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Shi L, Xue Y, Yu X, Wang Y, Hong T, Li X, Ma J, Zhu D, Mu Y. Prevalence and Risk Factors of Chronic Kidney Disease in Patients With Type 2 Diabetes in China: Cross-Sectional Study. JMIR Public Health Surveill 2024; 10:e54429. [PMID: 39213031 DOI: 10.2196/54429] [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: 11/09/2023] [Revised: 12/30/2023] [Accepted: 05/16/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is a significant long-term complication of diabetes and is a primary contributor to end-stage kidney disease. OBJECTIVE This study aimed to report comprehensive nationwide data on the prevalence, screening, and awareness rates of CKD in Chinese patients with type 2 diabetes, along with associated risk factors. METHODS Baseline data analysis of the ongoing prospective, observational IMPROVE study was conducted. The study cohort comprised patients who had been diagnosed with type 2 diabetes more than 12 months prior, received at least 1 hypoglycemic medication, and were aged ≥18 years. The participants completed questionnaires and underwent laboratory assessments, including blood and urine samples. The data encompassed patient demographics, medical history, concurrent medications, and comorbidities. Comprehensive evaluations involved physical examinations, urinary albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), glycated hemoglobin (HbA1c), fasting blood glucose, 2-hour postprandial blood glucose, fasting blood lipid profile, and urinalysis. Descriptive statistics were applied for data interpretation, and logistic regression analyses were used to identify the CKD-associated risk factors in patients with type 2 diabetes. RESULTS A national study from December 2021 to September 2022 enlisted 9672 participants with type 2 diabetes from 45 hospitals that had endocrinology departments. The enrollees were from diverse regions in China, as follows: central (n=1221), east (n=3269), south (n=1474), north (n=2219), and west (n=1489). The prevalence, screening, and awareness rates of CKD among patients with type 2 diabetes were 31% (2997/9672), 27% (810/2997), and 54.8% (5295/9672), respectively. Multivariate binary regression analysis revealed that the CKD risk factors were screening, awareness, smoking, age, diabetes duration, concurrent antihypertensive and microcirculation medications, diabetic complications (foot, retinopathy, and neuropathy), hypertension, elevated low-density lipoprotein (LDL) cholesterol, and suboptimal glycemic control. Subgroup analysis highlighted an increased CKD prevalence among older individuals, those with prolonged diabetes durations, and residents of fourth-tier cities. Residents of urban areas that had robust educational and economic development exhibited relatively high awareness and screening rates. Notably, 24.2% (1717/7107) of patients with an eGFR ≥90 mL/min/1.73 m2 had proteinuria, whereas 3.4% (234/6909) who had a UACR <30 mg/g presented with an eGFR <60 mL/min/1.73 m2. Compared with patients who were cognizant of CKD, those who were unaware of CKD had increased rates of HbA1c ≥7%, total cholesterol >5.18 μmol/L, LDL cholesterol >3.37 μmol/L, BMI ≥30 kg/m2, and hypertension. CONCLUSIONS In a Chinese population of adults with type 2 diabetes, the CKD prevalence was notable, at 31%, coupled with low screening and awareness rates. Multiple risk factors for CKD have been identified. TRIAL REGISTRATION ClinicalTrials.gov NCT05047471; https://clinicaltrials.gov/study/NCT05047471.
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Affiliation(s)
- Lixin Shi
- Department of Endocrinology and Metabolism, Guiqian International General Hospital, Guiyang, China
| | - Yaoming Xue
- Department of Endocrinology and Metabolism, Southern Medical University Nanfang Hospital, Guangzhou, China
| | - Xuefeng Yu
- Division of Endocrinology, Department of Internal Medcine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yangang Wang
- Department of Endocrinology and Metabolism, The Affiliated Hospital of Medical College Qingdao University, Qingdao, China
| | - Tianpei Hong
- Department of Endocrinology and Metabolism, Peking University Third Hospital, Beijing, China
| | - Xiaoying Li
- Department of Endocrinology and Metabolism, Zhongshan Hospital Affiliated to Fudan University, Shanghai, China
| | - Jianhua Ma
- Department of Endocrinology and Metabolism, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Dalong Zhu
- Department of Endocrinology, Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, China
| | - Yiming Mu
- Department of Endocrinology, The First Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
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O CK, Fan YN, Fan B, Lim C, Lau ESH, Tsoi STF, Wan R, Lai WY, Poon EW, Ho J, Ho CCY, Fung C, Lee EK, Wong SY, Wang M, Ozaki R, Cheung E, Ma RCW, Chow E, Kong APS, Luk A, Chan JCN. Precision Medicine to Redefine Insulin Secretion and Monogenic Diabetes-Randomized Controlled Trial (PRISM-RCT) in Chinese patients with young-onset diabetes: design, methods and baseline characteristics. BMJ Open Diabetes Res Care 2024; 12:e004120. [PMID: 38901858 PMCID: PMC11212116 DOI: 10.1136/bmjdrc-2024-004120] [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: 02/12/2024] [Accepted: 05/29/2024] [Indexed: 06/22/2024] Open
Abstract
INTRODUCTION We designed and implemented a patient-centered, data-driven, holistic care model with evaluation of its impacts on clinical outcomes in patients with young-onset type 2 diabetes (T2D) for which there is a lack of evidence-based practice guidelines. RESEARCH DESIGN AND METHODS In this 3-year Precision Medicine to Redefine Insulin Secretion and Monogenic Diabetes-Randomized Controlled Trial, we evaluate the effects of a multicomponent care model integrating use of information and communication technology (Joint Asia Diabetes Evaluation (JADE) platform), biogenetic markers and patient-reported outcome measures in patients with T2D diagnosed at ≤40 years of age and aged ≤50 years. The JADE-PRISM group received 1 year of specialist-led team-based management using treatment algorithms guided by biogenetic markers (genome-wide single-nucleotide polymorphism arrays, exome-sequencing of 34 monogenic diabetes genes, C-peptide, autoantibodies) to achieve multiple treatment goals (glycated hemoglobin (HbA1c) <6.2%, blood pressure <120/75 mm Hg, low-density lipoprotein-cholesterol <1.2 mmol/L, waist circumference <80 cm (women) or <85 cm (men)) in a diabetes center setting versus usual care (JADE-only). The primary outcome is incidence of all diabetes-related complications. RESULTS In 2020-2021, 884 patients (56.6% men, median (IQR) diabetes duration: 7 (3-12) years, current/ex-smokers: 32.5%, body mass index: 28.40±5.77 kg/m2, HbA1c: 7.52%±1.66%, insulin-treated: 27.7%) were assigned to JADE-only (n=443) or JADE-PRISM group (n=441). The profiles of the whole group included positive family history (74.7%), general obesity (51.4%), central obesity (79.2%), hypertension (66.7%), dyslipidemia (76.4%), albuminuria (35.4%), estimated glomerular filtration rate <60 mL/min/1.73 m2 (4.0%), retinopathy (13.8%), atherosclerotic cardiovascular disease (5.2%), cancer (3.1%), emotional distress (26%-38%) and suboptimal adherence (54%) with 5-item EuroQol for Quality of Life index of 0.88 (0.87-0.96). Overall, 13.7% attained ≥3 metabolic targets defined in secondary outcomes. In the JADE-PRISM group, 4.5% had pathogenic/likely pathogenic variants of monogenic diabetes genes; 5% had autoantibodies and 8.4% had fasting C-peptide <0.2 nmol/L. Other significant events included low/large birth weight (33.4%), childhood obesity (50.7%), mental illness (10.3%) and previous suicide attempts (3.6%). Among the women, 17.3% had polycystic ovary syndrome, 44.8% required insulin treatment during pregnancy and 17.3% experienced adverse pregnancy outcomes. CONCLUSIONS Young-onset diabetes is characterized by complex etiologies with comorbidities including mental illness and lifecourse events. TRIAL REGISTRATION NUMBER NCT04049149.
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Affiliation(s)
- Chun Kwan O
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Ying Nan Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Cadmon Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Sandra T F Tsoi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Raymond Wan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Wai Yin Lai
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Emily Wm Poon
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Jane Ho
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Cherry Cheuk Yee Ho
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Chloe Fung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Eric Kp Lee
- JC School of Public Health & Primary Care, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, People's Republic of China
| | - Samuel Ys Wong
- JC School of Public Health & Primary Care, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, People's Republic of China
| | - Maggie Wang
- JC School of Public Health & Primary Care, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, People's Republic of China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Elaine Cheung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Alice Pik Shan Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Andrea Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
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Chan JC, O CK, Luk AO. Young-Onset Diabetes in East Asians: From Epidemiology to Precision Medicine. Endocrinol Metab (Seoul) 2024; 39:239-254. [PMID: 38626908 PMCID: PMC11066447 DOI: 10.3803/enm.2024.1968] [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: 02/24/2024] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 05/03/2024] Open
Abstract
Precision diagnosis is the keystone of clinical medicine. In East Asians, classical type 1 diabetes is uncommon in patients with youngonset diabetes diagnosed before age of 40, in whom a family history, obesity, and beta-cell and kidney dysfunction are key features. Young-onset diabetes affects one in five Asian adults with diabetes in clinic settings; however, it is often misclassified, resulting in delayed or non-targeted treatment. Complex aetiologies, long disease duration, aggressive clinical course, and a lack of evidence-based guidelines have contributed to variable care standards and premature death in these young patients. The high burden of comorbidities, notably mental illness, highlights the numerous knowledge gaps related to this silent killer. The majority of adult patients with youngonset diabetes are managed as part of a heterogeneous population of patients with various ages of diagnosis. A multidisciplinary care team led by physicians with special interest in young-onset diabetes will help improve the precision of diagnosis and address their physical, mental, and behavioral health. To this end, payors, planners, and providers need to align and re-design the practice environment to gather data systematically during routine practice to elucidate the multicausality of young-onset diabetes, treat to multiple targets, and improve outcomes in these vulnerable individuals.
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Affiliation(s)
- Juliana C.N. Chan
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - Chun-Kwan O
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - Andrea O.Y. Luk
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
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Yu G, Tam HCH, Huang C, Shi M, Lim CKP, Chan JCN, Ma RCW. Lessons and Applications of Omics Research in Diabetes Epidemiology. Curr Diab Rep 2024; 24:27-44. [PMID: 38294727 PMCID: PMC10874344 DOI: 10.1007/s11892-024-01533-7] [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] [Accepted: 01/04/2024] [Indexed: 02/01/2024]
Abstract
PURPOSE OF REVIEW Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies. RECENT FINDINGS We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.
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Affiliation(s)
- Gechang Yu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Henry C H Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Chuiguo Huang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Mai Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
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Fan Y, Fan B, Lau ESH, Lim CKP, Wu H, Ma RCW, Ozaki R, Kong APS, Chow E, Luk AOY, Chan JCN. Comparison of beta-cell function between Hong Kong Chinese with young-onset type 2 diabetes and late-onset type 2 diabetes. Diabetes Res Clin Pract 2023; 205:110954. [PMID: 37839755 DOI: 10.1016/j.diabres.2023.110954] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/09/2023] [Accepted: 10/13/2023] [Indexed: 10/17/2023]
Abstract
AIMS We compared beta-cell function in Chinese with type 2 diabetes diagnosed at age < 40 years (young-onset diabetes, YOD) and ≥ 40 years (late-onset diabetes, LOD). METHODS In this cross-sectional study, we selected participants from two cohorts of people with type 2 diabetes recruited in 1996-2012 (n = 4,376) and 2020-2021 (n = 794). Multivariable linear regression models were applied to compare homeostasis model assessment of beta-cell function (HOMA2-%B) and fasting plasma C-peptide across diabetes duration at enrolment between YOD and LOD. RESULTS The YOD group (n = 1,876, mean [SD] age: 39.9 [7.5] years, median [IQR] diabetes duration: 6 [2-12] years) was more likely to have family history of diabetes (61.6 % vs 43.6 %), obesity (41.9 % vs 26.8 %), dyslipidaemia (61.7 % vs 54.4 %), and worse glycaemic control (mean HbA1c 7.7 % vs 7.4 %) than those with LOD (n = 3,294, age: 60.8 [10.6] years, diabetes duration: 5 [1-10] years). When compared to people with LOD, HOMA2-%B and fasting plasma C-peptide were lower in the YOD group, consistently among those with BMI < 27.5 kg/m2 and HOMA2-IR ≤ 1.6 (median value), adjusted for year at enrolment, sex, diabetes duration, family history of diabetes, HbA1c, weight and lipid indices (p < 0.01). Cross-sectionally, the slopes of decline in HOMA2-%B by diabetes duration were greater in YOD than LOD among individuals with BMI < 27.5 kg/m2 (p-interaction = 0.015). CONCLUSIONS Chinese with YOD had accelerated loss of beta-cell function than those with LOD especially in non-obese individuals.
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Affiliation(s)
- Yingnan Fan
- 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; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Cadmon K P Lim
- 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
| | - Hongjiang Wu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, 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; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Risa Ozaki
- Department of Medicine and Therapeutics, 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
| | - Alice P S Kong
- Department of Medicine and Therapeutics, 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; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Elaine Chow
- Department of Medicine and Therapeutics, 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 O Y Luk
- Department of Medicine and Therapeutics, 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; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region.
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, 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; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
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Baek HS, Park JY, Yu J, Lee J, Yang Y, Ha J, Lee SH, Cho JH, Lim DJ, Kim HS. Characteristics of Glycemic Control and Long-Term Complications in Patients with Young-Onset Type 2 Diabetes. Endocrinol Metab (Seoul) 2022; 37:641-651. [PMID: 36065646 PMCID: PMC9449113 DOI: 10.3803/enm.2022.1501] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 08/03/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGRUOUND The prevalence of young-onset diabetes (YOD) has been increasing worldwide. As the incidence of YOD increases, it is necessary to determine the characteristics of YOD and the factors that influence its development and associated complications. METHODS In this retrospective study, we recruited patients who were diagnosed with type 2 diabetes mellitus between June 2001 and December 2021 at a tertiary hospital. The study population was categorized according to age: YOD (age <40 years), middle-age-onset diabetes (MOD, 40≤ age <65 years), and late-onset diabetes (LOD, age ≥65 years). We examined trends in glycemic control by analyzing fasting glucose levels during the first year in each age group. A Cox proportional-hazards model was used to determine the relative risk of developing complications according to glycemic control trends. RESULTS The fasting glucose level at the time of diagnosis was highest in the YOD group (YOD 149±65 mg/dL; MOD 143±54 mg/dL; and LOD 140±55 mg/dL; p=0.009). In the YOD group, glucose levels decreased at 3 months, but increased by 12 months. YOD patients and those with poor glycemic control in the first year were at a higher risk of developing complications, whereas the risk in patients with LOD was not statistically significant. CONCLUSION YOD patients had higher glucose levels at diagnosis, and their glycemic control was poorly maintained. As poor glycemic control can influence the development of complications, especially in young patients, intensive treatment is necessary for patients with YOD.
