J. Weng
Sun Yat-sen University
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Featured researches published by J. Weng.
Experimental and Clinical Endocrinology & Diabetes | 2013
Zhaojun Yang; Xiaoyan Xing; Jianzhong Xiao; Juming Lu; J. Weng; Weiping Jia; Linong Ji; Zhongyan Shan; Jing Liu; Haoming Tian; Qiuhe Ji; Dalong Zhu; Jiapu Ge; Lixiang Lin; Li Chen; Xiaohui Guo; Zhigang Zhao; Qinglei Li; Zhiguang Zhou; Guangliang Shan; Wenying Yang
Cardiovascular disease (CVD) is one of the most common chronic diseases in China. This aim of this study is to determine the prevalence of CVDs and risk factors in Chinese impaired glucose regulation subjects.We used a multistage, stratified sampling method to select subjects from the general Chinese population aged 20 years and older. Subjects underwent an oral glucose tolerance test to identify normal glucose tolerance (NGT) and impaired glucose regulation including isolated impaired fasting glucose (i-IFG), impaired glucose tolerance (i-IGT), and combined IFG/IGT and diabetic mellitus (DM). A logistic regression analysis was performed to examine the association between glucose abnormalities and CVD events.We identified that 34 293 subjects had NGT, 1 469 i-IFG, 4 571 i-IGT, 957 IFG/IGT and 4 949 DM. The age-sex standardized prevalence rate of cardiovascular disease was 1.06% (95% CI 0.87-1.28), 1.79% (95% CI 1.37-2.33) and 3.83% (95% CI 2.79-5.24) in NGT, impaired glucose regulation and DM, respectively. Among impaired glucose subjects, prevalence of defined CVD risk factors (smoking, overweight, obesity, hypertension and dyslipidemia) was 29.52% (95% CI: 27.8-31.21), 36.25% (95% CI: 34.29-38.26), 10.05% (95% CI: 8.86-11.37), 36.43% (95% CI: 34.53-38.36) and 69.96% (95% CI: 67.87-71.98), respectively. Compared to 1 risk factor, the odds ratios (ORs) of CVDs with 2, 3 or 4 risk factors were 1.94 (95% CI: 0.74-5.09), 2.76 (95% CI: 1.06-7.21) and 5.84 (95% CI: 1.68-20.26), respectively. Additionally, compared to i-IFGs, ORs of CVDs with i-IGT and IFG/IGT were 2.88 (95%CI 1.36-6.01) and 2.12 (95% CI 0.83-5.44), respectively.The prevalence of cardiovascular risk factors was high in the Chinese impaired glucose regulation population. The postprandial hyperglycemia is more associated with CVD than isolated fasting hyperglycemia.
Biomedical and Environmental Sciences | 2014
Hai Cheng Zhou; Ya Xin Lai; Zhong Yan Shan; Wei Ping Jia; Wen Ying Yang; Ju Ming Lu; J. Weng; Li Nong Ji; Jie Liu; Hao Ming Tian; Qiu He Ji; Da Long Zhu; Li Chen; Xiao Hui Guo; Zhi Gang Zhao; Qiang Li; Zhiguang Zhou; Jia Pu Ge; Guang Liang Shan
OBJECTIVE To study the effectiveness of waist circumference cut-off values in predicting the prevalence of metabolic syndrome (MetS) and risk factors in adults in China. METHODS A cross-sectional survey was condcuted in 14 provinces (autonomous region, municipality) in China. A total of 47,325 adults aged⋝20 years were selected by multistage stratified sampling, and questionnaire survey and physical and clinical examination were conducted among them. MetS was defined according to the International Diabetes Federation (IDF) criteria and modified IDF criteria. RESULTS The age-standardized prevalence of MetS was 24.2% (22.1% in men and 25.8% in women) and 19.5% (22.1% in men and 18.0% in women) according to the IDF criteria and modified IDF criteria respectively. The age-standardized prevalence of pre-MetS was 8.1% (8.6% in men and 7.8% in women) according to the modified IDF criteria. The prevalence of MetS was higher in urban residents than rural residents and in northern China residents than in southern China residents. The prevalence of central obesity was about 30% in both men and women according to the ethnicity-specific cut-off values of waist circumference for central obesity (90 cm for men and 85 cm for women). Multivariate regression analysis revealed no significant difference in risk factors between the two MetS definitions. CONCLUSION Using both the modified IDF criteria and ethnicity-specific cut-off values of waist circumference can provide more useful information about the prevalence of MetS in China. Conclusion Using both the modified IDF criteria and ethnicity-specific cut-off values of waist circumference can provide more useful information about the prevalence of MetS in China.
