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Published in: BMC Endocrine Disorders 1/2021

Open Access 01-12-2021 | Diabetes | Research

Prediction model for the onset risk of impaired fasting glucose: a 10-year longitudinal retrospective cohort health check-up study

Authors: Yuqi Wang, Liangxu Wang, Yanli Su, Li Zhong, Bin Peng

Published in: BMC Endocrine Disorders | Issue 1/2021

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Abstract

Background

Impaired fasting glucose (IFG) is a prediabetic condition. Considering that the clinical symptoms of IFG are inconspicuous, these tend to be easily ignored by individuals, leading to conversion to diabetes mellitus (DM). In this study, we established a prediction model for the onset risk of IFG in the Chongqing health check-up population to provide a reference for prevention in a health check-up cohort.

Methods

We conducted a retrospective longitudinal cohort study in Chongqing, China from January 2009 to December 2019. The qualified subjects were more than 20 years old and had more than two health check-ups. After following the inclusion and exclusion criteria, the cohort population was randomly divided into a training set and a test set at a ratio of 7:3. We first selected the predictor variables through the univariate generalized estimation equation (GEE), and then the training set was used to establish the IFG risk model based on multivariate GEE. Finally, the sensitivity, specificity, and receiver operating characteristic curves were used to verify the performance of the model.

Results

A total of 4,926 subjects were included in this study, with an average of 3.87 check-up records, including 2,634 males and 2,292 females. There were 442 IFG cases during the follow-up period, including 286 men and 156 women. The incidence density was 26.88/1000 person-years for men and 18.53/1000 person-years for women (P<0.001). The predictor variables of our prediction model include male (relative risk (RR) =1.422, 95 % confidence interval (CI): 0.923-2.193, P=0.3849), age (RR=1.030, 95 %CI: 1.016-1.044, P<0.0001), waist circumference (RR=1.005, 95 %CI: 0.999-1.012, P=0.0975), systolic blood pressure (RR=1.004, 95 %CI: 0.993-1.016, P=0.4712), diastolic blood pressure (RR=1.023, 95 %CI: 1.005-1.041, P=0.0106), obesity (RR=1.797, 95 %CI: 1.126-2.867, P=0.0140), triglycerides (RR=1.107, 95 %CI: 0.943-1.299, P=0.2127), high-density lipoprotein cholesterol (RR=0.992, 95 %CI: 0.476-2.063, P=0.9818), low-density lipoprotein cholesterol (RR=1.793, 95 %CI: 1.085-2.963, P=0.0228), blood urea (RR=1.142, 95 %CI: 1.022-1.276, P=0.0192), serum uric acid (RR=1.004, 95 %CI: 1.002-1.005, P=0.0003), total cholesterol (RR=0.674, 95 %CI: 0.403-1.128, P=0.1331), and serum creatinine levels (RR=0.960, 95 %CI: 0.945-0.976, P<0.0001). The area under the receiver operating characteristic curve (AUC) in the training set was 0.740 (95 %CI: 0.712-0.768), and the AUC in the test set was 0.751 (95 %CI: 0.714-0.817).

