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Shibib L, Al-Qaisi M, Guess N, Miras AD, Greenwald SE, Pelling M, Ahmed A. Manipulation of Post-Prandial Hyperglycaemia in Type 2 Diabetes: An Update for Practitioners. Diabetes Metab Syndr Obes 2024; 17:3111-3130. [PMID: 39206417 PMCID: PMC11350065 DOI: 10.2147/dmso.s458894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 07/23/2024] [Indexed: 09/04/2024] Open
Abstract
This review paper explores post-prandial glycemia in type 2 diabetes. Post-prandial glycemia is defined as the period of blood glucose excursion from immediately after the ingestion of food or drink to 4 to 6 hours after the end of the meal. Post-prandial hyperglycemia is an independent risk factor for cardiovascular disease with glucose "excursions" being more strongly associated with markers of oxidative stress than the fasting or pre-prandial glucose level. High blood glucose is a major promoter of enhanced free radical production and is associated with the onset and progression of type 2 diabetes. Oxidative stress impairs insulin action creating a vicious cycle where repeated post-prandial glucose spikes are key drivers in the pathogenesis of the vascular complications of type 2 diabetes, both microvascular and macrovascular. Some authors suggest post-prandial hyperglycemia is the major cause of death in type 2 diabetes. Proper management of post-prandial hyperglycemia could yield up to a 35% cut in overall cardiovascular events, and a 64% cut in myocardial infarction. The benefits of managing post-prandial hyperglycemia are similar in magnitude to those seen in type 2 diabetes patients receiving secondary prevention with statins - prevention which today is regarded as fundamental by all practitioners. Given all the evidence surrounding the impact of post-prandial glycemia on overall outcome, it is imperative that any considered strategy for the management of type 2 diabetes should include optimum dietary, pharma, and lifestyle interventions that address glucose excursion. Achieving a low post-prandial glucose response is key to prevention and progression of type 2 diabetes and cardiometabolic diseases. Further, such therapeutic interventions should be sustainable and must benefit patients in the short and long term with the minimum of intrusion and side effects. This paper reviews the current literature around dietary manipulation of post-prandial hyperglycemia, including novel approaches. A great deal of further work is required to optimize and standardize the dietary management of post-prandial glycemia in type 2 diabetes, including consideration of novel approaches that show great promise.
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Affiliation(s)
- Lina Shibib
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Mo Al-Qaisi
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Nicola Guess
- Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK
| | | | - Steve E Greenwald
- Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Marc Pelling
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Ahmed Ahmed
- Department of Surgery and Cancer, Imperial College London, London, UK
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Wang Y, Fang Y, Aberson CL, Charchar FJ, Ceriello A. Postprandial Plasma Glucose between 4 and 7.9 h May Be a Potential Diagnostic Marker for Diabetes. Biomedicines 2024; 12:1313. [PMID: 38927521 PMCID: PMC11201079 DOI: 10.3390/biomedicines12061313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024] Open
Abstract
Postprandial glucose levels between 4 and 7.9 h (PPG4-7.9h) correlate with mortality from various diseases, including hypertension, diabetes, cardiovascular disease, and cancer. This study aimed to assess if predicted PPG4-7.9h could diagnose diabetes. Two groups of participants were involved: Group 1 (4420 participants) had actual PPG4-7.9h, while Group 2 (8422 participants) lacked this measure but had all the diabetes diagnostic measures. Group 1 underwent multiple linear regression to predict PPG4-7.9h using 30 predictors, achieving accuracy within 11.1 mg/dL in 80% of the participants. Group 2 had PPG4-7.9h predicted using this model. A receiver operating characteristic curve analysis showed that predicted PPG4-7.9h could diagnose diabetes with an accuracy of 87.3% in Group 2, with a sensitivity of 75.1% and specificity of 84.1% at the optimal cutoff of 102.5 mg/dL. A simulation on 10,000 random samples from Group 2 revealed that 175 participants may be needed to investigate PPG4-7.9h as a diabetes diagnostic marker with a power of at least 80%. In conclusion, predicted PPG4-7.9h appears to be a promising diagnostic indicator for diabetes. Future studies seeking to ascertain its definitive diagnostic value might require a minimum sample size of 175 participants.
