Literature DB >> 31149139

CORRELATION BETWEEN THE WAIST CIRCUMFERENCE, DIASTOLIC BLOOD PRESSURE AND INSULIN RESISTANCE IN NON-OBESE YOUNG ADULTS.

M Niţescu1,2, A Streinu-Cercel3,2, M Tusaliu4, D Piţigoi3, M Oţelea3.   

Abstract

CONTEXT: The metabolic syndrome is a profound, systemic impairment of the metabolism of lipids, carbohydrates and branched amino-acids, affecting specially obese people. Recently, many studies outlined the presence of the metabolic syndrome, also in non obese persons. OBJECTIVE AND
DESIGN: To assess the relationship between insulin resistance and the cardiovascular component of the metabolic syndrome in a group of young, non obese subjects using a cross sectional study. SUBJECTS AND METHODS: We enrolled 103 subjects with body mass index < 30 Kg/m2, without metabolic syndrome to whom fasting glucose, triglycerides, high density lipoprotein cholesterol, insulinemia, waist circumference and arterial pressure were recorded in a cross-sectional approach. Insulin resistance was evaluated using the homeostasis model assessment for insulin (HOMA-IR) index. Statistic data processing included Pearson relation and multiple regression (backward method), using the SPSS version 21 software.
RESULTS: A significant relationship between waist circumference, diastolic blood pressure and HOMA-IR is found. High value of HOMA-IR (>2.6) was more frequently in men (p=0.011). The incidence of the 2 metabolic components mentioned above was higher in the high value HOMA-IR group: 33% vs. 7% in women and 50% vs. 4% in men. Multiple regression showed a strong correlation between HOMA-IR and waist circumference (p<0.001) and diastolic blood pressure (p=0.008) that was maintained inside the women group (p=0.016 and p=0.032, respectively). In men, HOMA-IR correlated with waist circumference (p=0.031).
CONCLUSION: We found a significant interdepen-dence between waist circumference, diastolic blood pressure and HOMA-IR. Based on our results, we consider that lifestyle intervention should start as soon as abnormal waist circumference is recorded.

Entities:  

Keywords:  HOMA-IR; diastolic blood pressure; metabolically non-obese young population; waist circumference

Year:  2016        PMID: 31149139      PMCID: PMC6535238          DOI: 10.4183/aeb.2016.493

Source DB:  PubMed          Journal:  Acta Endocrinol (Buchar)        ISSN: 1841-0987            Impact factor:   0.877


  31 in total

1.  Prevalence and determinants of insulin resistance among U.S. adolescents: a population-based study.

Authors:  Joyce M Lee; Megumi J Okumura; Matthew M Davis; William H Herman; James G Gurney
Journal:  Diabetes Care       Date:  2006-11       Impact factor: 19.112

2.  The prevalence of the metabolic syndrome in young adults. The Cardiovascular Risk in Young Finns Study.

Authors:  N Mattsson; T Rönnemaa; M Juonala; J S A Viikari; O T Raitakari
Journal:  J Intern Med       Date:  2007-02       Impact factor: 8.989

3.  Identification of individuals with insulin resistance using routine clinical measurements.

Authors:  Steven E Stern; Ken Williams; Eleuterio Ferrannini; Ralph A DeFronzo; Clifton Bogardus; Michael P Stern
Journal:  Diabetes       Date:  2005-02       Impact factor: 9.461

4.  Cigarette smoking and fat distribution in 21,828 British men and women: a population-based study.

Authors:  Dexter Canoy; Nicholas Wareham; Robert Luben; Ailsa Welch; Sheila Bingham; Nicholas Day; Kay-Tee Khaw
Journal:  Obes Res       Date:  2005-08

Review 5.  Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage.

Authors:  Ranganath Muniyappa; Sihoon Lee; Hui Chen; Michael J Quon
Journal:  Am J Physiol Endocrinol Metab       Date:  2007-10-23       Impact factor: 4.310

6.  Tobacco smoking in relation to body fat mass and distribution in a general population sample.

Authors:  C Bamia; A Trichopoulou; D Lenas; D Trichopoulos
Journal:  Int J Obes Relat Metab Disord       Date:  2004-08

7.  The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999-2004).

Authors:  Rachel P Wildman; Paul Muntner; Kristi Reynolds; Aileen P McGinn; Swapnil Rajpathak; Judith Wylie-Rosett; MaryFran R Sowers
Journal:  Arch Intern Med       Date:  2008-08-11

8.  Diagnosing insulin resistance by simple quantitative methods in subjects with normal glucose metabolism.

Authors:  Juan F Ascaso; Susana Pardo; José T Real; Rosario I Lorente; Antonia Priego; Rafael Carmena
Journal:  Diabetes Care       Date:  2003-12       Impact factor: 19.112

Review 9.  Gender differences in insulin resistance, body composition, and energy balance.

Authors:  Eliza B Geer; Wei Shen
Journal:  Gend Med       Date:  2009

Review 10.  Antidiabetic actions of estrogen: insight from human and genetic mouse models.

Authors:  Jean-Francois Louet; Cedric LeMay; Franck Mauvais-Jarvis
Journal:  Curr Atheroscler Rep       Date:  2004-05       Impact factor: 5.113

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