Literature DB >> 26781921

Optimal cut-off values for the homeostasis model assessment of insulin resistance (HOMA-IR) and pre-diabetes screening: Developments in research and prospects for the future.

Qi Tang1, Xueqin Li, Peipei Song, Lingzhong Xu.   

Abstract

Diabetes mellitus (DM) appears to be increasing rapidly, threatening to reduce life expectancy for humans around the globe. The International Diabetes Federation (IDF) has estimated that there will be 642 million people living with the disease by 2040 and half as many again who will be not diagnosed. This means that pre-DM screening is a critical issue. Insulin resistance (IR) has emerged as a major pathophysiological factor in the development and progression of DM since it is evident in susceptible individuals at the early stages of DM, and particularly type 2 DM (T2DM). Therefore, assessment of IR via the homeostasis model assessment of IR (HOMA-IR) is a key index for the primary prevention of DM and is thus found in guidelines for screening of high-risk groups. However, the cut-off values of HOMA-IR differ for different races, ages, genders, diseases, complications, etc. due to the complexity of IR. This hampers the determination of specific cut-off values of HOMA-IR in different places and in different situations. China has not published an official index to gauge IR for primary prevention of T2DM in the diabetic and non-diabetic population except for children and adolescents ages 6-12 years. Hence, this article summarizes developments in research on IR, HOMA-IR, and pre-DM screening in order to provide a reference for optimal cut-off values of HOMA-IR for the diagnosis of DM in the Chinese population.

Entities:  

Mesh:

Year:  2015        PMID: 26781921     DOI: 10.5582/ddt.2015.01207

Source DB:  PubMed          Journal:  Drug Discov Ther        ISSN: 1881-7831


  67 in total

1.  Association of IL-1β, IL-1Ra and FABP1 gene polymorphisms with the metabolic features of polycystic ovary syndrome.

Authors:  Nadia Rashid; Aruna Nigam; Pikee Saxena; S K Jain; Saima Wajid
Journal:  Inflamm Res       Date:  2017-04-12       Impact factor: 4.575

2.  [Association of waist-to-hip ratio with insulin resistance in non-diabetic normal-weight individuals: a cross-sectional study].

Authors:  Xing-Yan Yang; Meng-Jiao Shao; Qin Zhou; Yue Xia; He-Qun Zou
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2017-11-20

3.  Insulin Resistance and Cancer-Specific and All-Cause Mortality in Postmenopausal Women: The Women's Health Initiative.

Authors:  Kathy Pan; Rebecca A Nelson; Jean Wactawski-Wende; Delphine J Lee; JoAnn E Manson; Aaron K Aragaki; Joanne E Mortimer; Lawrence S Phillips; Thomas Rohan; Gloria Y F Ho; Nazmus Saquib; Aladdin H Shadyab; Rami Nassir; Jinnie J Rhee; Arti Hurria; Rowan T Chlebowski
Journal:  J Natl Cancer Inst       Date:  2020-02-01       Impact factor: 13.506

4.  Bridging the gap between science and society: long-term effects of the Healthy Lifestyle Community Programme (HLCP, cohort 1) on weight and the metabolic risk profile: a controlled study.

Authors:  Corinna Anand; Ragna-Marie Kranz; Sarah Husain; Christian Koeder; Nora Schoch; Dima-Karam Alzughayyar; Reinhold Gellner; Karin Hengst; Heike Englert
Journal:  BMJ Nutr Prev Health       Date:  2022-02-22

5.  Haptoglobin levels, but not Hp1-Hp2 polymorphism, are associated with polycystic ovary syndrome.

Authors:  Laura M L Carvalho; Cláudia N Ferreira; Daisy K D de Oliveira; Kathryna F Rodrigues; Rita C F Duarte; Márcia F A Teixeira; Luana B Xavier; Ana Lúcia Candido; Fernando M Reis; Ieda F O Silva; Fernanda M F Campos; Karina B Gomes
Journal:  J Assist Reprod Genet       Date:  2017-09-13       Impact factor: 3.412

6.  Obstructive sleep apnea and insulin resistance in children with obesity.

Authors:  Rasintra Siriwat; Lu Wang; Vaishal Shah; Reena Mehra; Sally Ibrahim
Journal:  J Clin Sleep Med       Date:  2020-07-15       Impact factor: 4.062

7.  Visceral fat, cardiometabolic risk factors, and nocturnal blood pressure fall in young adults with primary hypertension.

Authors:  Tomasz Miazgowski; Aleksandra Taszarek; Bartosz Miazgowski
Journal:  J Clin Hypertens (Greenwich)       Date:  2019-08-01       Impact factor: 3.738

8.  Polycystic ovary syndrome: clinical and laboratory variables related to new phenotypes using machine-learning models.

Authors:  A A Veloso; K B Gomes; I S Silva; C N Ferreira; L B X Costa; M O Sóter; L M L Carvalho; J de C Albuquerque; M F Sales; A L Candido; F M Reis
Journal:  J Endocrinol Invest       Date:  2021-09-15       Impact factor: 4.256

9.  The immune-opioid axis in prediabetes: predicting prediabetes with insulin resistance by plasma interleukin-10 and endomorphin-2 to kappa-opioid receptors ratio.

Authors:  Shatha Rouf Moustafa
Journal:  Diabetol Metab Syndr       Date:  2021-06-07       Impact factor: 3.320

Review 10.  Phenotyping the Prediabetic Population-A Closer Look at Intermediate Glucose Status and Cardiovascular Disease.

Authors:  Elena Barbu; Mihaela-Roxana Popescu; Andreea-Catarina Popescu; Serban-Mihai Balanescu
Journal:  Int J Mol Sci       Date:  2021-06-25       Impact factor: 5.923

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