevation in MetS Z-score at the baseline, the RR for developing future T2DM and prediabetes was (RR = 1.94, RR = 3.84), (RR = 1.5, RR = 2.17) in total population and female group, respectively (P < 0.05). The associations remained significant after adjusting the potential confounding variables. A cut off value of 0.97 and 0.94 was defined in the receiver-operator characteristic curve based on the MetS Z-score for differentiating female patients with diabetes and prediabetes from the normal population, respectively.

CONCLUSION

The MetS Z-score was associated with an increased risk of future T2DM. Appropriate interventions at earlier stages for preventing and attenuating MetS effects may be considered as an effective strategy for FDR as at-risk population.

Screening for chronic conditions with reproductive factors using a machine learning based approach

A large proportion of cases with chronic conditions including diabetes or pre-diabetes, hypertension and dyslipidemia remain undiagnosed. To include reproductive factors (RF) might be able to improve current screening guidelines by providing extra effectiveness. The objective is to study the relationships between RFs and chronic conditions' biomarkers. A cross-sectional study was conducted. Demographics, RFs and metabolic biomarkers were collected. The relationship of the metabolic biomarkers were shown by correlation analysis. Principal component analysis (PCA) and autoencoder were compared by cross-validation. The better one was adopted to extract a single marker, the general chronic condition (GCC), to represent the body's chronic conditions. Multivariate linear regression was performed to explore the relationship between GCC and RFs. In total, 1,656 postmenopausal females were included. A multi-layer autoencoder outperformed PCA in the dimensionality reduction performance. The extracted variable by autoencoder, GCC, was verified to be representative of three chronic conditions (AUC for patoglycemia, hypertension and dyslipidemia were 0.844, 0.824 and 0.805 respectively). Linear regression showed that earlier age at menarche (OR = 0.9976) and shorter reproductive life span (OR = 0.9895) were associated with higher GCC. Autoencoder performed well in the dimensionality reduction of clinical metabolic biomarkers. Due to high accessibility and effectiveness, RFs have potential to be included in screening tools for general chronic conditions and could enhance current screening guidelines.

Associations of a metabolic syndrome severity score with coronary heart disease and diabetes in fasting vs. non-fasting individuals

BACKGROUND AND AIMS

Many traditional assessments of risk for coronary heart disease (CHD) and diabetes require laboratory studies performed after an 8-h fast. We assessed whether metabolic-syndrome (MetS) severity would remain linked to future CHD and diabetes even when assessed from non-fasting samples.

METHODS AND RESULTS

Participants in the Atherosclerosis Risk in Communities study were assessed at 4 visits and followed for 20-years of adjudicated CHD outcomes. We used Cox proportional-hazard models (for 20-year CHD outcomes) and logistic regression (for 9-year diabetes outcomes) to compare incident disease risk associated with a race/ethnicity-specific MetS-severity Z-score (MetS-Z) calculated in participants who were fasting (≥8 h) or non-fasting. All analyses were adjusted for sex, race, education, income and smoking. MetS Z-scores were overall similar between participants who were always fasting vs. those non-fasting at Visits 1-3 (all values -0.1 to 0.4), while MetS-Z for participants who were non-fasting at Visit-4 were higher at each visit. Baseline MetS-Z was linked to future CHD when calculated from both fasting and non-fasting measurements, with hazard ratio (HR) for fasting MetS-Z 1.53 (95% confidence interval [CI] 1.42, 1.66) and for non-fasting 1.28 (CI 1.08, 1.51). MetS-Z at Visit-1 also remained linked to future diabetes when measured from non-fasting samples, with odds ratio for fasting MetS-Z 3.10 (CI 2.88, 3.35) and for non-fasting 1.92 (CI 1.05, 3.51).

CONCLUSIONS

MetS-Z remained linked to future CHD and diabetes when assessed from non-fasting samples. A score such as this may allow for identification of at-risk individuals and serve as a motivation toward interventions to reduce risk.

Dietary inflammatory index and cardiometabolic risk in US adults

BACKGROUND AND AIMS

We investigated the association between Dietary Inflammatory Index (DII^®) scores and cardio-metabolic risk factors singly and in combination as metabolic syndrome (MetS).

METHODS

We used data from participants selected from the US National Health and Nutrition Examination Survey (NHANES). Analyses were restricted to participants with data available on dietary intake, biochemical data, and anthropometric measurements from 2005 to 2012. Statistical analyses used the SPSS^® Complex Samples v22.0 (IBM Corp, Armonk, NY) and accounted for the survey design and sample weights. Energy-adjusted-DII (E-DII^®) expressed per 1000 kcal was calculated from 24-h dietary recalls. Of the 17,689 participants with evaluable data, 8607 (48.3%) were men. The mean age was 45.8 years in the overall sample, with men being slightly younger than women (44.9 vs. 46.5 years, p = 0.05).

