Farideh Razi1, Patricia Khashayar2, Robabeh Ghodssi-Ghassemabadi3, Mohsen Mehrabzadeh4, Maryam Peimani5, Fatemeh Bandarian6, Ensieh Nasli-Esfahani7. 1. Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 2. Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 3. Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran. 4. Obesity and Eating Habits Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 5. Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 6. Elderly Health Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; Halal Research Center of IRI, FDA, Tehran, Iran. 7. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: n.nasli@yahoo.com.
Abstract
OBJECTIVES: The aim of this study was to evaluate the capability of glycated hemoglobin (A1C) levels to be a tool for identifying Iranian adults with diabetes and prediabetes. METHODS: In a cross-sectional population-based study, 1,813 adults, men and women 35 to 75 years of age and without a history of diabetes and hemoglobinopathies, were included. Fasting blood glucose and A1C levels were obtained. According to the criteria of the American Diabetes Association, participants were categorized into 3 groups: newly diagnosed diabetes, prediabetes and healthy subjects. The optimal cutoff point for A1C in diabetes and prediabetes diagnosis was determined by studying the sensitivity and specificity of different cutoff points for A1C, while using different levels of fasting blood glucose as the gold standard. RESULTS: Participants with newly diagnosed diabetes were significantly older than subjects with prediabetes and healthy subjects (mean [± SD] 47.3±12.9, 44.6±13.0 and 39.2±14.1 years, respectively) and also had higher body mass indexes. As expected, the levels of fasting blood glucose (8.79±2.24, 6.01±0.38 and 4.97±0.4 mmol/L) and A1C (6.55±1.4%, 5.61±0.61% and 5.28±0.59%) were significantly different in the groups (p<0.001). The optimal cutoff point for A1C to predict prediabetes was 5.5% (sensitivity of 60.5% and specificity of 63.1%) and for diabetes was 5.9% (sensitivity of 66.7% and specificity of 81.2%). ADA cutoff points for prediabetes and diabetes detection yielded a sensitivity of 45.2% and 39.8%, respectively. CONCLUSIONS: The findings suggest the necessity of determining the A1C cutoffs for detecting diabetes or prediabetes in each region's population. They also suggest that the combination of these A1C cutoffs with fasting blood glucose levels are required to determine diabetes and prediabetes more accurately.
OBJECTIVES: The aim of this study was to evaluate the capability of glycated hemoglobin (A1C) levels to be a tool for identifying Iranian adults with diabetes and prediabetes. METHODS: In a cross-sectional population-based study, 1,813 adults, men and women 35 to 75 years of age and without a history of diabetes and hemoglobinopathies, were included. Fasting blood glucose and A1C levels were obtained. According to the criteria of the American Diabetes Association, participants were categorized into 3 groups: newly diagnosed diabetes, prediabetes and healthy subjects. The optimal cutoff point for A1C in diabetes and prediabetes diagnosis was determined by studying the sensitivity and specificity of different cutoff points for A1C, while using different levels of fasting blood glucose as the gold standard. RESULTS:Participants with newly diagnosed diabetes were significantly older than subjects with prediabetes and healthy subjects (mean [± SD] 47.3±12.9, 44.6±13.0 and 39.2±14.1 years, respectively) and also had higher body mass indexes. As expected, the levels of fasting blood glucose (8.79±2.24, 6.01±0.38 and 4.97±0.4 mmol/L) and A1C (6.55±1.4%, 5.61±0.61% and 5.28±0.59%) were significantly different in the groups (p<0.001). The optimal cutoff point for A1C to predict prediabetes was 5.5% (sensitivity of 60.5% and specificity of 63.1%) and for diabetes was 5.9% (sensitivity of 66.7% and specificity of 81.2%). ADA cutoff points for prediabetes and diabetes detection yielded a sensitivity of 45.2% and 39.8%, respectively. CONCLUSIONS: The findings suggest the necessity of determining the A1C cutoffs for detecting diabetes or prediabetes in each region's population. They also suggest that the combination of these A1C cutoffs with fasting blood glucose levels are required to determine diabetes and prediabetes more accurately.
Authors: Sharifullah Alemi; Keiko Nakamura; Ahmad Shekib Arab; Mohammad Omar Mashal; Yuri Tashiro; Kaoruko Seino; Shafiqullah Hemat Journal: Int J Environ Res Public Health Date: 2021-05-26 Impact factor: 3.390