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Ho JPY, Lau ESH, Kwan O C, Fan B, Ko GTC, Kong APS, Ma RCW, Chow EYK, Chan JCN, Luk AOY. One-hour post-load plasma glucose level predicts future type 2 diabetes in a community-based study of Hong Kong Chinese workforce. Diabetes Res Clin Pract 2024; 212:111718. [PMID: 38796080 DOI: 10.1016/j.diabres.2024.111718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/08/2024] [Accepted: 05/19/2024] [Indexed: 05/28/2024]
Abstract
BACKGROUND We compared performance of high 1-hour PG level, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) in predicting type 2 diabetes in a longitudinal community-based cohort of Hong Kong Chinese. METHODS Between 2001 and 2003, 472 adults aged 18-55 years without diabetes underwent 75-gram oral glucose tolerance test (OGTT). Between 2012 and 2014, progression to diabetes was ascertained by reviewing medical records or repeating OGTT and HbA1c. We defined high 1-hour PG as PG ≥ 8.6 mmol/L at 1-hour. RESULTS In this cohort, 23.5% had normal glucose tolerance and high 1-hour PG, 10.0% had isolated IGT, 4.2% had isolated IFG. Over 12-year follow-up, 9.3% developed type 2 diabetes. In logistic regression, high 1-hour PG was associated with progression to type 2 diabetes with adjusted odds ratio (95% CI) of 4.20 (1.60, 12.40), independent of IFG, IGT and other clinical variables. Areas under ROC (95% CI) for type 2 diabetes were similar between 1-hour (0.84 [0.78, 0.89], 2-hour (0.79 [0.72, 0.86]) and fasting PG (0.79 [0.71, 0.86]). CONCLUSION High 1-hour PG identified young Chinese with 5-fold increased risk of type 2 diabetes independent of other intermediate hyperglycaemia status and clinical factors. 1-hour PG is similar to fasting and 2-hour PG in predicting type 2 diabetes.
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Affiliation(s)
- Jane Pui-Ying Ho
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Eric Siu-Him Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Chun Kwan O
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Gary Tin-Choi Ko
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Alice Pik-Shan Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Ronald Ching-Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Elaine Yee-Kwan Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Juliana Chung-Ngor Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Andrea On-Yan Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region.
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Bergman M, Manco M, Satman I, Chan J, Schmidt MI, Sesti G, Vanessa Fiorentino T, Abdul-Ghani M, Jagannathan R, Kumar Thyparambil Aravindakshan P, Gabriel R, Mohan V, Buysschaert M, Bennakhi A, Pascal Kengne A, Dorcely B, Nilsson PM, Tuomi T, Battelino T, Hussain A, Ceriello A, Tuomilehto J. International Diabetes Federation Position Statement on the 1-hour post-load plasma glucose for the diagnosis of intermediate hyperglycaemia and type 2 diabetes. Diabetes Res Clin Pract 2024; 209:111589. [PMID: 38458916 DOI: 10.1016/j.diabres.2024.111589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/10/2024]
Abstract
Many individuals with intermediate hyperglycaemia (IH), including impaired fasting glycaemia (IFG) and impaired glucose tolerance (IGT), as presently defined, will progress to type 2 diabetes (T2D). There is confirmatory evidence that T2D can be prevented by lifestyle modification and/or medications, in people with IGT diagnosed by 2-h plasma glucose (PG) during a 75-gram oral glucose tolerance test (OGTT). Over the last 40 years, a wealth of epidemiological data has confirmed the superior value of 1-h plasma glucose (PG) over fasting PG (FPG), glycated haemoglobin (HbA1c) and 2-h PG in populations of different ethnicity, sex and age in predicting diabetes and associated complications including death. Given the relentlessly rising prevalence of diabetes, a more sensitive, practical method is needed to detect people with IH and T2D for early prevention or treatment in the often lengthy trajectory to T2D and its complications. The International Diabetes Federation (IDF) Position Statement reviews findings that the 1-h post-load PG ≥ 155 mg/dL (8.6 mmol/L) in people with normal glucose tolerance (NGT) during an OGTT is highly predictive for detecting progression to T2D, micro- and macrovascular complications, obstructive sleep apnoea, cystic fibrosis-related diabetes mellitus, metabolic dysfunction-associated steatotic liver disease, and mortality in individuals with risk factors. The 1-h PG of 209 mg/dL (11.6 mmol/L) is also diagnostic of T2D. Importantly, the 1-h PG cut points for diagnosing IH and T2D can be detected earlier than the recommended 2-h PG thresholds. Taken together, the 1-h PG provides an opportunity to avoid misclassification of glycaemic status if FPG or HbA1c alone are used. The 1-h PG also allows early detection of high-risk people for intervention to prevent progression to T2D which will benefit the sizeable and growing population of individuals at increased risk of T2D. Using a 1-h OGTT, subsequent to screening with a non-laboratory diabetes risk tool, and intervening early will favourably impact the global diabetes epidemic. Health services should consider developing a policy for screening for IH based on local human and technical resources. People with a 1-h PG ≥ 155 mg/dL (8.6 mmol/L) are considered to have IH and should be prescribed lifestyle intervention and referred to a diabetes prevention program. People with a 1-h PG ≥ 209 mg/dL (11.6 mmol/L) are considered to have T2D and should have a repeat test to confirm the diagnosis of T2D and then referred for further evaluation and treatment. The substantive data presented in the Position Statement provides strong evidence for redefining current diagnostic criteria for IH and T2D by adding the 1-h PG.