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Affiliation(s)
- Yutang Wang
- Discipline of Life Science, Institute of Innovation, Science and Sustainability, Federation University Australia, Ballarat, VIC 3350, Australia
| | - Yan Fang
- Discipline of Life Science, Institute of Innovation, Science and Sustainability, Federation University Australia, Ballarat, VIC 3350, Australia
| | | | - Fadi J. Charchar
- Discipline of Life Science, Institute of Innovation, Science and Sustainability, Federation University Australia, Ballarat, VIC 3350, Australia
| | - Antonio Ceriello
- RCCS MultiMedica, Via Gaudenzio Fantoli, 16/15, 20138 Milan, Italy;
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Giorgino F, Battelino T, Bergenstal RM, Forst T, Green JB, Mathieu C, Rodbard HW, Schnell O, Wilmot EG. The Role of Ultra-Rapid-Acting Insulin Analogs in Diabetes: An Expert Consensus. J Diabetes Sci Technol 2023:19322968231204584. [PMID: 37937585 DOI: 10.1177/19322968231204584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
Ultra-rapid-acting insulin analogs (URAA) are a further development and refinement of rapid-acting insulin analogs. Because of their adapted formulation, URAA provide an even faster pharmacokinetics and thus an accelerated onset of insulin action than conventional rapid-acting insulin analogs, allowing for a more physiologic delivery of exogenously applied insulin. Clinical trials have confirmed the superiority of URAA in controlling postprandial glucose excursions, with a safety profile that is comparable to the rapid-acting insulins. Consequently, many individuals with diabetes mellitus may benefit from URAA in terms of prandial glycemic control. Unfortunately, there are only few available recommendations from authoritative sources for use of URAA in clinical practice. Therefore, this expert consensus report aims to define populations of people with diabetes mellitus for whom URAA may be beneficial and to provide health care professionals with concrete, practical recommendations on how best to use URAA in this context.
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Affiliation(s)
- Francesco Giorgino
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Precision and Regenerative Medicine and Ionian Area, University of Bari Aldo Moro, Bari, Italy
| | - Tadej Battelino
- Department of Endocrinology, Diabetes and Metabolism, UCH-University Medical Center Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | | | - Thomas Forst
- Department of Endocrinology and Metabolic Diseases, Johannes Gutenberg University Medical Center, Mainz, Germany
- Clinical Research Services, Mannheim, Germany
| | - Jennifer B Green
- Division of Endocrinology and Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA
| | - Chantal Mathieu
- Clinical and Experimental Endocrinology, University Hospital Gasthuisberg, Katholieke Universiteit Leuven, Leuven, Belgium
| | | | - Oliver Schnell
- Forschergruppe Diabetes eV at the Helmholtz Centre, Munich-Neuherberg, Germany
| | - Emma G Wilmot
- Department of Diabetes & Endocrinology, University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK
- Academic Unit for Translational Medical Sciences, University of Nottingham, Nottingham, England, UK
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Kharmats AY, Popp C, Hu L, Berube L, Curran M, Wang C, Pompeii ML, Li H, Bergman M, St-Jules DE, Segal E, Schoenthaler A, Williams N, Schmidt AM, Barua S, Sevick MA. A randomized clinical trial comparing low-fat with precision nutrition-based diets for weight loss: impact on glycemic variability and HbA1c. Am J Clin Nutr 2023; 118:443-451. [PMID: 37236549 PMCID: PMC10447469 DOI: 10.1016/j.ajcnut.2023.05.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 05/16/2023] [Accepted: 05/23/2023] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND Recent studies have demonstrated considerable interindividual variability in postprandial glucose response (PPGR) to the same foods, suggesting the need for more precise methods for predicting and controlling PPGR. In the Personal Nutrition Project, the investigators tested a precision nutrition algorithm for predicting an individual's PPGR. OBJECTIVE This study aimed to compare changes in glycemic variability (GV) and HbA1c in 2 calorie-restricted weight loss diets in adults with prediabetes or moderately controlled type 2 diabetes (T2D), which were tertiary outcomes of the Personal Diet Study. METHODS The Personal Diet Study was a randomized clinical trial to compare a 1-size-fits-all low-fat diet (hereafter, standardized) with a personalized diet (hereafter, personalized). Both groups received behavioral weight loss counseling and were instructed to self-monitor diets using a smartphone application. The personalized arm received personalized feedback through the application to reduce their PPGR. Continuous glucose monitoring (CGM) data were collected at baseline, 3 mo and 6 mo. Changes in mean amplitude of glycemic excursions (MAGEs) and HbA1c at 6 mo were assessed. We performed an intention-to-treat analysis using linear mixed regressions. RESULTS We included 156 participants [66.5% women, 55.7% White, 24.1% Black, mean age 59.1 y (standard deviation (SD) = 10.7 y)] in these analyses (standardized = 75, personalized = 81). MAGE decreased by 0.83 mg/dL per month for standardized (95% CI: 0.21, 1.46 mg/dL; P = 0.009) and 0.79 mg/dL per month for personalized (95% CI: 0.19, 1.39 mg/dL; P = 0.010) diet, with no between-group differences (P = 0.92). Trends were similar for HbA1c values. CONCLUSIONS Personalized diet did not result in an increased reduction in GV or HbA1c in patients with prediabetes and moderately controlled T2D, compared with a standardized diet. Additional subgroup analyses may help to identify patients who are more likely to benefit from this personalized intervention. This trial was registered at clinicaltrials.gov as NCT03336411.
