The Prevalence of Diabetes, Prediabetes and Associated Risk Factors in Hangzhou, Zhejiang Province: A Community-Based Cross-Sectional Study

被引:11
作者
Shi, Mingming [1 ]
Zhang, Xiao [2 ]
Wang, Hui [1 ]
机构
[1] Ctr Dis Control & Prevet Shangcheng Dist, Hangzhou 310000, Zhejiang, Peoples R China
[2] Zhejiang Chinese Med Univ, Hangzhou 310000, Zhejiang, Peoples R China
来源
DIABETES METABOLIC SYNDROME AND OBESITY-TARGETS AND THERAPY | 2022年 / 15卷
关键词
diabetes; prediabetes; prevalence; associated factors; CARDIOVASCULAR-DISEASE; HYPERTENSION; MELLITUS; CLASSIFICATION; DIAGNOSIS; SMOKING;
D O I
10.2147/DMSO.S351218
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective: Little information is available on the prevalence and associated risk factors of diabetes and prediabetes in the community located in Hangzhou city, Zhejiang Province, southeast China. This study aims to investigate the prevalence of adult diabetes and prediabetes and their associated risk factors among a community population in Hangzhou. Methods: A multistage sampling method was used in this study. Ten communities located in Shangcheng district of Hangzhou city were selected, and 3096 permanent residents (resident for >= 6 months) aged 18 years and above were enrolled into this study. Finally, a total of 2986 participants were included. A questionnaire interview and physical examination were conducted for all participants by trained investigators in a local medical center. Anthropometric measurements covered height, weight, waist circumference (WC) and blood pressure, while the blood tests included fasting blood glucose, an oral glucose tolerance test and fasting lipid profiles. The American Diabetes Association diabetes diagnosis criteria were used to discriminate among normal blood glucose, diabetes and prediabetes. The Rao-Scott adjusted chi(2) test and complex sampling design-based unconditional multivariate logistic regression analysis were used to evaluate factors associated with diabetes and prediabetes. Descriptive and inferential statistics were calculated in Stata version 15. P-values <0.05 indicate statistical significance. Results: The overall prevalence of diabetes was 13.97%, of which 81.54% had prediagnosed diabetes and 18.46% were newly diagnosed with diabetes in the present study. The prevalence of prediabetes was 18.89%. Multivariable logistic regression analysis showed that age, education, once smoking, family history of diabetes, obesity, central obesity and hypertension were factors associated with diabetes, while age, smoking, drinking, central obesity and hypertension were significant factors related to prediabetes. Conclusion: The prevalence of diabetes and prediabetes in adults in Hangzhou city remains high. Interventions aiming to modify risk factors such as drinking, obesity, central obesity and hypertension are urgently required.
引用
收藏
页码:713 / 721
页数:9
相关论文
共 46 条
  • [1] Prevalence of Prediabetes, Diabetes, and Its Associated Risk Factors among Males in Saudi Arabia: A Population-Based Survey
    Aldossari, Khaled K.
    Aldiab, Abdulrahman
    Al-Zahrani, Jamaan M.
    Al-Ghamdi, Sameer H.
    Abdelrazik, Mohammed
    Batais, Mohammed Ali
    Javad, Sundas
    Nooruddin, Shanila
    Razzak, Hira Abdul
    El-Metwally, Ashraf
    [J]. JOURNAL OF DIABETES RESEARCH, 2018, 2018
  • [2] Prevalence of diabetes, pre-diabetes and associated risk factors: second National Diabetes Survey of Pakistan (NDSP), 2016-2017
    Basit, Abdul
    Fawwad, Asher
    Qureshi, Huma
    Shera, A. S.
    [J]. BMJ OPEN, 2018, 8 (08):
  • [3] 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study
    Bray, G. A.
    Chatellier, A.
    Duncan, C.
    Greenway, F. L.
    Levy, E.
    Ryan, D. H.
    Polonsky, K. S.
    Tobian, J.
    Ehrmann, D.
    Matulik, M. J.
    Clark, B.
    Czech, K.
    DeSandre, C.
    Hilbrich, R.
    McNabb, W.
    Semenske, A. R.
    Goldstein, B. J.
    Smith, K. A.
    Wildman, W.
    Pepe, C.
    Goldberg, R. B.
    Calles, J.
    Ojito, J.
    Castillo-Florez, S.
    Florez, H. J.
    Giannella, A.
    Lara, O.
    Veciana, B.
    Haffner, S. M.
    Montez, M. G.
    Lorenzo, C.
    Martinez, A.
    Hamman, R. F.
    Testaverde, L.
    Bouffard, A.
    Dabelea, D.
    Jenkins, T.
    Lenz, D.
    Perreault, L.
    Price, D. W.
    Steinke, S. C.