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Affiliation(s)
- Michael Bergman
- NYU Grossman School of Medicine, Departments of Medicine and of Population Health, Division of Endocrinology, Diabetes and Metabolism, VA New York Harbor Healthcare System, New York, NY, USA.
| | - Melania Manco
- Predictive and Preventive Medicine Research Unit, Bambino Gesù Children's Hospital IRCCS, Rome, Italy
| | - Ilhan Satman
- Istanbul University Faculty of Medicine, Department of Internal Medicine, Division of Endocrinology and Metabolism, Istanbul, Turkey
| | - Juliana Chan
- The Chinese University of Hong Kong, Faculty of Medicine, Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Hong Kong, China
| | - Maria Inês Schmidt
- Postgraduate Program in Epidemiology, School of Medicine and Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Giorgio Sesti
- Department of Clinical and Molecular Medicine, University of Rome-Sapienza, 00189 Rome, Italy
| | - Teresa Vanessa Fiorentino
- Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, 88100 Catanzaro, Italy
| | - Muhammad Abdul-Ghani
- Division of Diabetes, University of Texas Health Science Center at San Antonio, San Antonio Texas, USA
| | - Ram Jagannathan
- Hubert Department of Global Health Rollins, School of Public Health, Emory University, Atlanta, GA, USA
| | | | - Rafael Gabriel
- Department of International Health, National School of Public Health, Instituto de Salud Carlos III, Madrid, Spain
| | - Viswanathan Mohan
- Dr. Mohan's Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
| | - Martin Buysschaert
- Department of Endocrinology and Diabetology, Université Catholique de Louvain, University, Clinic Saint-Luc, Brussels, Belgium
| | - Abdullah Bennakhi
- Dasman Diabetes Institute Office of Regulatory Affairs, Ethics Review Committee, Kuwait
| | - Andre Pascal Kengne
- South African Medical Research Council, Francie Van Zijl Dr, Parow Valley, Cape Town, 7501, South Africa
| | - Brenda Dorcely
- NYU Grossman School of Medicine, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, NY, USA
| | - Peter M Nilsson
- Department of Clinical Sciences and Lund University Diabetes Centre, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Tiinamaija Tuomi
- Folkhälsan Research Center, Helsinki, Finland; Abdominal Center, Endocrinology, Helsinki University Central Hospital, Research Program for Diabetes and Obesity, Center of Helsinki, Helsinki, Finland
| | | | - Akhtar Hussain
- Faculty of Health Sciences, Nord University, Bodø, Norway; Faculty of Medicine, Federal University of Ceará (FAMED-UFC), Brazil; International Diabetes Federation (IDF), Brussels, Belgium; Diabetes in Asia Study Group, Post Box: 752, Doha-Qatar; Centre for Global Health Research, Diabetic Association of Bangladesh, Dhaka, Bangladesh
| | | | - Jaakko Tuomilehto
- Department of International Health, National School of Public Health, Instituto de Salud Carlos III, Madrid, Spain; Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland; Department of Public Health, University of Helsinki, Helsinki, Finland; Saudi Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
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Li S, Chen Y, Zhang L, Li R, Kang N, Hou J, Wang J, Bao Y, Jiang F, Zhu R, Wang C, Zhang L. An environment-wide association study for the identification of non-invasive factors for type 2 diabetes mellitus: Analysis based on the Henan Rural Cohort study. Diabetes Res Clin Pract 2023; 204:110917. [PMID: 37748711 DOI: 10.1016/j.diabres.2023.110917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/16/2023] [Accepted: 09/21/2023] [Indexed: 09/27/2023]
Abstract
AIM To explore the influencing factors of Type 2 diabetes mellitus (T2DM) in the rural population of Henan Province and evaluate the predictive ability of non-invasive factors to T2DM. METHODS A total of 30,020 participants from the Henan Rural Cohort Study in China were included in this study. The dataset was randomly divided into a training set and a testing set with a 50:50 split for validation purposes. We used logistic regression analysis to investigate the association between 56 factors and T2DM in the training set (false discovery rate < 5 %) and significant factors were further validated in the testing set (P < 0.05). Gradient Boosting Machine (GBM) model was used to determine the ability of the non-invasive variables to classify T2DM individuals accurately and the importance ranking of these variables. RESULTS The overall population prevalence of T2DM was 9.10 %. After adjusting for age, sex, educational level, marital status, and body measure index (BMI), we identified 13 non-invasive variables and 6 blood biochemical indexes associated with T2DM in the training and testing dataset. The top three factors according to the GBM importance ranking were pulse pressure (PP), urine glucose (UGLU), and waist-to-hip ratio (WHR). The GBM model achieved a receiver operating characteristic (AUC) curve of 0.837 with non-invasive variables and 0.847 for the full model. CONCLUSIONS Our findings demonstrate that non-invasive variables that can be easily measured and quickly obtained may be used to predict T2DM risk in rural populations in Henan Province.
