New indices in predicting cardiometabolic risk and its relation to endothelial dysfunction in adolescents: The HELENA study

Nogueira, Maria Dinara de Araújo; Braga, Ribanna Aparecida Marques; Μanios, Yannis; Androutsos, Odysseas; Molnár, Denés; Polito, Angela; Gómez‐Martínez, Sonia; Béghin, Laurent; Widhalm, Kurt; Bueno, Gloria; Castillo, Manuel J.; Arum, Puspito; Moreno, Luis A.; Maia, Carla Soraya Costa

doi:10.1016/j.numecd.2023.01.015

Cited by 6 publications

(3 citation statements)

References 58 publications

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“…The biological plausibility of the CMI as a marker for arteriosclerosis can be understood through the lens of insulin resistance [ 18 ] and hyperglycemia [ 21 ], which are hallmarks of T2DM. These metabolic abnormalities contribute to the endothelial dysfunction [ 22 ], oxidative stress [ 23 ], and inflammatory processes[ 24 ] that are fundamental to the development of arteriosclerosis. Furthermore, the components of the CMI, which include measures of obesity and dyslipidemia, are known contributors to vascular pathology.…”

Section: Discussionmentioning

confidence: 99%

Correlation between the cardiometabolic index and arteriosclerosis in patients with type 2 diabetes mellitus

Tang,

Pang,

Dang

et al. 2024

BMC Cardiovasc Disord

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Background The cardiometabolic index (CMI) is a new metric derived from the triglyceride-glucose index and body mass index and is considered a potential marker for cardiovascular risk assessment. This study aimed to examine the correlation between the CMI and the presence and severity of arteriosclerosis in patients with type 2 diabetes mellitus (T2DM). Methods This study involved 2243 patients with T2DM. The CMI was derived by dividing the triglyceride level (mmol/L) by the high-density lipoprotein level (mmol/L) and then multiplying the quotient by the waist-to-height ratio. Multivariate logistic regression was used to analyze the correlations between the CMI and BMI blood biomarkers, blood pressure, and brachial-ankle pulse wave velocity (baPWV). Results Patients were categorized into three groups based on their CMI: Group C1 (CMI < 0.775; n = 750), Group C2 (CMI: 0.775–1.355; n = 743), and Group C3 (CMI > 1.355; n = 750). Increased BMI, fasting glucose, insulin (at 120 min), total cholesterol (TC), and baPWV values were observed in Groups C2 and C3, with statistically significant trends (all trends P < 0.05). The CMI was positively correlated with systolic blood pressure (r = 0.74, P < 0.001). Multivariate analysis revealed that an increased CMI contributed to a greater risk for arteriosclerosis (OR = 1.87, 95%CI: 1.66–2.10, P < 0.001). Compared to the C1 group, the C2 group and C3 group had a greater risk of developing arteriosclerosis, with ORs of 4.55 (95%CI: 3.57–5.81, P<0.001) and 5.56 (95%CI: 4.32–7.17, P<0.001), respectively. The association was notably stronger in patients with a BMI below 21.62 kg/m² than in those with a BMI of 21.62 kg/m² or higher (OR = 4.53 vs. OR = 1.59). Conclusions These findings suggest that the CMI is a relevant and independent marker of arteriosclerosis in patients with T2DM and may be useful in the risk stratification and management of these patients.

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Section: Discussionmentioning

confidence: 99%

Correlation between the cardiometabolic index and arteriosclerosis in patients with type 2 diabetes mellitus

Tang,

Pang,

Dang

et al. 2024

BMC Cardiovasc Disord

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“…Primarily, IR can disrupt glucose metabolism and trigger lipotoxicity. 33 Moreover, it frequently intertwines with endothelial dysfunction, 34 a pivotal factor in cardiovascular diseases. Endothelial dysfunction encompasses reduced nitric oxide bioavailability, heightened oxidative stress, increased expression of pro-inflammatory and pro-thrombotic factors, and abnormal vasoreactivity, collectively contributing to atherosclerosis.…”

Section: Discussionmentioning

confidence: 99%

The Association Between Triglyceride-Glucose Index and Its Combination with Obesity Indicators and Lower Extremity Peripheral Artery Disease in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study

Miao,

Wang,

Wang

et al. 2024

DMSO

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“…It is also a marker of adipose tissue dysfunction. The lipid accumulation product (LAP) is another fat accumulation marker, and previous studies have shown that LAP is a better predictor of cardiometabolic risk than the BMI z-score and WC [5]. Finally, the triglycerideglucose (TyG) marker is a surrogate for insulin resistance and more reliable than the homeostasis model assessment of insulin resistance (HOMA-IR) [6].Thus, the VAI, LAP, and TyG can assess factors in uencing CVD and are good predictors of CVD occurrence.…”

Section: Introductionmentioning

confidence: 99%

Relationships between cardiopulmonary function and dangerous cardiovascular factors in Chinese adults: A cross-sectional study

Liu,

Zhi-jian,

Bao-hu

et al. 2024

Preprint

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Background Cardiovascular disease (CVD) is a risk factor for mortality. Cardiopulmonary function (CRF) is a modifiable CVD risk factor, and low CRF levels are associated with an elevated CVD risk. However, few comprehensive explorations of the relationship between CRF and cardiometabolic health in CVD exist. Therefore, this study investigated the relationships between CVD risk factors and CRF. Methods In this cross-sectional study, CRF was measured using the peak oxygen uptake (i.e., peak VO2) and a cardiopulmonary exercise test. The participants were also assessed for body composition, blood glucose-related markers, blood lipid-related markers, blood pressure, and cardiovascular markers. Participants’ self-reported data on cigarette/snuff use and alcohol consumption were collected using a questionnaire. A multiple linear regression analysis was used to explore the cross-sectional correlations between CVD risk factors and CRF, controlling for covariates. Results Six hundred and fifty participants were included; the average age was 42 years (interquartile range: 35–51 years old), and the average CRF was 21.5 mL/kg/min. CRF was significantly and positively associated with body mass index (β = 0.149, p < 0.001), body fat percentage (β = 0.248, p < 0.001), waist circumference (β = 0.498, p < 0.001), hip circumference (β = 0.285, p < 0.001), waist-to-hip ratio (β = 0.02, p < 0.001), and high-density lipoprotein cholesterol (β = 0.005, p < 0.05). Significant negative correlations were observed between CRF and fasting blood glucose (β = − 0.023, p < 0.05), creatinine content (β = − 0.322, p < 0.05), C-reactive protein (β = − 0.026, p < 0.05), and lipid accumulation product (β = − 0.8824, p < 0.05). CRF was not related to glycosylated hemoglobin content, blood pressure, vascular markers, total cholesterol, triglycerides, or low-density lipoprotein cholesterol. Conclusions CRF was associated with several CVD risk factors, suggesting that improving CRF will benefit individuals by reducing the risk of CVD. CRF can be improved via exercise interventions.

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New indices in predicting cardiometabolic risk and its relation to endothelial dysfunction in adolescents: The HELENA study

Cited by 6 publications

References 58 publications

Correlation between the cardiometabolic index and arteriosclerosis in patients with type 2 diabetes mellitus

Correlation between the cardiometabolic index and arteriosclerosis in patients with type 2 diabetes mellitus

The Association Between Triglyceride-Glucose Index and Its Combination with Obesity Indicators and Lower Extremity Peripheral Artery Disease in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study

Relationships between cardiopulmonary function and dangerous cardiovascular factors in Chinese adults: A cross-sectional study

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