1
|
Masumi M, Bahadoran Z, Mirmiran P, Khalili D, Sarvghadi F, Azizi F. Effect of 3-year changes in adiposity measures on the pre-diabetes regression and progression: a community-based cohort study. BMC Public Health 2024; 24:3143. [PMID: 39533278 PMCID: PMC11559074 DOI: 10.1186/s12889-024-20680-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 11/08/2024] [Indexed: 11/16/2024] Open
Abstract
AIM We assessed the impact of a 3-year change-percent in adiposity measures on regression and pre-diabetes (Pre-DM) progression among Iranian adults. METHODS Three-year change-percent in body weight (BW), body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and visceral adiposity index (VAI) were calculated for 1458 Pre-DM subjects (mean age of 53.0 ± 13.7, 46.8% men), participated in the third examination of the Tehran Lipid and Glucose Study (2006-2008). Multinomial logistic regression models were used to estimate relative risk ratios (RRRs) of the outcomes [i.e., regression to normal glucose regulation (NGR), persistence in Pre-DM, and progression to newly diagnosed type 2 diabetes (T2D)] across 3-year change categories of adiposity measures (i.e., ≥ 5% decrease, 0-5% decrease, increase). RESULTS Over nine years of follow-up, 37.7 and 39.0% returned to NGR and progressed to T2D, respectively. Decreased BW (0-5 and ≥ 5%) was associated with regression to NGR (RRRs = 1.44, 95% CIs = 1.05-1.98, and 2.64, 1.63-4.28, respectively). Decreased BMI and WC ≥ 5% were also associated with regression to NGR (RRRs = 1.63, 95% CI = 1.01-2.64; 1.69, 1.20-2.37, respectively). Changes in WHR and VAI were not associated with Pre-DM regression or progression. Pre-DM subjects with ≥ 5% BW loss had a constant FSG level overtime and a lower overall mean of FSG (116 vs. 111 and 112 mg/dL, P = 0.023 and 0.009, respectively) and 2 h-SG (154 vs. 165 and 168 mg/dL) compared to those had 0-5% BW loss or BW gain. CONCLUSION Short-term management of adiposity measures increases the regression probability to NGR. Targeting BW loss seems a more potent predictor of Pre-DM reversion among the adiposity measures.
Collapse
Affiliation(s)
- Maryam Masumi
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Zahra Bahadoran
- Micronutrient Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, No 23, A'rabi St, Yeman Av, Velenjak, Tehran, P.O.Box: 19395-4763, Iran.
| | - Parvin Mirmiran
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farzaneh Sarvghadi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| |
Collapse
|
2
|
Peng M, He S, Wang J, An Y, Qian X, Zhang B, Zhang L, Chen B, Yang Z, Li G, Gong Q. Efficacy of 1-hour postload plasma glucose as a suitable measurement in predicting type 2 diabetes and diabetes-related complications: A post hoc analysis of the 30-year follow-up of the Da Qing IGT and Diabetes Study. Diabetes Obes Metab 2024; 26:2329-2338. [PMID: 38488254 DOI: 10.1111/dom.15547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/27/2024] [Accepted: 02/27/2024] [Indexed: 05/09/2024]
Abstract
AIM To evaluate whether 1-hour plasma glucose (1hPG) can be a comparable measurement to 2-hour plasma glucose (2hPG) in identifying individuals at high risk of developing diabetes. METHODS A total of 1026 non-diabetic subjects in the Da Qing IGT and Diabetes Study were included and classified according to baseline postload 1hPG. The participants were followed up and assessed at 6-, 20- and 30year follow-up for outcomes including diabetes, all-cause and cardiovascular mortality, cardiovascular disease (CVD) events, and microvascular disease. We then conducted a proportional hazards analysis in this post hoc study to determine the risks of developing type 2 diabetes and its complications in a '1hPG-normal' group (1hPG <8.6 mmol/L) and a '1hPG-high' group (≥8.6 mmol/L). The predictive values of 1hPG and 2hPG were evaluated using a time-dependent receiver-operating characteristic (ROC) curve. RESULTS Compared with the 1hPG-normal group, the 1hPG-high group had increased risk of diabetes (hazard ratio [HR] 4.45, 95% CI 3.43-5.79), all-cause mortality (HR 1.46, 95% CI 1.07-2.01), CVD mortality (HR 1.84, 95% CI 1.16-2.95), CVD events (HR 1.39, 95% CI 1.03-1.86) and microvascular disease (HR 1.70, 95% CI: 1.03-2.79) after adjusting for confounders. 1hPG exhibited a higher area under the ROC curve (AUC) for predicting diabetes than 2hPG during the long-term follow-up (AUC [1hPG vs. 2hPG]: 10 years: 0.86 vs. 0.84, p = 0.08; 20 years: 0.88 vs. 0.87, p = 0.04; 30 years: 0.85 vs. 0.82, p = 0.009). CONCLUSIONS Elevated 1hPG level (≥8.6 mmol/L) was associated with increased risk of developing type 2 diabetes and its long-term complications, and could be considered as a suitable measurement for identifying individuals at high risk of type 2 diabetes.
Collapse
Affiliation(s)
- Minying Peng
- Center of Endocrinology, National Center of Cardiology & Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Siyao He
- Center of Endocrinology, National Center of Cardiology & Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinping Wang
- Department of Cardiology, Da Qing Oilfield General Hospital, Daqing, China
| | - Yali An
- Center of Endocrinology, National Center of Cardiology & Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xin Qian
- Center of Endocrinology, National Center of Cardiology & Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bo Zhang
- China-Japan Friendship Hospital, Beijing, China
| | - Lihong Zhang
- Center of Endocrinology, National Center of Cardiology & Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bo Chen
- Division of Non-Communicable Disease Control and Community Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhiwei Yang
- Department of Cardiology, Da Qing Oilfield General Hospital, Daqing, China
| | - Guangwei Li
- Center of Endocrinology, National Center of Cardiology & Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- China-Japan Friendship Hospital, Beijing, China
| | - Qiuhong Gong
- Center of Endocrinology, National Center of Cardiology & Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| |
Collapse
|
3
|
Engin A. The Definition and Prevalence of Obesity and Metabolic Syndrome: Correlative Clinical Evaluation Based on Phenotypes. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1460:1-25. [PMID: 39287847 DOI: 10.1007/978-3-031-63657-8_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/19/2024]
Abstract
Increase in the prevalence of obesity has become a major worldwide health problem in adults as well as among children and adolescents. In the last four decades, studies have revealed that the significant increase in the prevalence of obesity has become a pandemic. Obesity is the result of complex interactions between biological, genetic, environmental, and behavioral factors. Indeed, almost all of the children suffering from obesity in early childhood face with being overweight or obese in adolescence. Different phenotypes have different risk factors in the clinical evaluation of obesity. Individuals suffering from metabolically unhealthy obesity (MUO) are at an excess risk of developing cardiovascular diseases (CVDs), several cancer types, and metabolic syndrome (MetS), whereas the metabolically healthy obesity (MHO) phenotype has a high risk of all-cause mortality and cardiometabolic events but not MetS. While most obese individuals have the MUO phenotype, the frequency of the MHO phenotype is at most 10-20%. Over time, approximately three-quarters of obese individuals transform from MHO to MUO. Total adiposity and truncal subcutaneous fat accumulation during adolescence are positively and independently associated with atherosclerosis in adulthood. Obesity, in general, causes a large reduction in life expectancy. However, the mortality rate of morbid obesity is greater among younger than older adults. Insulin resistance (IR) develops with the central accumulation of body fat. MHO patients are insulin-sensitive like healthy normal-weight individuals and have lower visceral fat content and cardiovascular consequences than do the majority of MUO patients. MetS includes clustering of abdominal obesity, dyslipidemia, hyperglycemia, and hypertension. The average incidence of MetS is 3%, with a 1.5-fold increase in the risk of death from all causes in these patients. If lifestyle modifications, dietary habits, and pharmacotherapy do not provide any benefit, then bariatric surgery is recommended to reduce weight and improve comorbid diseases. However, obesity treatment should be continuous in obese patients by monitoring the accompanying diseases and their consequences. In addition to sodium-glucose co-transporter-2 (SGLT2) inhibitors, the long-acting glucagon-like peptide-1 (GLP-1) receptor agonist reduces the mean body weight. However, caloric restriction provides more favorable improvement in body composition than does treatment with the GLP-1 receptor (GLP1R) agonist alone. Combination therapy with orlistat and phentermine are the US Food and Drug Administration (FDA)-approved anti-obesity drugs. Recombinant leptin and synthetic melanocortin-4-receptor agonists are used in rarely occurring, monogenic obesity, which is due to loss of function in the leptin-melanocortin pathway.