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Affiliation(s)
- Shuoyi Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China
| | - Ying Chen
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China
| | - Liying Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China
| | - Ruiying Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China
| | - Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China
| | - Jing Wang
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, PR China
| | - Yining Bao
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, PR China
| | - Feng Jiang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China
| | - Ruifang Zhu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, PR China.
| | - Lei Zhang
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, PR China; Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia; Central Clinical School, Faculty of Medicine, Monash University, Melbourne, Australia.
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Liu Q, Hu F, Zeng J, Ma L, Yan S, Li C, Tian H, Gong Y. Islet function changes of post-glucose-challenge relate closely to 15 years mortality of elderly men with a history of hyperglycemia. Heliyon 2023; 9:e14100. [PMID: 36950643 PMCID: PMC10025887 DOI: 10.1016/j.heliyon.2023.e14100] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 02/07/2023] [Accepted: 02/21/2023] [Indexed: 03/08/2023] Open
Abstract
Aims We aimed to investigate the relationship between islet function changes during a glucose challenge and 15-year mortality in elderly men. Methods Elderly men who did the oral glucose tolerance test in 2005 owing to an abnormal glucose history without diabetes were included. Changes in insulin resistance and secretion were evaluated using the homeostasis model assessment (HOMA) of fast, post-load, and ratios. Comparisons between the dead and the survival groups were analyzed using the Student's t-test (continuous variables) or χ2 test (Categorical variables). Single-factor logistic regression was used to identify the possible affecting factors. Multifactorial logistic regression was used to identify the independent risk factors in total population and in the subgroups. ROC curve was used to assess the predictive ability of risk factor and to determine the cut-off value. Results Of the 220 elderly men, 67 died according to 15-year retrospection. Age (OR = 1.243, P = 0.000), diastolic pressure (OR = 0.958, P = 0.027), and HOMA-IR (2 h/0 h) (OR = 1.040, P = 0.010) were independent risk factors for 15-year mortality. Subgroup analysis showed that HOMA-IR (2 h/0 h) was an obvious risk factor, especially for normal glucose tolerance (OR = 1.060, P = 0.030), age 60-70 years (OR = 1.068, P = 0.005), and hypertension (OR = 1.048, P = 0.013); HOMA-β (2 h/0 h) showed some protective effects in the impaired glucose regulation subgroup (OR = 0.779, P = 0.057). HOMA-IR (2 h/0 h) cut-off value was 15. Conclusions HOMA-IR (2 h/0 h) higher than 15 was an independent risk factor for 15-year mortality in elderly men with hyperglycemia history.
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Affiliation(s)
- Qianqian Liu
- Department of Endocrinology, The Second Medical Center, The People's Liberation Army General Hospital, National Clinical Research Center of Geriatric Disease, Beijing 100853, China
- Chinese People's Liberation Army Medical School, Beijing 100853, China
| | - Fan Hu
- Department of Endocrinology, The Second Medical Center, The People's Liberation Army General Hospital, National Clinical Research Center of Geriatric Disease, Beijing 100853, China
| | - Jing Zeng
- Department of Endocrinology, The Second Medical Center, The People's Liberation Army General Hospital, National Clinical Research Center of Geriatric Disease, Beijing 100853, China
- Chinese People's Liberation Army Medical School, Beijing 100853, China
| | - Lichao Ma
- Department of Endocrinology, The Second Medical Center, The People's Liberation Army General Hospital, National Clinical Research Center of Geriatric Disease, Beijing 100853, China
| | - Shuangtong Yan
- Department of Endocrinology, The Second Medical Center, The People's Liberation Army General Hospital, National Clinical Research Center of Geriatric Disease, Beijing 100853, China
| | - Chunlin Li
- Department of Endocrinology, The Second Medical Center, The People's Liberation Army General Hospital, National Clinical Research Center of Geriatric Disease, Beijing 100853, China
| | - Hui Tian
- Department of Endocrinology, The Second Medical Center, The People's Liberation Army General Hospital, National Clinical Research Center of Geriatric Disease, Beijing 100853, China
| | - Yanping Gong
- Department of Endocrinology, The Second Medical Center, The People's Liberation Army General Hospital, National Clinical Research Center of Geriatric Disease, Beijing 100853, China
- Corresponding author. Fuxing Road 28, Beijing, 100853, China.