Conclusions

The prediction model for the onset risk of IFG had good predictive ability in the health check-up cohort.
Literature
1.
go back to reference Mirzaei M, Rahmaninan M, Mirzaei M, Nadjarzadeh A, tafti A: Epidemiology of diabetes mellitus, pre-diabetes, undiagnosed and uncontrolled diabetes in Central Iran: results from Yazd health study. BMC Public Health 2020, 20. Mirzaei M, Rahmaninan M, Mirzaei M, Nadjarzadeh A, tafti A: Epidemiology of diabetes mellitus, pre-diabetes, undiagnosed and uncontrolled diabetes in Central Iran: results from Yazd health study. BMC Public Health 2020, 20.
2.
go back to reference Fan W. Epidemiology in diabetes mellitus and cardiovascular disease. Cardiovascular Endocrinology. 2017;6:8–16.CrossRef Fan W. Epidemiology in diabetes mellitus and cardiovascular disease. Cardiovascular Endocrinology. 2017;6:8–16.CrossRef
3.
go back to reference World Health O. Global report on diabetes. Geneva: World Health Organization; 2016. World Health O. Global report on diabetes. Geneva: World Health Organization; 2016.
4.
go back to reference Al-Lawati J. Diabetes Mellitus: A Local and Global Public Health Emergency! Oman Medical Journal. 2017;32:177–9.CrossRef Al-Lawati J. Diabetes Mellitus: A Local and Global Public Health Emergency! Oman Medical Journal. 2017;32:177–9.CrossRef
5.
go back to reference Pǎtru D, Mitrea A, Manea M, Preda SD, Mota M, Lacatis D: Diabetes mellitus epidemiology. 2011, 18:67-72. Pǎtru D, Mitrea A, Manea M, Preda SD, Mota M, Lacatis D: Diabetes mellitus epidemiology. 2011, 18:67-72.
6.
go back to reference Hu JI L, Zhang S. Challenge the huge economic burden that diabetes has brought to China with new strategies and management methods. China Medicine and Pharmacy. 2013;3(01):9–11. Hu JI L, Zhang S. Challenge the huge economic burden that diabetes has brought to China with new strategies and management methods. China Medicine and Pharmacy. 2013;3(01):9–11.
7.
go back to reference Mengzi S, Min W, Chong S, Pingping Z, Yaogai L, Liyuan P, Shuo L, Yan Y, Lina J: The cut-off value of impaired fasting glucose should be lower: Based on the associations of fasting blood glucose with blood lipids. Primary Care Diabetes 2019, 14. Mengzi S, Min W, Chong S, Pingping Z, Yaogai L, Liyuan P, Shuo L, Yan Y, Lina J: The cut-off value of impaired fasting glucose should be lower: Based on the associations of fasting blood glucose with blood lipids. Primary Care Diabetes 2019, 14.
8.
go back to reference Hanefeld M, Temelkova-Kurktschiev T, Schaper F, Henkel E, Siegert G, Köhler C. Impaired fasting glucose is not a risk factor for atherosclerosis. Diabetic medicine: a journal of the British Diabetic Association. 1999;16:212–8.CrossRef Hanefeld M, Temelkova-Kurktschiev T, Schaper F, Henkel E, Siegert G, Köhler C. Impaired fasting glucose is not a risk factor for atherosclerosis. Diabetic medicine: a journal of the British Diabetic Association. 1999;16:212–8.CrossRef
9.
go back to reference Rondanelli M, Riva A, Petrangolini G, Allegrini P, Bernardinelli L, Fazia T, Peroni G, Gasparri C, Nichetti M, Faliva MA et al: The Metabolic Effects of Cynara Supplementation in Overweight and Obese Class I Subjects with Newly Detected Impaired Fasting Glycemia: A Double-Blind, Placebo-Controlled, Randomized Clinical Trial. Nutrients 2020, 12(11). Rondanelli M, Riva A, Petrangolini G, Allegrini P, Bernardinelli L, Fazia T, Peroni G, Gasparri C, Nichetti M, Faliva MA et al: The Metabolic Effects of Cynara Supplementation in Overweight and Obese Class I Subjects with Newly Detected Impaired Fasting Glycemia: A Double-Blind, Placebo-Controlled, Randomized Clinical Trial. Nutrients 2020, 12(11).