Collapse
Affiliation(s)
- Atilla Engin
- Faculty of Medicine, Department of General Surgery, Gazi University, Besevler, Ankara, Turkey.
- Mustafa Kemal Mah. 2137. Sok. 8/14, 06520, Cankaya, Ankara, Turkey.
| |
Collapse
|
4
|
Ha J, Chung ST, Bogardus C, Jagannathan R, Bergman M, Sherman AS. One-hour glucose is an earlier marker of dysglycemia than two-hour glucose. Diabetes Res Clin Pract 2023; 203:110839. [PMID: 37482221 PMCID: PMC10592221 DOI: 10.1016/j.diabres.2023.110839] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/17/2023] [Accepted: 07/19/2023] [Indexed: 07/25/2023]
Abstract
AIMS The timing of increase in 1-hour PG and its utility as an earlier predictor of both prediabetes (PreDM) and type 2 diabetes (T2D) compared to 2-hour PG (2 h-PG) are unknown. To evaluate the timing of crossing of the 1 h-PG ≥ 155 mg/dl (8.6 mmol/L) for PreDM and 209 mg/dl (11.6 mmol/L) for T2D and respective current 2 h-PG thresholds of 140 mg/dl (7.8 mmol/L) and 200 mg/dl (11.1 mmol/L). METHODS Secondary analysis of 201 Southwest Native Americans who were followed longitudinally for 6-10 years and had at least 3 OGTTs. RESULTS We identified a subset of 43 individuals who first developed PreDM by both 1 h-PG and 2 h-PG criteria during the study. For most (32/43,74%), 1 h-PG ≥ 155 mg/dl was observed before 2 h-PG reached 140 mg/dl (median [IQR]: 1.7 [-0.25, 4.59] y; mean ± SEM: 5.3 ± 1.9 y). We also identified a subset of 33 individuals who first developed T2D during the study. For most (25/33, 75%), 1 h-PG reached 209 mg/dl earlier (median 1.0 [-0.56, 2.02] y; mean ± SEM: 1.6 ± 0.8 y) than 2 h-PG reached 200 mg/dl, diagnostic of T2D. CONCLUSIONS 1 h-PG ≥ 155 mg/dl is an earlier marker of elevated risk for PreDM and T2D than 2 h-PG ≥ 140 mg/dl.
Collapse
Affiliation(s)
- Joon Ha
- Department of Mathematics, Howard University, Washington, DC, USA
| | - Stephanie T Chung
- Section on Pediatric Diabetes, Obesity, and Metabolism, Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes, Digestive, and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Clifton Bogardus
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 N 5th Street, Phoenix, AZ 85004, USA
| | - Ram Jagannathan
- Hubert Department of Global Health, Emory University School of Public Health Atlanta, GA, USA
| | - Michael Bergman
- NYU Grossman School of Medicine, Departments of Medicine and Population Health, Division of Endocrinology, Diabetes, Metabolism, VA New York Harbor Healthcare System, Manhattan Campus, New York, NY 10010, USA
| | - Arthur S Sherman
- Laboratory of Biological Modeling, National Institute of Diabetes, Digestive, and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
| |
Collapse
|
5
|
Kaminska H, Szarpak L, Kosior D, Wieczorek W, Szarpak A, Al-Jeabory M, Gawel W, Gasecka A, Jaguszewski MJ, Jarosz-Chobot P. Impact of diabetes mellitus on in-hospital mortality in adult patients with COVID-19: a systematic review and meta-analysis. Acta Diabetol 2021; 58:1101-1110. [PMID: 33778910 PMCID: PMC8005367 DOI: 10.1007/s00592-021-01701-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 03/03/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND The novel coronavirus disease 2019 (COVID-19) has spread worldwide since the beginning of 2020, placing the heavy burden on the health systems all over the world. The population that particularly has been affected by the pandemic is the group of patients suffering from diabetes mellitus. Having taken the public health in considerations, we have decided to perform a systematic review and meta-analysis of diabetes mellitus on in-hospital mortality in patients with COVID-19. METHODS A systematic literature review (MEDLINE, EMBASE, Web of Science, Scopus, Cochrane) including all published clinical trials or observational studies published till December 10, 2020, was performed using following terms "diabetes mellitus" OR "diabetes" OR "DM" AND "survival" OR "mortality" AND "SARS-CoV-2" OR "COVID-19". RESULTS Nineteen studies were included out of the 7327 initially identified studies. Mortality of DM patients vs non-DM patients was 21.3 versus 6.1%, respectively (OR = 2.39; 95%CI: 1.65, 3.64; P < 0.001), while severe disease in DM and non-DM group varied and amounted to 34.8% versus 22.8% (OR = 1.43; 95%CI: 0.82, 2.50; P = 0.20). In the DM group, the complications were observed far more often when compared with non-DM group, both in acute respiratory distress (31.4 vs. 17.2%; OR = 2.38; 95%CI:1.80, 3.13; P < 0.001), acute cardiac injury (22.0% vs. 12.8%; OR = 2.59; 95%CI: 1.81, 3.73; P < 0.001), and acute kidney injury (19.1 vs. 10.2%; OR = 1.97; 95%CI: 1.36, 2.85; P < 0.001). CONCLUSIONS Based on the findings, we shall conclude that diabetes is an independent risk factor of the severity of COVID-19 in-hospital settings; therefore, patients with diabetes shall aim to reduce the exposure to the potential infection of COVID-19.
Collapse
Affiliation(s)
- Halla Kaminska
- Department of Pediatrics and Children's Diabetology, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Silesia, Poland
| | - Lukasz Szarpak
- Maria Sklodowska-Curie Bialystok Oncology Center, Ogrodowa 12 str., 15-027, Bialystok, Poland.
- Polish Society of Disaster Medicine, Warsaw, Poland.
