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Lizarzaburu-Robles JC, Herman WH, Garro-Mendiola A, Galdón Sanz-Pastor A, Lorenzo O. Prediabetes and Cardiometabolic Risk: The Need for Improved Diagnostic Strategies and Treatment to Prevent Diabetes and Cardiovascular Disease. Biomedicines 2024; 12:363. [PMID: 38397965 PMCID: PMC10887025 DOI: 10.3390/biomedicines12020363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 01/15/2024] [Accepted: 01/18/2024] [Indexed: 02/25/2024] Open
Abstract
The progression from prediabetes to type-2 diabetes depends on multiple pathophysiological, clinical, and epidemiological factors that generally overlap. Both insulin resistance and decreased insulin secretion are considered to be the main causes. The diagnosis and approach to the prediabetic patient are heterogeneous. There is no agreement on the diagnostic criteria to identify prediabetic subjects or the approach to those with insufficient responses to treatment, with respect to regression to normal glycemic values or the prevention of complications. The stratification of prediabetic patients, considering the indicators of impaired fasting glucose, impaired glucose tolerance, or HbA1c, can help to identify the sub-phenotypes of subjects at risk for T2DM. However, considering other associated risk factors, such as impaired lipid profiles, or risk scores, such as the Finnish Diabetes Risk Score, may improve classification. Nevertheless, we still do not have enough information regarding cardiovascular risk reduction. The sub-phenotyping of subjects with prediabetes may provide an opportunity to improve the screening and management of cardiometabolic risk in subjects with prediabetes.
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Affiliation(s)
- Juan Carlos Lizarzaburu-Robles
- Endocrinology Unit, Hospital Central de la Fuerza Aérea del Perú, 15046 Lima, Peru;
- Doctorate Program, Universidad Autónoma de Madrid, 28049 Madrid, Spain
| | - William H. Herman
- Department of Internal Medicine and Epidemiology, University of Michigan, Ann Arbor, MI 48109, USA;
| | | | | | - Oscar Lorenzo
- Laboratory of Diabetes and Vascular Pathology, IIS-Fundación Jiménez Díaz, Universidad Autónoma, 28049 Madrid, Spain;
- Biomedical Research Network on Diabetes and Associated Metabolic Disorders (CIBERDEM), Carlos III National Health Institute, 28029 Madrid, Spain
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Calabria E, Muollo V, Cavedon V, Capovin T, Saccenti L, Passarotti F, Ghiotto L, Milanese C, Gelati M, Rudi D, Salvagno GL, Lippi G, Tam E, Schena F, Pogliaghi S. Type 2 Diabetes Related Mitochondrial Defects in Peripheral Mononucleated Blood Cells from Overweight Postmenopausal Women. Biomedicines 2023; 11. [PMID: 36672627 DOI: 10.3390/biomedicines11010121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/24/2022] [Accepted: 12/30/2022] [Indexed: 01/05/2023] Open
Abstract
Type 2 diabetes (T2D) is a multisystem disease that is the subject of many studies, but the earliest cause of the disease has yet to be elucidated. Mitochondrial impairment has been associated with diabetes in several tissues. To extend the association between T2D and mitochondrial impairment to blood cells, we investigated T2D-related changes in peripheral mononucleated blood cells’ (PBMCs) mitochondrial function in two groups of women (CTRL vs. T2D; mean age: 54.1 ± 3.8 vs. 60.9 ± 4.8; mean BMI 25.6 ± 5.2 vs. 30.0 ± 5), together with a panel of blood biomarkers, anthropometric measurements and physiological parameters (VO2max and strength tests). Dual-energy X-ray absorptiometry (DXA) scan analysis, cardio-pulmonary exercise test and blood biomarkers confirmed hallmarks of diabetes in the T2D group. Mitochondrial function assays performed with high resolution respirometry highlighted a significant reduction of mitochondrial respiration in the ADP-stimulated state (OXPHOS; −30%, p = 0.006) and maximal non-coupled respiration (ET; −30%, p = 0.004) in PBMCs samples from the T2D group. The total glutathione antioxidant pool (GSHt) was significantly reduced (−38%: p = 0.04) in plasma samples from the T2D group. The fraction of glycated hemoglobin (Hb1Ac) was positively associated with markers of inflammation (C-reactive protein-CRP r = 0.618; p = 0.006) and of dyslipidemia (triglycerides-TG r = 0.815; p < 0.0001). The same marker (Hb1Ac) was negatively associated with mitochondrial activity levels (OXPHOS r = −0.502; p = 0.034; ET r = −0.529; p = 0.024). The results obtained in overweight postmenopausal women from analysis of PBMCs mitochondrial respiration and their association with anthropometric and physiological parameters indicate that PBMC could represent a reliable model for studying T2D-related metabolic impairment and could be useful for testing the effectiveness of interventions targeting mitochondria.