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Rong L, Cheng X, Yang Z, Gong Y, Li C, Yan S, Sun B. One-hour plasma glucose as a long-term predictor of cardiovascular events and all-cause mortality in a Chinese older male population without diabetes: A 20-year retrospective and prospective study. Front Cardiovasc Med 2022; 9:947292. [PMID: 36072872 PMCID: PMC9441686 DOI: 10.3389/fcvm.2022.947292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 08/02/2022] [Indexed: 11/29/2022] Open
Abstract
Introduction Elevated one-hour plasma glucose (1 h-PG) during oral glucose tolerance test predicts the development of type 2 diabetes mellitus and its complications. However, to date, there have been no studies investigating the predictive values of 1 h-PG for the risk of cardiovascular diseases (CVDs) and all-cause mortality in the elderly population in China. This study aimed to evaluate and compare the effectiveness of 1 h-PG and two-hour plasma glucose (2 h-PG) to predict the risk of CVD and all-cause mortality in the Chinese elderly population. Materials and methods This retrospective and prospective cohort study was conducted using data obtained from the Chinese People’s Liberation Army General Hospital. All the non-diabetic elderly participants, who had plasma glucose measured at 0, 1, and 2 h during an OGTT (75 g glucose), were followed for 20 years. The primary outcomes were all-cause mortality, myocardial infarction, unstable angina, and stroke. Multivariate-adjusted Cox proportional hazard regression models were performed to examine the association between risk factors and outcomes and to estimate the risk of CVD and all-cause mortality based on 1 h-PG levels. Results A total of 862 non-diabetic male individuals were included. The median age was 74.0 (25th–75th percentile: 68.0–79.0) years. There were 480 CVD events and 191 deaths during 15,527 person-years of follow-up. The adjusted hazard ratio (HR) of 1 h-PG as a continuous variable was 1.097 (95% CI 1.027–1.172; P = 0.006) for CVD events and 1.196 (95% CI 1.115–1.281; P < 0.001) for higher risk of mortality. When compared with the lowest 1 h-PG tertile, the other tertiles were associated with CVD events (HR 1.464, 95% CI 1.031–2.080; P = 0.033 and HR 1.538, 95% CI 1.092–2.166; P = 0.014, for tertile 2 and tertile 3 compared with tertile 1, respectively), and the highest 1 h-PG tertile had a significantly higher risk of mortality (HR 2.384, 95% CI 1.631–3.485; P < 0.001) after full adjustment. Compared with 1 h-PG, 2 h-PG had similar abilities to predict all-cause mortality. However, 2 h-PG was less closely associated with CVD when examined in the fully adjusted model, neither as a continuous variable nor as a categorical variable. Conversely, 1 h-PG remained an independent predictor of CVD and all-cause mortality after adjusting for various traditional risk factors. Conclusion Patients with higher 1 h-PG had a significantly increased risk of CVD and all-cause mortality regardless of prediabetes status or development of diabetes at follow-up. The 1 h-PG level might be a better predictor of cardiovascular risk than the 2 h-PG level for the Chinese elderly population.
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Affiliation(s)
- Lingjun Rong
- Department of Endocrinology, Second Medical Center, Chinese People’s Liberation Army General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
- Department of Geriatric Endocrinology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoling Cheng
- Department of Endocrinology, Second Medical Center, Chinese People’s Liberation Army General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Zaigang Yang
- Department of Geriatric Endocrinology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yanping Gong
- Department of Endocrinology, Second Medical Center, Chinese People’s Liberation Army General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Chunlin Li
- Department of Endocrinology, Second Medical Center, Chinese People’s Liberation Army General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Shuangtong Yan
- Department of Endocrinology, Second Medical Center, Chinese People’s Liberation Army General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
- *Correspondence: Shuangtong Yan,
| | - Banruo Sun
- Department of Endocrinology, Second Medical Center, Chinese People’s Liberation Army General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
- Banruo Sun,
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