Prevalence of Metabolic Syndrome and Its Determinants in Newly-Diagnosed Adult-Onset Diabetes in China: A Multi-Center, Cross-Sectional Survey

中国新诊断成人起病糖尿病患者代谢综合征及其决定因素的患病率:一项多中心横断面调查

阅读:1

Abstract

Aim: The study aimed to investigate the prevalence of metabolic syndrome (MetS) and its determinants in newly-diagnosed adult-onset diabetes in China. Methods: From April 2015 to October 2017, 15,492 consecutive patients with diabetes diagnosed within 1 year and aged ≥30 years were recruited from 46 tertiary care hospitals in 24 cities across China. Glutamic acid decarboxylase autoantibody was assayed centrally and clinical data were collected locally. Classic type 1 diabetes mellitus (T1DM), latent autoimmune diabetes in adults (LADA) and type 2 diabetes mellitus (T2DM) were defined using the criteria of American Diabetes Association, Immunology of Diabetes Society and World Health Organization. MetS was defined using Chinese Diabetes Society's criteria. Logistic regression analysis was used to obtain odds ratios (OR) of determinants of MetS. Results: The overall prevalence of MetS was 66.5%, with the highest prevalence in T2DM (68.1%), followed by those in LADA (44.3%) and T1DM (34.2%) (P < 0.05 for all comparisons). After adjustment for traditional risk factors, T2DM had a 2.8-fold [95% confidence interval (CI): 2.36-3.37] MetS risk compared with LADA, whereas T1DM had significantly lower OR than LADA (OR: 0.68, 95% CI: 0.50-0.92). After further adjustment for insulin resistance, the OR of T2DM vs. LADA was slightly reduced but the OR of T1DM vs. LADA was greatly attenuated to non-significance (OR: 0.96, 95% CI: 0.70-1.33). In addition to types of diabetes, age, gender, geographical residence, education attainment, alcohol consumption and HOMA2-IR were independent determinants of MetS. Conclusions: MetS was highly prevalent, not only in T2DM but also in T1DM and LADA in Chinese newly diagnosed patients; higher risk of MetS in LADA than in T1DM was partially attributable to higher insulin resistance in LADA.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。