10.
go back to reference Jacqueline MDekke, Zhang Y, Tan Y. : Blue: Oppose the American Diabetes Association’s new standard for impaired fasting glucose. Clinical Journal of Diabetes World. 2008;2(01):33–4. Jacqueline MDekke, Zhang Y, Tan Y. : Blue: Oppose the American Diabetes Association’s new standard for impaired fasting glucose. Clinical Journal of Diabetes World. 2008;2(01):33–4.
11.
go back to reference Yang X, He Q, Zhou R, Peng Q, Xiong J, Zhang R. Prevalence and risk factors of impaired fasting glucose among physical examination population in the western new city of Chongqing. Journal of Chongqing Medical University. 2016;41(05):499–503. Yang X, He Q, Zhou R, Peng Q, Xiong J, Zhang R. Prevalence and risk factors of impaired fasting glucose among physical examination population in the western new city of Chongqing. Journal of Chongqing Medical University. 2016;41(05):499–503.
12.
go back to reference Chien K-L, Cai T, Hsu H, Su T-C, Chang W-T, Chen M, Lee Y, Hu F. A prediction model for type 2 diabetes risk among Chinese people. Diabetologia. 2009;52:443–50.CrossRef Chien K-L, Cai T, Hsu H, Su T-C, Chang W-T, Chen M, Lee Y, Hu F. A prediction model for type 2 diabetes risk among Chinese people. Diabetologia. 2009;52:443–50.CrossRef
13.
go back to reference Rathmann W, Kowall B, Heier M, Herder C, Holle R, Thorand B, Strassburger K, Peters A, Wichmann HE, Giani G, et al. Prediction models for incident Type 2 diabetes mellitus in the older population: KORA S4/F4 cohort study. Diabetic Medicine. 2010;27(10):1116–23.CrossRef Rathmann W, Kowall B, Heier M, Herder C, Holle R, Thorand B, Strassburger K, Peters A, Wichmann HE, Giani G, et al. Prediction models for incident Type 2 diabetes mellitus in the older population: KORA S4/F4 cohort study. Diabetic Medicine. 2010;27(10):1116–23.CrossRef
14.
go back to reference Xiong X-l, Zhang R-x, Bi Y, Zhou W-h, Yu Y, Zhu D-l. Machine Learning Models in Type 2 Diabetes Risk Prediction: Results from a Cross-sectional Retrospective Study in Chinese Adults. Current Medical Science. 2019;39:582–8.CrossRef Xiong X-l, Zhang R-x, Bi Y, Zhou W-h, Yu Y, Zhu D-l. Machine Learning Models in Type 2 Diabetes Risk Prediction: Results from a Cross-sectional Retrospective Study in Chinese Adults. Current Medical Science. 2019;39:582–8.CrossRef
15.
go back to reference Zhang J, Li Q, Liu F, Han Y, Yang J. Trend of health management services model. Journal of Shandong University(Health Sciences). 2019;57(08):69–76. Zhang J, Li Q, Liu F, Han Y, Yang J. Trend of health management services model. Journal of Shandong University(Health Sciences). 2019;57(08):69–76.
16.
go back to reference Wen N, Liu Y, Yang H, Guan X, Shuai P, Wan Q. Discussing The Key Points and Implementation Methods of Integrated Health Management Service Mode in Hospital Physical Examination Center. Chinese Health Service Management. 2020;37(03):184-185+189. Wen N, Liu Y, Yang H, Guan X, Shuai P, Wan Q. Discussing The Key Points and Implementation Methods of Integrated Health Management Service Mode in Hospital Physical Examination Center. Chinese Health Service Management. 2020;37(03):184-185+189.
17.
go back to reference Shi F: Research on common chronic disease risk factors measuring and risk rating appraisal. Ph.D. Fourth Military Medical University 2015. Shi F: Research on common chronic disease risk factors measuring and risk rating appraisal. Ph.D. Fourth Military Medical University 2015.
18.
go back to reference Zhang Q: Stduy on design and statistical analysis strategies for large sample longitudinal health management cohort data. Master.Shang dong university 2013. Zhang Q: Stduy on design and statistical analysis strategies for large sample longitudinal health management cohort data. Master.Shang dong university 2013.