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Magkos F, Reeds DN, Mittendorfer B. Evolution of the diagnostic value of "the sugar of the blood": hitting the sweet spot to identify alterations in glucose dynamics. Physiol Rev 2023; 103:7-30. [PMID: 35635320 PMCID: PMC9576168 DOI: 10.1152/physrev.00015.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/23/2022] [Accepted: 05/24/2022] [Indexed: 11/22/2022] Open
Abstract
In this paper, we provide an overview of the evolution of the definition of hyperglycemia during the past century and the alterations in glucose dynamics that cause fasting and postprandial hyperglycemia. We discuss how extensive mechanistic, physiological research into the factors and pathways that regulate the appearance of glucose in the circulation and its uptake and metabolism by tissues and organs has contributed knowledge that has advanced our understanding of different types of hyperglycemia, namely prediabetes and diabetes and their subtypes (impaired fasting plasma glucose, impaired glucose tolerance, combined impaired fasting plasma glucose, impaired glucose tolerance, type 1 diabetes, type 2 diabetes, gestational diabetes mellitus), their relationships with medical complications, and how to prevent and treat hyperglycemia.
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Affiliation(s)
- Faidon Magkos
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark
| | - Dominic N Reeds
- Center for Human Nutrition, Washington University School of Medicine, St. Louis, Missouri
| | - Bettina Mittendorfer
- Center for Human Nutrition, Washington University School of Medicine, St. Louis, Missouri
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Auad R, Kakaje A, Alourfi Z. Prediabetes in Syria and Its Associated Factors: A Single-Center Cross-Sectional Study. Diabetes Ther 2022; 13:1573-1583. [PMID: 35821495 PMCID: PMC9399325 DOI: 10.1007/s13300-022-01293-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 06/20/2022] [Indexed: 11/27/2022] Open
Abstract
INTRODUCTION Prediabetes is a major risk factor for diabetes and many chronic complications, particularly cardiovascular disease (CVD). Risk factors vary among races and demographics. This is the first study to assess prediabetes in Syria and its relevant risk factors. METHODS This cross-sectional study was conducted in a primary health clinic in Al-Mouwasat University Hospital, the major Hospital in Damascus, Syria. Interviews, examinations, and blood investigations were carried out by qualified physicians in the clinic. RESULTS This study included 406 participants, of which 363 (89.4%) were females, 43(10.6%) were males, 91 (22.4%) had prediabetes, 108 (26.6%) were overweight, and 231 (56.9%) were obese. Older age, positive family history of diabetes, obesity, abdominal obesity in females, high cholesterol, being married, and CVD were statistically significantly associated with prediabetes (p < 0.05). However, prediabetes was not associated with gender, living in the city or country, cigarette smoking, hypertension, diet, triglycerides, or polycystic ovary syndrome (p > 0.05). However, in the multivariable analysis, only high cholesterol, familial diabetes, and waist diameter had significant association. CONCLUSIONS Prevalence of prediabetes in our study in Syria was higher than what was estimated by previous studies. While many risk factors were similar to other countries in the regions, other risk factors differed. These results were highly reflective of high burden of prediabetes and diabetes, mainly in relatively young females. Further studies are required to tackle this rising issue as it imposes major complications in the long term, and the high financial burden on the health care system.