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Affiliation(s)
- Han-sang Baek
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Ji-Yeon Park
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jin Yu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Joonyub Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Yeoree Yang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jeonghoon Ha
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Seung Hwan Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jae Hyoung Cho
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Dong-Jun Lim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Hun-Sung Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Corresponding author: Hun-Sung Kim. Department of Medical Informatics, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Korea Tel: +82-2-2258-8262, Fax: +82-2-2258-8297, E-mail:
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Jiang G, Luk AO, Tam CH, Ozaki R, Lim CK, Chow EY, Lau ES, Kong AP, Fan B, Lee KF, Siu SC, Hui G, Tsang CC, Lau KP, Leung JY, Tsang MW, Kam G, Lau IT, Li JK, Yeung VT, Lau E, Lo S, Fung S, Cheng YL, Chow CC, Tang NL, Huang Y, Lan HY, Oram RA, Szeto CC, So WY, Chan JC, Ma RC. Clinical Predictors and Long-term Impact of Acute Kidney Injury on Progression of Diabetic Kidney Disease in Chinese Patients With Type 2 Diabetes. Diabetes 2022; 71:520-529. [PMID: 35043149 PMCID: PMC8893937 DOI: 10.2337/db21-0694] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 12/14/2021] [Indexed: 11/13/2022]
Abstract
We aim to assess the long-term impact of acute kidney injury (AKI) on progression of diabetic kidney disease (DKD) and all-cause mortality and investigate determinants of AKI in Chinese patients with type 2 diabetes (T2D). A consecutive cohort of 9,096 Chinese patients with T2D from the Hong Kong Diabetes Register was followed for 12 years (mean ± SD age 57 ± 13.2 years; 46.9% men; median duration of diabetes 5 years). AKI was defined based on the Kidney Disease: Improving Global Outcomes (KDIGO) criteria using serum creatinine. Estimated glomerular filtration rate measurements were used to identify the first episode with chronic kidney disease (CKD) and end-stage renal disease (ESRD). Polygenic risk score (PRS) composed of 27 single nucleotide polymorphisms (SNPs) known to be associated with serum uric acid (SUA) in European populations was used to examine the role of SUA in pathogenesis of AKI, CKD, and ESRD. Validation was sought in an independent cohort including 6,007 patients (age 61.2 ± 10.9 years; 59.5% men; median duration of diabetes 10 years). Patients with AKI had a higher risk for developing incident CKD (hazard ratio 14.3 [95% CI 12.69-16.11]), for developing ESRD (12.1 [10.74-13.62]), and for all-cause death (7.99 [7.31-8.74]) compared with those without AKI. Incidence rate for ESRD among patients with no episodes of AKI and one, two, and three or more episodes of AKI was 7.1, 24.4, 32.4, and 37.3 per 1,000 person-years, respectively. Baseline SUA was a strong independent predictor for AKI. A PRS composed of 27 SUA-related SNPs was associated with AKI and CKD in both discovery and replication cohorts but not ESRD. Elevated SUA may increase the risk of DKD through increasing AKI. The identification of SUA as a modifiable risk factor and PRS as a nonmodifiable risk factor may facilitate the identification of individuals at high risk to prevent AKI and its long-term impact in T2D.
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Affiliation(s)
- Guozhi Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
| | - Andrea O. Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Claudia H.T. Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
| | - Cadmon K.P. Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong
| | - Elaine Y.K. Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
| | - Eric S. Lau
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong
| | - Alice P.S. Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong
| | | | - Ka Fai Lee
- Department of Medicine and Geriatrics, Kwong Wah Hospital, Hong Kong
| | | | - Grace Hui
- Diabetes Centre, Tung Wah Eastern Hospital, Hong Kong
| | - Chiu Chi Tsang
- Diabetes and Education Centre, Alice Ho Miu Ling Nethersole Hospital, Hong Kong
| | | | - Jenny Y. Leung
- Department of Medicine and Geriatrics, Ruttonjee Hospital, Hong Kong
| | - Man-wo Tsang
- Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong
| | - Grace Kam
- Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong
| | | | - June K. Li
- Department of Medicine, Yan Chai Hospital, Hong Kong
| | - Vincent T. Yeung
- Centre for Diabetes Education and Management, Our Lady of Maryknoll Hospital, Hong Kong
| | - Emmy Lau
- Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Hong Kong
| | - Stanley Lo
- Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Hong Kong
| | - Samuel Fung
- Department of Medicine and Geriatrics, Princess Margaret Hospital, Hong Kong
| | - Yuk Lun Cheng
- Department of Medicine, Alice Ho Miu Ling Nethersole Hospital, Hong Kong
| | - Chun Chung Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | | | - Nelson L.S. Tang
- Department of Chemical Pathology, The Chinese University of Hong Kong, Hong Kong
| | - Yu Huang
- School of Biomedical Sciences, The Chinese University of Hong Kong
| | - Hui-yao Lan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Richard A. Oram
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K
| | - Cheuk Chun Szeto
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
| | - Juliana C.N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong
| | - Ronald C.W. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong
- Corresponding author: Ronald C.W. Ma,
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8
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Cheng F, Luk AO, Wu H, Tam CHT, Lim CKP, Fan B, Jiang G, Carroll L, Yang A, Lau ESH, Ng ACW, Lee HM, Chow E, Kong APS, Keech AC, Joglekar MV, So WY, Hardikar AA, Chan JCN, Jenkins AJ, Ma RCW. Relative leucocyte telomere length is associated with incident end-stage kidney disease and rapid decline of kidney function in type 2 diabetes: analysis from the Hong Kong Diabetes Register. Diabetologia 2022; 65:375-386. [PMID: 34807303 PMCID: PMC8741666 DOI: 10.1007/s00125-021-05613-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 09/07/2021] [Indexed: 11/09/2022]
Abstract
AIMS/HYPOTHESIS Few large-scale prospective studies have investigated associations between relative leucocyte telomere length (rLTL) and kidney dysfunction in individuals with type 2 diabetes. We examined relationships between rLTL and incident end-stage kidney disease (ESKD) and the slope of eGFR decline in Chinese individuals with type 2 diabetes. METHODS We studied 4085 Chinese individuals with type 2 diabetes observed between 1995 and 2007 in the Hong Kong Diabetes Register with stored baseline DNA and available follow-up data. rLTL was measured using quantitative PCR. ESKD was diagnosed based on the ICD-9 code and eGFR. RESULTS In this cohort (mean ± SD age 54.3 ± 12.6 years) followed up for 14.1 ± 5.3 years, 564 individuals developed incident ESKD and had shorter rLTL at baseline (4.2 ± 1.2 vs 4.7 ± 1.2, p < 0.001) than the non-progressors (n = 3521). On Cox regression analysis, each ∆∆Ct decrease in rLTL was associated with an increased risk of incident ESKD (HR 1.21 [95% CI 1.13, 1.30], p < 0.001); the association remained significant after adjusting for baseline age, sex, HbA1c, lipids, renal function and other risk factors (HR 1.11 [95% CI 1.03, 1.19], p = 0.007). Shorter rLTL at baseline was associated with rapid decline in eGFR (>4% per year) during follow-up (unadjusted OR 1.22 [95% CI 1.15, 1.30], p < 0.001; adjusted OR 1.09 [95% CI 1.01, 1.17], p = 0.024). CONCLUSIONS/INTERPRETATION rLTL is independently associated with incident ESKD and rapid eGFR loss in individuals with type 2 diabetes. Telomere length may be a useful biomarker for the progression of kidney function and ESKD in type 2 diabetes.
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Affiliation(s)
- Feifei Cheng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Andrea O Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Hongjiang Wu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Guozhi Jiang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Luke Carroll
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Aimin Yang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Alex C W Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Heung Man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Anthony C Keech
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Mugdha V Joglekar
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
- Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Sydney, NSW, Australia
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Anandwardhan A Hardikar
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
- Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Sydney, NSW, Australia
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- The Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Prince of Wales Hospital, Hong Kong, SAR, China
| | - Alicia J Jenkins
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China.
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, SAR, China.
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
- The Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Prince of Wales Hospital, Hong Kong, SAR, China.
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9
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Hung HHY, Chan EYY, Chow EYK, Chung GKK, Lai FTT, Yeoh E. Non-skilled occupation as a risk factor of diabetes among working population: A population-based study of community-dwelling adults in Hong Kong. HEALTH & SOCIAL CARE IN THE COMMUNITY 2022; 30:e86-e94. [PMID: 34169598 PMCID: PMC9291875 DOI: 10.1111/hsc.13415] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 03/05/2021] [Accepted: 04/04/2021] [Indexed: 06/13/2023]
Abstract
Diabetes among working population brings to society concerns on productivity and social welfare cost, in addition to healthcare burden. While lower socio-economic status has been recognised as a risk factor of diabetes; occupation, compared with other socio-economic status indicators (e.g., education and income), has received less attention. There is some evidence from studies conducted in Europe that occupation is associated with diabetes risk, but less is known in Asia, which has different organisational cultures and management styles from the West. This study examines the association between occupation and diabetes risk in a developed Asian setting, which is experiencing an increasing number of young onset of diabetes and aging working population at the same time. This is a cross-sectional study of working population aged up to 65 with data from a population-based survey collecting demographic, socio-economic, behavioural and metabolic data from Hong Kong residents, through both self-administered questionnaires and clinical health examinations (1,429 participants). Non-skilled occupation was found to be an independent risk factor for diabetes, with an odds ratio (OR) of 3.38 (p < 0.001) and adjusted OR of 2.59 (p = 0.022) after adjusting for demographic, behavioural and metabolic risk factors. Older age (adjusted OR = 1.08, p < 0.001), higher body mass index (adjusted OR = 1.23, p < 0.001) and having hypertriglyceridemia (adjusted OR = 1.93, p = 0.033) were also independently associated with diabetes. Non-skilled workers were disproportionately affected by diabetes with the highest age-standardized prevalence (6.3%) among all occupation groups (4.9%-5.0%). This study provides evidence that non-skilled occupation is an independent diabetes risk factor in a developed Asian setting. Health education on improving lifestyle practices and diabetes screening should prioritise non-skilled workers, in particular through company-based and sector-based diabetes screening programmes. Diabetes health service should respond to the special needs of non-skilled workers, including service at non-office hour and practical health advice in light of their work setting.
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Affiliation(s)
- Heidi H. Y. Hung
- The Jockey Club School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
| | - Emily Y. Y. Chan
- The Jockey Club School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
- Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response (CCOUC), The Jockey Club School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
- Nuffield Department of MedicineUniversity of OxfordOxfordUK
- François‐Xavier Bagnoud Center for Health & Human RightsHarvard UniversityBostonMAUSA
| | - Elaine Y. K. Chow
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongHong KongChina
| | - Gary K. K. Chung
- The Jockey Club School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
- CUHK Institute of Health EquityThe Chinese University of Hong KongHong KongChina
| | - Francisco T. T. Lai
- The Jockey Club School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
- Department of Pharmacology and PharmacyThe University of Hong KongHong KongChina
- Laboratory of Data Discovery for Health (D24H)Hong Kong Science and Technology ParkHong KongChina
| | - Eng‐Kiong Yeoh
- Centre for Health Systems and Policy ResearchThe Jockey Club School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
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10
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Chan JCN, Lim LL, Wareham NJ, Shaw JE, Orchard TJ, Zhang P, Lau ESH, Eliasson B, Kong APS, Ezzati M, Aguilar-Salinas CA, McGill M, Levitt NS, Ning G, So WY, Adams J, Bracco P, Forouhi NG, Gregory GA, Guo J, Hua X, Klatman EL, Magliano DJ, Ng BP, Ogilvie D, Panter J, Pavkov M, Shao H, Unwin N, White M, Wou C, Ma RCW, Schmidt MI, Ramachandran A, Seino Y, Bennett PH, Oldenburg B, Gagliardino JJ, Luk AOY, Clarke PM, Ogle GD, Davies MJ, Holman RR, Gregg EW. The Lancet Commission on diabetes: using data to transform diabetes care and patient lives. Lancet 2021; 396:2019-2082. [PMID: 33189186 DOI: 10.1016/s0140-6736(20)32374-6] [Citation(s) in RCA: 303] [Impact Index Per Article: 101.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 07/06/2020] [Accepted: 11/05/2020] [Indexed: 01/19/2023]
Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China.
| | - Lee-Ling Lim
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China; Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Nicholas J Wareham
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jonathan E Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; School of Life Sciences, La Trobe University, Melbourne, VIC, Australia
| | - Trevor J Orchard
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, KS, USA
| | - Ping Zhang
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Eric S H Lau
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China
| | - Björn Eliasson
- Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Endocrinology and Metabolism, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Alice P S Kong
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Majid Ezzati
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Medical Research Council Centre for Environment and Health, Imperial College London, London, UK; WHO Collaborating Centre on NCD Surveillance and Epidemiology, Imperial College London, London, UK
| | - Carlos A Aguilar-Salinas
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Margaret McGill
- Diabetes Centre, Royal Prince Alfred Hospital, University of Sydney, Sydney, NSW, Australia
| | - Naomi S Levitt
- Chronic Disease Initiative for Africa, Department of Medicine, Faculty of Medicine and Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Guang Ning
- Shanghai Clinical Center for Endocrine and Metabolic Disease, Department of Endocrinology, Ruijin Hospital, Shanghai Jiaotong University, School of Medicine, Shanghai, China; Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Jean Adams
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Paula Bracco
- School of Medicine and Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Gabriel A Gregory
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia; Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| | - Jingchuan Guo
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, KS, USA
| | - Xinyang Hua
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Emma L Klatman
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia
| | - Dianna J Magliano
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Boon-Peng Ng
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA; College of Nursing and Disability, Aging and Technology Cluster, University of Central Florida, Orlando, FL, USA
| | - David Ogilvie
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jenna Panter
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Meda Pavkov
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Hui Shao
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Nigel Unwin
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Martin White
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Constance Wou
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Maria I Schmidt
- School of Medicine and Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Ambady Ramachandran
- India Diabetes Research Foundation and Dr A Ramachandran's Diabetes Hospitals, Chennai, India
| | - Yutaka Seino
- Center for Diabetes, Endocrinology and Metabolism, Kansai Electric Power Hospital, Osaka, Japan; Yutaka Seino Distinguished Center for Diabetes Research, Kansai Electric Power Medical Research Institute, Kobe, Japan
| | - Peter H Bennett
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Brian Oldenburg
- Nossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre on Implementation Research for Prevention and Control of NCDs, University of Melbourne, Melbourne, VIC, Australia
| | - Juan José Gagliardino
- Centro de Endocrinología Experimental y Aplicada, UNLP-CONICET-CICPBA, Facultad de Ciencias Médicas, Universidad Nacional de La Plata, La Plata, Argentina
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China
| | - Philip M Clarke
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Graham D Ogle
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia; National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia
| | - Melanie J Davies
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Rury R Holman
- Diabetes Trials Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Edward W Gregg
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
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11
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Narh CT, Der JB, Ofosu A, Blettner M, Wollschlaeger D. Trends in hospitalization of patients with diabetes mellitus in Ghana from 2012 to 2017 with predictions to 2032. Int Health 2021; 14:588-596. [PMID: 34849982 DOI: 10.1093/inthealth/ihab076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 07/13/2021] [Accepted: 11/01/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND This study explores sociodemographic and health factors associated with hospitalizing diabetes mellitus (DM) patients and estimates the number of future hospitalizations for DM in Ghana. METHODS We conducted a secondary analysis using nationally representative patient hospitalization data provided by the Ghana Health Service and projected population counts from the Ghana Statistical Service. Data were stratified by year, age, sex and region. We employed Poisson regression to determine associations between sociodemographic and health factors and hospitalization rates of DM patients. Using projected population counts, the number of DM-related hospitalizations for 2018 through 2032 were predicted. We analysed 39 846 DM records from nearly three million hospitalizations over a 6-y period (2012-2017). RESULTS Most hospitalized DM patients were elderly, female and from the Eastern Region. The hospitalization rate for DM was higher among patients ages 75-79 y (rate ratio [RR] 23.7 [95% confidence interval {CI} 18.6 to 30.3]) compared with those ages 25-29 y, females compared with males (RR 1.9 [95% CI 1.4 to 2.5]) and the Eastern Region compared with the Greater Accra Region (RR 1.9 [95% CI 1.7 to 2.2]). The predicted number of DM hospitalizations in 2022 was 11 202, in 2027 it was 12 414 and in 2032 it was 13 651. CONCLUSIONS Females and older patients are more at risk to be hospitalized, therefore these groups need special surveillance with targeted public health education aimed at behavioural changes.