| | - Dariusz Kosior
- Faculty of Medicine, Collegium Medicum, Cardinal Stefan Wyszynski University, Warsaw, Poland
- Department of Cardiology and Hypertension With Electrophysiological Lab, Central Clinical Hospital of the Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
| | - Wojciech Wieczorek
- Department of Emergency Medicine, Medical University of Warsaw, Warsaw, Poland
| | | | | | - Wladyslaw Gawel
- Department of Surgery, The Silesian Hospital in Opava, Opava, Czech Republic
| | - Aleksandra Gasecka
- Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands
- Laboratory of Experimental Clinical Chemistry, Amsterdam University Medical Center, Amsterdam, The Netherlands
- 1St Chair and Department of Cardiology, Medical University of Warsaw, Warsaw, Poland
| | | | - Przemyslawa Jarosz-Chobot
- Department of Pediatrics and Children's Diabetology, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Silesia, Poland
| |
Collapse
|
6
|
Obura M, Beulens JWJ, Slieker R, Koopman ADM, Hoekstra T, Nijpels G, Elders P, Dekker JM, Koivula RW, Kurbasic A, Laakso M, Hansen TH, Ridderstråle M, Hansen T, Pavo I, Forgie I, Jablonka B, Ruetten H, Mari A, McCarthy MI, Walker M, McDonald TJ, Perry MH, Pearson ER, Franks PW, 't Hart LM, Rutters F. Clinical profiles of post-load glucose subgroups and their association with glycaemic traits over time: An IMI-DIRECT study. Diabet Med 2021; 38:e14428. [PMID: 33067862 DOI: 10.1111/dme.14428] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 09/10/2020] [Accepted: 10/14/2020] [Indexed: 12/11/2022]
Abstract
AIM To examine the hypothesis that, based on their glucose curves during a seven-point oral glucose tolerance test, people at elevated type 2 diabetes risk can be divided into subgroups with different clinical profiles at baseline and different degrees of subsequent glycaemic deterioration. METHODS We included 2126 participants at elevated type 2 diabetes risk from the Diabetes Research on Patient Stratification (IMI-DIRECT) study. Latent class trajectory analysis was used to identify subgroups from a seven-point oral glucose tolerance test at baseline and follow-up. Linear models quantified the associations between the subgroups with glycaemic traits at baseline and 18 months. RESULTS At baseline, we identified four glucose curve subgroups, labelled in order of increasing peak levels as 1-4. Participants in Subgroups 2-4, were more likely to have higher insulin resistance (homeostatic model assessment) and a lower Matsuda index, than those in Subgroup 1. Overall, participants in Subgroups 3 and 4, had higher glycaemic trait values, with the exception of the Matsuda and insulinogenic indices. At 18 months, change in homeostatic model assessment of insulin resistance was higher in Subgroup 4 (β = 0.36, 95% CI 0.13-0.58), Subgroup 3 (β = 0.30; 95% CI 0.10-0.50) and Subgroup 2 (β = 0.18; 95% CI 0.04-0.32), compared to Subgroup 1. The same was observed for C-peptide and insulin. Five subgroups were identified at follow-up, and the majority of participants remained in the same subgroup or progressed to higher peak subgroups after 18 months. CONCLUSIONS Using data from a frequently sampled oral glucose tolerance test, glucose curve patterns associated with different clinical characteristics and different rates of subsequent glycaemic deterioration can be identified.
Collapse
Affiliation(s)
- M Obura
- Epidemiology and Data Science, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
| | - J W J Beulens
- Epidemiology and Data Science, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - R Slieker
- Epidemiology and Data Science, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Centre, Leiden, The Netherlands
| | - A D M Koopman
- Epidemiology and Data Science, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
| | - T Hoekstra
- Epidemiology and Data Science, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
- Department of Health Sciences, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands
| | - G Nijpels
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, VU University Medical Centre, Amsterdam, The Netherlands
| | - P Elders
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, VU University Medical Centre, Amsterdam, The Netherlands
| | - J M Dekker
- Epidemiology and Data Science, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
| | - R W Koivula
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford, Oxford, UK
| | - A Kurbasic
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
| | - M Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Finland
| | - T H Hansen
- The Novo Nordisk Foundation Centre for Basic Metabolic Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Cardiology and Endocrinology, Slagelse Hospital, Slagelse, Denmark
| | - M Ridderstråle
- The Novo Nordisk Foundation Centre for Basic Metabolic Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - T Hansen
- The Novo Nordisk Foundation Centre for Basic Metabolic Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - I Pavo
- Eli Lilly Regional Operations GmbH, Vienna, Austria
| | - I Forgie
- Division of Cardiovascular & Diabetes Medicine, Medical Research Institute, University of Dundee, Dundee, UK
| | - B Jablonka
- Sanofi-Aventis Deutschland GmbH, R&D, Frankfurt am Main, Germany
| | - H Ruetten
- Sanofi-Aventis Deutschland GmbH, R&D, Frankfurt am Main, Germany
| | - A Mari
- Institute of Biomedical Engineering, National Research Council, Padova, Italy
| | - M I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - M Walker
- Institute of Cellular Medicine (Diabetes), Newcastle University, Newcastle upon Tyne, UK
| | - T J McDonald
- NIHR Exeter Clinical Research Facility, University of Exeter Medical School and Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - M H Perry
- Department of Blood Sciences, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - E R Pearson
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - P W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford, Oxford, UK
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
| | - L M 't Hart
- Epidemiology and Data Science, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Centre, Leiden, The Netherlands
- Department of Biomedical Data Sciences, Molecular Epidemiology Section, Leiden University Medical Centre, Leiden, The Netherlands
| | - F Rutters
- Epidemiology and Data Science, Amsterdam Public Health research institute, VU University Medical Center, Amsterdam, The Netherlands
| |
Collapse
|
7
|
Obura M, Beulens JWJ, Slieker R, Koopman ADM, Hoekstra T, Nijpels G, Elders P, Koivula RW, Kurbasic A, Laakso M, Hansen TH, Ridderstråle M, Hansen T, Pavo I, Forgie I, Jablonka B, Ruetten H, Mari A, McCarthy MI, Walker M, Heggie A, McDonald TJ, Perry MH, De Masi F, Brunak S, Mahajan A, Giordano GN, Kokkola T, Dermitzakis E, Viñuela A, Pedersen O, Schwenk JM, Adamski J, Teare HJA, Pearson ER, Franks PW, ‘t Hart LM, Rutters F, for the IMI-DIRECT Consortium. Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes: An IMI-DIRECT study. PLoS One 2020; 15:e0242360. [PMID: 33253307 PMCID: PMC7703960 DOI: 10.1371/journal.pone.0242360] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 10/31/2020] [Indexed: 11/19/2022] Open
Abstract
Aim Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. Methods The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. Results At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1–3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18–1.92) for subgroup 2 and 1.88 (-0.08–3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. Conclusions Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.
Collapse
Affiliation(s)
- Morgan Obura
- Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Joline W. J. Beulens
- Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- * E-mail:
| | - Roderick Slieker
- Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anitra D. M. Koopman
- Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Trynke Hoekstra
- Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Giel Nijpels
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Petra Elders
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Robert W. Koivula
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford, Oxford, United Kingdom
| | - Azra Kurbasic
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Tue H. Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Cardiology and Endocrinology, Slagelse Hospital, Slagelse, Denmark
| | - Martin Ridderstråle
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Imre Pavo
- Eli Lilly Regional Operations GmbH, Vienna, Austria
| | - Ian Forgie
- Division of Cardiovascular & Diabetes Medicine, Medical Research Institute, University of Dundee, Dundee, United Kingdom
| | - Bernd Jablonka
- Sanofi-Aventis Deutschland GmbH, R&D, Frankfurt am Main, Germany
| | - Hartmut Ruetten
- Sanofi-Aventis Deutschland GmbH, R&D, Frankfurt am Main, Germany
| | - Andrea Mari
- Institute of Biomedical Engineering, National Research Council, Padova, Italy
| | - Mark I. McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford, Oxford, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Mark Walker
- Institute of Cellular Medicine (Diabetes), Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Alison Heggie
- Institute of Cellular Medicine (Diabetes), Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Timothy J. McDonald
- NIHR Exeter Clinical Research Facility, University of Exeter Medical School and Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom
| | - Mandy H. Perry
- Department of Blood Sciences, Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom
| | - Federico De Masi
- Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Søren Brunak
- Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Giuseppe N. Giordano
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
| | - Tarja Kokkola
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Emmanouil Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Institute of Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland
- Swiss Institute of Bioinformatics, Geneva, Switzerland
| | - Ana Viñuela
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Institute of Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland
- Swiss Institute of Bioinformatics, Geneva, Switzerland
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, 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
| | - Jurek Adamski
- Research Unit Molecular Endocrinology and Metabolism, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg, Germany
- Lehrstuhl für Experimentelle Genetik, Technische Universität München, Freising-Weihenstephan, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Harriet J. A. Teare
- HeLEX, Nuffield Department of Population Health, University of Oxford, Headington, Oxford, United Kingdom
| | - Ewan R. Pearson
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, United Kingdom
| | - Paul W. Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford, Oxford, United Kingdom
- Department of Nutrition, Harvard School of Public Health, Boston, MA, United States of America
| | - Leen M. ‘t Hart
- Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Biomedical Data Sciences, Molecular Epidemiology Section, Leiden University Medical Center, Leiden, The Netherlands
| | - Femke Rutters
- Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Location VU University Medical Center, Amsterdam, The Netherlands
| | | |
Collapse
|
8
|
Mengen E, Uçaktürk SA. Evaluation of the relationship between the one-hour plasma glucose concentration and beta-cell functions and cardiometabolic parameters during oral glucose tolerance test in obese children and adolescents. J Pediatr Endocrinol Metab 2020; 33:767-775. [PMID: 32447335 DOI: 10.1515/jpem-2020-0016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 03/19/2020] [Indexed: 11/15/2022]
Abstract
Background In this study, we aimed to evaluate the relationship between the 1-h plasma glucose (PG) level in the oral glucose tolerance test (OGTT) and conventional glycemic parameters, indices evaluating beta-cell functions, and cardiometabolic risk factors. Methods The records of 532 obese patients who were followed up in the Pediatric Endocrinology Polyclinic and who underwent standard OGTT were evaluated retrospectively. All patients were divided into two groups according to OGTT data as the 1-h plasma glucose concentration <155 mg/dL (n=329) and ≥155 mg/dL (n=203). Patients with normal glucose tolerance (NGT) were divided into two groups according to the 1-h PG level, as 218 patients with NGT 1 h-low (<155 mg/dL) and 53 patients with high NGT 1 h-high (≥155 mg/dL). Results There was a statistically significant difference between the lipid profiles of individuals with NGT 1 h-low (<155 mg/dL) and individuals with NGT 1 h-high (≥155 mg/dL) (p<0.001). Total cholesterol, LDL cholesterol, and triglyceride levels were higher, while HDL cholesterol levels were lower in individuals with NGT 1 h-high (≥155 mg/dL). The indices evaluating beta-cell functions were significantly higher in individuals with NGT 1 h-low (<155 mg/dL). Conclusion As a result, a plasma glucose concentration above or equal to 155 mg/dL at 1 h during an OGTT is associated with a worse clinical phenotype characterized by changes in insulin sensitivity and β-cell function. Therefore, this threshold value can predict the progression of prediabetes in obese young people with NGT.
