2026-06-14T05:06:23Zhttps://repisalud.isciii.es/rest/oai/request
oai:repisalud.isciii.es:20.500.12105/190662024-09-28T01:23:25Zcom_20.500.12105_2052com_20.500.12105_2051col_20.500.12105_19613
Repisalud author Wang, Pin author Li, Yuanjing author Wang, Mingqi author Song, Lin author Dong, Yi author Han, Xiaolei author Tuomilehto, Jaakko author Wang, Yongxiang author Du, Yifeng author Qiu, Chengxuan funder Ministry of Science and Technology (China) funder National Natural Science Foundation of China funder Shandong First Medical University (China) funder Swedish Research Council funder Swedish Foundation for International Cooperation in Research and Higher Education funder Karolinska Institutet 2024-03-22T13:44:38Z 2024-03-22T13:44:38Z 2024-01 PLoS One. 2024 Jan 25;19(1):e0296694. 10.1371/journal.pone.0296694 1932-6203 PloS one 38271374 http://hdl.handle.net/20.500.12105/19066 Background: We sought to identify the optimal cut-off of glycated hemoglobin (HbA1c) for defining diabetes and to assess the agreements of fasting plasma glucose (FPG), fasting serum glucose (FSG), and HbA1c in defining diabetes among rural older adults in China. Methods: This population-based cross-sectional study included 3547 participants (age ≥61 years, 57.8% women) from the Multidomain Interventions to Delay Dementia and Disability in Rural China from 2018-2019; of these, 3122 had no previously diagnosed diabetes. We identified the optimal cut-off of HbA1c against FPG ≥7.0 mmol/L for defining diabetes by using receiver operating characteristic curve and Youden index. The agreements of FPG, FSG, and HbA1c in defining diabetes were assessed using kappa statistics. Results: Among participants without previously diagnosed diabetes (n = 3122), the optimal HbA1c cut-off for defining diabetes was 6.5% (48 mmol/mol), with the sensitivity of 88.9%, specificity of 93.7%, and Youden index of 0.825. The correlation coefficients were 0.845 between FPG and FSG, 0.574 between FPG and HbA1c, and 0.529 between FSG and HbA1c in the total sample (n = 3547). The kappa statistic for defining diabetes was 0.962 between FSG and FPG, and 0.812 between HbA1c and FPG. Conclusions: The optimal cut-off of HbA1c for diagnosing diabetes against FPG >7.0 mmol/L is ≥6.5% in Chinese rural-dwelling older adults. The agreement in defining diabetes using FPG, FSG, and HbA1c is nearly perfect. These results have relevant implications for diabetes research and clinical practice among older adults in China. Clinical trial registration: The protocol of MIND-China was registered in the Chinese Clinical Trial Registry (ChiCTR, www.chictr.org.cn; registration no.: ChiCTR1800017758). eng Comparing glycemic traits in defining diabetes among rural Chinese older adults research article 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 URL https://repisalud.isciii.es/bitstreams/3b0835ad-78b0-4931-bd56-2f0421effd34/download File MD5 f6c27ef2c47f97e738ad71e0189b94c1 800070 application/pdf ComparingGlycemicTraitsDefiningDiabetes_2024.pdf URL https://repisalud.isciii.es/bitstreams/3e5dfde2-66d8-49d0-835a-f07a970dd976/download File MD5 c5e8d8b7a36278acc7cf0939b75b7992 36645 text/plain ComparingGlycemicTraitsDefiningDiabetes_2024.pdf.txt