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Affiliation(s)
- Clement T Narh
- Department of Epidemiology and Biostatistics, School of Public Health, University of Health and Allied Sciences, Hohoe, Ghana.,Institute for Medical Biostatistics, Epidemiology, and Informatics, University Medical Centre of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Joyce B Der
- Department of Epidemiology and Biostatistics, School of Public Health, University of Health and Allied Sciences, Hohoe, Ghana
| | - Anthony Ofosu
- Center for Health Information Management, Ghana Health Service, Accra, Ghana
| | - Maria Blettner
- Institute for Medical Biostatistics, Epidemiology, and Informatics, University Medical Centre of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Daniel Wollschlaeger
- Institute for Medical Biostatistics, Epidemiology, and Informatics, University Medical Centre of the Johannes Gutenberg-University Mainz, Mainz, Germany
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12
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Cheng F, Luk AO, Wu H, Lim CKP, Carroll L, Tam CHT, Fan B, Yang A, Lau ESH, Ng ACW, Lee HM, Chow E, Kong APS, Keech AC, Joglekar MV, So WY, Jenkins AJ, Chan JCN, Hardikar AA, Ma RCW. Shortened relative leukocyte telomere length is associated with all-cause mortality in type 2 diabetes- analysis from the Hong Kong Diabetes Register. Diabetes Res Clin Pract 2021; 173:108649. [PMID: 33422583 DOI: 10.1016/j.diabres.2021.108649] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 12/16/2020] [Accepted: 01/04/2021] [Indexed: 12/23/2022]
Abstract
AIMS Few studies have investigated the relationship between rLTL and mortality in patients with type 2 diabetes in a large prospective study, particularly in the Asian population. This study investigates the relationship between rLTL and the risk of death in Chinese patients with type 2 diabetes. METHODS Consecutive Chinese patients with type 2 diabetes (N = 5349) from the Hong Kong Diabetes Register with stored baseline DNA and available follow-up data were studied. rLTL was measured using a quantitative polymerase chain reaction. Mortality and clinical outcomes were obtained based on ICD-9 codes. RESULTS The mean (SD) age of the subjects was 57.5 (13.3) years and mean (SD) follow-up duration was 13.4 (5.5) years. Baseline rLTL was significantly shorter in the 1925 subjects who subsequently died compared with the remaining subjects (4.3 ± 1.2 vs. 4.7 ± 1.2, P < 0.001). Shorter rLTL was associated with a higher risk of mortality (HR: 1.19 (1.14-1.23), P < 0.001), which remained significant after adjusting for traditional risk factors. CONCLUSIONS Shorter rLTL was significantly associated with an increased risk of all-cause and CVD mortality in patients with type 2 diabetes, independent of established risk factors. Telomere length may be a useful biomarker for mortality risk in patients with type 2 diabetes.
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Affiliation(s)
- Feifei Cheng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Andrea O Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Hongjiang Wu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Luke Carroll
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Australia
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Aimin Yang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Alex C W Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Heung Man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Anthony C Keech
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Australia
| | - Mugdha V Joglekar
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Australia; Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Australia
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Alicia J Jenkins
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Australia
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; The Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Prince of Wales Hospital, Hong Kong Special Administrative Region
| | - Anandwardhan A Hardikar
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Australia; Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Australia
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region; NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Australia; The Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Prince of Wales Hospital, Hong Kong Special Administrative Region.
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13
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Yang A, Wu H, Lau ESH, Ma RCW, Kong APS, So WY, Luk AOY, Chan JCN, Chow E. Trends in Glucose-Lowering Drug Use, Glycemic Control, and Severe Hypoglycemia in Adults With Diabetes in Hong Kong, 2002-2016. Diabetes Care 2020; 43:2967-2974. [PMID: 33046501 DOI: 10.2337/dc20-0260] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 09/14/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE There has been a shift toward new classes of glucose-lowering drugs (GLDs) in the past decade but no improvements in glycemic control or hospitalization rates due to severe hypoglycemia (SH) in previous surveys. We examined trends in GLDs use, glycemic control, and SH rate among patients with diabetes in Hong Kong, which introduced a territory-wide, team-based diabetes care model since 2000. RESEARCH DESIGN AND METHODS Using population-based data from the Hong Kong Diabetes Surveillance Database, we estimated age- and sex-standardized proportion of GLD classes, mean hemoglobin A1c (HbA1c) levels, and SH rates in 763,809 patients with diabetes aged ≥20 years between 2002 and 2016. RESULTS Between 2002 and 2016, use declined for sulfonylureas (62.9% to 35.3%) but increased for metformin (48.4% to 61.4%) and dipeptidyl peptidase 4 inhibitors (DPP-4is) (0.01% in 2007 to 8.3%). The proportion of patients with HbA1c of 6.0-7.0% (42-53 mmol/mol) increased from 28.6% to 43.4%, while the SH rate declined from 4.2/100 person-years to 1.3/100 person-years. The main improvement in HbA1c occurred between 2007 and 2014, decreasing from mean (SD) 7.6% (1.6) (59.5 [19.0] mmol/mol) to 7.2% (1.7) (54.8 [18.9] mmol/mol) (P < 0.001). The 20-44 years age-group had the highest proportion of HbA1c ≥9% (75 mmol/mol) and rising proportions not on GLDs (from 2.0% to 7.7%). CONCLUSIONS In this 15-year survey, the modest but important improvement in HbA1c since 2007 coincided with diabetes service reforms, increase in metformin, decrease in sulfonylureas, and modest rise in DPP-4i use. Persistently poor glycemic control and underuse of GLDs in the youngest group calls for targeted action.
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Affiliation(s)
- Aimin Yang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Hongjiang Wu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Wing Yee So
- Hong Kong Hospital Authority Head Office, Hong Kong Special Administrative Region, China
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China .,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
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14
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Lim LL, Lau ESH, Ozaki R, Chung H, Fu AWC, Chan W, Kong APS, Ma RCW, So WY, Chow E, Cheung KKT, Yau T, Chow CC, Lau V, Yue R, Ng S, Zee B, Goggins W, Oldenburg B, Clarke PM, Lau M, Wong R, Tsang CC, Gregg EW, Wu H, Tong PCY, Ko GTC, Luk AOY, Chan JCN. Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis. PLoS Med 2020; 17:e1003367. [PMID: 33007052 PMCID: PMC7531841 DOI: 10.1371/journal.pmed.1003367] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Accepted: 08/26/2020] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Diabetes outcomes are influenced by host factors, settings, and care processes. We examined the association of data-driven integrated care assisted by information and communications technology (ICT) with clinical outcomes in type 2 diabetes in public and private healthcare settings. METHODS AND FINDINGS The web-based Joint Asia Diabetes Evaluation (JADE) platform provides a protocol to guide data collection for issuing a personalized JADE report including risk categories (1-4, low-high), 5-year probabilities of cardiovascular-renal events, and trends and targets of 4 risk factors with tailored decision support. The JADE program is a prospective cohort study implemented in a naturalistic environment where patients underwent nurse-led structured evaluation (blood/urine/eye/feet) in public and private outpatient clinics and diabetes centers in Hong Kong. We retrospectively analyzed the data of 16,624 Han Chinese patients with type 2 diabetes who were enrolled in 2007-2015. In the public setting, the non-JADE group (n = 3,587) underwent structured evaluation for risk factors and complications only, while the JADE (n = 9,601) group received a JADE report with group empowerment by nurses. In a community-based, nurse-led, university-affiliated diabetes center (UDC), the JADE-Personalized (JADE-P) group (n = 3,436) received a JADE report, personalized empowerment, and annual telephone reminder for reevaluation and engagement. The primary composite outcome was time to the first occurrence of cardiovascular-renal diseases, all-site cancer, and/or death, based on hospitalization data censored on 30 June 2017. During 94,311 person-years of follow-up in 2007-2017, 7,779 primary events occurred. Compared with the JADE group (136.22 cases per 1,000 patient-years [95% CI 132.35-140.18]), the non-JADE group had higher (145.32 [95% CI 138.68-152.20]; P = 0.020) while the JADE-P group had lower event rates (70.94 [95% CI 67.12-74.91]; P < 0.001). The adjusted hazard ratios (aHRs) for the primary composite outcome were 1.22 (95% CI 1.15-1.30) and 0.70 (95% CI 0.66-0.75), respectively, independent of risk profiles, education levels, drug usage, self-care, and comorbidities at baseline. We reported consistent results in propensity-score-matched analyses and after accounting for loss to follow-up. Potential limitations include its nonrandomized design that precludes causal inference, residual confounding, and participation bias. CONCLUSIONS ICT-assisted integrated care was associated with a reduction in clinical events, including death in type 2 diabetes in public and private healthcare settings.
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Affiliation(s)
- Lee-Ling Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Eric S. H. Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Harriet Chung
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Amy W. C. Fu
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Wendy Chan
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Alice P. S. Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Ronald C. W. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Wing-Yee So
- Hospital Authority Head Office, Hong Kong SAR, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Kitty K. T. Cheung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Tiffany Yau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - C. C. Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Vanessa Lau
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Rebecca Yue
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Shek Ng
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Benny Zee
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - William Goggins
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Brian Oldenburg
- Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Philip M. Clarke
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Maggie Lau
- Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong SAR, China
| | - Rebecca Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - C. C. Tsang
- Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong SAR, China
| | - Edward W. Gregg
- School of Public Health, Imperial College London, London, United Kingdom
| | - Hongjiang Wu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Peter C. Y. Tong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Gary T. C. Ko
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Andrea O. Y. Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Juliana C. N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- * E-mail:
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15
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Liu L, Xia R, Song X, Zhang B, He W, Zhou X, Li S, Yuan G. Association between the triglyceride-glucose index and diabetic nephropathy in patients with type 2 diabetes: A cross-sectional study. J Diabetes Investig 2020; 12:557-565. [PMID: 33319507 PMCID: PMC8015837 DOI: 10.1111/jdi.13371] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 06/27/2020] [Accepted: 07/17/2020] [Indexed: 12/12/2022] Open
Abstract
Aims/Introduction The triglyceride–glucose (TyG) index has been proposed as a reliable and simple marker of insulin resistance. We investigated the association between TyG index and diabetic nephropathy (DN) in patients with type 2 diabetes. Materials and Methods A consecutive case series of 682 adult patients with type 2 diabetes hospitalized in the Department of Endocrinology at the Tongji Hospital (Wuhan, Hubei, China) from January 2007 to December 2009 was included in this cross‐sectional analysis. Receiver operating characteristics curve analysis, correlation analysis and multiple logistic regression analysis were carried out. Results A total of 232 (34.0%) participants were identified with DN. Compared with the non‐DN group, the DN group had longer disease duration, and higher bodyweight, systolic blood pressure, diastolic blood pressure, glycated hemoglobin, triglycerides, total cholesterol, serum uric acid, 24 h‐urinary albumin, TyG index and homeostasis model assessment 2 estimates for insulin resistance (HOMA2‐IR; P < 0.05 for each). The TyG index with an optimal cut‐off point >9.66 showed a higher area under the receiver operating characteristic curve of 0.67 (P = 0.002) than HOMA2‐IR (area under the curve 0.61, P = 0.029) on receiver operating characteristic curve analysis for DN identification. Additionally, the TyG index positively correlated with the levels of metabolic indicators (bodyweight, glycated hemoglobin, triglycerides, total cholesterol, serum uric acid, fasting glucose and HOMA2‐IR) and natural logarithmic 24 h‐urinary albumin (P < 0.05 for each), but not natural logarithm of estimated glomerular filtration rate. On multiple regression analysis, an increased TyG index was shown to be an independent risk factor (odds ratio 1.91, P = 0.001) for DN. Conclusions The TyG index was independently associated with DN in patients with type 2 diabetes, and was a better marker than HOMA2‐IR for identification of DN in type 2 diabetes patients.
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Affiliation(s)
- Li Liu
- Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Rui Xia
- Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoqing Song
- Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Benping Zhang
- Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wentao He
- Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xinrong Zhou
- Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shengzhong Li
- Department of Surgery, Wuhan Jinyintan Hospital, Wuhan, Hubei, China
| | - Gang Yuan
- Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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16
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Cheng F, Luk AO, Tam CHT, Fan B, Wu H, Yang A, Lau ESH, Ng ACW, Lim CKP, Lee HM, Chow E, Kong AP, Keech AC, Joglekar MV, So WY, Jenkins AJ, Chan JCN, Hardikar AA, Ma RCW. Shortened Relative Leukocyte Telomere Length Is Associated With Prevalent and Incident Cardiovascular Complications in Type 2 Diabetes: Analysis From the Hong Kong Diabetes Register. Diabetes Care 2020; 43:2257-2265. [PMID: 32661111 DOI: 10.2337/dc20-0028] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 06/12/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Several studies support potential links between relative leukocyte telomere length (rLTL), a biomarker of biological aging, and type 2 diabetes. This study investigates relationships between rLTL and incident cardiovascular disease (CVD) in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS Consecutive Chinese patients with type 2 diabetes (N = 5,349) from the Hong Kong Diabetes Register for whom DNA obtained at baseline was stored and follow-up data were available were studied. rLTL was measured by using quantitative PCR. CVD was diagnosed on the basis of ICD-9 code. RESULTS Mean follow-up was 13.4 years (SD 5.5 years). rLTL was correlated inversely with age, diabetes duration, blood pressure, HbA1c, and urine albumin-to-creatinine ratio (ACR), and positively with estimated glomerular filtration rate (eGFR) (all P < 0.001). Subjects with CVD at baseline had a shorter rLTL (4.3 ± 1.2 ΔΔCt) than did subjects without CVD (4.6 ± 1.2 ΔΔCt) (P < 0.001). Of the 4,541 CVD-free subjects at baseline, the 1,140 who developed CVD during follow-up had a shorter rLTL (4.3 ± 1.2 ΔΔCt) than those who remained CVD-free after adjusting for age, sex, smoking, and albuminuria status (4.7 ± 1.2 ΔΔCt) (P < 0.001). In Cox regression models, shorter rLTL was associated with higher risk of incident CVD (for each unit decrease, hazard ratio 1.252 [95% CI 1.195-1.311], P < 0.001), which remained significant after adjusting for age, sex, BMI, systolic blood pressure, LDL cholesterol, HbA1c, eGFR, and ACR (hazard ratio 1.141 [95% CI 1.084-1.200], P < 0.001). CONCLUSIONS rLTL is significantly shorter in patients with type 2 diabetes and CVD, is associated with cardiometabolic risk factors, and is independently associated with incident CVD. Telomere length may be a useful biomarker for CVD risk in patients with type 2 diabetes.