19.
go back to reference Wang L:Health Manager: National Vocational Qualification Level III: Health Manager: National Vocational Qualification Level III 2013. Wang L:Health Manager: National Vocational Qualification Level III: Health Manager: National Vocational Qualification Level III 2013.
20.
go back to reference Chinese guidelines for the prevention and treatment of type 2 diabetes (2017 Edition), Chinese Journal of practical internal medicine 2018, 38 (04): 292-344 Chinese guidelines for the prevention and treatment of type 2 diabetes (2017 Edition), Chinese Journal of practical internal medicine 2018, 38 (04): 292-344
21.
go back to reference Williams J, Zimmet P, Shaw J, de Courten M, Cameron A, Chitson P, Tuomilehto J, Alberti G. Gender differences in the prevalence of impaired fasting glycaemia and impaired glucose tolerance in Mauritius. Does sex matter? Diabetic medicine: a journal of the British Diabetic Association. 2003;20:915–20.CrossRef Williams J, Zimmet P, Shaw J, de Courten M, Cameron A, Chitson P, Tuomilehto J, Alberti G. Gender differences in the prevalence of impaired fasting glycaemia and impaired glucose tolerance in Mauritius. Does sex matter? Diabetic medicine: a journal of the British Diabetic Association. 2003;20:915–20.CrossRef
22.
go back to reference Zhao Y, Liu Y, Sun H, Sun X, Yin Z, Li H, Ren Y, Wang B, Zhang D, Liu X, et al. Body mass index and risk of all-cause mortality with normoglycemia, impaired fasting glucose and prevalent diabetes: Results from the Rural Chinese Cohort Study. Journal of Epidemiology and Community Health. 2018;72:jech-2017. Zhao Y, Liu Y, Sun H, Sun X, Yin Z, Li H, Ren Y, Wang B, Zhang D, Liu X, et al. Body mass index and risk of all-cause mortality with normoglycemia, impaired fasting glucose and prevalent diabetes: Results from the Rural Chinese Cohort Study. Journal of Epidemiology and Community Health. 2018;72:jech-2017.
23.
go back to reference Gautier A, Roussel R, Ducluzeau P, Lange C, Vol S, Balkau B, Bonnet F. Increases in Waist Circumference and Weight As Predictors of Type 2 Diabetes in Individuals With Impaired Fasting Glucose: Influence of Baseline BMI Data from the DESIR study. Diabetes care. 2010;33:1850–2.CrossRef Gautier A, Roussel R, Ducluzeau P, Lange C, Vol S, Balkau B, Bonnet F. Increases in Waist Circumference and Weight As Predictors of Type 2 Diabetes in Individuals With Impaired Fasting Glucose: Influence of Baseline BMI Data from the DESIR study. Diabetes care. 2010;33:1850–2.CrossRef
24.
go back to reference Noale M, Maggi S, Zanoni S, Limongi F, Zambon S, Crepaldi G: Lipid risk factors among elderly with normal fasting glucose, impaired fasting glucose and type 2 diabetes mellitus. The Italian longitudinal study on aging. Nutrition, metabolism, and cardiovascular diseases: NMCD 2011, 23 Noale M, Maggi S, Zanoni S, Limongi F, Zambon S, Crepaldi G: Lipid risk factors among elderly with normal fasting glucose, impaired fasting glucose and type 2 diabetes mellitus. The Italian longitudinal study on aging. Nutrition, metabolism, and cardiovascular diseases: NMCD 2011, 23
25.
go back to reference Yoshida N, Miyake T, Yamamoto S, Furukawa S, Senba H, Kanzaki S, Koizumi M, Ishihara T, Yoshida O, Hirooka M, et al. The Serum Creatinine Level Might Be Associated with the Onset of Impaired Fasting Glucose: A Community-based Longitudinal Cohort Health Checkup Study. Internal Medicine. 2019;58(4):505–10.CrossRef Yoshida N, Miyake T, Yamamoto S, Furukawa S, Senba H, Kanzaki S, Koizumi M, Ishihara T, Yoshida O, Hirooka M, et al. The Serum Creatinine Level Might Be Associated with the Onset of Impaired Fasting Glucose: A Community-based Longitudinal Cohort Health Checkup Study. Internal Medicine. 2019;58(4):505–10.CrossRef
