Hang Sun1,2,3, Lu Xu4, Lili Liu5, Siyan Zhan6,7,8, Shengfeng Wang9, Yongfeng Song10,11,12. 1. Department of Endocrinology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, China. 2. Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, Shandong, 250021, China. 3. Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, Shandong, 250021, China. 4. Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, 100191, China. 5. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China. 6. Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, 100191, China. siyan-zhan@bjmu.edu.cn. 7. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China. siyan-zhan@bjmu.edu.cn. 8. Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing, 100191, China. siyan-zhan@bjmu.edu.cn. 9. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China. shengfeng1984@126.com. 10. Department of Endocrinology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, China. syf198506@163.com. 11. Shandong Institute of Endocrine & Metabolic Diseases, Jinan, Shandong, 250000, China. syf198506@163.com. 12. Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China. syf198506@163.com.
Abstract
BACKGROUND: Limited studies have explored the predictive efficiency of prediabetes based on two definitions for diabetes among Chinese middle-aged and older populations with prediabetes. OBJECTIVE: To evaluate the predictive efficiency of prediabetes based on two definitions for diabetes and the clinical and public health benefit in Chinese middle-aged and older populations. DESIGN: A 5-year cohort study from the China Health and Retirement Longitudinal Study. PARTICIPANTS: A total of 5208 participants who had blood sample data at baseline in 2011. MAIN MEASURES: The exposure was prediabetes based on American Diabetes Association (ADA) and World Health Organization (WHO) definition. The main outcome was incident diabetes. The ability of prediabetes for predicting diabetes was assessed by sensitivity, specificity, positive predictive value, and negative predictive value. Cox proportional hazards regression was used to explore the associations between prediabetes and the 5-year risk of diabetes and all-cause mortality. KEY RESULTS: Among those with prediabetes according to the ADA definition, only 426 (15.45%) with baseline prediabetes progressed to total diabetes, while according to the WHO definition, 208 (21.89%) progressed to total diabetes. In terms of the ability of predicting the incident total diabetes in 5 years, the ADA definition has a higher sensitivity than the WHO definition (70.76% versus 34.55%, P < 0.001), while the WHO definition has a higher specificity than the ADA definition (84.09% versus 49.35%, P < 0.001). Positive predictive values based on the two definitions were low (< 24%); negative predictive values were high (> 90%). CONCLUSIONS: Neither definition of prediabetes is robust for predicting diabetes development in Chineses middle-aged and older populations.
BACKGROUND: Limited studies have explored the predictive efficiency of prediabetes based on two definitions for diabetes among Chinese middle-aged and older populations with prediabetes. OBJECTIVE: To evaluate the predictive efficiency of prediabetes based on two definitions for diabetes and the clinical and public health benefit in Chinese middle-aged and older populations. DESIGN: A 5-year cohort study from the China Health and Retirement Longitudinal Study. PARTICIPANTS: A total of 5208 participants who had blood sample data at baseline in 2011. MAIN MEASURES: The exposure was prediabetes based on American Diabetes Association (ADA) and World Health Organization (WHO) definition. The main outcome was incident diabetes. The ability of prediabetes for predicting diabetes was assessed by sensitivity, specificity, positive predictive value, and negative predictive value. Cox proportional hazards regression was used to explore the associations between prediabetes and the 5-year risk of diabetes and all-cause mortality. KEY RESULTS: Among those with prediabetes according to the ADA definition, only 426 (15.45%) with baseline prediabetes progressed to total diabetes, while according to the WHO definition, 208 (21.89%) progressed to total diabetes. In terms of the ability of predicting the incident total diabetes in 5 years, the ADA definition has a higher sensitivity than the WHO definition (70.76% versus 34.55%, P < 0.001), while the WHO definition has a higher specificity than the ADA definition (84.09% versus 49.35%, P < 0.001). Positive predictive values based on the two definitions were low (< 24%); negative predictive values were high (> 90%). CONCLUSIONS: Neither definition of prediabetes is robust for predicting diabetes development in Chineses middle-aged and older populations.
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