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Affiliation(s)
- Feifei Cheng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Andrea O Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Hongjiang Wu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Aimin Yang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Alex C W Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Heung Man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Alice P Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Anthony C Keech
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Mugdha V Joglekar
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Alicia J Jenkins
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,The Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Prince of Wales Hospital, Hong Kong SAR, China
| | - Anandwardhan A Hardikar
- NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China .,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,NHMRC Clinical Trial Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,The Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Prince of Wales Hospital, Hong Kong SAR, China
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17
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Ke C, Stukel TA, Shah BR, Lau E, Ma RC, So WY, Kong AP, Chow E, Chan JCN, Luk A. Age at diagnosis, glycemic trajectories, and responses to oral glucose-lowering drugs in type 2 diabetes in Hong Kong: A population-based observational study. PLoS Med 2020; 17:e1003316. [PMID: 32946450 PMCID: PMC7500681 DOI: 10.1371/journal.pmed.1003316] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 08/14/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Lifetime glycemic exposure and its relationship with age at diagnosis in type 2 diabetes (T2D) are unknown. Pharmacologic glycemic management strategies for young-onset T2D (age at diagnosis <40 years) are poorly defined. We studied how age at diagnosis affects glycemic exposure, glycemic deterioration, and responses to oral glucose-lowering drugs (OGLDs). METHODS AND FINDINGS In a population-based cohort (n = 328,199; 47.2% women; mean age 34.6 and 59.3 years, respectively, for young-onset and usual-onset [age at diagnosis ≥40 years] T2D; 2002-2016), we used linear mixed-effects models to estimate the association between age at diagnosis and A1C slope (glycemic deterioration) and tested for an interaction between age at diagnosis and responses to various combinations of OGLDs during the first decade after diagnosis. In a register-based cohort (n = 21,016; 47.1% women; mean age 43.8 and 58.9 years, respectively, for young- and usual-onset T2D; 2000-2015), we estimated the glycemic exposure from diagnosis until age 75 years. People with young-onset T2D had a higher mean A1C (8.0% [standard deviation 0.15%]) versus usual-onset T2D (7.6% [0.03%]) throughout the life span (p < 0.001). The cumulative glycemic exposure was >3 times higher for young-onset versus usual-onset T2D (41.0 [95% confidence interval 39.1-42.8] versus 12.1 [11.8-12.3] A1C-years [1 A1C-year = 1 year with 8% average A1C]). Younger age at diagnosis was associated with faster glycemic deterioration (A1C slope over time +0.08% [0.078-0.084%] per year for age at diagnosis 20 years versus +0.02% [0.016-0.018%] per year for age at diagnosis 50 years; p-value for interaction <0.001). Age at diagnosis ≥60 years was associated with glycemic improvement (-0.004% [-0.005 to -0.004%] and -0.02% [-0.027 to -0.0244%] per year for ages 60 and 70 years at diagnosis, respectively; p-value for interaction <0.001). Responses to OGLDs differed by age at diagnosis (p-value for interaction <0.001). Those with young-onset T2D had smaller A1C decrements for metformin-based combinations versus usual-onset T2D (metformin alone: young-onset -0.15% [-0.105 to -0.080%], usual-onset -0.17% [-0.179 to -0.169%]; metformin, sulfonylurea, and dipeptidyl peptidase-4 inhibitor: young-onset -0.44% [-0.476 to -0.405%], usual-onset -0.48% [-0.498 to -0.459%]; metformin and α-glucosidase inhibitor: young-onset -0.40% [-0.660 to -0.144%], usual-onset -0.25% [-0.420 to -0.077%]) but greater responses to other combinations containing sulfonylureas (sulfonylurea alone: young-onset -0.08% [-0.099 to -0.065%], usual-onset +0.06% [+0.059 to +0.072%]; sulfonylurea and α-glucosidase inhibitor: young-onset -0.10% [-0.266 to 0.064%], usual-onset: 0.25% [+0.196% to +0.312%]). Limitations include possible residual confounding and unknown generalizability outside Hong Kong. CONCLUSIONS In this study, we observed excess glycemic exposure and rapid glycemic deterioration in young-onset T2D, indicating that improved treatment strategies are needed in this setting. The differential responses to OGLDs between young- and usual-onset T2D suggest that better disease classification could guide personalized therapy.
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Affiliation(s)
- Calvin Ke
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Department of Medicine, University of Toronto, Canada
| | - Thérèse A. Stukel
- Institute of Health Policy, Management and Evaluation, University of Toronto, Canada
- ICES, Toronto, Canada
| | - Baiju R. Shah
- Department of Medicine, University of Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Canada
- ICES, Toronto, Canada
- Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Eric Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Metropole Square, Shatin, Hong Kong SAR, China
| | - Ronald C. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Alice P. Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Juliana C. N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Metropole Square, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- * E-mail:
| | - Andrea Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Metropole Square, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
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18
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Dong W, Wan EYF, Bedford LE, Wu T, Wong CKH, Tang EHM, Lam CLK. Prediction models for the risk of cardiovascular diseases in Chinese patients with type 2 diabetes mellitus: a systematic review. Public Health 2020; 186:144-156. [PMID: 32836004 DOI: 10.1016/j.puhe.2020.06.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 05/23/2020] [Accepted: 06/07/2020] [Indexed: 12/27/2022]
Abstract
OBJECTIVES Diabetes mellitus (DM) is a serious public health issue worldwide, and DM patients have higher risk of cardiovascular diseases (CVDs), which is the leading cause of DM-related deaths. China has the largest DM population, yet a robust model to predict CVDs in Chinese DM patients is still lacking. This systematic review is carried out to summarize existing models and identify potentially important predictors for CVDs in Chinese DM patients. STUDY DESIGN Systematic review. METHODS Medline and Embase were searched for data from April 1st, 2011 to May 31st, 2018. A study was eligible if it developed CVD (defined as total CVD or any major cardiovascular component) risk prediction models or explored potential predictors of CVD specifically for Chinese people with type 2 DM. Standardized forms were utilized to extract information, appraise applicability, risk of bias, and availabilities. RESULTS Five models and 29 studies focusing on potential predictors were identified. Models for a primary care setting, or to predict total CVD, are rare. A number of common predictors (e.g. age, sex, diabetes duration, smoking status, glycated hemoglobin (HbA1c), blood pressure, lipid profile, and treatment modalities) were observed in existing models, in which urine albumin:creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) are highly recommended for the Chinese population. Variability of blood pressure (BP) and HbA1c should be included in prediction model development as novel factors. Meanwhile, interactions between age, sex, and risk factors should also be considered. CONCLUSIONS A 10-year prediction model for CVD risk in Chinese type 2 DM patients is lacking and urgently needed. There is insufficient evidence to support the inclusion of other novel predictors in CVDs risk prediction functions for routine clinical use.
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Affiliation(s)
- W Dong
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F, Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - E Y F Wan
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F, Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China; Department of Pharmacology and Pharmacy, The University of Hong Kong, L02-56, 2/F, Laboratory Block, 21 Sassoon Road, Pokfulam, Hong Kong, China.
| | - L E Bedford
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F, Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - T Wu
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F, Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - C K H Wong
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F, Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - E H M Tang
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F, Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - C L K Lam
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F, Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
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19
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Ke C, Stukel TA, Luk A, Shah BR, Jha P, Lau E, Ma RCW, So WY, Kong AP, Chow E, Chan JCN. Development and validation of algorithms to classify type 1 and 2 diabetes according to age at diagnosis using electronic health records. BMC Med Res Methodol 2020; 20:35. [PMID: 32093635 PMCID: PMC7038546 DOI: 10.1186/s12874-020-00921-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 02/10/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Validated algorithms to classify type 1 and 2 diabetes (T1D, T2D) are mostly limited to white pediatric populations. We conducted a large study in Hong Kong among children and adults with diabetes to develop and validate algorithms using electronic health records (EHRs) to classify diabetes type against clinical assessment as the reference standard, and to evaluate performance by age at diagnosis. METHODS We included all people with diabetes (age at diagnosis 1.5-100 years during 2002-15) in the Hong Kong Diabetes Register and randomized them to derivation and validation cohorts. We developed candidate algorithms to identify diabetes types using encounter codes, prescriptions, and combinations of these criteria ("combination algorithms"). We identified 3 algorithms with the highest sensitivity, positive predictive value (PPV), and kappa coefficient, and evaluated performance by age at diagnosis in the validation cohort. RESULTS There were 10,196 (T1D n = 60, T2D n = 10,136) and 5101 (T1D n = 43, T2D n = 5058) people in the derivation and validation cohorts (mean age at diagnosis 22.7, 55.9 years; 53.3, 43.9% female; for T1D and T2D respectively). Algorithms using codes or prescriptions classified T1D well for age at diagnosis < 20 years, but sensitivity and PPV dropped for older ages at diagnosis. Combination algorithms maximized sensitivity or PPV, but not both. The "high sensitivity for type 1" algorithm (ratio of type 1 to type 2 codes ≥ 4, or at least 1 insulin prescription within 90 days) had a sensitivity of 95.3% (95% confidence interval 84.2-99.4%; PPV 12.8%, 9.3-16.9%), while the "high PPV for type 1" algorithm (ratio of type 1 to type 2 codes ≥ 4, and multiple daily injections with no other glucose-lowering medication prescription) had a PPV of 100.0% (79.4-100.0%; sensitivity 37.2%, 23.0-53.3%), and the "optimized" algorithm (ratio of type 1 to type 2 codes ≥ 4, and at least 1 insulin prescription within 90 days) had a sensitivity of 65.1% (49.1-79.0%) and PPV of 75.7% (58.8-88.2%) across all ages. Accuracy of T2D classification was high for all algorithms. CONCLUSIONS Our validated set of algorithms accurately classifies T1D and T2D using EHRs for Hong Kong residents enrolled in a diabetes register. The choice of algorithm should be tailored to the unique requirements of each study question.
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Affiliation(s)
- Calvin Ke
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Department of Medicine, University of Toronto, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Thérèse A. Stukel
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
| | - Andrea Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Baiju R. Shah
- Department of Medicine, University of Toronto, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
- Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Prabhat Jha
- Centre for Global Health Research, St. Michael’s Hospital, and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Eric Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, Hong Kong
| | - Ronald C. W. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Wing-Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Alice P. Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Juliana C. N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
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20
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Chan JCN, Lim LL, Luk AOY, Ozaki R, Kong APS, Ma RCW, So WY, Lo SV. From Hong Kong Diabetes Register to JADE Program to RAMP-DM for Data-Driven Actions. Diabetes Care 2019; 42:2022-2031. [PMID: 31530658 DOI: 10.2337/dci19-0003] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 08/14/2019] [Indexed: 02/03/2023]
Abstract
In 1995, the Hong Kong Diabetes Register (HKDR) was established by a doctor-nurse team at a university-affiliated, publicly funded, hospital-based diabetes center using a structured protocol for gathering data to stratify risk, triage care, empower patients, and individualize treatment. This research-driven quality improvement program has motivated the introduction of a territory-wide diabetes risk assessment and management program provided by 18 hospital-based diabetes centers since 2000. By linking the data-rich HKDR to the territory-wide electronic medical record, risk equations were developed and validated to predict clinical outcomes. In 2007, the HKDR protocol was digitalized to establish the web-based Joint Asia Diabetes Evaluation (JADE) Program complete with risk levels and algorithms for issuance of personalized reports to reduce clinical inertia and empower self-management. Through this technologically assisted, integrated diabetes care program, we have generated big data to track secular trends, identify unmet needs, and verify interventions in a naturalistic environment. In 2009, the JADE Program was adapted to form the Risk Assessment and Management Program for Diabetes Mellitus (RAMP-DM) in the publicly funded primary care clinics, which reduced all major events by 30-60% in patients without complications. Meanwhile, a JADE-assisted assessment and empowerment program provided by a university-affiliated, self-funded, nurse-coordinated diabetes center, aimed at complementing medical care in the community, also reduced all major events by 30-50% in patients with different risk levels. By combining universal health coverage, public-private partnerships, and data-driven integrated care, the Hong Kong experience provides a possible solution than can be adapted elsewhere to make quality diabetes care accessible, affordable, and sustainable.
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Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China .,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China
| | - Lee-Ling Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China.,Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hospital Authority, Hong Kong SAR, China
| | - Su-Vui Lo
- Hospital Authority, Hong Kong SAR, China
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21
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Wetmore JB, Li S, Ton TGN, Peng Y, Hansen MK, Neslusan C, Riley R, Liu J, Gilbertson DT. Association of diabetes-related kidney disease with cardiovascular and non-cardiovascular outcomes: a retrospective cohort study. BMC Endocr Disord 2019; 19:89. [PMID: 31455289 PMCID: PMC6712860 DOI: 10.1186/s12902-019-0417-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 08/11/2019] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Diabetes-related kidney disease is associated with end-stage renal disease and mortality, but opportunities remain to quantify its association with cardiovascular and non-cardiovascular morbidity outcomes. METHODS We used the Truven Health MarketScan Commercial Claims and Encounters Database, 2010-2014, which includes specific health services records for employees and their dependents from a selection of large employers, health plans, and government and public organizations. We used administrative claims data to quantify the association between diabetes-related kidney disease and end-stage renal disease, myocardial infarction, congestive heart failure, stroke, and infections. Cox proportional hazard regression models were used to estimate adjusted hazard ratios of developing complications. RESULTS Among 2.2 million patients with diabetes, 7.1% had diabetes-related kidney disease: 13.5%, stage 1-2; 33.8%, stage 3; 13.2% stages 4-5; 39.5%, unknown stage. In multivariable Cox proportional hazard models adjusted for demographic characteristics, baseline comorbid conditions, and total hospital days during the baseline period, hazard ratios for each outcome increased with greater diabetes-related kidney disease severity (stage 1-2 vs. stage 4-5) compared with no diabetes-related kidney disease: myocardial infarction, 1.2 (95% confidence interval 1.1-1.4) and 3.1 (2.9-3.4); congestive heart failure, 1.7 (1.6-1.9) and 5.6 (5.3-5.8); stroke, 1.3 (1.2-1.5) and 2.3 (2.1-2.5); infection, 1.4 (1.3-1.5) and 2.9 (2.8-3.0). Among patients with stage 4-5 disease, 36-month cumulative incidence was nearly 22.8% for congestive heart failure, and 25.8% for infections. CONCLUSIONS Diabetes-related kidney disease appears to be formally diagnosed at a more advanced stage than might be expected, given clinical practice guidelines. Risks of cardiovascular and non-cardiovascular outcomes are high.
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Affiliation(s)
- James B. Wetmore
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, 701 Park Avenue, Suite S4.100, Minneapolis, MN 55415 USA
- Division of Nephrology, Hennepin Healthcare, Minneapolis, MN USA
| | - Suying Li
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, 701 Park Avenue, Suite S4.100, Minneapolis, MN 55415 USA
| | | | - Yi Peng
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, 701 Park Avenue, Suite S4.100, Minneapolis, MN 55415 USA
| | | | | | - Ralph Riley
- Janssen Global Services, LLC, Raritan, NJ USA
| | - Jiannong Liu
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, 701 Park Avenue, Suite S4.100, Minneapolis, MN 55415 USA
| | - David T. Gilbertson
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, 701 Park Avenue, Suite S4.100, Minneapolis, MN 55415 USA
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22
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Ke C, Lau E, Shah BR, Stukel TA, Ma RC, So WY, Kong AP, Chow E, Clarke P, Goggins W, Chan JCN, Luk A. Excess Burden of Mental Illness and Hospitalization in Young-Onset Type 2 Diabetes: A Population-Based Cohort Study. Ann Intern Med 2019; 170:145-154. [PMID: 30641547 DOI: 10.7326/m18-1900] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Type 2 diabetes (T2D) increases hospitalization risk. Young-onset T2D (YOD) (defined as onset before age 40 years) is associated with excess morbidity and mortality, but its effect on hospitalizations is unknown. OBJECTIVE To determine hospitalization rates among persons with YOD and to examine the effect of age at onset on hospitalization risk. DESIGN Prospective cohort study. SETTING Hong Kong. PARTICIPANTS Adults aged 20 to 75 years in population-based (2002 to 2014; n = 422 908) and registry-based (2000 to 2014; n = 20 886) T2D cohorts. MEASUREMENTS All-cause and cause-specific hospitalization rates. Negative binomial regression models estimated effect of age at onset on hospitalization rate and cumulative bed-days from onset to age 75 years for YOD. RESULTS Patients with YOD had the highest hospitalization rates by attained age. In the registry cohort, 36.8% of YOD bed-days before age 40 years were due to mental illness. The adjusted rate ratios showed increased hospitalization in YOD versus usual-onset T2D (onset at age ≥40 years) (all-cause, 1.8 [95% CI, 1.7 to 2.0]; renal, 6.7 [CI, 4.2 to 10.6]; diabetes, 3.7 [CI, 3.0 to 4.6]; cardiovascular, 2.1 [CI, 1.8 to 2.5]; infection, 1.7 [CI, 1.4 to 2.1]; P < 0.001 for all). Models estimated that intensified risk factor control in YOD (hemoglobin A1c level <6.2%, systolic blood pressure <120 mm Hg, low-density lipoprotein cholesterol level <2.0 mmol/L [<77.3 mg/dL], triglyceride level <1.3 mmol/L [<115.1 mg/dL], waist circumference of 85 cm [men] or 80 cm [women], and smoking cessation) was associated with a one-third reduction in cumulative bed-days from onset to age 75 years (97 to 65 bed-days). LIMITATION Possible residual confounding. CONCLUSION Adults with YOD have excess hospitalizations across their lifespan compared with persons with usual-onset T2D, including an unexpectedly large burden of mental illness in young adulthood. Efforts to prevent YOD and intensify cardiometabolic risk factor control while focusing on mental health are urgently needed. PRIMARY FUNDING SOURCE Asia Diabetes Foundation.