    Horton, E. S.
    Poirier, C. S.
    Swift, K.
    Caballero, E.
    Jackson, S. D.
    Lambert, L.
    Lawton, K. E.
    Ledbury, S.
    Kahn, S. E.
    [J]. LANCET, 2009, 374 (9702) : 1677 - 1686
  • [4] Associations between waist circumference, metabolic risk and executive function in adolescents: A cross-sectional mediation analysis
    Bugge, Anna
    Moller, Soren
    Westfall, Daniel R.
    Tarp, Jakob
    Gejl, Anne K.
    Wedderkopp, Niels
    Hillman, Charles H.
    [J]. PLOS ONE, 2018, 13 (06):
  • [5] Combined Influence of Waist and Hip Circumference on Risk of Death in a Large Cohort of European and Australian Adults
    Cameron, Adrian J.
    Romaniuk, Helena
    Orellana, Liliana
    Dallongeville, Jean
    Dobson, Annette J.
    Drygas, Wojciech
    Ferrario, Marco
    Ferrieres, Jean
    Giampaoli, Simona
    Gianfagna, Francesco
    Iacoviello, Licia
    Jousilahti, Pekka
    Kee, Frank
    Moitry, Marie
    Niiranen, Teemu J.
    Pajak, Andrzej
    Palmieri, Luigi
    Palosaari, Tarja
    Satu, Mannisto
    Tamosiunas, Abdonas
    Thorand, Barbara
    Toft, Ulla
    Vanuzzo, Diego
    Veikko, Salomaa
    Veronesi, Giovanni
    Wilsgaard, Tom
    Kuulasmaa, Kari
    Soderberg, Stefan
    [J]. JOURNAL OF THE AMERICAN HEART ASSOCIATION, 2020, 9 (13):
  • [6] Chen Chunming, 2004, Biomed Environ Sci, V17 Suppl, P1
  • [7] Factors associated with continued smoking after the diagnosis of type 2 diabetes: a retrospective study in the Korean cohort
    Cho, Mi Hee
    Kim, Sung Min
    Lee, Kiheon
    Park, Sang Min
    Chang, Jooyoung
    Choi, Seulggie
    Kim, Kyuwoong
    Koo, Hye-Yeon
    Jun, Ji-Hye
    [J]. BMJ OPEN, 2018, 8 (06):
  • [8] IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045
    Cho, N. H.
    Shaw, J. E.
    Karuranga, S.
    Huang, Y.
    Fernandes, J. D. da Rocha
    Ohlrogge, A. W.
    Malanda, B.
    [J]. DIABETES RESEARCH AND CLINICAL PRACTICE, 2018, 138 : 271 - 281
  • [9] Elevated lipoprotein(a) and risk of coronary heart disease according to different lipid profiles in the general Chinese community population: the CHCN-BTH study
    Guo, Chunyue
    Cao, Han
    Shan, Guangliang
    Zhao, Wei
    Zhang, Han
    Niu, Kaijun
    Cui, Ze
    Tang, Naijun
    Liu, Kuo
    Pan, Li
    Han, Xiaoyan
    Wang, Zhengfang
    Meng, Ge
    Sun, Jixin
    Shan, Anqi
    Yan, Yuxiang
    He, Huijing
    Xu, Zhiyuan
    Cao, Yajing
    Peng, Wenjuan
    Sun, Yanyan
    Xie, Yunyi
    Liu, Xiaohui
    Li, Bingxiao
    Wen, Fuyuan
    Zhang, Ling
    [J]. ANNALS OF TRANSLATIONAL MEDICINE, 2021, 9 (01)
  • [10] Optimal Waist Circumference Cut-off values for Identifying Metabolic Risk Factors in Middle-aged and Elderly Subjects in Shandong Province of China
    Guo, Hou Xin
    Chuan, Wang
    Qiang, Ma Ze
    Fang, Yang Wei
    Xiang, Wang Ji
    Qiao, Li Cheng
    Lian, Wang Yu
    Min, Liu Shu
    Ping, Hu Xiu
    Ping, Zhang Xiu
    Mei, Jiang
    Qing, Wang Wei
    Guang, Ning
    Zhen, Zheng Hui
    Xia, Ma Ai
    Yu, Sun
    Jun, Song
    Peng, Lin
    Kai, Liang
    Qiang, Liu Fu
    Juan, Li Wen
    Juan, Xiao
    Lei, Gong
    Jian, Wang Mei
    Dong, Liu Ji
    Fei, Yan
    Peng, Yang Jun
    Shu, Wang Ling
    Meng, Tian
    Xing, Zhao Ru
    Ling, Jiang
    Li, Chen
    [J]. BIOMEDICAL AND ENVIRONMENTAL SCIENCES, 2014, 27 (05) : 353 - 359