Collapse
Affiliation(s)
- Eda Mengen
- Department of Pediatric Endocrinology, Ankara City Hospital, Children's Hospital, Ankara, Turkey
| | - Seyit Ahmet Uçaktürk
- Department of Pediatric Endocrinology, Ankara City Hospital, Children's Hospital, Ankara, Turkey
| |
Collapse
|
9
|
Lazo-Porras M, Bernabe-Ortiz A, Ruiz-Alejos A, Smeeth L, Gilman RH, Checkley W, Málaga G, Miranda JJ. Regression from prediabetes to normal glucose levels is more frequent than progression towards diabetes: The CRONICAS Cohort Study. Diabetes Res Clin Pract 2020; 163:107829. [PMID: 31465811 PMCID: PMC7239508 DOI: 10.1016/j.diabres.2019.107829] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2019] [Revised: 06/18/2019] [Accepted: 08/23/2019] [Indexed: 12/13/2022]
Abstract
AIMS This study aimed to (1) estimate the prevalence of prediabetes according to different definitions, (2) evaluate regression to normal glucose levels and progression towards T2DM, and (3) determine factors associated with regression and progression across four diverse geographical settings in a Latin American country. METHODS The CRONICAS Cohort Study was conducted in four different areas in Peru. Enrollment started in September 2010 and follow-up was conducted in 2013. Prediabetes, T2DM and normal glucose levels were determined according to definitions from the World Health Organization (WHO), American Diabetes Association (ADA), and National Institute for Health and Care Excellence (NICE). The main outcomes were regression to normal glucose levels and incidence of T2DM. Prevalence estimates and 95% confidence intervals (95% CI) were calculated. Crude and adjusted models using Poisson regression were performed and relative risk ratios (RRR) and 95% CI were calculated. RESULTS At baseline, the prevalence of prediabetes varied markedly by definition used: 6.5%(95% CI 5.6-7.6%), 53.6% (95% CI 51.6-55.6%), and 24.6% (95% CI 22.8-26.4%) according to WHO, ADA and NICE criteria, respectively. After 2.2 years of follow-up, in those with prediabetes, the cumulative incidence of regression to euglycemia ranged between 31.4% and 68.9%, whereas the incidence of T2DM varied from 5.5% to 28.8%. Factors associated with regression to normal glucose levels and progression to diabetes were age, body mass index, and insulin resistance. CONCLUSIONS Regression from pre-diabetes back to euglycemia was much more common than progression to diabetes.
Collapse
Affiliation(s)
- Maria Lazo-Porras
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; CONEVID Unidad de Conocimiento y Evidencia, Universidad Peruana Cayetano Heredia, Lima, Peru.
| | - Antonio Bernabe-Ortiz
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
| | - Andrea Ruiz-Alejos
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
| | - Liam Smeeth
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
| | - Robert H Gilman
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States; Área de Investigación y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru.
| | - William Checkley
- Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, MD, United States.
| | - German Málaga
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; CONEVID Unidad de Conocimiento y Evidencia, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru.
| | - J Jaime Miranda
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru.
| |
Collapse
|
10
|
Bergman M, Jagannathan R, Buysschaert M, Pareek M, Olsen MH, Nilsson PM, Medina JL, Roth J, Chetrit A, Groop L, Dankner R. Lessons learned from the 1-hour post-load glucose level during OGTT: Current screening recommendations for dysglycaemia should be revised. Diabetes Metab Res Rev 2018; 34:e2992. [PMID: 29460410 DOI: 10.1002/dmrr.2992] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 01/14/2018] [Accepted: 02/02/2018] [Indexed: 02/06/2023]
Abstract
This perspective covers a novel area of research describing the inadequacies of current approaches for diagnosing dysglycaemia and proposes that the 1-hour post-load glucose level during the 75-g oral glucose tolerance test may serve as a novel biomarker to detect dysglycaemia earlier than currently recommended screening criteria for glucose disorders. Considerable evidence suggests that a 1-hour post-load plasma glucose value ≥155 mg/dl (8.6 mmol/L) may identify individuals with reduced β-cell function prior to progressing to prediabetes and diabetes and is highly predictive of those likely to progress to diabetes more than the HbA1c or 2-hour post-load glucose values. An elevated 1-hour post-load glucose level was a better predictor of type 2 diabetes than isolated 2-hour post-load levels in Indian, Japanese, and Israeli and Nordic populations. Furthermore, epidemiological studies have shown that a 1-hour PG ≥155 mg/dl (8.6 mmol/L) predicted progression to diabetes as well as increased risk for microvascular disease and mortality when the 2-hour level was <140 mg/dl (7.8 mmol/L). The risk of myocardial infarction or fatal ischemic heart disease was also greater among subjects with elevated 1-hour glucose levels as were risks of retinopathy and peripheral vascular complications in a Swedish cohort. The authors believe that the considerable evidence base supports redefining current screening and diagnostic recommendations with the 1-hour post-load level. Measurement of the 1-hour PG level would increase the likelihood of identifying a larger, high-risk group with the additional practical advantage of potentially replacing the conventional 2-hour oral glucose tolerance test making it more acceptable in a clinical setting.