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Affiliation(s)
- Calvin Ke
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, and University of Toronto, Toronto, Ontario, Canada (C.K.)
| | - Eric Lau
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (E.L., R.C.M., W.S., A.P.K., E.C., W.G., J.C.C., A.L.)
| | - Baiju R Shah
- University of Toronto, Institute for Clinical Evaluative Sciences, and Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada (B.R.S.)
| | - Thérèse A Stukel
- University of Toronto and Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada (T.A.S.)
| | - Ronald C Ma
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (E.L., R.C.M., W.S., A.P.K., E.C., W.G., J.C.C., A.L.)
| | - Wing-Yee So
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (E.L., R.C.M., W.S., A.P.K., E.C., W.G., J.C.C., A.L.)
| | - Alice P Kong
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (E.L., R.C.M., W.S., A.P.K., E.C., W.G., J.C.C., A.L.)
| | - Elaine Chow
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (E.L., R.C.M., W.S., A.P.K., E.C., W.G., J.C.C., A.L.)
| | - Philip Clarke
- University of Melbourne, Melbourne, Victoria, Australia (P.C.)
| | - William Goggins
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (E.L., R.C.M., W.S., A.P.K., E.C., W.G., J.C.C., A.L.)
| | - Juliana C N Chan
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (E.L., R.C.M., W.S., A.P.K., E.C., W.G., J.C.C., A.L.)
| | - Andrea Luk
- The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (E.L., R.C.M., W.S., A.P.K., E.C., W.G., J.C.C., A.L.)
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Attallah MI, Ibrahim AN, Elnaggar RA. Effects of Pioglitazone and Irbesartan on Endothelial Dysfunction on Experimentally Streptozotocin-Induced Diabetic Nephropathy in Rats. EGYPTIAN JOURNAL OF BASIC AND CLINICAL PHARMACOLOGY 2018. [DOI: 10.11131/2018/101368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Magdy I. Attallah
- Department of Medical Pharmacology, Faculty of Medicine, Cairo University, Kasr Alainy, Cairo, Egypt
| | - Amany N. Ibrahim
- Department of Clinical Pharmacology, Faculty of Medicine, Benha University, Benha, Qalubiya, Egypt
| | - Reham Abdelrahman Elnaggar
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Misr University for Science and Technology (MUST), 6th of October City, Giza, Egypt
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Abstract
The People's Republic of China (herein referred to as China) has witnessed one of the most dramatic rises in diabetes prevalence anywhere in the world. The latest epidemiological study suggests that approximately 11% of the population has diabetes, with a significant proportion remaining undiagnosed. Risk factors for diabetes in the Chinese population are similar to those in other populations, though gestational diabetes and young-onset diabetes is becoming increasingly common. Data on the prevalence of diabetic complications remain limited, though cardio-renal complications account for significant morbidity and mortality. Other diabetes-related comorbidities are becoming increasingly common, with cancer emerging as a major cause of mortality among individuals with diabetes. There are many challenges and obstacles that impede effective diabetes prevention and the delivery of care, though much progress has occurred over recent years. Lessons learnt from how China has responded to the challenges posed by the diabetes epidemic will be invaluable for other countries facing the many threats of diabetes and its complications.
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Affiliation(s)
- Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, 30-32 Ngan Shing Street, Shatin, New Territories, Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
- Chinese University of Hong Kong and Shanghai Jiao Tong University (CUHK-SJTU) Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
- NHMRC Clinical Trials Centre, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia.
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25
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Ng IHY, Cheung KKT, Yau TTL, Chow E, Ozaki R, Chan JCN. Evolution of Diabetes Care in Hong Kong: From the Hong Kong Diabetes Register to JADE-PEARL Program to RAMP and PEP Program. Endocrinol Metab (Seoul) 2018; 33:17-32. [PMID: 29589385 PMCID: PMC5874192 DOI: 10.3803/enm.2018.33.1.17] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 02/26/2018] [Accepted: 02/28/2018] [Indexed: 12/14/2022] Open
Abstract
The rapid increase in diabetes prevalence globally has contributed to large increases in health care expenditure on diabetic complications, posing a major health burden to countries worldwide. Asians are commonly observed to have poorer β-cell function and greater insulin resistance compared to the Caucasian population, which is attributed by their lower lean body mass and central obesity. This "double phenotype" as well as the rising prevalence of young onset diabetes in Asia has placed Asians with diabetes at high risk of cardiovascular and renal complications, with cancer emerging as an important cause of morbidity and mortality. The experience from Hong Kong had demonstrated that a multifaceted approach, involving team-based integrated care, information technological advances, and patient empowerment programs were able to reduce the incidence of diabetic complications, hospitalizations, and mortality. System change and public policies to enhance implementation of such programs may provide solutions to combat the burgeoning health problem of diabetes at a societal level.
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Affiliation(s)
- Ivy H Y Ng
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
- Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong
| | - Kitty K T Cheung
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Tiffany T L Yau
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Elaine Chow
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Risa Ozaki
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong.
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Wan EYF, Fong DYT, Fung CSC, Yu EYT, Chin WY, Chan AKC, Lam CLK. Development of a cardiovascular diseases risk prediction model and tools for Chinese patients with type 2 diabetes mellitus: A population-based retrospective cohort study. Diabetes Obes Metab 2018; 20:309-318. [PMID: 28722290 DOI: 10.1111/dom.13066] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 07/11/2017] [Accepted: 07/13/2017] [Indexed: 01/03/2023]
Abstract
AIMS Evidence-based cardiovascular diseases (CVD) risk prediction models and tools specific for Chinese patients with type 2 diabetes mellitus (T2DM) are currently unavailable. This study aimed to develop and validate a CVD risk prediction model for Chinese T2DM patients. METHODS A retrospective cohort study was conducted with 137 935 Chinese patients aged 18 to 79 years with T2DM and without prior history of CVD, who had received public primary care services between January 1, 2010 and December 31, 2010. Using the derivation cohort over a median follow-up of 5 years, the interaction effect between predictors and age were derived using Cox proportional hazards regression with a forward stepwise approach. Harrell's C statistic and calibration plot were used on the validation cohort to assess the discrimination and calibration of the models. The web calculator and chart were developed based on the developed models. RESULTS For both genders, predictors for higher risk of CVD were older age, smoking, longer diabetes duration, usage of anti-hypertensive drug and insulin, higher body mass index, haemoglobin A1c (HbA1c), systolic and diastolic blood pressure, a total cholesterol to high-density lipoprotein-cholesterol (TC/HDL-C) ratio and urine albumin to creatinine ratio, and lower estimated glomerular filtration rate. Interaction factors with age demonstrated a greater weighting of TC/HDL-C ratio in both younger females and males, and smoking status and HbA1c in younger males. CONCLUSION The developed models, translated into a web calculator and color-coded chart, served as evidence-based visual aids that facilitate clinicians to estimate quickly the 5-year CVD risk for Chinese T2DM patients and to guide intervention.
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Affiliation(s)
- Eric Yuk Fai Wan
- Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong
- Department of Surgery, School of Nursing, The University of Hong Kong, Ap Lei Chau, Hong Kong
| | - Daniel Yee Tak Fong
- Department of Surgery, School of Nursing, The University of Hong Kong, Ap Lei Chau, Hong Kong
| | - Colman Siu Cheung Fung
- Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong
| | - Esther Yee Tak Yu
- Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong
| | - Weng Yee Chin
- Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong
| | - Anca Ka Chun Chan
- Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong
| | - Cindy Lo Kuen Lam
- Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong
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27
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Fung ACH, Tse G, Cheng HL, Lau ESH, Luk A, Ozaki R, So TTY, Wong RYM, Tsoh J, Chow E, Wing YK, Chan JCN, Kong APS. Depressive Symptoms, Co-Morbidities, and Glycemic Control in Hong Kong Chinese Elderly Patients With Type 2 Diabetes Mellitus. Front Endocrinol (Lausanne) 2018; 9:261. [PMID: 29896155 PMCID: PMC5986894 DOI: 10.3389/fendo.2018.00261] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2018] [Accepted: 05/07/2018] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Undiagnosed depression is an important comorbidity in type 2 diabetes (T2D) which can be detected using the Geriatric Depression Scale (GDS-15) questionnaire. In this cross-sectional study, we examined the associations of depression using GDS score with control of cardiometabolic risk factors and health status in elderly patients with T2D. SETTING AND PARTICIPANTS Between February and December 2013, patients aged ≥65 years who underwent structured comprehensive assessment as a quality improvement program at the Diabetes Center of a teaching hospital were invited to complete the GDS-15 questionnaire. MAIN OUTCOME MEASURES Depression was defined as a GDS score ≥7. Demographic data, prior history of co-morbidities, frequency of self-reported hypoglycemia, and attainment of treatment targets defined as HbA1c, <7%, blood pressure <130/80 mmHg, and LDL-C <2.6 mmol/L were documented. RESULTS Among 325 participants (65% male, median [interquartile range] age: 69 [8] years), 42 (13%) had depression. Patients with depression had longer disease durations (mean ± SD: 15.1 ± 9.1 vs. 11.6 ± 8.1 years, P = 0.02), more frequent self-reported hypoglycemic events (17 vs. 6%, P = 0.03) and were less likely to attain all three treatment targets (0 vs. 16%, P = 0.004) than those without depression. On multivariable analysis, patients with depression had an odds ratio of 2.84 (95% confidence intervals: 1.35-6.00, P = 0.006) of reporting prior history of co-morbidities. CONCLUSION In elderly patients with T2D, depression was not uncommon especially in those with poor control of risk factors, hypoglycemia, and co-morbidities. Inclusion of GDS-15 questionnaire during structured assessment for complications and risk factors can identify these high-risk patients for more holistic management of their physical and mental health.
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Affiliation(s)
- Annie C. H. Fung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Gary Tse
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Hiu Lam Cheng
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Eric S. H. Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Andrea Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Tammy T. Y. So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Rebecca Y. M. Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Joshua Tsoh
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Yun Kwok Wing
- Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Juliana C. N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Alice P. S. Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong
- *Correspondence: Alice P. S. Kong,
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Deerochanawong C, Bajpai S, Dwipayana IMP, Hussein Z, Mabunay MA, Rosales R, Tsai ST, Tsang MW. Optimizing Glycemic Control Through Titration of Insulin Glargine 100 U/mL: A Review of Current and Future Approaches with a Focus on Asian Populations. Diabetes Ther 2017; 8:1197-1214. [PMID: 29094298 PMCID: PMC5688987 DOI: 10.1007/s13300-017-0322-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Indexed: 01/25/2023] Open
Abstract
Various data have demonstrated inadequate glycemic control amongst Asians with type 2 diabetes mellitus (T2DM), possibly on account of suboptimal titration of basal insulin-an issue which needs to be further examined. Here we review the available global and Asia-specific data on titration of basal insulin, with a focus on the use of insulin glargine 100 U/mL (Gla-100). We also discuss clinical evidence on the efficacy and safety of titrating Gla-100, different approaches to titration, including some of the latest technological advancements, and guidance on the titration of basal insulin from international and local Asian guidelines. The authors also provide their recommendations for the initiation and titration of basal insulin for Asian populations. Discussion of the data included in this review and in relation to the authors' clinical experience with treating T2DM in Asian patients is also included. Briefly, clinical studies demonstrate the achievement of adequate glycemic control in adults with T2DM through titration of Gla-100. However, studies investigating approaches to titration, specifically in Asian populations, are lacking and need to be conducted. Given that the management of insulin therapy is a multidisciplinary team effort involving endocrinologists, primary care physicians, nurse educators, and patients, greater resources and education targeted at these groups are needed regarding the optimal titration of basal insulin. Technological advancements in the form of mobile or web-based applications for automated dose adjustment can aid different stakeholders in optimizing the dose of basal insulin, enabling a larger number of patients in Asia to reach their target glycemic goals with improved outcomes.
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Wan EYF, Fong DYT, Fung CSC, Yu EYT, Chin WY, Chan AKC, Lam CLK. Classification Rule for 5-year Cardiovascular Diseases Risk using decision tree in Primary Care Chinese Patients with Type 2 Diabetes Mellitus. Sci Rep 2017; 7:15238. [PMID: 29127341 PMCID: PMC5681694 DOI: 10.1038/s41598-017-15579-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 10/30/2017] [Indexed: 12/31/2022] Open
Abstract
Cardiovascular disease(CVD) is the leading cause of mortality among patients with type 2 diabetes mellitus(T2DM), and a risk classification model for CVD among primary care diabetic patients is pivotal for risk-based interventions and patient information. This study developed a simple tool for a 5-year CVD risk prediction for primary care Chinese patients with T2DM. A retrospective cohort study was conducted on 137,935 primary care Chinese T2DM patients aged 18-79 years without history of CVD between 1 January 2010 and 31 December 2010. New events of CVD of the cohort over a median follow up of 5 years were extracted from the medical records. A classification rule of 5-year CVD risk was obtained from the derivation cohort and validated in the validation cohort. Significant risk factors included in decision tree were age, gender, smoking status, diagnosis duration, obesity, unsatisfactory control on haemoglobin A1c and cholesterol, albuminuria and stage of chronic kidney disease, which categorized patients into five 5-year CVD risk groups(<5%; 5-9%; 10-14%; 15-19% and ≥20%). Taking the group with the lowest CVD risk, the hazard ratios varied from 1.92(1.77,2.08) to 8.46(7.75,9.24). The present prediction model performed comparable discrimination and better calibration from the plot compared to other current existing models.
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Affiliation(s)
- Eric Yuk Fai Wan
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | | | - Colman Siu Cheung Fung
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - Esther Yee Tak Yu
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - Weng Yee Chin
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - Anca Ka Chun Chan
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
| | - Cindy Lo Kuen Lam
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong, China
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30
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Wan EYF, Fong DYT, Fung CSC, Yu EYT, Chin WY, Chan AKC, Lam CLK. Prediction of new onset of end stage renal disease in Chinese patients with type 2 diabetes mellitus - a population-based retrospective cohort study. BMC Nephrol 2017; 18:257. [PMID: 28764641 PMCID: PMC5539616 DOI: 10.1186/s12882-017-0671-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 07/19/2017] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Since diabetes mellitus (DM) is the leading cause of end stage renal disease (ESRD), this study aimed to develop a 5-year ESRD risk prediction model among Chinese patients with Type 2 DM (T2DM) in primary care. METHODS A retrospective cohort study was conducted on 149,333 Chinese adult T2DM primary care patients without ESRD in 2010. Using the derivation cohort over a median of 5 years follow-up, the gender-specific models including the interaction effect between predictors and age were derived using Cox regression with a forward stepwise approach. Harrell's C-statistic and calibration plot were applied to the validation cohort to assess discrimination and calibration of the models. RESULTS Prediction models showed better discrimination with Harrell's C-statistics of 0.866 (males) and 0.862 (females) and calibration power from the plots than other established models. The predictors included age, usages of anti-hypertensive drugs, anti-glucose drugs, and Hemogloblin A1c, blood pressure, urine albumin/creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR). Specific predictors for male were smoking and presence of sight threatening diabetic retinopathy while additional predictors for female included longer duration of diabetes and quadratic effect of body mass index. Interaction factors with age showed a greater weighting of insulin and urine ACR in younger males, and eGFR in younger females. CONCLUSIONS Our newly developed gender-specific models provide a more accurate 5-year ESRD risk predictions for Chinese diabetic primary care patients than other existing models. The models included several modifiable risk factors that clinicians can use to counsel patients, and to target at in the delivery of care to patients.