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Affiliation(s)
- Anna Y Kharmats
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Collin Popp
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Lu Hu
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Lauren Berube
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.
| | - Margaret Curran
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Chan Wang
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Mary Lou Pompeii
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Huilin Li
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Michael Bergman
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States; Division of Endocrinology, Diabetes and Metabolism, New York University Grossman School of Medicine, New York, NY, United States
| | - David E St-Jules
- Department of Nutrition, University of Nevada, Reno, Reno, NV, United States
| | - Eran Segal
- Department of Computer Science and Applied Math, Weizmann Institute of Science, Rehovot, Israel
| | - Antoinette Schoenthaler
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Natasha Williams
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Ann Marie Schmidt
- Diabetes Research Program, Department of Medicine, New York University Langone Health, New York, NY, United States
| | - Souptik Barua
- Division of Precision Medicine, Department of Medicine, New York University Langone Health, New York, NY, United States
| | - Mary Ann Sevick
- Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States; Division of Endocrinology, Diabetes and Metabolism, New York University Grossman School of Medicine, New York, NY, United States
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Wang Y, Fang Y. Late non-fasting plasma glucose predicts cardiovascular mortality independent of hemoglobin A1c. Sci Rep 2022; 12:7778. [PMID: 35545695 PMCID: PMC9095589 DOI: 10.1038/s41598-022-12034-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 04/20/2022] [Indexed: 12/25/2022] Open
Abstract
It is unknown whether non-fasting plasma glucose (PG) is associated with cardiovascular disease (CVD) mortality. This study aimed to investigate this association in US adults. This study included adults from the National Health and Nutrition Examination Surveys from 1988 to 2014. Mortality outcomes were ascertained by linkage to the National Death Index records. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of PG for CVD mortality. Among 34,907 participants, 1956, 5564, and 27,387 had PG from participants in early non-fasting, late non-fasting, and fasting states, respectively (defined as a period since last calorie intake of 0–2.9, 3.0–7.9, or ≥ 8.0 h, respectively). This cohort was followed up for 455,177 person-years (mean follow-up, 13.0 years), with 2,387 CVD deaths being recorded. After adjustment for all confounders including hemoglobin A1c (HbA1c), only late non-fasting PG (continuous, natural log-transformed) was positively associated with CVD mortality risks (hazard ratio, 1.73; 95% confidence interval 1.12–2.67). Higher late non-fasting PG (dichotomous, at a cut-off of 105, 110, or 115 mg/dL) was associated with higher CVD mortality risks. In addition, at the cut-off of 115 mg/dL, higher late non-fasting PG was associated with higher CVD mortality risks in those with either a normal (< 5.7%) or prediabetic HbA1c level (from 5.7 to 6.4%). In conclusion, late non-fasting PG predicts CVD mortality independent of HbA1c. Late non-fasting PG with a cut-off of 115 mg/dL may be used to identify those at high CVD risk.
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Affiliation(s)
- Yutang Wang
- Discipline of Life Sciences, School of Science, Psychology and Sport, Federation University Australia, University Drive, Mt Helen, Ballarat, VIC, 3350, Australia.
| | - Yan Fang
- Discipline of Life Sciences, School of Science, Psychology and Sport, Federation University Australia, University Drive, Mt Helen, Ballarat, VIC, 3350, Australia
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Kleissl-Muir S, Rasmussen B, Owen A, Zinn C, Driscoll A. Low Carbohydrate Diets for Diabetic Cardiomyopathy: A Hypothesis. Front Nutr 2022; 9:865489. [PMID: 35529461 PMCID: PMC9069235 DOI: 10.3389/fnut.2022.865489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Elevated blood glucose levels, insulin resistance (IR), hyperinsulinemia and dyslipidemia the key aspects of type 2 diabetes mellitus (T2DM), contribute to the development of a certain form of cardiomyopathy. This cardiomyopathy, also known as diabetic cardiomyopathy (DMCM), typically occurs in the absence of overt coronary artery disease (CAD), hypertension or valvular disease. DMCM encompasses a variety of pathophysiological processes impacting the myocardium, hence increasing the risk for heart failure (HF) and significantly worsening outcomes in this population. Low fat (LF), calorie-restricted diets have been suggested as the preferred eating pattern for patients with HF. However, LF diets are naturally higher in carbohydrates (CHO). We argue that in an insulin resistant state, such as in DMCM, LF diets may worsen glycaemic control and promote further insulin resistance (IR), contributing to a physiological and functional decline in DMCM. We postulate that CHO restriction targeting hyperinsulinemia may be able to improve tissue and systemic IR. In recent years low carbohydrate diets (LC) including ketogenic diets (KD), have emerged as a safe and effective tool for the management of various clinical conditions such as T2DM and other metabolic disorders. CHO restriction achieves sustained glycaemic control, lower insulin levels and successfully reverses IR. In addition to this, its pleiotropic effects may present a metabolic stress defense and facilitate improvement to cardiac function in patients with HF. We therefore hypothesize that patients who adopt a LC diet may require less medications and experience improvements in HF-related symptom burden.