26.
go back to reference Alberti G, Zimmet PZ: Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1 Diagnosis and classification of diabetes mellitus Provisional report of a WHO consultation Diabet Med 1998, 15. Alberti G, Zimmet PZ: Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1 Diagnosis and classification of diabetes mellitus Provisional report of a WHO consultation Diabet Med 1998, 15.
27.
go back to reference Gu D, Reynolds K, Duan XF, An X, Chen J, Wu XG, Mo JP, Whelton P, He J. Erratum to: Prevalence of diabetes and impaired fasting glucose in the Chinese adult population: International Collaborative Study of Cardiovascular Disease in Asia (InterASIA). Diabetologia. 2003;46:1190–8.CrossRef Gu D, Reynolds K, Duan XF, An X, Chen J, Wu XG, Mo JP, Whelton P, He J. Erratum to: Prevalence of diabetes and impaired fasting glucose in the Chinese adult population: International Collaborative Study of Cardiovascular Disease in Asia (InterASIA). Diabetologia. 2003;46:1190–8.CrossRef
28.
go back to reference Cho NH, Shaw J, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge A, Malanda B: IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Research and Clinical Practice 2018, 138. Cho NH, Shaw J, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge A, Malanda B: IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Research and Clinical Practice 2018, 138.
29.
go back to reference Huang Y: IDF Diabetes Atlas 8th Edition; 2017. Huang Y: IDF Diabetes Atlas 8th Edition; 2017.
30.
go back to reference Yeboah J, Bertoni A, Herrington D, Post W, Burke G. Impaired Fasting Glucose and the Risk of Incident Diabetes Mellitus and Cardiovascular Events in an Adult Population MESA (Multi-Ethnic Study of Atherosclerosis). Journal of the American College of Cardiology. 2011;58:140–6.CrossRef Yeboah J, Bertoni A, Herrington D, Post W, Burke G. Impaired Fasting Glucose and the Risk of Incident Diabetes Mellitus and Cardiovascular Events in an Adult Population MESA (Multi-Ethnic Study of Atherosclerosis). Journal of the American College of Cardiology. 2011;58:140–6.CrossRef
31.
go back to reference Gerstein H, Santaguida P, Raina P, Morrison K, Balion C, Hunt D, Yazdi H, Booker L. Annual incidence and relative risk of diabetes in people with various categories of dysglycemia: A systematic overview and meta-analysis of prospective studies. Diabetes research and clinical practice. 2008;78:305–12.CrossRef Gerstein H, Santaguida P, Raina P, Morrison K, Balion C, Hunt D, Yazdi H, Booker L. Annual incidence and relative risk of diabetes in people with various categories of dysglycemia: A systematic overview and meta-analysis of prospective studies. Diabetes research and clinical practice. 2008;78:305–12.CrossRef
32.
go back to reference Danaei G, Lawes C, Vander Hoorn S, Murray C, Ezzati M. Global and regional mortality from ischaemic heart disease and stroke attributable to higher-than-optimum blood glucose concentration: Comparative risk assessment. Lancet. 2006;368:1651–9.CrossRef Danaei G, Lawes C, Vander Hoorn S, Murray C, Ezzati M. Global and regional mortality from ischaemic heart disease and stroke attributable to higher-than-optimum blood glucose concentration: Comparative risk assessment. Lancet. 2006;368:1651–9.CrossRef
33.
