ArticleClinical interventions in aging2017
Models for estimating the metabolic syndrome biological age as the new index for evaluation and management of metabolic syndrome.
Article in Clinical interventions in aging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Molecular markers, mechanisms and metrics of biological aging: a scoping review.Frontiers in aging · 2026Review
- Article
- AcidAGE: a biological age determination neural network based on urine organic acids.Biogerontology · 2024Article
- EchoAGE: Echocardiography-based Neural Network Model Forecasting Heart Biological Age.Aging and disease · 2024Article
- Progress in biological age research.Frontiers in public health · 2023Review
- A Model for Estimating Biological Age From Physiological Biomarkers of Healthy Aging: Cross-sectional Study.JMIR aging · 2022Article
- Article
- Biological age and lifestyle in the diagnosis of metabolic syndrome: the NHIS health screening data, 2014-2015.Scientific reports · 2021Article
- Biological Age Is Associated with the Active Use of Nutrition Data.International journal of environmental research and public health · 2018Article
- Is Sleep Duration Associated with Biological Age (BA)?: Analysis of (2010⁻2015) South Korean NHANES Dataset South Korea.International journal of environmental research and public health · 2018Article
- Biological age as a health index for mortality and major age-related disease incidence in Koreans: National Health Insurance Service - Health screening 11-year follow-up study.Clinical interventions in aging · 2018Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aims to propose a metabolic syndrome (MS) biological age model, through which overall evaluation and management of the health status and aging state in MS can be done easily. Through this model, we hope to provide a novel evaluation and management health index that can be utilized in various health care fields. PATIENT AND
methodsMS parameters from American Heart Association/National Heart, Lung, and Blood Institute guidelines in 2005 were used as biomarkers for the estimation of MS biological age. MS biological age model development was done by analyzing data of 263,828 participants and clinical application of the developed MS biological age was assessed by analyzing the data of 188,886 subjects.
resultsThe principal component accounted for 36.1% in male and 38.9% in female of the total variance in the battery of five variables. The correlation coefficient between corrected biological age and chronological age in males and females were 0.711 and 0.737, respectively. Significant difference for mean MS biological age and chronological age between the three groups, normal, at risk and MS, was seen (
conclusionFor the comprehensive approach in MS management, MS biological age is expected to be additionally utilized as a novel evaluation and management index along with the traditional MS diagnosis.
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