RESULTS

In multivariable-adjusted regression models, the odds of MetS, its components, as well as obesity, and elevated high-sensitivity C-reactive protein (hsCRP) increased across increasing quartiles of E-DII (p < 0.001). In age, sex, race, income-to-poverty ratio-adjusted models, these and other cardiovascular disease risk factors (triglycerides/high density lipoprotein cholesterol (HDL-C) ratio, apolipoprotein (B) and HbA1C) increased across quartiles of the E-DII (all p < 0.001), while HDL-C levels decreased (p < 0.001).

CONCLUSIONS

This study suggests associations between MetS, its components, subclinical inflammation, and the DII. These results reinforce the view that diet plays an important role in the occurrence of cardiovascular diseases.

Examining trends in prediabetes and its relationship with the metabolic syndrome in US adolescents, 1999-2014

AIMS

We sought to investigate temporal trends in prediabetes prevalence among US adolescents using two definitions and evaluate relationships with obesity and a MetS-severity score.

METHODS

We evaluated data from 5418 non-Hispanic white, non-Hispanic black, and Hispanic adolescents aged 12-19 participating in the National Health and Nutrition Examination Survey 1999-2014 with complete data regarding MetS and hemoglobin A1c (HbA1c). Prediabetes status was defined by American Diabetes Association (ADA) criteria: fasting glucose 100-125 mg/dL or HbA1c 5.7%-6.4%. MetS severity was assessed with a MetS-severity Z-score.

RESULTS

Prevalence of prediabetes as defined by HbA1c abnormalities significantly increased from 1999-2014, while prevalence of prediabetes as defined by fasting glucose abnormalities showed no significant temporal trend. There were variations in these trends across different racial/ethnic groups. MetS Z-score was overall more strongly correlated with HbA1c, fasting insulin, and the homeostasis model of insulin resistance than was BMI Z-score. These correlations were true in each racial/ethnic group with the exception that in non-Hispanic white adolescents, in whom the MetS Z-score was not significantly correlated with HbA1c measurements.

CONCLUSION

We found conflicting findings of temporal trends of US adolescent prediabetes prevalence based on the ADA's prediabetes criteria. The increasing prevalence of prediabetes by HbA1c assessment is concerning and raises the urgency for increased awareness and appropriate measures of prediabetes status among physicians and patients.

Circulating Zinc-α2-glycoprotein levels and Insulin Resistance in Polycystic Ovary Syndrome

The aim of study was to assess the relationship between zinc-α2-glycoprotein (ZAG) and androgen excess with insulin resistance in polycystic ovary syndrome (PCOS) women. 99 PCOS women and 100 healthy controls were recruited. Euglycemic-hyperinsulinemic clamp (EHC) was preformed to assess their insulin sensitivity. Circulating ZAG was determined with an ELISA kit. In healthy subjects, circulating ZAG levels exhibited a characteristic diurnal rhythm in humans, with a major nocturnal rise occurring between midnight and early morning. Circulating ZAG and M-value were much lower in PCOS women than in the controls. In all population, overweight/obese subjects had significantly lower circulating ZAG levels than lean individuals. Multiple linear regression analysis revealed that only M-value and the area under the curve for glucose were independently related factors to circulating ZAG in PCOS women. Multivariate logistic regression analysis showed that circulating ZAG was significantly associated with PCOS even after controlling for anthropometric variables, blood pressure, lipid profile and hormone levels. The PCOS women with high ZAG had fewer MetS, IGT and polycystic ovaries as compared with the low ZAG PCOS women. Taken together, circulating ZAG levels are reduced in women with PCOS and ZAG may be a cytokine associated with insulin resistance in PCOS women.

Probing the factor structure of metabolic syndrome in Sardinian genetic isolates

BACKGROUND AND AIMS

Owing to the multiplicity of the key components of metabolic syndrome (MetS), its diagnosis is very complex. The lack of a unique definition is responsible for the prevalence variability observed among studies; therefore, a definition based on continuous variables was recommended. The aim of this study was to compare competing models of the MetS factor structure for selecting the one that explains the best clustering pattern and to propose an algorithm for computing MetS as a continuous variable.

METHODS AND RESULTS

Data were from isolated Sardinian populations (n = 8102). Confirmatory factor analysis (CFA) and two-group CFA by gender were performed to evaluate the sex-specific factor structure of MetS. After selecting the best model, an algorithm was obtained using factor loadings/residual variances. The quality of the MetS score was evaluated by the receiver operating characteristics curve and the area under the curve. Cross-validation was performed to validate the score and to determine the best cut point. The best fit model was a bifactor one with a general factor (MetS) and three specific factors (f1: obesity/adiposity trait; f2: hypertension/blood pressure trait; and f3: lipid trait). Gender-specific algorithms were implemented to obtain MetS scores showing a good diagnostic performance (0.80 specificity and 0.80 sensitivity for the cut point). Furthermore, cross-validation confirmed these results.

CONCLUSION

These analyses suggested that the bifactor model was the most representative one. In addition, they provided a score and a cut point that are both clinically accessible and interpretable measures for MetS diagnosis and likely useful for evaluating the association with adverse cardiovascular disease and diabetes and for investigating the MetS genetic component.