Collapse
Affiliation(s)
- Michael Bergman
- Division of Endocrinology and Metabolism, Department of Medicine and of Population Health, School of Medicine, NYU Langone Diabetes Prevention Program, New York, NY, USA
| | - Ram Jagannathan
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Martin Buysschaert
- Department of Endocrinology and Diabetology, Université Catholique de Louvain, University Clinic Saint-Luc, Brussels, Belgium
| | - Manan Pareek
- Centre for Individualized Medicine in Arterial Diseases (CIMA), Odense University Hospital, University of Southern Denmark, Odense, Denmark
- Cardiology Section, Department of Internal Medicine, Holbaek Hospital, Holbaek, Denmark
| | - Michael H Olsen
- Centre for Individualized Medicine in Arterial Diseases (CIMA), Odense University Hospital, University of Southern Denmark, Odense, Denmark
- Cardiology Section, Department of Internal Medicine, Holbaek Hospital, Holbaek, Denmark
| | - Peter M Nilsson
- Department of Clinical Sciences and Lund University Diabetes Centre, Lund University, Skåne University Hospital, Malmö, Sweden
| | | | - Jesse Roth
- The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Angela Chetrit
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Israel
| | - Leif Groop
- Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Rachel Dankner
- The Feinstein Institute for Medical Research, Manhasset, NY, USA
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| |
Collapse
|
11
|
Hulman A, Vistisen D, Glümer C, Bergman M, Witte DR, Færch K. Glucose patterns during an oral glucose tolerance test and associations with future diabetes, cardiovascular disease and all-cause mortality rate. Diabetologia 2018; 61:101-107. [PMID: 28983719 DOI: 10.1007/s00125-017-4468-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 09/07/2017] [Indexed: 10/18/2022]
Abstract
AIMS/HYPOTHESIS In addition to blood glucose concentrations measured in the fasting state and 2 h after an OGTT, intermediate measures during an OGTT may provide additional information regarding a person's risk of future diabetes and cardiovascular disease (CVD). First, we aimed to characterise heterogeneity of glycaemic patterns based on three time points during an OGTT. Second, we compared the incidences of diabetes and CVD and all-cause mortality rates among those with different patterns. METHODS Our cohort study included 5861 participants without diabetes at baseline from the Danish Inter99 study. At baseline, all participants underwent an OGTT with measurements of plasma glucose levels at 0, 30 and 120 min. Latent class mixed-effects models were fitted to identify distinct patterns of glycaemic response during the OGTT. Information regarding incident diabetes, CVD and all-cause mortality rates during a median follow-up time of 11, 12 and 13 years, respectively, was extracted from national registers. Cox proportional hazard models with adjustment for several cardiometabolic risk factors were used to compare the risk of diabetes, CVD and all-cause mortality among individuals in the different latent classes. RESULTS Four distinct glucose patterns during the OGTT were identified. One pattern was characterised by high 30 min but low 2 h glucose values. Participants with this pattern had an increased risk of developing diabetes compared with participants with lower 30 min and 2 h glucose levels (HR 4.1 [95% CI 2.2, 7.6]) and participants with higher 2 h but lower 30 min glucose levels (HR 1.5 [95% CI 1.0, 2.2]). Furthermore, the all-cause mortality rate differed between the groups with significantly higher rates in the two groups with elevated 30 min glucose. Only small non-significant differences in risk of future CVD were observed across latent classes after confounder adjustment. CONCLUSIONS/INTERPRETATION Elevated 30 min glucose is associated with increased risk of diabetes and all-cause mortality rate independent of fasting and 2 h glucose levels. Therefore, subgroups at high risk may not be revealed when considering only fasting and 2 h glucose levels during an OGTT.
Collapse
Affiliation(s)
- Adam Hulman
- Department of Public Health, Aarhus University, Bartholins Allé 2, Building 1260, DK-8000, Aarhus C, Denmark.
- Danish Diabetes Academy, Odense, Denmark.
- Department of Medical Physics and Informatics, University of Szeged, Szeged, Hungary.
| | | | - Charlotte Glümer
- Research Centre for Prevention and Health, Glostrup Hospital, Glostrup, Denmark
| | - Michael Bergman
- Division of Endocrinology, Diabetes and Metabolism, NYU School of Medicine, NYU Langone Diabetes Prevention Program, New York, NY, USA
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Bartholins Allé 2, Building 1260, DK-8000, Aarhus C, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | | |
Collapse
|
12
|
Engin A. The Definition and Prevalence of Obesity and Metabolic Syndrome. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 960:1-17. [PMID: 28585193 DOI: 10.1007/978-3-319-48382-5_1] [Citation(s) in RCA: 713] [Impact Index Per Article: 89.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Increase in prevalence of obesity has become a worldwide major health problem in adults, as well as among children and adolescents. Furthermore, total adiposity and truncal subcutaneous fat accumulation during adolescence are positively and independently associated with atherosclerosis at adult ages. Centrally accumulation of body fat is associated with insulin resistance, whereas distribution of body fat in a peripheral pattern is metabolically less important. Obesity is associated with a large decrease in life expectancy. The effect of extreme obesity on mortality is greater among younger than older adults. In this respect, obesity is also associated with increased risk of several cancer types. However, up to 30% of obese patients are metabolically healthy with insulin sensitivity similar to healthy normal weight individuals, lower visceral fat content, and lower intima media thickness of the carotid artery than the majority of metabolically "unhealthy" obese patients.Abdominal obesity is the most frequently observed component of metabolic syndrome. The metabolic syndrome; clustering of abdominal obesity, dyslipidemia, hyperglycemia and hypertension, is a major public health challenge. The average prevalence of metabolic syndrome is 31%, and is associated with a two-fold increase in the risk of coronary heart disease, cerebrovascular disease, and a 1.5-fold increase in the risk of all-cause mortality.
Collapse
Affiliation(s)
- Atilla Engin
- Faculty of Medicine, Department of General Surgery, Gazi University, Besevler, Ankara, Turkey. .,, Mustafa Kemal Mah. 2137. Sok. 8/14, 06520, Cankaya, Ankara, Turkey.
| |
Collapse
|
13
|
Buysschaert M, Bergman M, Yanogo D, Jagannathan R, Buysschaert B, Preumont V. An elevated 1-h post- load glucose level during the oral glucose tolerance test detects prediabetes. Diabetes Metab Syndr 2017; 11:137-139. [PMID: 27986405 DOI: 10.1016/j.dsx.2016.12.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 12/08/2016] [Indexed: 10/20/2022]
Abstract
AIM The objective of the study was to compare the diagnosis of dysglycemic states by conventional oral glucose tolerance test (OGTT) criteria (fasting and 2-h plasma glucose) with the 1-h post-load plasma glucose level. MATERIAL AND METHODS 34 individuals (mean age: 55±13years; BMI: 27.7±6.3kg/m2) at risk for prediabetes were administered a 75g OGTT. Individuals with normal glucose tolerance (NGT) or prediabetes were identified according to fasting and/or 2-h plasma glucose (PG) concentrations. Subsequently, subjects were divided in 2 groups: group 1 (n=21) with a 1-h PG<155mg/dl and group 2 (n=13) with a 1-h PG≥155mg/dl. HOMA was performed to assess β-cell function and insulin sensitivity. RESULTS NGT or prediabetes based on conventional criteria correlated with the 1-h PG<or≥155mg/dl (p<0.001). Moreover, the 1-h PG≥155mg/dl was associated with higher HbA1c levels (6.1±0.5 vs. 5.5±0.3%, p<0.001) and significantly impaired insulin secretion and hyperbolic product (BxS) on HOMA test vs. 1-h PG<155mg/dl. CONCLUSION The 1-h post-load plasma glucose value ≥155mg/dl is strongly associated with conventional criteria for (pre)diabetes and alterations of β-cell function.