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Affiliation(s)
- Rama Auad
- Division of Endocrinology, Department of Internal Medicine, Faculty of Medicine, Damascus University, Damascus, Syria.
- Damascus University, Faculty of Medicine, Damascus, Syria.
| | - Ameer Kakaje
- Damascus University, Faculty of Medicine, Damascus, Syria
| | - Zaynab Alourfi
- Division of Endocrinology, Department of Internal Medicine, Faculty of Medicine, Damascus University, Damascus, Syria
- Damascus University, Faculty of Medicine, Damascus, Syria
- Department of Internal Medicine, Faculty of Medicine, Damascus University, Damascus, Syria
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Magkos F, Mittendorfer B. Editorial: Type 2 diabetes therapeutics: weight loss and other strategies. Curr Opin Clin Nutr Metab Care 2022; 25:256-259. [PMID: 35762161 DOI: 10.1097/mco.0000000000000839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Faidon Magkos
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
| | - Bettina Mittendorfer
- Center for Human Nutrition, Washington University School of Medicine, St. Louis, Missouri, USA
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Zhou Y, Yang G, Qu C, Chen J, Qian Y, Yuan L, Mao T, Xu Y, Li X, Zhen S, Liu S. Predictive performance of lipid parameters in identifying undiagnosed diabetes and prediabetes: a cross-sectional study in eastern China. BMC Endocr Disord 2022; 22:76. [PMID: 35331213 PMCID: PMC8952267 DOI: 10.1186/s12902-022-00984-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 03/08/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Dyslipidaemia is a risk factor for abnormal blood glucose. However, studies on the predictive values of lipid markers in prediabetes and diabetes simultaneously are limited. This study aimed to assess the associations and predictive abilities of lipid indices and abnormal blood glucose. METHODS A sample of 7667 participants without diabetes were enrolled in this cross-sectional study conducted in 2016, and all of them were classified as having normal glucose tolerance (NGT), prediabetes or diabetes. Blood glucose, blood pressure and lipid parameters (triglycerides, TG; total cholesterol, TC; high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; non-high-density lipoprotein cholesterol, non-HDL-C; and triglyceride glucose index, TyG) were evaluated or calculated. Logistic regression models were used to analyse the association between lipids and abnormal blood glucose. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the discriminatory power of lipid parameters for detecting prediabetes or diabetes. RESULTS After adjustment for potential confounding factors, the TyG was the strongest marker related to abnormal blood glucose compared to other lipid indices, with odds ratios of 2.111 for prediabetes and 5.423 for diabetes. For prediabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.605, 0.617, 0.481, 0.615, 0.603, 0.590, 0.626 and 0.660, respectively, and the cut-off points were 1.34, 4.59, 1.42, 2.69, 3.39, 1.00, 3.19 and 8.52, respectively. For diabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.712, 0.679, 0.440, 0.652, 0.686, 0.692, 0.705, and 0.827, respectively, and the cut-off points were 1.35, 4.68, 1.42, 2.61, 3.44, 0.98, 3.13 and 8.80, respectively. CONCLUSIONS The TyG, TG and non-HDL-C, especially TyG, are accessible biomarkers for screening individuals with undiagnosed diabetes.
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Affiliation(s)
- Yimin Zhou
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China
| | - Guoping Yang
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Chen Qu
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Jiaping Chen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China
| | - Yinan Qian
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China
| | - Lei Yuan
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China
| | - Tao Mao
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Yan Xu
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Xiaoning Li
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Shiqi Zhen
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China.
| | - Sijun Liu
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China.
