Literature DB >> 32753917

Evaluation of Several Anthropometric and Metabolic Indices as Correlates of Hyperglycemia in Overweight/Obese Adults.

Maryam Abolhasani1, Nastaran Maghbouli2, Faeze Sazgara3, Shahrokh Karbalai Saleh4, Maryam Tahmasebi5, Haleh Ashraf1,4.   

Abstract

AIM: Rapid and growing rise in obesity and diabetes mellitus, as serious human health-threatening issues, is alarming. The aim of the present study was assessing the accuracy of several obesity indices to predict hyperglycemia in overweight and obese Iranian populations and determining the value of such indices in comparison to the conventional parameters. We also evaluated new latent combined scores in this matter. PATIENTS AND METHODS: Overall, there were 2088 patients recruited from the weight loss clinic of Sina Hospital, an educational hospital of Tehran University of Medical Sciences for this cross-sectional study. Demographic information, anthropometric indices and biochemical measurements were collected and calculated. The multivariable regression modeling as well as area under the receiver-operating characteristic (ROC) analysis was used. To detect the existence of new combined scores, we used SEM (structural equation modeling) analysis through SmartPLS.
RESULTS: Combined latent scores and WHtR (waist-to-height ratio) gave us a higher area under the curve in predicting hyperglycemia associated with WC (waist circumference) in women, whereas FFMI (fat-free mass index) gave low values. Additionally, BRI (body roundness index) and latent scores had slightly higher AUC values in predicting hyperglycemia in men. According to the age-adjusted odds ratio (OR) in the presence of hyperglycemia, OR was the highest for WHR (waist to hip ratio) in women (OR, 7.74; 95% confidence interval [CI], 1.71-15.13). The association of WHR and hyperglycemia remained significant by adjusting for BMI (body mass index), WC and menopausal status.
CONCLUSION: WHR had the strongest association with hyperglycemia in women with only sufficient discrimination ability. However, neither BSI (body shape index) and BAI (body adiposity index) nor FMI (fat mass index) and FFMI were superior to BMI (body mass index), WC or WHtR in predicting hyperglycemia. It was revealed that BRI and combined scores had a more predictive power compared to the BSI, BAI, FMI and FFMI, simplifying hyperglycemia evaluation.
© 2020 Abolhasani et al.

Entities:  

Keywords:  anthropometric indices; diabetes mellitus; obesity

Year:  2020        PMID: 32753917      PMCID: PMC7342503          DOI: 10.2147/DMSO.S254741

Source DB:  PubMed          Journal:  Diabetes Metab Syndr Obes        ISSN: 1178-7007            Impact factor:   3.168


  44 in total

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Journal:  Acta Med Iran       Date:  2015-10

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Authors:  Alireza Esteghamati; Koorosh Etemad; Jalil Koohpayehzadeh; Mehrshad Abbasi; Alipasha Meysamie; Sina Noshad; Fereshteh Asgari; Mostafa Mousavizadeh; Ali Rafei; Elias Khajeh; Mohamadreza Neishaboury; Sara Sheikhbahaei; Manouchehr Nakhjavani
Journal:  Diabetes Res Clin Pract       Date:  2014-01-03       Impact factor: 5.602

3.  Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.

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Authors:  Nir Y Krakauer; Jesse C Krakauer
Journal:  PLoS One       Date:  2012-07-18       Impact factor: 3.240

5.  The association of hypertriglyceridemic waist phenotype with type 2 diabetes mellitus among individuals with first relative history of diabetes.

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6.  The "lipid accumulation product" performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison.

Authors:  Henry S Kahn
Journal:  BMC Cardiovasc Disord       Date:  2005-09-08       Impact factor: 2.298

7.  A Novel Visceral Adiposity Index for Prediction of Type 2 Diabetes and Pre-diabetes in Chinese adults: A 5-year prospective study.

Authors:  Jinshan Wu; Lilin Gong; Qifu Li; Jinbo Hu; Shuping Zhang; Yue Wang; Huang Zhou; Shuming Yang; Zhihong Wang
Journal:  Sci Rep       Date:  2017-10-23       Impact factor: 4.379

8.  The utility of fat mass index vs. body mass index and percentage of body fat in the screening of metabolic syndrome.

Authors:  Pengju Liu; Fang Ma; Huiping Lou; Yanping Liu
Journal:  BMC Public Health       Date:  2013-07-03       Impact factor: 3.295

9.  Body mass index, waist circumference, body adiposity index, and risk for type 2 diabetes in two populations in Brazil: general and Amerindian.

Authors:  Rafael de Oliveira Alvim; Carlos Alberto Mourao-Junior; Camila Maciel de Oliveira; José E Krieger; José G Mill; Alexandre C Pereira
Journal:  PLoS One       Date:  2014-06-17       Impact factor: 3.240

10.  Comparison of waist to height ratio and body indices for prediction of metabolic disturbances in the Korean population: the Korean National Health and Nutrition Examination Survey 2008-2011.

Authors:  Seok Hui Kang; Kyu Hyang Cho; Jong Won Park; Jun Young Do
Journal:  BMC Endocr Disord       Date:  2015-12-08       Impact factor: 2.763

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1.  High incidence of type 1 diabetes, type 2 diabetes and gestational diabetes in Central Iran: A six years results from Semnan health cohort.

Authors:  Masoudeh Babakhanian; Alireza Razavi; Sajjad Rahimi Pordanjani; Sepehr Hassanabadi; Gholamreza Mohammadi; Abolfazl Fattah
Journal:  Ann Med Surg (Lond)       Date:  2022-09-23
  1 in total

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