Diabetic Medicine | 2016
A. Luk; Xinzhong Li; Yuying Zhang; Xiaohui Guo; Weiping Jia; Wenhui Li; J. Weng; Wenying Yang; Wing-Bun Chan; Risa Ozaki; Chiu-Chi Tsang; Monojitketan Mukhopadhyay; A. K. Ojha; Eun Gyoung Hong; Kun-Ho Yoon; Leorino Sobrepena; R. M. Toledo; M. Duran; Wayne Huey-Herng Sheu; T. Q. Do; Thy Khue Nguyen; Ronald C.W. Ma; A. P. S. Kong; Chun-Chung Chow; P. C. Y. Tong; W.Y. So; Juliana C.N. Chan
Diabetic kidney disease independently predicts cardiovascular disease and premature death. We examined the burden of chronic kidney disease (CKD, defined as an estimated GFR < 60 ml/min/1.73 m2) and quality of care in a cross‐sectional survey of adults (age ≥ 18 years) with Type 2 diabetes across Asia.
Diabetic Medicine | 2012
Changyu Pan; Wenying Yang; Weiping Jia; J. Weng; G. Liu; B. Luo; Xia Li; Z. Fu; Hui Tian
Diabet. Med. 29, 515–521 (2012)
Diabetic Medicine | 2006
Dongshan Zhang; Zhiguang Zhou; Li Lr; J. Weng; Gan Huang; P. Jing; Zhang C; Jian Peng; Xiu Ll
Aims To explore the contribution of islet autoimmunity and genetic mutations in Chinese patients initially thought to have Type 1B diabetes.
Diabetic Medicine | 2017
G. E. Tutino; Wenying Yang; X. Li; W. H. Li; Yuying Zhang; Xiaohui Guo; A. Luk; Roseanne Yeung; Junmei Yin; Risa Ozaki; W.Y. So; Ronald C.W. Ma; Linong Ji; A. P. S. Kong; J. Weng; G. T. C. Ko; Weiping Jia; Juliana C.N. Chan
To test the hypothesis that delivery of integrated care augmented by a web‐based disease management programme and nurse coordinator would improve treatment target attainment and health‐related behaviour.
Diabetic Medicine | 2017
Hua Liang; Xu W; L. Zhou; Wenying Yang; J. Weng
To elucidate the effects of rs2289669, an intron variant of the SLC47A1 gene, on glucose response to metformin in Chinese people with newly diagnosed Type 2 diabetes.
Experimental and Clinical Endocrinology & Diabetes | 2015
H. Yang; W. Xu; Z. Zhou; Jianjun Liu; X. Li; L. Chen; J. Weng; Z. Yu
Diabetes Technology & Therapeutics | 2015
Lihua Zhang; Linong Ji; Lixin Guo; Juming Lu; Haoming Tian; Dalong Zhu; Xiaoping Xing; J. Weng; Weiping Jia
Chinese journal of internal medicine | 2010
Li Y; Zeng Ly; Lixin Shi; Dongshan Zhu; Zhiguang Zhou; Yan L; Haoming Tian; Luo Zj; Yang L; Jing Liu; J. Weng