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Zhu X, Yang Z, He Z, Hu J, Yin T, Bai H, Li R, Cai L, Guo H, Li M, Yan T, Li Y, Shen C, Sun K, Liu Y, Sun Z, Wang B. Factors correlated with targeted prevention for prediabetes classified by impaired fasting glucose, impaired glucose tolerance, and elevated HbA1c: A population-based longitudinal study. Front Endocrinol (Lausanne) 2022; 13:965890. [PMID: 36072930 PMCID: PMC9441664 DOI: 10.3389/fendo.2022.965890] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND There is still controversy surrounding the precise characterization of prediabetic population. We aim to identify and examine factors of demographic, behavioral, clinical, and biochemical characteristics, and obesity indicators (anthropometric characteristics and anthropometric prediction equation) for prediabetes according to different definition criteria of the American Diabetes Association (ADA) in the Chinese population. METHODS A longitudinal study consisted of baseline survey and two follow-ups was conducted, and a pooled data were analyzed. Prediabetes was defined as either impaired fasting glucose (IFG), impaired glucose tolerance (IGT), or elevated glycosylated hemoglobin (HbA1c) according to the ADA criteria. Robust generalized estimating equation models were used. RESULTS A total of 5,713 (58.42%) observations were prediabetes (IGT, 38.07%; IGT, 26.51%; elevated HbA1c, 23.45%); 9.66% prediabetes fulfilled all the three ADA criteria. Among demographic characteristics, higher age was more evident in elevated HbA1c [adjusted OR (aOR)=2.85]. Female individuals were less likely to have IFG (aOR=0.70) and more likely to suffer from IGT than male individuals (aOR=1.41). Several inconsistency correlations of biochemical characteristics and obesity indicators were detected by prediabetes criteria. Body adiposity estimator exhibited strong association with prediabetes (D10: aOR=4.05). For IFG and elevated HbA1c, the odds of predicted lean body mass exceed other indicators (D10: aOR=3.34; aOR=3.64). For IGT, predicted percent fat presented the highest odds (D10: aOR=6.58). CONCLUSION Some correlated factors of prediabetes under different criteria differed, and obesity indicators were easily measured for target identification. Our findings could be used for targeted intervention to optimize preventions to mitigate the obviously increased prevalence of diabetes.
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Affiliation(s)
- Xiaoyue Zhu
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Zhipeng Yang
- School of Software, Fudan University, Shanghai, China
| | - Zhiliang He
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Jingyao Hu
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Tianxiu Yin
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Hexiang Bai
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Ruoyu Li
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Le Cai
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Haijian Guo
- Integrated Business Management Office, Jiangsu Province Centre Disease Control and Prevention, Nanjing, China
| | - Mingma Li
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Tao Yan
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - You Li
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Chenye Shen
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Kaicheng Sun
- Yandu Centre for Disease Control and Prevention, Yancheng, China
| | - Yu Liu
- Jurong Centre for Disease Control and Prevention, Jurong, China
| | - Zilin Sun
- Department of Endocrinology, Institute of Diabetes, Medical School, Southeast University, Nanjing, China
| | - Bei Wang
- Key Laboratory of Environment Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
- *Correspondence: Bei Wang,
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Sathish T, Tapp RJ, Shaw JE. Do lifestyle interventions reduce diabetes incidence in people with isolated impaired fasting glucose? Diabetes Obes Metab 2021; 23:2827-2828. [PMID: 34432366 DOI: 10.1111/dom.14529] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 08/13/2021] [Accepted: 08/16/2021] [Indexed: 01/24/2023]
Affiliation(s)
| | - Robyn J Tapp
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Intelligent Healthcare, Faculty of Health and Life Sciences, Coventry University, Coventry, UK
| | - Jonathan E Shaw
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
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Tura A, Grespan E, Göbl CS, Koivula RW, Franks PW, Pearson ER, Walker M, Forgie IM, Giordano GN, Pavo I, Ruetten H, Dermitzakis ET, McCarthy MI, Pedersen O, Schwenk JM, Adamski J, De Masi F, Tsirigos KD, Brunak S, Viñuela A, Mahajan A, McDonald TJ, Kokkola T, Vangipurapu J, Cederberg H, Laakso M, Rutters F, Elders PJM, Koopman ADM, Beulens JW, Ridderstråle M, Hansen TH, Allin KH, Hansen T, Vestergaard H, Mari A. Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study. Diabetes 2021; 70:2092-2106. [PMID: 34233929 DOI: 10.2337/db21-0227] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 06/24/2021] [Indexed: 11/13/2022]
Abstract
Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (P < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr (P < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, P < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.