Collapse
Affiliation(s)
- Martin Buysschaert
- Cliniques Universitaires Saint-Luc, Service d'Endocrinologie et Nutrition, B-1200 Bruxelles, Belgium.
| | - Michael Bergman
- NYU School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism, NYU Langone Diabetes Prevention Program, 530 First Avenue, Schwartz East, New-York, NY10.016, USA
| | - Donald Yanogo
- Hôpital National Blaise Compaoré, Ouagadougou, Burkina Faso
| | - Ram Jagannathan
- NYU School of Medicine, Department of Population Health Center for Healthful Behavior Change, New York, NY 10016, USA
| | - Benoit Buysschaert
- Cliniques Universitaires Saint-Luc, Service d'Endocrinologie et Nutrition, B-1200 Bruxelles, Belgium
| | - Vanessa Preumont
- Cliniques Universitaires Saint-Luc, Service d'Endocrinologie et Nutrition, B-1200 Bruxelles, Belgium
| |
Collapse
|
14
|
Bergman M, Jagannathan R, Buysschaert M, Medina JL, Sevick MA, Katz K, Dorcely B, Roth J, Chetrit A, Dankner R. Reducing the prevalence of dysglycemia: is the time ripe to test the effectiveness of intervention in high-risk individuals with elevated 1 h post-load glucose levels? Endocrine 2017; 55:697-701. [PMID: 28124259 DOI: 10.1007/s12020-017-1236-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2016] [Accepted: 01/17/2017] [Indexed: 02/07/2023]
Abstract
Identifying the earliest time point on the prediabetic continuum is critical to avoid progressive deterioration in β-cell function. Progressively rising glucose levels even within the "normal range" occur considerably late in the evolution to diabetes thus presenting an important opportunity for earlier diagnosis, treatment, and possible reversal. An elevated 1 h postprandial glucose level, not detected by current diagnostic standards, may provide an opportunity for the early identification of those at risk. When the 1 h post-load glucose level is elevated, lifestyle intervention may have the greatest benefit for preserving β-cell function and prevent further progression to prediabetes and diabetes. In view of the considerable consistent epidemiologic data in large disparate populations supporting the predictive capacity of the1 h post-load value for predicting progression to diabetes and mortality, the time is therefore ripe to evaluate this hypothesis in a large, prospective multicenter randomized trial with lifestyle intervention.
Collapse
Affiliation(s)
- Michael Bergman
- NYU School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism, NYU Langone Diabetes Prevention Program, New York, NY, 10016, USA.
| | - Ram Jagannathan
- NYU School of Medicine, Department of Population Health, Division of Health Behavior Change, New York, NY, 10016, USA
| | - Martin Buysschaert
- Department of Endocrinology and Diabetology, Université Catholique de Louvain, University Clinic Saint-Luc, Brussels, Belgium
| | | | - Mary Ann Sevick
- NYU School of Medicine, Department of Population Health, Division of Health Behavior Change, New York, NY, 10016, USA
| | - Karin Katz
- NYU School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism, NYU Langone Diabetes Prevention Program, New York, NY, 10016, USA
| | - Brenda Dorcely
- NYU School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism, NYU Langone Diabetes Prevention Program, New York, NY, 10016, USA
| | - Jesse Roth
- The Feinstein Institute for Medical Research, Manhasset, North Shore, New York, 11030, USA
| | - Angela Chetrit
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel
| | - Rachel Dankner
- The Feinstein Institute for Medical Research, Manhasset, North Shore, New York, 11030, USA
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel
- Sackler Faculty of Medicine, School of Public Health, Department of Epidemiology and Preventive Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel
| |
Collapse
|
15
|
Hulman A, Simmons RK, Vistisen D, Tabák AG, Dekker JM, Alssema M, Rutters F, Koopman ADM, Solomon TPJ, Kirwan JP, Hansen T, Jonsson A, Gjesing AP, Eiberg H, Astrup A, Pedersen O, Sørensen TIA, Witte DR, Færch K. Heterogeneity in glucose response curves during an oral glucose tolerance test and associated cardiometabolic risk. Endocrine 2017; 55:427-434. [PMID: 27699707 DOI: 10.1007/s12020-016-1126-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Accepted: 09/14/2016] [Indexed: 02/06/2023]
Abstract
We aimed to examine heterogeneity in glucose response curves during an oral glucose tolerance test with multiple measurements and to compare cardiometabolic risk profiles between identified glucose response curve groups. We analyzed data from 1,267 individuals without diabetes from five studies in Denmark, the Netherlands and the USA. Each study included between 5 and 11 measurements at different time points during a 2-h oral glucose tolerance test, resulting in 9,602 plasma glucose measurements. Latent class trajectories with a cubic specification for time were fitted to identify different patterns of plasma glucose change during the oral glucose tolerance test. Cardiometabolic risk factor profiles were compared between the identified groups. Using latent class trajectory analysis, five glucose response curves were identified. Despite similar fasting and 2-h values, glucose peaks and peak times varied greatly between groups, ranging from 7-12 mmol/L, and 35-70 min. The group with the lowest and earliest plasma glucose peak had the lowest estimated cardiovascular risk, while the group with the most delayed plasma glucose peak and the highest 2-h value had the highest estimated risk. One group, with normal fasting and 2-h values, exhibited an unusual profile, with the highest glucose peak and the highest proportion of smokers and men. The heterogeneity in glucose response curves and the distinct cardiometabolic risk profiles may reflect different underlying physiologies. Our results warrant more detailed studies to identify the source of the heterogeneity across the different phenotypes and whether these differences play a role in the development of type 2 diabetes and cardiovascular disease.
Collapse
Affiliation(s)
- Adam Hulman
- Department of Public Health, Section of Epidemiology, Aarhus University, Aarhus, Denmark.
- Danish Diabetes Academy, Odense, Denmark.
- Department of Medical Physics and Informatics, University of Szeged, Szeged, Hungary.
| | - Rebecca K Simmons
- Danish Diabetes Academy, Odense, Denmark
- Department of Public Health, Section of General Practice, Aarhus University, Aarhus, Denmark
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | | | - Adam G Tabák
- 1st Department of Medicine, Semmelweis University Faculty of Medicine, Budapest, Hungary
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Jacqueline M Dekker
- Department of Biostatistics and Epidemiology, VU Medical Center, Amsterdam, Netherlands
- EMGO+ Institute for Health and Care Research, VU Medical Center, Amsterdam, Netherlands
| | - Marjan Alssema
- Department of Biostatistics and Epidemiology, VU Medical Center, Amsterdam, Netherlands
- Unilever Research and Development, Vlaardingen, Netherlands
| | - Femke Rutters
- Department of Biostatistics and Epidemiology, VU Medical Center, Amsterdam, Netherlands
- EMGO+ Institute for Health and Care Research, VU Medical Center, Amsterdam, Netherlands
| | - Anitra D M Koopman
- Department of Biostatistics and Epidemiology, VU Medical Center, Amsterdam, Netherlands
- EMGO+ Institute for Health and Care Research, VU Medical Center, Amsterdam, Netherlands
| | - Thomas P J Solomon
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Edgbaston, UK
- Institute for Metabolism and Systems Research, University of Birmingham, Edgbaston, UK
| | - John P Kirwan
- Department of Pathobiology, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anna Jonsson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anette Prior Gjesing
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hans Eiberg
- Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Arne Astrup
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg University Hospital, The Capital Region, Copenhagen, Denmark
| | - Daniel R Witte
- Department of Public Health, Section of Epidemiology, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | | |
Collapse
|
16
|
Chamukuttan S, Ram J, Nanditha A, Shetty AS, Sevick MA, Bergman M, Johnston DG, Ramachandran A. Baseline level of 30-min plasma glucose is an independent predictor of incident diabetes among Asian Indians: analysis of two diabetes prevention programmes. Diabetes Metab Res Rev 2016; 32:762-767. [PMID: 26991329 DOI: 10.1002/dmrr.2799] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Revised: 03/02/2016] [Accepted: 03/06/2016] [Indexed: 12/21/2022]
Abstract
BACKGROUND The objective was to study the ability of the 30-min plasma glucose (30-min PG) during an oral glucose tolerance test to predict the future risk of type 2 diabetes among Asian Indians with impaired glucose tolerance. METHODS For the present analyses, we utilized data from 753 participants from two diabetes primary prevention studies, having complete data at the end of the study periods, including 236 from Indian Diabetes Prevention Programme-1 and 517 from the 2013 study. Baseline 30-min PG values were divided into tertiles: T1 < 9.1 mmol/L (<163.0 mg/dL); T2 9.2-10.4 mmol/L (164.0-187.0 mg/dL) and T3 ≥ 10.4 mmol/L (≥188 mg/dL). The predictive values of tertiles of 30-min PG for incident diabetes were assessed using Cox regression analyses RESULTS: At the end of the studies, 230 (30.5%) participants developed diabetes. Participants with higher levels of 30-min PG were more likely to have increased fasting, 2-h PG and HbA1c levels, increased prevalence of impaired fasting glucose and decreased beta cell function. The progression rate of diabetes increased with increasing tertiles of 30-min PG. Cox's regression analysis showed that 30-min PG was an independent predictor of incident diabetes after adjustment for an array of covariates [Hazard Ratio (HR):1.44 (1.01-2.06)] CONCLUSIONS: This prospective analysis demonstrates, for the first time, an independent association between an elevated 30-min PG level and incident diabetes among Asian Indians with impaired glucose tolerance. Predictive utility of glycemic thresholds at various time points other than the traditional fasting and 2-h PG values should therefore merit further consideration. Copyright © 2016 John Wiley & Sons, Ltd.
