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CN 34-1304/RISSN 1674-3679

Volume 25 Issue 1
Jan.  2021
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WANG Cun, CHEN Zhi-xin, REN Hong-yun, WANG Zi-chao, GUO Yuan-yuan, CAI Xiang-ying, SHEN Pei-xuan, HOU Li-ying, LIU Hai-feng, LI Yun. Analysis of prevalence and influencing factors of impaired fasting glucose in residents of Tangshan[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(1): 95-100. doi: 10.16462/j.cnki.zhjbkz.2021.01.018
Citation: WANG Cun, CHEN Zhi-xin, REN Hong-yun, WANG Zi-chao, GUO Yuan-yuan, CAI Xiang-ying, SHEN Pei-xuan, HOU Li-ying, LIU Hai-feng, LI Yun. Analysis of prevalence and influencing factors of impaired fasting glucose in residents of Tangshan[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(1): 95-100. doi: 10.16462/j.cnki.zhjbkz.2021.01.018

Analysis of prevalence and influencing factors of impaired fasting glucose in residents of Tangshan

doi: 10.16462/j.cnki.zhjbkz.2021.01.018
Funds:

The Science and Technology Innovation Team Project of Tangshan 20130206D

More Information
  • Corresponding author: LI Yun, E-mail:liyun8022@163.com
  • Received Date: 2020-06-28
  • Rev Recd Date: 2020-10-15
  • Publish Date: 2021-01-10
  •   Objective  To investigate the prevalence and influencing factors of impaired fasting glucose(IFG) in residents of Tangshan, and to provide evidence for the prevention and control of diabetes and cardiovascular risk factors in the region.  Methods  Based on the survey of chronic diseases and their risk factors in Tangshan city, 11 475 adult residents in urban and rural districts of Tangshan were randomly enrolled in this study from January 1, 2018 to December 31, 2018. All data were collected by questionnaire and physical examination. The prevalence of IFG was calculated. The Logistic regression analysis model was used to analyze the risk factors of IFG.  Results  A total of 10 510 valid questionnaires (91.6%) were retrieved. Among all the subjects, there were 829 cases of IFG, with a total prevalence of 7.89%. The prevalence was 8.59% for males and 7.04% for females, and the difference was statistically significant (χ2 =15.458, P < 0.001). The prevalence was 10.95% for urban residents and 6.36% for rural residents, (9.56% for residents in mountainous areas, 6.55% for residents in plain areas and 3.59% for residents in coastal areas). Multivariate unconditional Logistic regression analysis showed that age, body mass index, hypertension, hyperlipidemia, family history of diabetes, urban or rural areas were associated with the risk of IFG.  Conclusions  The prevalence of IFG is relatively high for adult residents in Tangshan area. Age, overweight, hypertension, hyperlipidemia, family history of diabetes and urban area are the influencing factors of IFG.
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