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Affiliation(s)
- Andrea Tura
- CNR Institute of Neuroscience, Padova, Italy
| | | | - Christian S Göbl
- Division of Obstetrics and Feto-Maternal Medicine, Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
| | - Robert W Koivula
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- Genetic and Molecular Epidemiology, Department of Clinical Science, Lund University, Skåne University Hospital Malmö, Malmö, Sweden
| | - Paul W Franks
- Genetic and Molecular Epidemiology, Department of Clinical Science, Lund University, Skåne University Hospital Malmö, Malmö, Sweden
| | - Ewan R Pearson
- Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, Scotland, U.K
| | - Mark Walker
- Institute of Cellular Medicine, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, U.K
| | - Ian M Forgie
- Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, Scotland, U.K
| | - Giuseppe N Giordano
- Genetic and Molecular Epidemiology, Department of Clinical Science, Lund University, Skåne University Hospital Malmö, Malmö, Sweden
| | - Imre Pavo
- Eli Lilly Regional Operations Ges.m.b.H., Vienna, Austria
| | - Hartmut Ruetten
- CardioMetabolism & Respiratory Medicine, Boehringer Ingelheim International GmbH, Ingelheim/Rhein, Germany
| | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Mark I McCarthy
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Oluf Pedersen
- Section of Metabolic Genetics, Novo Nordisk Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Jochen M Schwenk
- Affinity Proteomics, Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Federico De Masi
- Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
- Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Konstantinos D Tsirigos
- Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
- Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Søren Brunak
- Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
- Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ana Viñuela
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, U.K
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Timothy J McDonald
- Blood Sciences, Royal Devon and Exeter NHS Foundation Trust, Exeter, U.K
| | - Tarja Kokkola
- Internal Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jagadish Vangipurapu
- Internal Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Henna Cederberg
- Internal Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Markku Laakso
- Internal Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Femke Rutters
- Department of Epidemiology and Data Science, Amsterdam Medical Centre, location VUMC, Amsterdam, the Netherlands
| | - Petra J M Elders
- Department of Epidemiology and Data Science, Amsterdam Medical Centre, location VUMC, Amsterdam, the Netherlands
| | - Anitra D M Koopman
- Department of Epidemiology and Data Science, Amsterdam Medical Centre, location VUMC, Amsterdam, the Netherlands
| | - Joline W Beulens
- Department of Epidemiology and Data Science, Amsterdam Medical Centre, location VUMC, Amsterdam, the Netherlands
| | - Martin Ridderstråle
- Department of Clinical Sciences, Diabetes & Endocrinology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden
| | - Tue H Hansen
- Section of Metabolic Genetics, Novo Nordisk Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Kristine H Allin
- Section of Metabolic Genetics, Novo Nordisk Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Section of Metabolic Genetics, Novo Nordisk Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Vestergaard
- Section of Metabolic Genetics, Novo Nordisk Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Bornholms Hospital, Rønne, Denmark
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Luzi L, Carruba M, Crialesi R, Da Empoli S, Dagani R, Lovati E, Nicolucci A, Berra CC, Cipponeri E, Vaccaro K, Lenzi A. Telemedicine and urban diabetes during COVID-19 pandemic in Milano, Italy during lock-down: epidemiological and sociodemographic picture. Acta Diabetol 2021; 58:919-927. [PMID: 33740123 PMCID: PMC7977495 DOI: 10.1007/s00592-021-01700-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/03/2021] [Indexed: 12/15/2022]
