Geographical variation and related factors in prediabetes prevalence in Chinese adults in 2013
10.3760/cma.j.issn.0253-9624.2018.02.008
- VernacularTitle: 2013年中国成人糖尿病前期的地理分布及相关因素分析
- Author:
Zhenping ZHAO
1
;
Yichong LI
;
Limin WANG
;
Mei ZHANG
;
Zhengjing HUANG
;
Xiao ZHANG
;
Chun LI
;
Qian DENG
;
Maigeng ZHOU
Author Information
1. National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
- Publication Type:Journal Article
- Keywords:
Prediabetic state;
Risk factor;
Cross-sectional study;
Multi-level model
- From:
Chinese Journal of Preventive Medicine
2018;52(2):158-164
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the geographical variation of prediabetes in adults in different regions of China, and to analyze the related factors of prediabetes.
Methods:Data was obtained from China Chronic Disease and Related Risk Factor Surveillance in 2013. The surveillance adopted multiple-stage stratified cluster random sampling method, which sampled 177 099 residents aged above 18 years old among 298 surveillance points in 31 provinces of Chinese Mainland. Questionnaire interview was used to obtain demographic variables, personal living style, and socio-economical information. Physical examination was conducted and fasting venous blood sample and (oral glucose tolerance test-2 hours, OGTT-2 h) venous blood sample were obtained from the participants. A total of 171 567 residents aged 18 and above were included in the analysis. The prevalence of prediabetes was analyzed by provinces and by China's geographical regions, after complex weighting. Multilevel logistic models were established to explore the related factors of prediabetes on the area level and individual level.
Results:The prevalence of prediabetes among residents aged 18 and above was 16.6% (95%CI: 15.6%-17.6%) in China. The prevalence of prediabetes was the highest (18.3%) in the south China and lowest (13.1%) in the northwest area. The difference of the prevalence in different areas were not statistically significant (P=0.510). If categorized the prevalence of prediabetes into 5 groups by quintile, Hainan, Jilin, Shandong, Anhui, Hunan and Chongqing were in the highest group of prevalence of prediabetes (18.6%-22.7%), and Tibet, Qinghai, Gansu, Ningxia, Guizhou, and Jiangxi were in the lowest group (7.6%-12.6%). The variance of prevalence of prediabetes on the county level (MOR: 1.60 (95%CI:1.53-1.67)) was more diverse than the province level (MOR: 1.21(95%CI:1.08-1.29)) and higher than the street level (1.23 (95%CI:1.14-1.30)). Several factors increased risk of pre-diabetes, including smoking, hazardous drinking and harmful drinking, drinking in the past 30 days, overweight, obesity, central obesity, sugary drink intake, hypertension, high total cholesterol, high triglycerides, high blood low-density lipoprotein cholesterol, low blood high-density lipoprotein cholesterol (all P<0.05). After adjusted the above variables, 92.5% of variance of prediabetes prevalence conld be explained on the provincial level.
Conclusion:The geographical distribution of prediabetes in adults in China differed by geographic areas, and it significantly varied on the county level. The related variables included demographic variables, personal behavior, and geographic related variables.