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Affiliation(s)
- Eric Yuk Fai Wan
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
- School of Nursing, the University of Hong Kong, Pok Fu Lam, Hong Kong
| | | | - Colman Siu Cheung Fung
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
| | - Esther Yee Tak Yu
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
| | - Weng Yee Chin
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
| | - Anca Ka Chun Chan
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
| | - Cindy Lo Kuen Lam
- Department of Family Medicine and Primary Care, the University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
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Wan EYF, Fong DYT, Fung CSC, Yu EYT, Chin WY, Chan AKC, Lam CLK. Prediction of five-year all-cause mortality in Chinese patients with type 2 diabetes mellitus - A population-based retrospective cohort study. J Diabetes Complications 2017; 31:939-944. [PMID: 28238555 DOI: 10.1016/j.jdiacomp.2017.01.017] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 01/25/2017] [Accepted: 01/29/2017] [Indexed: 10/20/2022]
Abstract
AIMS This study aimed to develop and validate an all-cause mortality risk prediction model for Chinese primary care patients with type 2 diabetes mellitus(T2DM) in Hong Kong. METHODS A population-based retrospective cohort study was conducted on 132,462 Chinese patients who had received public primary care services during 2010. Each gender sample was randomly split on a 2:1 basis into derivation and validation cohorts and was followed-up for a median period of 5years. Gender-specific mortality risk prediction models showing the interaction effect between predictors and age were derived using Cox proportional hazards regression with forward stepwise approach. Developed models were compared with pre-existing models by Harrell's C-statistic and calibration plot using validation cohort. RESULTS Common predictors of increased mortality risk in both genders included: age; smoking habit; diabetes duration; use of anti-hypertensive agents, insulin and lipid-lowering drugs; body mass index; hemoglobin A1c; systolic blood pressure(BP); total cholesterol to high-density lipoprotein-cholesterol ratio; urine albumin to creatinine ratio(urine ACR); and estimated glomerular filtration rate(eGFR). Prediction models showed better discrimination with Harrell"'s C-statistics of 0.768(males) and 0.782(females) and calibration power from the plots than previously established models. CONCLUSIONS Our newly developed gender-specific models provide a more accurate predicted 5-year mortality risk for Chinese diabetic patients than other established models.
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Affiliation(s)
- Eric Yuk Fai Wan
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong.
| | | | - Colman Siu Cheung Fung
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
| | - Esther Yee Tak Yu
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
| | - Weng Yee Chin
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
| | - Anca Ka Chun Chan
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
| | - Cindy Lo Kuen Lam
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F Ap Lei Chau Clinic, 161 Main Street, Ap Lei Chau, Hong Kong
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Shu H, Gu LN, Men LC, Lu JM. Lixisenatide Improves Glycemic Control in Asian Type 2 Diabetic Patients Inadequately Controlled With Oral Antidiabetic Drugs: An Individual Patient Data Meta-Analysis. Diabetes Ther 2016; 7:777-792. [PMID: 27796905 PMCID: PMC5118245 DOI: 10.1007/s13300-016-0207-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Indexed: 02/06/2023] Open
Abstract
INTRODUCTION Lixisenatide is a novel GLP-1 receptor agonist for the treatment of type 2 diabetes mellitus (T2DM). Its efficacy and safety have been assessed in a series of phase 3 studies included in the GetGoal program. In these studies, lixisenatide was found to be superior to placebo in glycemic control. The aim of this meta-analysis was to assess the safety and efficacy of lixisenatide as an adjunct therapy in Asian patients with T2DM in adequately controlled with oral antidiabetic drugs (OADs). METHODS We performed a meta-analysis from five lixisenatide phase 3 studies. In each of these multiethnic studies, patients with T2DM inadequately controlled (glycated hemoglobin, HbA1c ≥7%) with established OADs were randomized to lixisenatide or placebo for 24 weeks, with a balanced distribution of Asian patients in these two arms (503 and 338 patients in the intent-to-treat population, respectively). RESULTS Lixisenatide was superior to placebo in reducing HbA1c (weighted, total mean difference -0.57%; P = 0.002). More patients treated with lixisenatide versus placebo achieved HbA1c targets of ≤7% (49.1% vs. 28.4%, P = 0.003). Lixisenatide was superior to placebo in lowering 2-h postprandial glucose (PPG) (weighted, total mean difference -5.50 mmol/l, P = 0.0005). More patients treated with lixisenatide versus placebo achieved 2-h PPG targets of ≤7.8 mmol/l (39.2% vs. 2.2%, P < 0.0001). More patients treated with lixisenatide versus placebo achieved both an HbA1c target of ≤7% and a 2-h PPG target of ≤10 mmol/l (34.8% vs. 2.69%, P < 0.00001). The body weight of the lixisenatide group tended to decrease. Lixisenatide was generally well tolerated. CONCLUSION Lixisenatide as an adjunct therapy can significantly improve the glycemic control of Asian patients with type 2 DM who do not meet targets for glycemic control with an established OAD regimen. FUNDING Sanofi (China) Investment Co., Ltd., Shanghai, China.
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Affiliation(s)
- Hua Shu
- Department of Endocrinology, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, China
| | - Li-Na Gu
- Sanofi (China) Investment Co., Ltd., 19F Tower III Kerry Center, 1228 Middle Yan'an Road, Shanghai, China
| | - Li-Chuang Men
- Sanofi (China) Investment Co., Ltd., 19F Tower III Kerry Center, 1228 Middle Yan'an Road, Shanghai, China
| | - Ju-Ming Lu
- Department of Endocrinology, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, China.
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Goh SY, Ang E, Bajpai S, Deerochanawong C, Hong EG, Hussein Z, Joshi S, Kamaruddin NA, Kho S, Kong APS, Pan CY, Perfetti R, Vichayanrat A, Vlajnic A, Chan JCN. A patient-centric approach to optimise insulin therapy in Asia. J Diabetes Complications 2016; 30:973-80. [PMID: 27288201 DOI: 10.1016/j.jdiacomp.2016.05.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Revised: 05/20/2016] [Accepted: 05/20/2016] [Indexed: 11/16/2022]
Affiliation(s)
| | - Ernesto Ang
- Cardinal Santos Medical Center, San Juan, Philippines; The Institute for Studies on Diabetes Foundation Inc., Metro Manila, Philippines
| | | | | | - Eun-Gyoung Hong
- Hallym University School of Medicine, Dongtan Sacred Heart Hospital, Gyeonggi-do, South Korea
| | | | | | | | - Sjoberg Kho
- University of Santo Tomas, Manila, Philippines
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Song XY, Pan D, Liu PF, Cai JH. Bayesian analysis of transformation latent variable models with multivariate censored data. Stat Methods Med Res 2016; 25:2337-2358. [DOI: 10.1177/0962280214522786] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Transformation latent variable models are proposed in this study to analyze multivariate censored data. The proposed models generalize conventional linear transformation models to semiparametric transformation models that accommodate latent variables. The characteristics of the latent variables were assessed based on several correlated observed indicators through measurement equations. A Bayesian approach was developed with Bayesian P-splines technique and the Markov chain Monte Carlo algorithm to estimate the unknown parameters and transformation functions. Simulation shows that the performance of the proposed methodology is satisfactory. The proposed method was applied to analyze a cardiovascular disease data set.
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Affiliation(s)
- Xin-Yuan Song
- Department of Statistics, The Chinese University of Hong Kong, Hong Kong
| | - Deng Pan
- Department of Statistics, The Chinese University of Hong Kong, Hong Kong
| | - Peng-Fei Liu
- School of Mathematics and Statistics, Jiangsu Normal University, Xuzhou, China
| | - Jing-Heng Cai
- Department of Statistics, Sun Yat-sen University, Guangzhou, China
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Genetic and clinical variables identify predictors for chronic kidney disease in type 2 diabetes. Kidney Int 2016; 89:411-20. [PMID: 26806836 DOI: 10.1016/j.kint.2015.09.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Revised: 09/24/2015] [Accepted: 09/24/2015] [Indexed: 01/13/2023]
Abstract
Type 2 diabetes and chronic kidney disease (CKD) may share common risk factors. Here we used a 3-stage procedure to discover novel predictors of CKD by repeatedly applying a stepwise selection based on the Akaike information criterion to subsamples of a prospective complete-case cohort of 2755 patients. This cohort encompassed 25 clinical variables and 36 genetic variants associated with type 2 diabetes, obesity, or fasting plasma glucose. We compared the performance of the clinical, genetic, and clinico-genomic models and used net reclassification improvement to evaluate the impact of top selected genetic variants to the clinico-genomic model. Associations of selected genetic variants with CKD were validated in 2 independent cohorts followed by meta-analyses. Among the top 6 single-nucleotide polymorphisms selected from clinico-genomic data, three (rs478333 of G6PC2, rs7754840 and rs7756992 of CDKAL1) contributed toward the improvement of prediction performance. The variant rs478333 was associated with rapid decline (over 4% per year) in estimated glomerular filtration rate. In a meta-analysis of 2 replication cohorts, the variants rs478333 and rs7754840 showed significant associations with CKD after adjustment for conventional risk factors. Thus, this novel 3-stage approach to a clinico-genomic data set identified 3 novel genetic predictors of CKD in type 2 diabetes. This method can be applied to similar data sets containing clinical and genetic variables to select predictors for clinical outcomes.
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Abstract
The prevalence of diabetes is increasing globally, particularly in Asia. According to the 2013 Diabetes Atlas, an estimated 366 million people are affected by diabetes worldwide; 36% of those affected live in the Western Pacific region, with a significant proportion in East Asia. The reasons for this marked increase in the prevalence of diabetes can be extrapolated from several distinct features of the Asian region. First, the two most populated countries, China and India, are located in Asia. Second, Asians have experienced extremely rapid economic growth, including rapid changes in dietary patterns, during the past decades. As a result, Asians tend to have more visceral fat within the same body mass index range compared with Westerners. In addition, increased insulin resistance relative to reduced insulin secretory function is another important feature of Asian individuals with diabetes. Young age of disease onset is also a distinctive characteristic of these patients. Moreover, changing dietary patterns, such as increased consumption of white rice and processed red meat, contributes to the deteriorated lifestyle of this region. Recent studies suggest a distinctive responsiveness to novel anti-diabetic agents in Asia; however, further research and efforts to reverse the increasing prevalence of diabetes are needed worldwide.
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Affiliation(s)
- Eun Jung Rhee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.
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Saxena Y, Purwar B, Meena H, Sarthi P. Dolichos biflorus Linn. ameliorates diabetic complications in streptozotocin induced diabetic rats. Ayu 2015. [PMID: 26195910 PMCID: PMC4492032 DOI: 10.4103/0974-8520.159022] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Background: Horsegram (Dolichos biflorus Linn.) is a known antilithiatic, hypolipedemic and has free radical scavenging activity and increased production of reactive oxygen species play a role in pathophysiological mechanisms that trigger diabetic complications. Aim: To see the effect of daily oral feeding of D.biflorous on nephropathy and retinopathy in streptozotocin (STZ) induced-diabetic rats. Materials and Methods: A total of 24 healthy rats were randomly grouped into controls, diabetic and diabetic on Dolichos. Diabetes was induced by a single dose of STZ (55 mg/kg) and animals were given prepared food and water ad libitum. Dolichos was orally given at 300 mg/kg/day to rats in diabetic on Dolichos group for next 30 days. Fasting blood glucose levels was monitored at beginning and at the end of the experiment while assessment of serum creatinine levels and histopathological study of kidney and retina was carried only at the end of the experiment. Statistical differences between groups were analyzed using analysis of variance followed by, Bonferroni test as posthoc test. Results: Results indicated improvement in serum creatinine levels and reduced glomerular sclerosing and Bowman's space with interstitial alterations and significantly reduced renal hypertrophy in diabetic rat son Dolichos diabetic rats (P < 0.001). Retinal layers showed inconsistent improvement in the width of the neuronal layers and decreased vacuolization of plexiform layers and retinal vessel density. Conclusion: D. biflorus at doses of 300 mg/kg/day for 30 days resulted in gradual but significant decreased diabetic nephropathy.
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Affiliation(s)
- Yogesh Saxena
- Department of Physiology, Himalayan Institute of Medical Sciences, SRH University, Dehradun, Uttarakhand, India
| | - Brijesh Purwar
- Department of Physiology, Himalayan Institute of Medical Sciences, SRH University, Dehradun, Uttarakhand, India
| | - Harsh Meena
- Department of Pathology, Himalayan Institute of Medical Sciences, SRH University, Dehradun, Uttarakhand, India
| | - Parth Sarthi
- Department of Physiology, Integral Institute of Medical Sciences and Research, Integral University, Lucknow, Uttar Pradesh, India
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Complication profiles and their associated factors in Malaysian adult type 2 diabetes mellitus—an analysis of ADCM registry. Int J Diabetes Dev Ctries 2015. [DOI: 10.1007/s13410-015-0298-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
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Yeung RO, Zhang Y, Luk A, Yang W, Sobrepena L, Yoon KH, Aravind SR, Sheu W, Nguyen TK, Ozaki R, Deerochanawong C, Tsang CC, Chan WB, Hong EG, Do TQ, Cheung Y, Brown N, Goh SY, Ma RC, Mukhopadhyay M, Ojha AK, Chakraborty S, Kong AP, Lau W, Jia W, Li W, Guo X, Bian R, Weng J, Ji L, Reyes-dela Rosa M, Toledo RM, Himathongkam T, Yoo SJ, Chow CC, Ho LLT, Chuang LM, Tutino G, Tong PC, So WY, Wolthers T, Ko G, Lyubomirsky G, Chan JCN. Metabolic profiles and treatment gaps in young-onset type 2 diabetes in Asia (the JADE programme): a cross-sectional study of a prospective cohort. Lancet Diabetes Endocrinol 2014; 2:935-43. [PMID: 25081582 DOI: 10.1016/s2213-8587(14)70137-8] [Citation(s) in RCA: 192] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND The prevalence of diabetes is increasing in young adults in Asia, but little is known about metabolic control or the burden of associated complications in this population. We assessed the prevalence of young-onset versus late-onset type 2 diabetes, and associated risk factors and complication burdens, in the Joint Asia Diabetes Evaluation (JADE) cohort. METHODS JADE is an ongoing prospective cohort study. We enrolled adults with type 2 diabetes from 245 outpatient clinics in nine Asian countries or regions. We classified patients as having young-onset diabetes if they were diagnosed before the age of 40 years, and as having late-onset diabetes if they were diagnosed at 40 years or older. Data for participants' first JADE assessment was extracted for cross-sectional analysis. We compared clinical characteristics, metabolic risk factors, and the prevalence of complications between participants with young-onset diabetes and late-onset diabetes. FINDINGS Between Nov 1, 2007, and Dec 21, 2012, we enrolled 41,029 patients (15,341 from Hong Kong, 9107 from India, 7712 from Philippines, 5646 from China, 1751 from South Korea, 705 from Vietnam, 385 from Singapore, 275 from Thailand, 107 from Taiwan). 7481 patients (18%) had young-onset diabetes, with age at diagnosis of mean 32·9 years [SD 5·7] versus 53·9 years [9·0] with late-onset diabetes (n=33,548). Those with young-onset diabetes had longer disease duration (median 10 years [IQR 3-18]) than those with late-onset diabetes (5 years [2-11]). Fewer patients with young-onset diabetes achieved HbA1c concentrations lower than 7% compared to those with late-onset diabetes (27% vs 42%; p<0·0001) Patients with young-onset diabetes had higher mean concentrations of HbA1c (mean 8·32% [SD 2·03] vs 7·69% [1·82]; p<0·0001), LDL cholesterol (2·78 mmol/L [0·96] vs 2·74 [0·93]; p=0·009), and a higher prevalence of retinopathy (1363 [20%] vs 5714 (18%); p=0·011) than those with late-onset diabetes, but were less likely to receive statins (2347 [31%] vs 12,441 [37%]; p<0·0001) and renin-angiotensin-system inhibitors (1868 [25%] vs 9665 [29%]; p=0·006). INTERPRETATION In clinic-based settings across Asia, one in five adult patients had young-onset diabetes. Compared with patients with late-onset diabetes, metabolic control in those with young-onset diabetes was poor, and fewer received organ-protective drugs. Given the risk conferred by long-term suboptimum metabolic control, our findings suggest an impending epidemic of young-onset diabetic complications. FUNDING The Asia Diabetes Foundation (ADF) and Merck.
