ArticleScientific reports2021
The hypertriglyceridemic-waist phenotype as a valuable and integrative mirror of metabolic syndrome traits.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- The Relationship Between Dynamic Changes in the Insulin Resistance-Related Indices and Metabolic Syndrome in Middle-Aged and Elderly Population.International journal of endocrinology · 2026Article
- Obesity promotes conserved inflammatory and metabolic transcriptional programs in colon tumors: evidence from mouse models and the ColoCare Study Patient Cohort.The American journal of clinical nutrition · 2025Article
- Article
- The long-term impact of hypertriglyceridemia-waist phenotype on major adverse cardiovascular events in elderly patients with OSA.Sleep & breathing = Schlaf & Atmung · 2025Article
- The Prevalence of Metabolic Syndrome and Hypertriglyceridemic Waist Based on Sociodemographic Variables and Healthy Habits in Healthcare Workers: A Retrospective Study.Life (Basel, Switzerland) · 2025Article
- Article
- The interplay of factors in metabolic syndrome: understanding its roots and complexity.Molecular medicine (Cambridge, Mass.) · 2024Review
- Genetic variations in IKZF3, LET7-a2, and CDKN2B-AS1: Exploring associations with metabolic syndrome susceptibility and clinical manifestations.Journal of clinical laboratory analysis · 2024Article
- Relationship Between Asymptomatic Hyperuricemia and the Hypertriglyceridemic-Waist Phenotype in Korean Adults: A Cross-Sectional Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- Association between hypertriglyceridemic-waist phenotype and circadian syndrome risk: a longitudinal cohort study.Hormones (Athens, Greece) · 2023Article
- Hypertriglyceridemic-waist phenotype is strongly associated with cardiovascular risk factor clustering in Chinese adolescents.Scientific reports · 2022Article
- Review
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5 authors.
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Abstract
Rates of non-communicable diseases (NCDs), such as obesity, diabetes, cardiovascular events and cancer, continue to rise worldwide, which require objective instruments for preventive and management actions. Diverse anthropometric and biochemical markers have been used to qualitatively evaluate degrees of disease, metabolic traits and evolution of nutritional status. The aim of this study was to integrate and assess the interactions between an anthropometric measurement, such as waist circumference (WC), and biochemical data, such as the triglyceride glucose index (TyG), in order to individually characterize metabolic syndrome (MetS) features considering the hypertriglyceridemic waist phenotype as a marker. An ancillary cross-sectional study was conducted using anthropometric measurements, such as weight, height, waist and hip circumferences, as well as fasting biochemical data of 314 participants. Different indices based on WC (WC, WC*TG and WC*TyG) were estimated to compute MetS components and accompanying comorbidities. ROC curves were fitted to define the strength of the analyses and the validity of the relationships. Associations were confirmed between anthropometric, biochemical and combined indices with some chronic disease manifestations, including hyperglycemia, hypertension and dyslipidemia. Both WC*TG and WC*TyG indices showed similar performance in diagnosing MetS (area under the ROC curve = 0.81). Interestingly, when participants were categorized according to a reference value of the WC*TyG index (842.7 cm*mg/dl), our results evidenced that subjects classified over this limit presented statistically higher prevalence of MetS and accompanying individual components with clinical relevance for interventions. These results revealed that WC*TyG mirrors the hypertriglyceridemic phenotype, which suggests may serve as a good indicator to define the metabolic syndrome phenotype and a suitable, sensitive, and simple proxy to complement others. A reference point was proposed with a good clinical performance and maximized sensitivity and specificity values.
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