go back to reference Kaneko H, Itoh H, Kiriyama H, Kamon T, Fujiu K, Morita K, Michihata N, Jo T, Takeda N, Morita H, et al. Fasting plasma glucose and subsequent cardiovascular disease among young adults: Analysis of a nationwide epidemiological database. Atherosclerosis. 2021;319:35–41.CrossRef Kaneko H, Itoh H, Kiriyama H, Kamon T, Fujiu K, Morita K, Michihata N, Jo T, Takeda N, Morita H, et al. Fasting plasma glucose and subsequent cardiovascular disease among young adults: Analysis of a nationwide epidemiological database. Atherosclerosis. 2021;319:35–41.CrossRef
34.
go back to reference Volpe M, Borghi C, Perin P, Chiariello M, Manzato E, Miccoli R, Modena M, Riccardi G, Sesti G, Tiengo A, et al. Cardiovascular Prevention in Subjects with Impaired Fasting Glucose or Impaired Glucose Tolerance. High Blood Pressure & Cardiovascular Prevention. 2010;17:73–102.CrossRef Volpe M, Borghi C, Perin P, Chiariello M, Manzato E, Miccoli R, Modena M, Riccardi G, Sesti G, Tiengo A, et al. Cardiovascular Prevention in Subjects with Impaired Fasting Glucose or Impaired Glucose Tolerance. High Blood Pressure & Cardiovascular Prevention. 2010;17:73–102.CrossRef
35.
go back to reference Liu S: Study on the incidence of prediabetes and diabetes and related factors based on a cohort population from 10 provinces in China. Master. Chinese Center for Disease Control and Prevention 2020. Liu S: Study on the incidence of prediabetes and diabetes and related factors based on a cohort population from 10 provinces in China. Master. Chinese Center for Disease Control and Prevention 2020.
36.
go back to reference Zhang X, Zhao X, Huo L, Yuan N, Sun J, Du J, Nan M, Ji L: Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study. Scientific Reports 2020, 10. Zhang X, Zhao X, Huo L, Yuan N, Sun J, Du J, Nan M, Ji L: Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study. Scientific Reports 2020, 10.
37.
go back to reference James J: Personalised medicine, disease prevention, and the inverse care law: More harm than benefit? European journal of epidemiology 2014, 29. James J: Personalised medicine, disease prevention, and the inverse care law: More harm than benefit? European journal of epidemiology 2014, 29.
38.
go back to reference Kraegen E, James D, Jenkins A, Chisholm D. Dose–response curves for in vivo insulin sensitivity in individual tissues in rats. The American journal of physiology. 1985;248:E353-362. Kraegen E, James D, Jenkins A, Chisholm D. Dose–response curves for in vivo insulin sensitivity in individual tissues in rats. The American journal of physiology. 1985;248:E353-362.
39.
go back to reference Andrews R, Greenhaff P, Curtis S, Perry A, Cowley AJ. The effect of dietary creatine supplementation on skeletal muscle metabolism in congestive heart failure. European heart journal. 1998;19:617–22.CrossRef Andrews R, Greenhaff P, Curtis S, Perry A, Cowley AJ. The effect of dietary creatine supplementation on skeletal muscle metabolism in congestive heart failure. European heart journal. 1998;19:617–22.CrossRef
40.
go back to reference Harita N, Hayashi T, Sato K, Nakamura Y, Yoneda T, Endo G, Kambe H. Lower Serum Creatinine Is a New Risk Factor of Type 2 Diabetes. Diabetes care. 2008;32:424–6.CrossRef Harita N, Hayashi T, Sato K, Nakamura Y, Yoneda T, Endo G, Kambe H. Lower Serum Creatinine Is a New Risk Factor of Type 2 Diabetes. Diabetes care. 2008;32:424–6.CrossRef
41.
go back to reference Zierath JR, Krook A, Wallberg-Henriksson H. Insulin action and insulin resistance in human skeletal muscle. Diabetologia. 2000;43:821–35.CrossRef Zierath JR, Krook A, Wallberg-Henriksson H. Insulin action and insulin resistance in human skeletal muscle. Diabetologia. 2000;43:821–35.CrossRef
42.