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Affiliation(s)
| | - Yuying Zhang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Andrea Luk
- Prince of Wales Hospital, Hong Kong, China
| | | | | | - Kun-Ho Yoon
- The Catholic University of Korea, Seoul, South Korea
| | | | - Wayne Sheu
- Taichung Veterans General Hospital, Taichung, Taiwan
| | - Thy Khue Nguyen
- HCMC University of Pharmaceutical and Medicine, Ho Chi Mihn City, Vietnam
| | - Risa Ozaki
- Prince of Wales Hospital, Hong Kong, China
| | | | | | - Wing-Bun Chan
- Qualigenics Diabetes Centre, Hong Kong, Hong Kong SAR
| | | | | | - Yu Cheung
- Ma On Shan Family Medicine Centre, Hong Kong, China
| | | | | | - Ronald C Ma
- The Chinese University of Hong Kong, Hong Kong, China
| | | | | | | | - Alice P Kong
- The Chinese University of Hong Kong, Hong Kong, China
| | - Winnie Lau
- Prince of Wales Hospital, Hong Kong, China
| | - Weiping Jia
- Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Wenhui Li
- Peking Union Medical College Hospital, Beijing, China
| | - Xiaohui Guo
- Peking Union Medical College Hospital, Beijing, China
| | | | - Jianping Weng
- The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Linong Ji
- Peking University People's Hospital, Beijing, China
| | | | | | | | - Soon-Jib Yoo
- The Catholic University Bucheon St Mary's Hospital, Bucheon, South Korea
| | - C C Chow
- Prince of Wales Hospital, Hong Kong, China
| | - Larry L T Ho
- Taipei Veterans General Hospital and National Yang-Ming University, Taipei, Taiwan
| | - Lee-Ming Chuang
- National Taiwan University College of Medicine, Taipei, Taiwan
| | - Greg Tutino
- The Chinese University of Hong Kong, Hong Kong, China
| | | | | | | | - Gary Ko
- The Chinese University of Hong Kong, Hong Kong, China
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Abstract
China has a large burden of diabetes: in 2013, one in four people with diabetes worldwide were in China, where 11·6% of adults had diabetes and 50·1% had prediabetes. Many were undiagnosed, untreated, or uncontrolled. This epidemic is the result of rapid societal transition that has led to an obesogenic environment against a backdrop of traditional lifestyle and periods of famine, which together puts Chinese people at high risk of diabetes and multiple morbidities. Societal determinants including social disparity and psychosocial stress interact with factors such as low-grade infection, environmental pollution, care fragmentation, health illiteracy, suboptimal self-care, and insufficient community support to give rise to diverse subphenotypes and consequences, notably renal dysfunction and cancer. In the China National Plan for Non-Communicable Disease Prevention and Treatment (2012-15), the Chinese Government proposed use of public measures, multisectoral collaborations, and social mobilisation to create a health-enabling environment and to reform the health-care system. While awaiting results from these long-term strategies, we advocate the use of a targeted and proactive approach to identify people at high risk of diabetes for prevention, and of private-public-community partnerships that make integrated care more accessible and sustainable, focusing on registry, empowerment, and community support. The multifaceted nature of the societal and personal challenge of diabetes requires a multidimensional solution for prevention in order to reduce the growing disease burden.
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Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China; Li Ka Shing Institute of Health Sciences, Hong Kong Institute of Diabetes and Obesity, and International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China.
| | - Yuying Zhang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China
| | - Guang Ning
- Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai Clinical Center for Endocrine and Metabolic Disease, National Clinical Research Center for Metabolic Diseases, E-Institute of Shanghai Universities, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Chan JCN, Ozaki R, Luk A, Kong APS, Ma RCW, Chow FCC, Wong P, Wong R, Chung H, Chiu C, Wolthers T, Tong PCY, Ko GTC, So WY, Lyubomirsky G. Delivery of integrated diabetes care using logistics and information technology--the Joint Asia Diabetes Evaluation (JADE) program. Diabetes Res Clin Pract 2014; 106 Suppl 2:S295-304. [PMID: 25550057 DOI: 10.1016/s0168-8227(14)70733-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Diabetes is a global epidemic, and many affected individuals are undiagnosed, untreated, or uncontrolled. The silent and multi-system nature of diabetes and its complications, with complex care protocols, are often associated with omission of periodic assessments, clinical inertia, poor treatment compliance, and care fragmentation. These barriers at the system, patient, and care-provider levels have resulted in poor control of risk factors and under-usage of potentially life-saving medications such as statins and renin-angiotensin system inhibitors. However, in the clinical trial setting, use of nurses and protocol with frequent contact and regular monitoring have resulted in marked differences in event rates compared to epidemiological data collected in the real-world setting. The phenotypic heterogeneity and cognitive-psychological-behavioral needs of people with diabetes call for regular risk stratification to personalize care. Quality improvement initiatives targeted at patient education, task delegation, case management, and self-care promotion had the largest effect size in improving cardio-metabolic risk factors. The Joint Asia Diabetes Evaluation (JADE) program is an innovative care prototype that advocates a change in clinic setting and workflow, coordinated by a doctor-nurse team and augmented by a web-based portal, which incorporates care protocols and a validated risk engine to provide decision support and regular feedback. By using logistics and information technology, supported by a network of health-care professionals to provide integrated, holistic, and evidence-based care, the JADE Program aims to establish a high-quality regional diabetes database to reflect the status of diabetes care in real-world practice, confirm efficacy data, and identify unmet needs. Through collaborative efforts, we shall evaluate the feasibility, acceptability, and cost-effectiveness of this "high tech, soft touch" model to make diabetes and chronic disease care more accessible, affordable, and sustainable.
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Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, China; Hong Kong Institute of Diabetes and Obesity, China; Li Ka Shing Institute of Health Sciences, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China; Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, China.
| | - Risa Ozaki
- Department of Medicine and Therapeutics, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Andrea Luk
- Department of Medicine and Therapeutics, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, China; Hong Kong Institute of Diabetes and Obesity, China; Li Ka Shing Institute of Health Sciences, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, China; Hong Kong Institute of Diabetes and Obesity, China; Li Ka Shing Institute of Health Sciences, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Francis C C Chow
- Department of Medicine and Therapeutics, China; Hong Kong Institute of Diabetes and Obesity, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China; Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, China
| | - Patrick Wong
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, China
| | - Rebecca Wong
- Department of Medicine and Therapeutics, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Harriet Chung
- Hong Kong Institute of Diabetes and Obesity, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Cherry Chiu
- Department of Medicine and Therapeutics, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Troels Wolthers
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, China
| | - Peter C Y Tong
- Department of Medicine and Therapeutics, China; Qualigenics Diabetes Centre, Central, Hong Kong SAR, China
| | - Gary T C Ko
- Department of Medicine and Therapeutics, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, China; International Diabetes Federation Centre of Education, The Chinese University of Hong Kong, Prince of Wales Hospital, China
| | - Greg Lyubomirsky
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, China
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Chan JCN, Lau ESH, Luk AOY, Cheung KKT, Kong APS, Yu LWL, Choi KC, Chow FCC, Ozaki R, Brown N, Yang X, Bennett PH, Ma RCW, So WY. Premature mortality and comorbidities in young-onset diabetes: a 7-year prospective analysis. Am J Med 2014; 127:616-24. [PMID: 24680795 DOI: 10.1016/j.amjmed.2014.03.018] [Citation(s) in RCA: 98] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Revised: 03/19/2014] [Accepted: 03/19/2014] [Indexed: 12/13/2022]
Abstract
BACKGROUND There is an increasing prevalence of young-onset diabetes, especially in developing areas. We compared the clinical outcomes and predictors for cardiovascular-renal events between Chinese patients with type 2 diabetes with young- or late-onset of disease diagnosed before or after the age of 40 years, respectively. METHODS The Hong Kong Diabetes Registry was established in 1995 as an ongoing quality improvement initiative with consecutive enrollment of diabetic patients from ambulatory settings for documentation of risk factors, microvascular and macrovascular complications, and clinical outcomes using a structured protocol. RESULTS In 9509 Chinese patients with type 2 diabetes with a median (interquartile range) follow-up period of 7.5 (3.9-10.8) years, 21.3% (n = 2066) had young-onset diabetes. Despite 20 years difference in age, patients with young-onset diabetes (mean age, 41.3 years) had a similar or worse risk profile than those with late-onset disease (mean age, 61.9 years). Compared with the patients with late-onset diabetes, those with young-onset diabetes had lower rates of cardiovascular disease and chronic kidney disease for the same disease duration but a higher cumulative incidence of clinical events at any given age. With the use of stepwise Cox proportional hazard analysis, patients with young-onset diabetes had higher risks for cardiovascular and renal events when adjusted by age, but no difference in risks than in the patients with late-onset diabetes when further adjusted by disease duration. CONCLUSIONS Patients with young-onset diabetes had a similar or worse metabolic risk profile compared with those with late-onset disease. This group had higher risks for cardiovascular-renal complications at any given age, driven by longer disease duration.
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Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong; Hong Kong Institute of Diabetes and Obesity, Hong Kong; Li Ka Shing Institute of Health Sciences, Hong Kong
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong.
| | - Kitty K T Cheung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong; Hong Kong Institute of Diabetes and Obesity, Hong Kong
| | | | - Kai-Chow Choi
- Nethersole School of Nursing, Public Health College, Tianjin Medical University, Tianjin, China
| | - Francis C C Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong; Hong Kong Institute of Diabetes and Obesity, Hong Kong
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong; Hong Kong Institute of Diabetes and Obesity, Hong Kong
| | - Nicola Brown
- Asia Diabetes Foundation, Public Health College, Tianjin Medical University, Tianjin, China
| | - Xilin Yang
- Department of Epidemiology, Public Health College, Tianjin Medical University, Tianjin, China
| | | | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong; Hong Kong Institute of Diabetes and Obesity, Hong Kong
| | - Wing-Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong; Hong Kong Institute of Diabetes and Obesity, Hong Kong
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Kong APS, Yang X, So WY, Luk A, Ma RCW, Ozaki R, Cheung KKT, Lee HM, Yu L, Xu G, Chow CC, Chan JCN. Additive effects of blood glucose lowering drugs, statins and renin-angiotensin system blockers on all-site cancer risk in patients with type 2 diabetes. BMC Med 2014; 12:76. [PMID: 24886453 PMCID: PMC4046510 DOI: 10.1186/1741-7015-12-76] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2014] [Accepted: 03/25/2014] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Hyperglycemia is associated with increased risk of all-site cancer that may be mediated through activation of the renin-angiotensin-system (RAS) and 3-hydroxy-3-methyl-glutaryl-coenzyme-A-reductase (HMGCR) pathways. We examined the joint associations of optimal glycemic control (HbA1c <7%), RAS inhibitors and HMGCR inhibitors on cancer incidence in patients with type 2 diabetes. METHODS Patients with type 2 diabetes, with or without a history of cancer or prior exposure to RAS or HMGCR inhibitors at baseline were observed between 1996 and 2005. All patients underwent a comprehensive assessment at baseline and were followed until the censored date at 2005 or their death. RESULTS After a median follow-up period of 4.91 years (interquartile range, 2.81 to 6.98), 271 out of 6,103 patients developed all-site cancer. At baseline, patients with incident cancers were older, had longer disease duration of diabetes, higher alcohol and tobacco use, and higher systolic blood pressure and albuminuria, but lower triglyceride levels and estimated glomerular filtration rate (P <0.05). Patients who developed cancers during follow-up were less likely to have started using statins (22.5% versus 38.6%, P <0.001), fibrates (5.9% versus 10.2%, P = 0.02), metformin (63.8% versus 74.5%, P <0.001) or thiazolidinedione (0.7% versus 6.8%, P <0.001) than those who remained cancer-free. After adjusting for co-variables, new treatment with metformin (hazard ratio: 0.39; 95% confidence interval: 0.25, 0.61; P <0.001), thiazolidinedione (0.18; 0.04, 0.72; P = 0.015), sulphonylurea (0.44; 0.27, 0.73; P = 0.014), insulin (0.58; 0.38, 0.89; P = 0.01), statins (0.47; 0.31, 0.70; P <0.001) and RAS inhibitors (0.55; 0.39, 0.78; P <0.001) were associated with reduced cancer risk. Patients with all three risk factors of HbA1c ≥7%, non-use of RAS inhibitors and non-use of statins had four-fold adjusted higher risk of cancer than those without any risk factors (incidence per 1,000-person-years for no risk factors: 3.40 (0.07, 6.72); one risk factor: 6.34 (4.19, 8.50); two risk factors: 8.40 (6.60, 10.20); three risk factors: 13.08 (9.82, 16.34); P <0.001). CONCLUSIONS Hyperglycemia may promote cancer growth that can be attenuated by optimal glycemic control and inhibition of the RAS and HMGCR pathways.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, SAR, China.
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Ma RCW, Lee HM, Lam VKL, Tam CHT, Ho JSK, Zhao HL, Guan J, Kong APS, Lau E, Zhang G, Luk A, Wang Y, Tsui SKW, Chan TF, Hu C, Jia WP, Park KS, Lee HK, Furuta H, Nanjo K, Tai ES, Ng DPK, Tang NLS, Woo J, Leung PC, Xue H, Wong J, Leung PS, Lau TCK, Tong PCY, Xu G, Ng MCY, So WY, Chan JCN. Familial young-onset diabetes, pre-diabetes and cardiovascular disease are associated with genetic variants of DACH1 in Chinese. PLoS One 2014; 9:e84770. [PMID: 24465431 PMCID: PMC3896349 DOI: 10.1371/journal.pone.0084770] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Accepted: 11/19/2013] [Indexed: 01/02/2023] Open
Abstract
In Asia, young-onset type 2 diabetes (YOD) is characterized by obesity and increased risk for cardiovascular disease (CVD). In a genome-wide association study (GWAS) of 99 Chinese obese subjects with familial YOD diagnosed before 40-year-old and 101 controls, the T allele of rs1408888 in intron 1 of DACH1(Dachshund homolog 1) was associated with an odds ratio (OR) of 2.49(95% confidence intervals:1.57-3.96, P = 8.4 × 10(-5)). Amongst these subjects, we found reduced expression of DACH1 in peripheral blood mononuclear cells (PBMC) from 63 cases compared to 65 controls (P = 0.02). In a random cohort of 1468 cases and 1485 controls, amongst top 19 SNPs from GWAS, rs1408888 was associated with type 2 diabetes with a global P value of 0.0176 and confirmation in a multiethnic Asian case-control cohort (7370/7802) with an OR of 1.07(1.02-1.12, P(meta) = 0.012). In 599 Chinese non-diabetic subjects, rs1408888 was linearly associated with systolic blood pressure and insulin resistance. In a case-control cohort (n = 953/953), rs1408888 was associated with an OR of 1.54(1.07-2.22, P = 0.019) for CVD in type 2 diabetes. In an autopsy series of 173 non-diabetic cases, TT genotype of rs1408888 was associated with an OR of 3.31(1.19-9.19, P = 0.0214) and 3.27(1.25-11.07, P = 0.0184) for coronary heart disease (CHD) and coronary arteriosclerosis. Bioinformatics analysis revealed that rs1408888 lies within regulatory elements of DACH1 implicated in islet development and insulin secretion. The T allele of rs1408888 of DACH1 was associated with YOD, prediabetes and CVD in Chinese.
