ArticleBMC endocrine disorders2018
Identification of an obesity index for predicting metabolic syndrome by gender: the rural Chinese cohort study.
Article in BMC endocrine disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 26 citations in OpenAlex.
- 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
- Obesity indices as predictors of metabolic syndrome: 1-year findings from a Peruvian cohort of private educational institution workers.Therapeutic advances in endocrinology and metabolism · 2026Article
- Article
- Correlation Between Body-Shape Index, Body-Roundness Index, Body-Mass Index, and Apnea-Hypopnea Index in Patients with Obstructive Sleep Apnea Syndrome.Journal of multidisciplinary healthcare · 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
- Impact of sleep duration and dietary patterns on risk of metabolic syndrome in middle-aged and elderly adults: a cross-sectional study from a survey in Anhui, Eastern China.Lipids in health and disease · 2024Article
- Association of Three Novel Inflammatory Markers: Lymphocyte to HDL-C Ratio, High-Sensitivity C-Reactive Protein to HDL-C Ratio and High-Sensitivity C-Reactive Protein to Lymphocyte Ratio With Metabolic Syndrome.Endocrinology, diabetes & metabolism · 2024Article
- Diagnostic Accuracy of Waist-to-Height Ratio, Waist Circumference, and Body Mass Index in Identifying Metabolic Syndrome and Its Components in Older Adults: A Systematic Review and Meta-Analysis.Current developments in nutrition · 2024Article
- Obesity among Asian American people in the United States: A review.Obesity (Silver Spring, Md.) · 2023Review
- Optimal Anthropometric Indicators and Cut Points for Predicting Metabolic Syndrome in Chinese Patients with Type 2 Diabetes Mellitus by Gender.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Article
- Relationship between lipid accumulation product and new-onset diabetes in the Japanese population: a retrospective cohort study.Frontiers in endocrinology · 2023Article
- Assessing metabolic syndrome prediction quality using seven anthropometric indices among Jordanian adults: a cross-sectional study.Scientific reports · 2022Article
- Article
- Opening the black box: interpretable machine learning for predictor finding of metabolic syndrome.BMC endocrine disorders · 2022Article
- Association of Lipid Accumulation Product and Triglyceride-Glucose Index with Metabolic Syndrome in Young Adults: A Cross-sectional Study.International journal of endocrinology and metabolism · 2022Article
- Construction of Xinjiang metabolic syndrome risk prediction model based on interpretable models.BMC public health · 2022Article
- Children's Lipid Accumulation Product Combining Visceral Adiposity Index is a Novel Indicator for Predicting Unhealthy Metabolic Phenotype Among Chinese Children and Adolescents.Diabetes, metabolic syndrome and obesity : targets and therapy · 2021Article
- Sex Difference in the Associations among Obesity-Related Indices with Metabolic Syndrome in Patients with Type 2 Diabetes Mellitus.International journal of medical sciences · 2021Article
- The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics.International journal of environmental research and public health · 2020Article
- Occupational Assessments of Risk Factors for Cardiovascular Diseases in Labors: An Application of Metabolic Syndrome Scoring Index.International journal of environmental research and public health · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundTo compare the accuracy of different obesity indexes, including waist circumference (WC), weight-to-height ratio (WHtR), body mass index (BMI), and lipid accumulation product (LAP), in predicting metabolic syndrome (MetS) and to estimate the optimal cutoffs of these indexes in a rural Chinese adult population.
methodsThis prospective cohort involved 8468 participants who were followed up for 6 years. MetS was defined by the International Diabetes Federation, American Heart Association, and National Heart, Lung, and Blood Institute criteria. The power of the 4 indexes for predicting MetS was estimated by receiver operating characteristic (ROC) curve analysis and optimal cutoffs were determined by the maximum of Youden's index.
resultsAs compared with WHtR, BMI, and LAP, WC had the largest area under the ROC curve (AUC) for predicting MetS after adjusting for age, smoking, drinking, physical activity, and education level. The AUCs (95% CIs) for WC, WHtR, BMI, and LAP for men and women were 0.862 (0.851-0.873) and 0.806 (0.794-0.817), 0.832 (0.820-0.843) and 0.789 (0.777-0.801), 0.824 (0.812-0.835) and 0.790 (0.778-0.802), and 0.798 (0.785-0.810) and 0.771 (0.759-0.784), respectively. The optimal cutoffs of WC for men and women were 83.30 and 76.80 cm. Those of WHtR, BMI, and LAP were approximately 0.51 and 0.50, 23.90 and 23.00 kg/m
conclusionsWC as a preferred index over WHtR, BMI, and LAP for predicting MetS in rural Chinese adults of both genders; the optimal cutoffs for men and women were 83.30 and 76.80 cm.
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.