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Affiliation(s)
| | - Bodil Rasmussen
- School of Nursing and Midwifery, Deakin University, Geelong, VIC, Australia
- Centre for Quality and Patient Safety, School of Nursing and Midwifery, Institute for Health Transformation, Deakin University, Geelong, VIC, Australia
- The Centre for Quality and Patient Safety, Institute of Health Transformation -Western Health Partnership, Western Health, St Albans, VIC, Australia
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health Sciences, University of Southern Denmark and Steno Diabetes Centre, Odense, Denmark
| | - Alice Owen
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Caryn Zinn
- Human Potential Centre, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland, New Zealand
| | - Andrea Driscoll
- School of Nursing and Midwifery, Deakin University, Geelong, VIC, Australia
- Centre for Quality and Patient Safety, School of Nursing and Midwifery, Institute for Health Transformation, Deakin University, Geelong, VIC, Australia
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Department of Cardiology, Austin Health, Heidelberg, VIC, Australia
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Lim S, Kim YJ, Khang AR, Eckel RH. Postprandial dyslipidemia after a standardized high-fat meal in BMI-matched healthy individuals, and in subjects with prediabetes or type 2 diabetes. Clin Nutr 2021; 40:5538-5546. [PMID: 34656950 DOI: 10.1016/j.clnu.2021.09.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 08/18/2021] [Accepted: 09/03/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND & AIMS A relationship between postprandial hyperlipidemia and glucose homeostasis/cardiovascular diseases has been suggested. We investigated postprandial plasma lipid patterns after a standardized high-fat meal and their association with glucose homeostasis and subclinical atherosclerosis. METHODS Using matching by BMI, 32 healthy individuals with normal glucose tolerance (NGT), 21 subjects with impaired glucose tolerance (IGT), and 20 subjects with drug-naïve type 2 diabetes (T2D) were enrolled. Plasma concentrations of triglycerides (TGs), apolipoprotein-B (ApoB), ApoB48, ApoB100, glucose, and insulin at baseline and 1, 2, 3, 4, 5, 6, and 8 h after a standardized meal (1041.03 kcal with 70.99 g of fat) were measured. Body composition, abdominal visceral fat area, and resting energy expenditure (REE) were measured using dual energy X-ray absorptiometry, computed tomography, and indirect calorimetry, respectively. The intima-media thickness (IMT) of the carotid artery and the ankle-brachial index (ABI) were used to detect subclinical atherosclerosis. RESULTS Baseline data and area under the curve (AUC) of plasma concentrations of TGs, ApoB, and ApoB48 in the IGT and T2D groups were higher than in the NGT group. The peak TG concentrations after the meal was observed at 5 h in subjects with IGT and T2D, while healthy subjects showed the highest concentrations at 4 h. In multivariable analysis, high abdominal visceral fat area and low HDL-cholesterol concentrations were independently associated with the AUCTG and AUCApoB after adjusting for confounders including baseline TG and the REE. High LDL-cholesterol and high HbA1c concentrations were also associated with the AUCApoB. Furthermore, high AUCTG and AUCApoB values were independent factors for an increased carotid IMT and a low ABI after adjusting for relevant variables. CONCLUSIONS Abdominal visceral obesity and low HDL-cholesterol concentrations were associated with increased post load excursions of TGs and ApoB in this series. These elevated concentrations of TGs and ApoB were linked with subclinical atherosclerosis.
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Affiliation(s)
- Soo Lim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea.
| | - Yoon Ji Kim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea; Department of Internal Medicine, Mediplex Sejong Hospital, Incheon, South Korea
| | - Ah Reum Khang
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea; Department of Internal Medicine, Pusan National University Yangsan Hospital, Pusan National University College of Medicine, Yangsan, South Korea
| | - Robert H Eckel
- Division of Endocrinology, Metabolism and Diabetes, Division of Cardiology, Emeritus University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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