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Affiliation(s)
- Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Heung Man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Vincent Kwok Lim Lam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Claudia Ha Ting Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Janice Siu Ka Ho
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Hai-Lu Zhao
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Jing Guan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Alice Pik Shan Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Eric Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Guozhi Zhang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Andrea Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Ying Wang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Stephen Kwok Wing Tsui
- School of Biomedical Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Ting Fung Chan
- School of Life Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Cheng Hu
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, People’s Republic of China
| | - Wei Ping Jia
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, People’s Republic of China
| | - Kyong Soo Park
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and Department of Internal Medicine, College of Medicine, Seoul National University, Chongno-gu, Seoul, Korea
| | - Hong Kyu Lee
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and Department of Internal Medicine, College of Medicine, Seoul National University, Chongno-gu, Seoul, Korea
| | - Hiroto Furuta
- First Department of Medicine, Wakayama Medical University, Wakayama, Japan
| | - Kishio Nanjo
- First Department of Medicine, Wakayama Medical University, Wakayama, Japan
| | - E. Shyong Tai
- Department of Epidemiology and Public Health, National University of Singapore, Singapore, Singapore
| | - Daniel Peng-Keat Ng
- Department of Epidemiology and Public Health, National University of Singapore, Singapore, Singapore
| | - Nelson Leung Sang Tang
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Department of Chemical Pathology, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Jean Woo
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Ping Chung Leung
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Hong Xue
- Department of Biochemistry, Hong Kong University of Science and Technology, Hong Kong SAR, People’s Republic of China
| | - Jeffrey Wong
- Department of Biochemistry, Hong Kong University of Science and Technology, Hong Kong SAR, People’s Republic of China
| | - Po Sing Leung
- School of Biomedical Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Terrence C. K. Lau
- School of Biomedical Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Peter Chun Yip Tong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Gang Xu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Maggie Chor Yin Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Juliana Chung Ngor Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- * E-mail:
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Use of net reclassification improvement (NRI) method confirms the utility of combined genetic risk score to predict type 2 diabetes. PLoS One 2013; 8:e83093. [PMID: 24376643 PMCID: PMC3869744 DOI: 10.1371/journal.pone.0083093] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Accepted: 11/03/2013] [Indexed: 11/28/2022] Open
Abstract
Background Recent genome-wide association studies (GWAS) identified more than 70 novel loci for type 2 diabetes (T2D), some of which have been widely replicated in Asian populations. In this study, we investigated their individual and combined effects on T2D in a Chinese population. Methodology We selected 14 single nucleotide polymorphisms (SNPs) in T2D genes relating to beta-cell function validated in Asian populations and genotyped them in 5882 Chinese T2D patients and 2569 healthy controls. A combined genetic score (CGS) was calculated by summing up the number of risk alleles or weighted by the effect size for each SNP under an additive genetic model. We tested for associations by either logistic or linear regression analysis for T2D and quantitative traits, respectively. The contribution of the CGS for predicting T2D risk was evaluated by receiver operating characteristic (ROC) analysis and net reclassification improvement (NRI). Results We observed consistent and significant associations of IGF2BP2, WFS1, CDKAL1, SLC30A8, CDKN2A/B, HHEX, TCF7L2 and KCNQ1 (8.5×10−18<P<8.5×10−3), as well as nominal associations of NOTCH2, JAZF1, KCNJ11 and HNF1B (0.05<P<0.1) with T2D risk, which yielded odds ratios ranging from 1.07 to 2.09. The 8 significant SNPs exhibited joint effect on increasing T2D risk, fasting plasma glucose and use of insulin therapy as well as reducing HOMA-β, BMI, waist circumference and younger age of diagnosis of T2D. The addition of CGS marginally increased AUC (2%) but significantly improved the predictive ability on T2D risk by 11.2% and 11.3% for unweighted and weighted CGS, respectively using the NRI approach (P<0.001). Conclusion In a Chinese population, the use of a CGS of 8 SNPs modestly but significantly improved its discriminative ability to predict T2D above and beyond that attributed to clinical risk factors (sex, age and BMI).
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Measuring depressive symptoms using the Patient Health Questionnaire-9 in Hong Kong Chinese subjects with type 2 diabetes. J Affect Disord 2013; 151:660-666. [PMID: 23938133 DOI: 10.1016/j.jad.2013.07.014] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2013] [Revised: 07/23/2013] [Accepted: 07/23/2013] [Indexed: 11/21/2022]
Abstract
BACKGROUND Depression is common in type 2 diabetes although the prevalence in Chinese patients remains unclear. We validated the Patient Health Questionnaire(PHQ-9), a popular depression screening tool, in Chinese with type 2 diabetes, and documented the prevalence, demographic,and clinical characteristics associated with depression. METHODS A consecutive cohort of 586 Hong Kong Chinese outpatients completed the PHQ-9 during comprehensive diabetes complication assessment. Within 2-4 weeks, 40 patients were retested via telephone survey. Ninety-nine randomly selected patients were interviewed by psychiatrists using the Mini International Neuropsychiatric Interview as a golden standard. Receiver operating characteristic curve was used to assess performance of the PHQ-9. RESULTS The internal consistency of the PHQ-9 was 0.86 and test-retest reliability was 0.70. The 3 somatic items explained 53.6% of the PHQ-9 score. The optimal cutoff value was 7 with 82.6% sensitivity and 73.7% specificity, giving a depression prevalence of 18.3% (n=107). Of these, 18.7% had been previously diagnosed with depression. Depression was more prevalent in women than men. After controlling for confounders, patients with depression had higher HbA1c (7.80 ± 1.86% versus 7.43 ± 1.29%, [61.7 ± 20.4 versus 57.8 ± 14.1 mmol/mol], P<0.05), reduced likelihood of achieving HbA1c target of <7.0% (33.6% versus 41.8%, P<0.05), and were more likely to have self-reported hypoglycemia in the previous 3 months (18.7% versus 6.7%, P<0.01). LIMITATION A small sample was used in the criterion validation and the cross-sectional design precludes causal inference. CONCLUSIONS PHQ-9 is a validated tool for screening for depression, which is common and frequently undiagnosed in Chinese type 2 diabetic patients and is associated with suboptimal glycemic control, hypoglycemia, and somatization.
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Abstract
Fetal programming associated with in utero exposure to maternal stress is thought to alter gene expression, resulting in phenotypes that promote survival in a pathogen-rich and nutrient-poor environment but substantially increase the risk of cardiovascular, metabolic and renal disorders (such as diabetes mellitus) in adults with obesity. These (epi)genetic phenomena are modified by environmental and socioeconomic factors, resulting in multiple subphenotypes and clinical consequences. In individuals from areas undergoing rapid economic development, which is associated with a transition from communicable to noncommunicable diseases, an efficient innate immune response can exaggerate obesity-associated inflammation. By contrast, in individuals with a genetic predisposition to autoimmune or monogenic diabetes mellitus, obesity can lead to atypical presentation of diabetes mellitus, termed 'double diabetes mellitus'. The increasingly young age at diagnosis of diabetes mellitus in developing countries results in prolonged exposure to glucolipotoxicity, low-grade inflammation and increased oxidative stress, which put enormous strain on pancreatic β cells and renal function. These conditions create a metabolic milieu conducive to cancer growth. This Review discusses how rapid changes in technology and human behaviour have brought on the global epidemic of metabolic diseases, and suggests that solutions will be based on using system change, technology and behavioural strategies to combat this societal-turned-medical problem.
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Affiliation(s)
- Alice P S Kong
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT Hong Kong Special Administrative Region, China
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Lam VKL, Ma RCW, Lee HM, Hu C, Park KS, Furuta H, Wang Y, Tam CHT, Sim X, Ng DPK, Liu J, Wong TY, Tai ES, Morris AP, Tang NLS, Woo J, Leung PC, Kong APS, Ozaki R, Jia WP, Lee HK, Nanjo K, Xu G, Ng MCY, So WY, Chan JCN. Genetic associations of type 2 diabetes with islet amyloid polypeptide processing and degrading pathways in asian populations. PLoS One 2013; 8:e62378. [PMID: 23776430 PMCID: PMC3679113 DOI: 10.1371/journal.pone.0062378] [Citation(s) in RCA: 7] [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: 07/14/2012] [Accepted: 03/21/2013] [Indexed: 01/09/2023] Open
Abstract
Type 2 diabetes (T2D) is a complex disease characterized by beta cell dysfunctions. Islet amyloid polypeptide (IAPP) is highly conserved and co-secreted with insulin with over 40% of autopsy cases of T2D showing islet amyloid formation due to IAPP aggregation. Dysregulation in IAPP processing, stabilization and degradation can cause excessive oligomerization with beta cell toxicity. Previous studies examining genetic associations of pathways implicated in IAPP metabolism have yielded conflicting results due to small sample size, insufficient interrogation of gene structure and gene-gene interactions. In this multi-staged study, we screened 89 tag single nucleotide polymorphisms (SNPs) in 6 candidate genes implicated in IAPP metabolism and tested for independent and joint associations with T2D and beta cell dysfunctions. Positive signals in the stage-1 were confirmed by de novo and in silico analysis in a multi-centre unrelated case-control cohort. We examined the association of significant SNPs with quantitative traits in a subset of controls and performed bioinformatics and relevant functional analyses. Amongst the tag SNPs, rs1583645 in carboxypeptidase E (CPE) and rs6583813 in insulin degrading enzyme (IDE) were associated with 1.09 to 1.28 fold increased risk of T2D (PMeta = 9.4×10−3 and 0.02 respectively) in a meta-analysis of East Asians. Using genetic risk scores (GRS) with each risk variant scoring 1, subjects with GRS≥3 (8.2% of the cohort) had 56% higher risk of T2D than those with GRS = 0 (P = 0.01). In a subcohort of control subjects, plasma IAPP increased and beta cell function index declined with GRS (P = 0.008 and 0.03 respectively). Bioinformatics and functional analyses of CPE rs1583645 predicted regulatory elements for chromatin modification and transcription factors, suggesting differential DNA-protein interactions and gene expression. Taken together, these results support the importance of dysregulation of IAPP metabolism in T2D in East Asians.
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Affiliation(s)
- Vincent Kwok Lim Lam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People's Republic of China
- Li Ka Shing Institute of Health, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Heung Man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Cheng Hu
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
| | - Kyong Soo Park
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and Department of Internal Medicine, College of Medicine, Seoul National University, Chongno-gu, Seoul, Korea
| | - Hiroto Furuta
- First Department of Medicine, Wakayama Medical University, Wakayama, Japan
| | - Ying Wang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Claudia Ha Ting Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Xueling Sim
- Centre for Molecular Epidemiology, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Daniel Peng-Keat Ng
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Jianjun Liu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - E. Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Andrew P. Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Nelson Leung Sang Tang
- Department of Chemical Pathology, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Jean Woo
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Ping Chung Leung
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Alice Pik Shan Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Wei Ping Jia
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
| | - Hong Kyu Lee
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and Department of Internal Medicine, College of Medicine, Seoul National University, Chongno-gu, Seoul, Korea
| | - Kishio Nanjo
- First Department of Medicine, Wakayama Medical University, Wakayama, Japan
| | - Gang Xu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People's Republic of China
- Li Ka Shing Institute of Health, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Maggie Chor Yin Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Juliana Chung Ngor Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People's Republic of China
- Li Ka Shing Institute of Health, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
- * E-mail:
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Ma RCW, Chan JCN. Type 2 diabetes in East Asians: similarities and differences with populations in Europe and the United States. Ann N Y Acad Sci 2013; 1281:64-91. [PMID: 23551121 PMCID: PMC3708105 DOI: 10.1111/nyas.12098] [Citation(s) in RCA: 565] [Impact Index Per Article: 51.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
There is an epidemic of diabetes in Asia. Type 2 diabetes develops in East Asian patients at a lower mean body mass index (BMI) compared with those of European descent. At any given BMI, East Asians have a greater amount of body fat and a tendency to visceral adiposity. In Asian patients, diabetes develops at a younger age and is characterized by early β cell dysfunction in the setting of insulin resistance, with many requiring early insulin treatment. The increasing proportion of young-onset and childhood type 2 diabetes is posing a particular threat, with these patients being at increased risk of developing diabetic complications. East Asian patients with type 2 diabetes have a higher risk of developing renal complications than Europeans and, with regard to cardiovascular complications, a predisposition for developing strokes. In addition to cardiovascular-renal disease, cancer is emerging as the other main cause of mortality. While more research is needed to explain these interethnic differences, urgent and concerted actions are needed to raise awareness, facilitate early diagnosis, and encourage preventive strategies to combat these growing disease burdens.
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Affiliation(s)
- Ronald C W Ma
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, The Prince of Wales Hospital, Hong Kong, China.
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Liu KH, Chu WCW, Kong APS, Ko GTC, Ma RCW, Chan JWS, So WY, Luk AOY, Cheung KKT, Ozaki R, Ahuja AT, Chan JCN. Intrarenal arterial resistance is associated with microvascular complications in Chinese type 2 diabetic patients. Nephrol Dial Transplant 2012; 28:651-8. [PMID: 23223219 DOI: 10.1093/ndt/gfs471] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Increased renal arterial resistance is associated with various types of chronic renal parenchymal diseases. A resistance index (RI) > 0.8 predicts deterioration in renal function in diabetic subjects. However, the association between renal RI and other diabetic complications has not been investigated. In this study, we examined the association between intrarenal arterial RI and diabetic complications in Chinese type 2 diabetic subjects. METHODS Three hundred and eighty-seven Chinese type 2 diabetic patients were recruited from a structured assessment programme to evaluate their risk factors and complications as a part of the quality improvement programme at the Prince of Wales Hospital. All subjects underwent ultrasound examinations for the assessment of intrarenal arterial RI of both kidneys. Clinical and biochemical parameters, including diabetes-related microvascular complications (nephropathy, retinopathy and sensory neuropathy) and macrovascular diseases, were examined. RESULTS The mean RI of patients with any microvascular complications (0.70 ± 0.09 versus 0.65 ± 0.06) such as nephropathy (0.71 ± 0.09 versus 0.66 ± 0.06), retinopathy (0.71 ± 0.08 versus 0.67 ± 0.08) and sensory neuropathy (0.75 ± 0.07 versus 0.68 ± 0.08) and with any macrovascular complications (0.71 ± 0.09 versus 0.68 ± 0.08) was higher than those without (P < 0.05). On multivariate analysis, after controlling for confounding variables, an RI ≥0.75 was associated with microvascular complications, nephropathy, retinopathy and sensory neuropathy, with odds ratio of 4.02 [95% confidence interval (CI) 1.72-9.4], 4.99 (2.61-9.56), 2.78 (1.52-5.09) and 5.74 (1.8-18.3), respectively. The association of RI with macrovascular complications was not significant in multivariate analysis. CONCLUSION Increased intrarenal arterial resistance was independently associated with an increased risk of microvascular complications including diabetic nephropathy, diabetic retinopathy and diabetic sensory neuropathy in Chinese type 2 diabetic patients.
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Affiliation(s)
- Kin Hung Liu
- 1Department of Imaging and Interventional Radiology, The ChineseUniversity of Hong Kong, Hong Kong, China
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