Noninvasive screening tool to detect undiagnosed diabetes among young and middle-aged people in Chinese community

Zhang, M; Lin, L; Xu, X; Wu, X; Jin, Q; Liu, H

Noninvasive screening tool to detect undiagnosed diabetes among young and middle-aged people in Chinese community

Zhang, M Lin, L Xu, X

Wu, X Jin, Q Liu, H

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Publication Type:: Journal Article
Citation:: International Journal of Diabetes in Developing Countries, 2019, 39 (3), pp. 458 - 462
Issue Date:: 2019-07-01

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Field	Value	Language
dc.contributor.author	Zhang, M	en_US
dc.contributor.author	Lin, L	en_US
dc.contributor.author	Xu, X https://orcid.org/0000-0003-4787-6547	en_US
dc.contributor.author	Wu, X	en_US
dc.contributor.author	Jin, Q	en_US
dc.contributor.author	Liu, H	en_US
dc.date.issued	2019-07-01	en_US
dc.identifier.citation	International Journal of Diabetes in Developing Countries, 2019, 39 (3), pp. 458 - 462	en_US
dc.identifier.issn	0973-3930	en_US
dc.identifier.uri	http://hdl.handle.net/10453/135639
dc.description.abstract	© 2018, Research Society for Study of Diabetes in India. To develop a noninvasive screening tool for diagnosing type 2 diabetes among young and middle-aged people in Chinese community. In total, 1432 participants without diabetes diagnosis were enrolled from Chinese communities. Diabetes was defined as fasting plasma glucose (FPG) ≥ 126 mg/dL (≥ 7.0 mmol/L) or glycated hemoglobin (HbA1c) ≥ 6.5%. The noninvasive diabetes screening model score was developed using the coefficients of the final multivariable logistic regression model. Undiagnosed diabetes was detected using a receiver-operating characteristic curve and the area under the curve (AUC). Of the 1432 participants, 142 (9.9%) were newly diagnosed with diabetes through FPG or HbA1c, 67 (4.7%) through FPG alone, and 121 (8.4%) through HbA1c alone. The noninvasive diabetes screening model was developed using significant risk factors, namely age, family history of diabetes, hypertension, waist circumference, body mass index, smoking, daily consumption of vegetables, and daily consumption of fruits. The cutoff score of 22.5 was the optimum to detect undiagnosed diabetes with an AUC of 0.758 (95% confidence interval 0.714–0.803), sensitivity of 83.1%, and specificity of 60.0%. We developed a practical and effective noninvasive screening tool for detecting undiagnosed diabetes among young and middle-aged people in Chinese community.	en_US
dc.relation.ispartof	International Journal of Diabetes in Developing Countries	en_US
dc.relation.isbasedon	10.1007/s13410-018-0698-y	en_US
dc.title	Noninvasive screening tool to detect undiagnosed diabetes among young and middle-aged people in Chinese community	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	39	en_US
utslib.for	1103 Clinical Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
utslib.copyright.status	closed_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	39	en_US

Abstract:

© 2018, Research Society for Study of Diabetes in India. To develop a noninvasive screening tool for diagnosing type 2 diabetes among young and middle-aged people in Chinese community. In total, 1432 participants without diabetes diagnosis were enrolled from Chinese communities. Diabetes was defined as fasting plasma glucose (FPG) ≥ 126 mg/dL (≥ 7.0 mmol/L) or glycated hemoglobin (HbA1c) ≥ 6.5%. The noninvasive diabetes screening model score was developed using the coefficients of the final multivariable logistic regression model. Undiagnosed diabetes was detected using a receiver-operating characteristic curve and the area under the curve (AUC). Of the 1432 participants, 142 (9.9%) were newly diagnosed with diabetes through FPG or HbA1c, 67 (4.7%) through FPG alone, and 121 (8.4%) through HbA1c alone. The noninvasive diabetes screening model was developed using significant risk factors, namely age, family history of diabetes, hypertension, waist circumference, body mass index, smoking, daily consumption of vegetables, and daily consumption of fruits. The cutoff score of 22.5 was the optimum to detect undiagnosed diabetes with an AUC of 0.758 (95% confidence interval 0.714–0.803), sensitivity of 83.1%, and specificity of 60.0%. We developed a practical and effective noninvasive screening tool for detecting undiagnosed diabetes among young and middle-aged people in Chinese community.

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http://hdl.handle.net/10453/135639