Abstract
BACKGROUND Since 2010, more than half of World population lives in Urban Environments. Urban Diabetes has arisen as a novel nosological entity in Medicine. Urbanization leads to the accrual of a number of factors increasing the vulnerability to diabetes mellitus and related diseases. Herein we report clinical-epidemiological data of the Milano Metropolitan Area in the contest of the Cities Changing Diabetes Program. Since the epidemiological picture was taken in January 2020, on the edge of COVID-19 outbreak in the Milano Metropolitan Area, a perspective addressing potential interactions between diabetes and obesity prevalence and COVID-19 outbreak, morbidity and mortality will be presented. To counteract lock-down isolation and, in general, social distancing a pilot study was conducted to assess the feasibility and efficacy of tele-monitoring via Flash Glucose control in a cohort of diabetic patients in ASST North Milano. METHODS Data presented derive from 1. ISTAT (National Institute of Statistics of Italy), 2. Milano ATS web site (Health Agency of Metropolitan Milano Area), which entails five ASST (Health Agencies in the Territories). A pilot study was conducted in 65 screened diabetic patients (only 40 were enrolled in the study of those 36 were affected by type 2 diabetes and 4 were affected by type 1 diabetes) of ASST North Milano utilizing Flash Glucose Monitoring for 3 months (mean age 65 years, HbA1c 7,9%. Patients were subdivided in 3 groups using glycemic Variability Coefficient (VC): a. High risk, VC > 36, n. 8 patients; Intermediate risk 20 < VC < 36, n. 26 patients; Low risk VC < 20, n. 4 patients. The control group was constituted by 26 diabetic patients non utilizing Flash Glucose monitoring. RESULTS In a total population of 3.227.264 (23% is over 65 y) there is an overall prevalence of 5.65% with a significant difference between Downtown ASST (5.31%) and peripheral ASST (ASST North Milano, 6.8%). Obesity and overweight account for a prevalence of 7.8% and 27.7%, respectively, in Milano Metropolitan Area. We found a linear relationship (R = 0.36) between prevalence of diabetes and aging index. Similarly, correlations between diabetes prevalence and both older people depending index and structural dependence index (R = 0.75 and R = 0.93, respectively), were found. A positive correlation (R = 0.46) with percent of unoccupied people and diabetes prevalence was also found. A reverse relationship between diabetes prevalence and University level instruction rate was finally identified (R = - 0.82). Our preliminary study demonstrated a reduction of Glycated Hemoglobin (p = 0.047) at 3 months follow-up during the lock-down period, indicating Flash Glucose Monitoring and remote control as a potential methodology for diabetes management during COVID-19 lock-down. HYPOTHESIS AND DISCUSSION The increase in diabetes and obesity prevalence in Milano Metropolitan Area, which took place over 30 years, is related to several environmental factors. We hypothesize that some of those factors may have also determined the high incidence and virulence of COVID-19 in the Milano area. Health Agencies of Milano Metropolitan Area are presently taking care of diabetic patients facing the new challenge of maintaining sustainable diabetes care costs in light of an increase in urban population and of the new life-style. The COVID-19 pandemic will modify the management of diabetic and obese patients permanently, via the implementation of approaches that entail telemedicine technology. The pilot study conducted during the lock-down period indicates an improvement of glucose control utilizing a remote glucose control system in the Milano Metropolitan Area, suggesting a wider utilization of similar methodologies during the present "second wave" lock-down.
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Affiliation(s)
- Livio Luzi
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy.
- Department of Endocrinology, Nutrition and Metabolic Diseases, IRCCS Multimedica, Via Milanese 300, 20099, Sesto San Giovanni, Milan, Italy.
