ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2021
Evaluation of Eight Anthropometric Indices for Identification of Metabolic Syndrome in Adults with Diabetes.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 29 citations in OpenAlex.
- Comparison of anthropometric indicators for assessing current type 2 diabetes risk in adult patients.BMC endocrine disorders · 2026Observational
- Determination of the Optimal Cut-Off Point of Anthropometric Indices to Predict the Risk of Metabolic Syndrome in Iranian Adult Population With Type 2 Diabetes Mellitus: A Cross-Sectional-Analytical Study.Endocrinology, diabetes & metabolism · 2026Article
- Establishing optimal cut-offs of cardio-metabolic indices for diagnosing metabolic syndrome in type 2 diabetes.BMC endocrine disorders · 2025Article
- CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort.The journal of nutrition, health & aging · 2025Article
- Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.Lipids in health and disease · 2025Article
- Associations between eight anthropometric indices and Parkinson's disease: a nationwide population-based study.Frontiers in nutrition · 2025Article
- The predictive power of conventional and novel obesity indices in identifying metabolic syndrome among the southern Iranian populations: findings from PERSIAN cohort study.Journal of health, population, and nutrition · 2024Article
- Predictive ability of anthropometric indices for risk of developing metabolic syndrome: a cross-sectional study.The Journal of international medical research · 2024Article
- Association of the CUN-BAE body adiposity estimator and other obesity indicators with cardiometabolic multimorbidity: a cross-sectional study.Scientific reports · 2024Article
- Article
- Investigating the efficiency of novel indicators in predicting risk of metabolic syndrome in the Iranian adult population.Journal of education and health promotion · 2024Article
- The relationship between the CUN-BAE body fatness index and incident diabetes: a longitudinal retrospective study.Lipids in health and disease · 2023Article
- Obesity- and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study.Frontiers in public health · 2023Article
- Association of the Clínica Universidad de Navarra-Body Adiposity Estimator With Type 2 Diabetes: A Retrospective Cohort Study.International journal of public health · 2023Article
- Gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio is a more powerful marker than TyG index for predicting metabolic syndrome in patients with type 2 diabetes mellitus.Frontiers in endocrinology · 2023Article
- Conicity-index predicts all-cause mortality in Chinese older people: a 10-year community follow-up.BMC geriatrics · 2022Article
- Assessing metabolic syndrome prediction quality using seven anthropometric indices among Jordanian adults: a cross-sectional study.Scientific reports · 2022Article
- Relationship of body fat and left ventricular hypertrophy with the risk of all-cause death in patients with coronary artery disease.Journal of geriatric cardiology : JGC · 2022Article
- Waist-to-height ratio is a simple and practical alternative to waist circumference to diagnose metabolic syndrome in type 2 diabetes.Frontiers in nutrition · 2022Article
- Associations between Metabolic Syndrome and Obesity-Related Indices and Bone Mineral Density T-Score in Hemodialysis Patients.Journal of personalized medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeSeveral previous reports have highlighted the association between adiposity and risk of metabolic syndrome (MetS). Although it is necessary to identify which adiposity indices are best suited to identify MetS, no such study has been completed in diabetic patients. The aim of this study was to evaluate the ability of eight anthropometric indices to identify MetS in diabetic, middle-aged and elderly Chinese patients. PATIENTS AND
methodsA cross-sectional study was conducted in 906 type 2 diabetic patients in Guangxi.
resultsThe highest odds ratios for the identification of MetS were identified with CUN-BAE (OR = 28.306). The largest areas under the curve (AUCs) were observed for WHtR and BRI in men aged 40-59; CUN-BAE in men aged 60 and over; WHtR, BRI, and TyG in women aged 40-59; and BMI for women aged 60 and over. The weakest indicator for the screening of MetS in type 2 diabetes was the ABSI.
conclusionThe most effective anthropometric indicator for the identification of MetS varied across sex and age subgroups.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.