Collapse
Affiliation(s)
- Snehalatha Chamukuttan
- India Diabetes Research Foundation and Dr. A. Ramachandran's Diabetes Hospitals, Chennai, 600008, India
| | - Jagannathan Ram
- Department of Population Health, Center for Healthful Behavior Change, NYU School of Medicine, NYU Langone Medical Centre, New York, USA
| | - Arun Nanditha
- India Diabetes Research Foundation and Dr. A. Ramachandran's Diabetes Hospitals, Chennai, 600008, India
| | - Ananth Samith Shetty
- India Diabetes Research Foundation and Dr. A. Ramachandran's Diabetes Hospitals, Chennai, 600008, India
| | - Mary Ann Sevick
- Department of Population Health, Center for Healthful Behavior Change, NYU School of Medicine, NYU Langone Medical Centre, New York, USA
| | - Michael Bergman
- Department of Medicine, Division of Endocrinology and Metabolism, NYU Diabetes Prevention Program, NYU Langone Medical Centre, New York, USA
| | | | - Ambady Ramachandran
- India Diabetes Research Foundation and Dr. A. Ramachandran's Diabetes Hospitals, Chennai, 600008, India.
| |
Collapse
|
17
|
Bergman M, Chetrit A, Roth J, Jagannathan R, Sevick M, Dankner R. One-hour post-load plasma glucose level during the OGTT predicts dysglycemia: Observations from the 24year follow-up of the Israel Study of Glucose Intolerance, Obesity and Hypertension. Diabetes Res Clin Pract 2016; 120:221-8. [PMID: 27596059 DOI: 10.1016/j.diabres.2016.08.013] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2016] [Revised: 08/09/2016] [Accepted: 08/19/2016] [Indexed: 01/04/2023]
Abstract
AIMS The present study assessed the longitudinal association of an elevated 1-h plasma glucose [1-h-PG >8.6mmol/l (155mg/dl)] with and without impaired glucose tolerance [IGT; 2-h-PG 7.8-11.0mmol/l (140-199mg/dl)] with cumulative incident of diabetes and prediabetes over 24years in a non-diabetic cohort. METHODS From 1979 to 1984, 1970 non-diabetic men and women completed an oral glucose tolerance test (OGTT), physical and biochemical measurements as well as a questionnaire related to lifestyle and medical background. During the years 2000-2004, 853 survivors of the original cohort were interviewed and re-examined for glycemic progression. RESULTS Individuals with 1-h-PG >8.6mmol/l (155mg/dl) but with 2-h-PG <7.8mmol/l (140mg/dl) had a significantly elevated risk, compared to those with both 1-h-PG ⩽8.6mmol/l (155mg/dl) and 2-h-PG <7.8mmol/l (140mg/dl), for both diabetes [OR:4.35 (95%CI: 2.50-7.73)] and prediabetes outcomes [OR:1.87 (95%CI 1.09-3.26)], adjusted for sex and age, smoking, body mass index, blood pressure, fasting blood glucose and insulin. CONCLUSIONS The risk for diabetes associated with a 1-h level >8.6mmol/l (155mg/dl) is increased and further worsened in the presence of IGT. Identifying individuals at risk with a 1-h-PG glucose level during an OGTT is recommended.
Collapse
Affiliation(s)
- Michael Bergman
- NYU School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism, NYU Langone Diabetes Prevention Program, 530 First Avenue, Schwartz East, Suite 5E, New York, NY 10016, USA.
| | - Angela Chetrit
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer 52621, Israel
| | - Jesse Roth
- The Feinstein Institute for Medical Research, Manhasset, North Shore, New York 11030, USA
| | - Ram Jagannathan
- NYU School of Medicine, Department of Population Health, Division of Health Behavior Change, New York, NY 10016, USA
| | - Mary Sevick
- NYU School of Medicine, Department of Population Health, Division of Health Behavior Change, New York, NY 10016, USA
| | - Rachel Dankner
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer 52621, Israel; The Feinstein Institute for Medical Research, Manhasset, North Shore, New York 11030, USA; Sackler Faculty of Medicine, School of Public Health, Department of Epidemiology and Preventive Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
| |
Collapse
|
18
|
Jagannathan R, Sevick MA, Fink D, Dankner R, Chetrit A, Roth J, Buysschaert M, Bergman M. The 1-hour post-load glucose level is more effective than HbA1c for screening dysglycemia. Acta Diabetol 2016; 53:543-50. [PMID: 26794497 DOI: 10.1007/s00592-015-0829-6] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Accepted: 12/11/2015] [Indexed: 12/12/2022]
Abstract
AIM To assess the performance of HbA1c and the 1-h plasma glucose (PG ≥ 155 mg/dl; 8.6 mmol/l) in identifying dysglycemia based on the oral glucose tolerance test (OGTT) from a real-world clinical care setting. METHODS This was a diagnostic test accuracy study. For this analysis, we tested the HbA1c diagnostic criteria advocated by the American Diabetes Association (ADA 5.7-6.4 %) and International Expert Committee (IEC 6.0-6.4 %) against conventional OGTT criteria. We also tested the utility of 1-h PG ≥ mg/dl; 8.6 mmol/l. Prediabetes was defined according to ADA-OGTT guidelines. Spearman correlation tests were used to determine the relationships between HbA1c, 1-h PG with fasting, 2-h PG and indices of insulin sensitivity and β-cell function. The levels of agreement between diagnostic methods were ascertained using Cohen's kappa coefficient (Κ). Receiver operating characteristic (ROC) curve was used to analyze the performance of the HbA1c and 1-h PG test in identifying prediabetes considering OGTT as reference diagnostic criteria. The diagnostic properties of different HbA1c thresholds were contrasted by determining sensitivity, specificity and likelihood ratios (LR). RESULTS Of the 212 high-risk individuals, 70 (33 %) were identified with prediabetes, and 1-h PG showed a stronger association with 2-h PG, insulin sensitivity index, and β-cell function than HbA1c (P < 0.05). Furthermore, the level of agreement between 1-h PG ≥ 155 mg/dl (8.6 mmol/l) and the OGTT (Κ[95 % CI]: 0.40[0.28-0.53]) diagnostic test was stronger than that of ADA-HbA1c criteria 0.1[0.03-0.16] and IEC criteria (0.17[0.04-0.30]). The ROC (AUC[95 % CI]) for HbA1c and 1-h PG were 0.65[0.57-0.73] and 0.79[0.72-0.85], respectively. Importantly, 1-h PG ≥ 155 mg/dl (8.6 mmol/l) showed good sensitivity (74.3 % [62.4-84.0]) and specificity 69.7 % [61.5-77.1]) with a LR of 2.45. The ability of 1-h PG to discriminate prediabetes was better than that of HbA1c (∆AUC: -0.14; Z value: 2.5683; P = 0.01022). CONCLUSION In a real-world clinical practice setting, the 1-h PG ≥ 155 mg/dl (8.6 mmol/l) is superior for detecting high-risk individuals compared with HbA1c. Furthermore, HbA1c is a less precise correlate of insulin sensitivity and β-cell function than the 1-h PG and correlates poorly with the 2-h PG during the OGTT.
