Literature DB >> 25734622

Synergistic interactions among metabolic syndrome components and homeostasis model assessment of insulin resistance in a middle-aged general population over time.

Benedetta Maria Bonora1, Mariacristina Marescotti, Giorgio Marcuzzo, Angelo Avogaro, Gian Paolo Fadini.   

Abstract

BACKGROUND: Insulin resistance is considered a hallmark feature of the metabolic syndrome, but how metabolic syndrome components and insulin resistance measures interact over time is unclear. The homeostasis model assessment of insulin resistance (HOMA-IR) is a static index of insulin resistance typically used in epidemiological studies. We explored how HOMA-IR is affected by clustering metabolic syndrome components over time in a population of middle-aged, healthy subjects.
METHODS: A total of 1757 subjects aged 41.3±7.5 years (39% males) free from diabetes at baseline were followed-up for a median of 5.7 years. At baseline and at the end of observation, we determined metabolic syndrome components and HOMA-IR.
RESULTS: Cross-sectionally, HOMA-IR was synergistically increased by clustering of at least two to three metabolic syndrome components as determined at baseline and at study end by departure from additivity. Some combinations of metabolic syndrome components were associated with a significant synergic increase in HOMA-IR, and some combinations of two components entailed a synergistic risk of developing metabolic syndrome. Over time, the average change in HOMA-IR was more than additively affected by change in the number of metabolic syndrome components. Baseline HOMA-IR values were predictive of incident metabolic syndrome independent from age, sex, and each metabolic syndrome component.
CONCLUSIONS: We show synergistic interaction between clustering metabolic syndrome components and insulin resistance, estimated by HOMA-IR, cross-sectionally and over time. This more than additive effect explains the incremental value of HOMA-IR in predicting metabolic risk.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25734622     DOI: 10.1089/met.2014.0163

Source DB:  PubMed          Journal:  Metab Syndr Relat Disord        ISSN: 1540-4196            Impact factor:   1.894


  5 in total

Review 1.  Management of immunosuppressant agents following liver transplantation: Less is more.

Authors:  Mustafa S Ascha; Mona L Ascha; Ibrahim A Hanouneh
Journal:  World J Hepatol       Date:  2016-01-28

2.  Fasting triglycerides and glucose index is more suitable for the identification of metabolically unhealthy individuals in the Chinese adult population: A nationwide study.

Authors:  Xinwen Yu; Li Wang; Wencheng Zhang; Jie Ming; Aihua Jia; Shaoyong Xu; Qiaoyue Li; Qiuhe Ji
Journal:  J Diabetes Investig       Date:  2018-12-12       Impact factor: 4.232

3.  Positive correlation of serum angiopoietin-like protein 3 levels with metabolic syndrome in patients with coronary artery disease.

Authors:  Sy-Harn Lian; Bang-Gee Hsu; Ji-Hung Wang; Ming-Chun Chen
Journal:  Tzu Chi Med J       Date:  2021-08-14

4.  The association between metabolic syndrome and successful aging- using an extended definition of successful aging.

Authors:  Yi-Hsuan Lin; Jeng-Min Chiou; Ta-Fu Chen; Liang-Chuan Lai; Jen-Hau Chen; Yen-Ching Chen
Journal:  PLoS One       Date:  2021-11-30       Impact factor: 3.240

5.  Visceral adiposity indicators as predictors of metabolic syndrome in postmenopausal women.

Authors:  Gökçe Anık İlhan; Begüm Yıldızhan
Journal:  Turk J Obstet Gynecol       Date:  2019-10-10
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.