Zheng Ke, Gao Wenjing, Lyu Jun, Yu Canqing, Wang Shengfeng, Huang Tao, Sun Dianjianyi, Liao Chunxiao, Pang Yuanjie, Pang Zengchang, Yu Min, Wang Hua, Wu Xianping, Dong Zhong, Wu Fan, Jiang Guohong, Wang Xiaojie, Liu Yu, Deng Jian, Lu Lin, Cao Weihua, Li Liming
Abstract
ObjectiveTo describe the distribution characteristics of type 2 diabetes in twins in Chinese National Twin Registry (CNTR), provide clues and evidence for revealing the influence of genetic and environmental factors for type 2 diabetes.
MethodsOf all twins registered in the CNTR during 2010-2018, a total 18 855 twin pairs aged ≥30 years with complete registration information were included in the analysis. The random effect model was used to describe the population and area distribution characteristics and concordance of type 2 diabetes in twin pairs.
ResultsThe mean age of the subjects was (42.8±10.2) years, the study subjects included 10 339 monozygotic (MZ) twin pairs and 8 516 dizygotic (DZ) twin pairs. The self-reported prevalence rate of type 2 diabetes was 2.2% in total population and there was no sighificant difference between MZ and DZ. Intra-twin pairs analysis showed that the concordance rate of type 2 diabetes was 38.2% in MZ twin pairs, and 16.0% in DZ twin pairs, the difference was statistically significant (P<0.001). The concordance rate of type 2 diabetes in MZ twin parts was higher than that in DZ twin pairs in both men and women, in different age groups and in different areas (P<0.05). Further stratified analysis showed that in northern China, only MZ twin pairs less than 60 years old were found to have a higher concordance rate of type 2 diabetes compared with DZ twin pairs (P<0.05). In southern China, the co-prevalence rate in male MZ twin pairs aged ≥60 years was still higher than that in DZ twin pairs (P<0.05).
ConclusionThe twin pairs in this study had a lower self-reported prevalence of type 2 diabetes than the general population. The study results suggested that genetic factors play a role in type 2 diabetes prevalence in both men and women, in different age groups and in different areas, however, the effect might vary.
Key words:
Type 2 diabetes; Twin study; Concordance rate; Cross-sectional study
Contributor Information
Zheng Ke
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Gao Wenjing
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Lyu Jun
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Yu Canqing
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Wang Shengfeng
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Huang Tao
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Sun Dianjianyi
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Liao Chunxiao
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Pang Yuanjie
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Pang Zengchang
Qingdao Municipal Center for Disease Control and Prevention, Qingdao 266033, China
Yu Min
Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
Wang Hua
Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
Wu Xianping
Sichuan Provincial Center for Disease Control and Prevention, Chengdu 610041, China
Dong Zhong
Beijing Center for Disease Prevention and Control, Beijing 100013, China
Wu Fan
Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
Jiang Guohong
Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
Wang Xiaojie
Qinghai Center for Diseases Prevention and Control, Xining 810007, China
Liu Yu
Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150090, China
Deng Jian
Handan Center for Disease Control and Prevention, Handan 056001, China
Lu Lin
Yunnan Center for Disease Control and Prevention, Kunming 650034, China
Cao Weihua
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Li Liming
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
