淡江大學機構典藏:Item 987654321/124172
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 64191/96979 (66%)
造访人次 : 8199555      在线人数 : 7742
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/124172


    题名: Prevalence and predictive modeling of undiagnosed diabetes and impaired fasting glucose in Taiwan: a Taiwan Biobank study
    作者: Chen, Ying-erh
    关键词: early diagnosis；pre-diabetic state；risk assessment
    日期: 2023-06
    上传时间: 2023-06-22 12:05:13 (UTC+8)
    摘要: Introduction: We investigated the prevalence of undiagnosed diabetes and impaired fasting glucose (IFG) in individuals without known diabetes in Taiwan and developed a risk prediction model for identifying undiagnosed diabetes and IFG.

    Research design and methods: Using data from a large population-based Taiwan Biobank study linked with the National Health Insurance Research Database, we estimated the standardized prevalence of undiagnosed diabetes and IFG between 2012 and 2020. We used the forward continuation ratio model with the Lasso penalty, modeling undiagnosed diabetes, IFG, and healthy reference group (individuals without diabetes or IFG) as three ordinal outcomes, to identify the risk factors and construct the prediction model. Two models were created: Model 1 predicts undiagnosed diabetes, IFG_110 (ie, fasting glucose between 110 mg/dL and 125 mg/dL), and the healthy reference group, while Model 2 predicts undiagnosed diabetes, IFG_100 (ie, fasting glucose between 100 mg/dL and 125 mg/dL), and the healthy reference group.

    Results: The standardized prevalence of undiagnosed diabetes for 2012-2014, 2015-2016, 2017-2018, and 2019-2020 was 1.11%, 0.99%, 1.16%, and 0.99%, respectively. For these periods, the standardized prevalence of IFG_110 and IFG_100 was 4.49%, 3.73%, 4.30%, and 4.66% and 21.0%, 18.26%, 20.16%, and 21.08%, respectively. Significant risk prediction factors were age, body mass index, waist to hip ratio, education level, personal monthly income, betel nut chewing, self-reported hypertension, and family history of diabetes. The area under the curve (AUC) for predicting undiagnosed diabetes in Models 1 and 2 was 80.39% and 77.87%, respectively. The AUC for predicting undiagnosed diabetes or IFG in Models 1 and 2 was 78.25% and 74.39%, respectively.

    Conclusions: Our results showed the changes in the prevalence of undiagnosed diabetes and IFG. The identified risk factors and the prediction models could be helpful in identifying individuals with undiagnosed diabetes or individuals with a high risk of developing diabetes in Taiwan.
    關聯: BMJ Open Diabetes Research & Care
    DOI: 10.1136/bmjdrc-2023-003423
    显示于类别:[風險管理與保險學系] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML137检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