go back to reference Yamada T, Fukatsu M, Suzuki S, Wada T, Joh T. Elevated serum uric acid predicts impaired fasting glucose and type 2 diabetes only among Japanese women undergoing health checkups. Diabetes & Metabolism. 2011;37(3):252–8.CrossRef Yamada T, Fukatsu M, Suzuki S, Wada T, Joh T. Elevated serum uric acid predicts impaired fasting glucose and type 2 diabetes only among Japanese women undergoing health checkups. Diabetes & Metabolism. 2011;37(3):252–8.CrossRef
43.
go back to reference Miyake T, Kumagi T, Furukawa S, Hirooka M, Kawasaki K, Koizumi M, Todo Y, Yamamoto S, Abe M, Kitai K, et al. Hyperuricemia Is a Risk Factor for the Onset of Impaired Fasting Glucose in Men with a High Plasma Glucose Level: A Community-Based Study. PloS one. 2014;9:e107882.CrossRef Miyake T, Kumagi T, Furukawa S, Hirooka M, Kawasaki K, Koizumi M, Todo Y, Yamamoto S, Abe M, Kitai K, et al. Hyperuricemia Is a Risk Factor for the Onset of Impaired Fasting Glucose in Men with a High Plasma Glucose Level: A Community-Based Study. PloS one. 2014;9:e107882.CrossRef
44.
go back to reference Nakanishi N, Okamoto M, Yoshida H, Matsuo Y, Suzuki K, Tatara K. Serum uric acid and risk for development of hypertension and impaired fasting glucose or Type II diabetes in Japanese male office workers. European journal of epidemiology. 2003;18:523–30.CrossRef Nakanishi N, Okamoto M, Yoshida H, Matsuo Y, Suzuki K, Tatara K. Serum uric acid and risk for development of hypertension and impaired fasting glucose or Type II diabetes in Japanese male office workers. European journal of epidemiology. 2003;18:523–30.CrossRef
45.
go back to reference Taniguchi Y, Hayashi T, Tsumura K, Endo G, Fujii S, Okada K. Serum uric acid and the risk for hypertension and Type 2 diabetes in Japanese men: The Osaka Health Survey. Journal of hypertension. 2001;19:1209–15.CrossRef Taniguchi Y, Hayashi T, Tsumura K, Endo G, Fujii S, Okada K. Serum uric acid and the risk for hypertension and Type 2 diabetes in Japanese men: The Osaka Health Survey. Journal of hypertension. 2001;19:1209–15.CrossRef
46.
go back to reference Alfredo Q, Natali A, Baldi S, Frascerra S, Sanna G, Ciociaro D, Ferrannini E. Effect of insulin on uric acid excretion in humans. The American journal of physiology. 1995;268:E1-5. Alfredo Q, Natali A, Baldi S, Frascerra S, Sanna G, Ciociaro D, Ferrannini E. Effect of insulin on uric acid excretion in humans. The American journal of physiology. 1995;268:E1-5.
47.
go back to reference Khosla U, Zharikov S, Finch J, Nakagawa T, Roncal C, Krotova K, Block E, Prabhakar S, Johnson R. Hyperuricemia induces endothelial dysfunction. Kidney international. 2005;67:1739–42.CrossRef Khosla U, Zharikov S, Finch J, Nakagawa T, Roncal C, Krotova K, Block E, Prabhakar S, Johnson R. Hyperuricemia induces endothelial dysfunction. Kidney international. 2005;67:1739–42.CrossRef
48.
go back to reference Yang X, Xu C, Wang Y, Cao C, Tao Q, Zhan S, Sun F: Risk prediction model of dyslipidaemia over a 5-year period based on the Taiwan MJ health check-up longitudinal database. Lipids in Health and Disease 2018, 17. Yang X, Xu C, Wang Y, Cao C, Tao Q, Zhan S, Sun F: Risk prediction model of dyslipidaemia over a 5-year period based on the Taiwan MJ health check-up longitudinal database. Lipids in Health and Disease 2018, 17.
Metadata
Title
Prediction model for the onset risk of impaired fasting glucose: a 10-year longitudinal retrospective cohort health check-up study
Authors
Yuqi Wang
Liangxu Wang
Yanli Su
Li Zhong
Bin Peng
Publication date
01-12-2021
Publisher
BioMed Central
Keyword
Diabetes
Published in
BMC Endocrine Disorders / Issue 1/2021
Electronic ISSN: 1472-6823
DOI
https://doi.org/10.1186/s12902-021-00878-4

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