| | - Michele Carruba
- Department of Medical Biotechnology and Translational Medicine (BIOMETRA), University of Milan, Milan, Italy
- Centre for Study and Research on Obesity of the University of Milan, Milan, Italy
| | | | | | - Regina Dagani
- Italian Diabetes Society Foundation Association - AMD Lombardy, Milan, Italy
- Health Agencies in the Territories (ASST) Rhodense, Milan, Italy
| | - Elisabetta Lovati
- Italian Diabetes Society - SID Lombardy, Pavia, Italy
- I.R.C.C.S. Policlinico San Matteo, Pavia, Italy
| | - Antonio Nicolucci
- Centre for Outcomes Research and Clinical Epidemiology - CORESEARCH, Pescara, Italy
| | - Cesare C Berra
- Department of Endocrinology, Nutrition and Metabolic Diseases, IRCCS Multimedica, Via Milanese 300, 20099, Sesto San Giovanni, Milan, Italy
| | - Elisa Cipponeri
- Department of Endocrinology, Nutrition and Metabolic Diseases, IRCCS Multimedica, Via Milanese 300, 20099, Sesto San Giovanni, Milan, Italy
| | | | - Andrea Lenzi
- Health City Institute, Rome, Italy
- Department Experimental Medicine, La Sapienza University, Rome, Italy
- Biotechnology and Life Sciences of Prime Minister Council - CNBBSV, Rome, Italy
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11
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Barbu E, Popescu MR, Popescu AC, Balanescu SM. Phenotyping the Prediabetic Population-A Closer Look at Intermediate Glucose Status and Cardiovascular Disease. Int J Mol Sci 2021; 22:6864. [PMID: 34202289 PMCID: PMC8268766 DOI: 10.3390/ijms22136864] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 06/12/2021] [Accepted: 06/17/2021] [Indexed: 01/08/2023] Open
Abstract
Even though the new thresholds for defining prediabetes have been around for more than ten years, there is still controversy surrounding the precise characterization of this intermediate glucose metabolism status. The risk of developing diabetes and macro and microvascular disease linked to prediabetes is well known. Still, the prediabetic population is far from being homogenous, and phenotyping it into less heterogeneous groups might prove useful for long-term risk assessment, follow-up, and primary prevention. Unfortunately, the current definition of prediabetes is quite rigid and disregards the underlying pathophysiologic mechanisms and their potential metabolic progression towards overt disease. In addition, prediabetes is commonly associated with a cluster of risk factors that worsen the prognosis. These risk factors all revolve around a common denominator: inflammation. This review focuses on identifying the population that needs to be screened for prediabetes and the already declared prediabetic patients who are at a higher risk of cardiovascular disease and require closer monitoring.
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Affiliation(s)
| | - Mihaela-Roxana Popescu
- Department of Cardiology, Elias Emergency University Hospital, Carol Davila University of Medicine and Pharmacy, 011461 Bucharest, Romania; (E.B.); (S.-M.B.)
| | - Andreea-Catarina Popescu
- Department of Cardiology, Elias Emergency University Hospital, Carol Davila University of Medicine and Pharmacy, 011461 Bucharest, Romania; (E.B.); (S.-M.B.)
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12
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Fritsche A, Häring H, Birkenfeld AL, Wagner R. Neue Subtypen bei Prädiabetes. Diabetologe 2021; 17:26-31. [DOI: 10.1007/s11428-020-00697-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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13
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He Y, Chiang C, Gebremariam LW, Hirakawa Y, Yatsuya H, Aoyama A. Factors Associated With Prediabetes and Diabetes Among Public Employees in Northern Ethiopia. Asia Pac J Public Health 2020; 33:242-250. [PMID: 33289398 DOI: 10.1177/1010539520974848] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The increasing burden of diabetes mellitus is one of the major public health challenges in African countries, including Ethiopia. This is the first study aimed to identify factors associated with prediabetes and diabetes defined by both fasting blood glucose and glycated hemoglobin in Ethiopians. We analyzed data of a cross-sectional survey (1372 adults aged 25-64 years) conducted between October 2015 and February 2016; multinomial logistic regression models were applied. Abdominal obesity, total cholesterol, and non-high-density lipoprotein cholesterol were independently associated with prediabetes and diabetes in both sexes. Increased triglycerides and religious fasting practices were independently associated with prediabetes and diabetes only in men; hypertension was associated with prediabetes and diabetes only in women, while high-density lipoprotein cholesterol was not associated with prediabetes and diabetes in either sex. Sex differences in the association of triglycerides, hypertension, and dietary habit suggest that different approaches of lifestyle modification may be required for men and women.
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Affiliation(s)
| | | | | | | | - Hiroshi Yatsuya
- Nagoya University, Nagoya, Japan.,Fujita Health University, Toyoake, Aichi, Japan
| | - Atsuko Aoyama
- Nagoya University, Nagoya, Japan.,Nagoya University of Arts and Sciences, Nisshin, Aichi, Japan
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