Collapse
Affiliation(s)
- Ram Jagannathan
- NYU School of Medicine, Department of Population Health, Center for Healthful Behavior Change, New York, NY, USA
| | - Mary Ann Sevick
- NYU School of Medicine, Department of Population Health, Center for Healthful Behavior Change, New York, NY, USA
| | - Dorothy Fink
- NYU School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism, NYU Langone Diabetes Prevention Program, 530 First Avenue, Schwartz East, Suite 5E, New York, NY, 10016, USA
| | - Rachel Dankner
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel
- The Feinstein Institute for Medical Research, Manhasset, North Shore, NY, 11030, USA
- Sackler Faculty of Medicine, School of Public Health, Department of Epidemiology and Preventive Medicine, Tel Aviv University, Ramat Aviv, 69978, Tel Aviv, Israel
| | - Angela Chetrit
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel
| | - Jesse Roth
- The Feinstein Institute for Medical Research, Manhasset, North Shore, NY, 11030, USA
| | - Martin Buysschaert
- Service d'Endocrinologie et Nutrition Cliniques Universitaires St-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Michael Bergman
- NYU School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism, NYU Langone Diabetes Prevention Program, 530 First Avenue, Schwartz East, Suite 5E, New York, NY, 10016, USA.
| |
Collapse
|
19
|
Bergman M, Chetrit A, Roth J, Dankner R. One-hour post-load plasma glucose level during the OGTT predicts mortality: observations from the Israel Study of Glucose Intolerance, Obesity and Hypertension. Diabet Med 2016; 33:1060-6. [PMID: 26996391 DOI: 10.1111/dme.13116] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/14/2016] [Indexed: 12/28/2022]
Abstract
AIMS The relationship between 1- and 2-h glucose levels following an oral glucose tolerance test (OGTT) and long-term mortality was evaluated. METHODS Over a 33-year period, 2138 individuals were followed for all-cause mortality. Fasting and post-OGTT glucose parameters categorized the cohort according to baseline glycaemic status. Four categories were established according to 1- and 2-h glucose levels (in mmol/l): group A = 1 h ≤ 8.8 and 2 h < 7.8; group B = 1 h > 8.6 and 2 h < 7.8; group C = 1 h ≤ 8.6 and 2 h = 7.8-11.1 (impaired glucose tolerance); group D = 1 h > 8.6 and 2 h = 7.8-11.1 (impaired glucose tolerance). Individuals with diabetes at baseline were excluded from the cohort. RESULTS By August 2013, 51% of the study cohort had died. The worst prognosis occurred in group D (73.8% mortality), followed by groups C (67.5%), B and A (57.9% and 41.6%, respectively). When the 2-h glucose value is 'normal' (< 7.8 mmol/l), the 1-h glucose value > 8.6 mmol/l is an important predictor of mortality (28% increased risk) compared with group A, controlling for sex, age, smoking, BMI, systolic and diastolic blood pressures. A gradual increased hazard for mortality was seen by study group (hazard ratio = 1.28, 1.60 and 1.76, for groups B, C and D, respectively; group A = reference). CONCLUSIONS A 1-h glucose value > 8.6 mmol/l predicts mortality even when the 2-h level is < 7.8 mmol/l. However, when the 2-h level is in the impaired glucose tolerance range, the hazard for mortality rises significantly independent of the 1-h value. Individuals at risk for developing diabetes could be identified earlier using the 1-h threshold value of 8.6 mmol/l, which could avert progression to diabetes and increased mortality..
Collapse
Affiliation(s)
- M Bergman
- NYU Diabetes Prevention Program, NYU School of Medicine, New York, USA
| | - A Chetrit
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Tel Hashomer, Israel
| | - J Roth
- The Feinstein Institute for Medical Research, Manhasset, USA
| | - R Dankner
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Tel Hashomer, Israel
- The Feinstein Institute for Medical Research, Manhasset, USA
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| |
Collapse
|
20
|
Jagannathan R, Sevick MA, Li H, Fink D, Dankner R, Chetrit A, Roth J, Bergman M. Elevated 1-hour plasma glucose levels are associated with dysglycemia, impaired beta-cell function, and insulin sensitivity: a pilot study from a real world health care setting. Endocrine 2016; 52:172-5. [PMID: 26419850 PMCID: PMC5319479 DOI: 10.1007/s12020-015-0746-z] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 09/16/2015] [Indexed: 10/23/2022]
Affiliation(s)
- Ram Jagannathan
- Department of Population Health, Division of Health Behavior Change, NYU School of Medicine, New York, NY, USA
| | - Mary Ann Sevick
- Department of Population Health, Division of Health Behavior Change, NYU School of Medicine, New York, NY, USA
| | - Huilin Li
- Department of Population Health, Division of Biostatistics, NYU School of Medicine, New York, NY, USA
| | - Dorothy Fink
- Department of Medicine, NYU Diabetes Prevention Program, Division of Endocrinology and Metabolism, NYU School of Medicine, 530 First Avenue, Schwartz East, Suite 5E, New York, NY, 10016, USA
| | - Rachel Dankner
- Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, 69978, Tel Aviv, Israel
- The Feinstein Institute for Medical Research, Manhasset, North Shore, NY, 11030, USA
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel
| | - Angela Chetrit
- Unit for Cardiovascular Epidemiology, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel
| | - Jesse Roth
- The Feinstein Institute for Medical Research, Manhasset, North Shore, NY, 11030, USA
| | - Michael Bergman
- Department of Medicine, NYU Diabetes Prevention Program, Division of Endocrinology and Metabolism, NYU School of Medicine, 530 First Avenue, Schwartz East, Suite 5E, New York, NY, 10016, USA.
| |
Collapse
|
21
|
Lee SS, Seo H, Ryu S, Kwon TD. The effect of swimming exercise and powdered-Salicornia herbacea L. ingestion on glucose metabolism in STZ-induced diabetic rats. J Exerc Nutrition Biochem 2015; 19:235-45. [PMID: 26525167 PMCID: PMC4624125 DOI: 10.5717/jenb.2015.15083110] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2015] [Revised: 08/15/2015] [Accepted: 08/31/2015] [Indexed: 11/24/2022] Open
Abstract
Purpose The purpose of this study is to observe the effects of Salicornia herbacea L. powder ingestion on carbohydrate metabolism in STZ-induced diabetic rats. Methods To achieve this objective, 35 Sprague-Dawley male rats were raised with feed mixed with Salicornia herbacia L. powder and given specific periods to swim for 5 weeks. There was no significant difference in the insulin increase rate while ingesting Salicornia herbacea L. powder and simultaneously exercising. Results Compared to the diabetes mellitus group, HOMA-IR was significantly decreased in the diabetes mellitus + exercise group, diabetes mellitus + Salicornia herbacea group, and the diabetes mellitus + Salicornia herbacea + exercise group. However, changes in blood glucose were significant in each group. Thus, for the result of GLUT-4 and GLUT-2, which are the glycose transporters of the liver and muscle, diabetes mellitus + exercise group, diabetes mellitus + Salicornia herbacea group, and diabetes mellitus + Salicornia herbacea + exercise group showed significantly higher expressions. The glycogen concentration of the liver and muscle was significantly increased in the diabetes mellitus + exercise group, diabetes mellitus + Salicornia herbacea group, and diabetes mellitus + Salicornia herbacea + exercise group. Conclusion With the results above, it seems that taking Salicornia herbacea L. powder and exercise will help prevent various diabetic complications. Therefore, the findings of this study could justify Salicornia herbacea L. powder with its basal data of physiological activities and pharmacological components as a type of health functional food.
Collapse
Affiliation(s)
- Se Sil Lee
- Department of Leisure Sports, Kyungpook National University, Sangju, Republic of Korea
| | - Hyobin Seo
- Department of Leisure Sports, Kyungpook National University, Sangju, Republic of Korea
| | - Sungpil Ryu
- Department of Leisure Sports, Kyungpook National University, Sangju, Republic of Korea
| | - Tae-Dong Kwon
- Department of Leisure Sports, Kyungpook National University, Sangju, Republic of Korea
| |
Collapse
|