TY - JOUR
T1 - Dysglycemia risk score in Saudi Arabia
T2 - A tool to identify people at high future risk of developing type 2 diabetes
AU - Bahijri, Suhad
AU - Al-Raddadi, Rajaa
AU - Ajabnoor, Ghada
AU - Jambi, Hanan
AU - Al Ahmadi, Jawaher
AU - Borai, Anwar
AU - Barengo, Noël C.
AU - Tuomilehto, Jaakko
N1 - Funding Information:
This work was supported by King Abdulaziz University, grant number (2-140-1434-HiCi).
Publisher Copyright:
© 2020 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Aims/Introduction: To develop a non-invasive risk score to identify Saudis having prediabetes or undiagnosed type 2 diabetes. Methods: Adult Saudis without diabetes were recruited randomly using a stratified two-stage cluster sampling method. Demographic, dietary, lifestyle variables, personal and family medical history were collected using a questionnaire. Blood pressure and anthropometric measurements were taken. Body mass index was calculated. The 1-h oral glucose tolerance test was carried out. Glycated hemoglobin, fasting and 1-h plasma glucose were measured, and obtained values were used to define prediabetes and type 2 diabetes (dysglycemia). Logistic regression models were used for assessing the association between various factors and dysglycemia, and Hosmer–Lemeshow summary statistics were used to assess the goodness-of-fit. Results: A total of 791 men and 612 women were included, of whom 69 were found to have diabetes, and 259 had prediabetes. The prevalence of dysglycemia was 23%, increasing with age, reaching 71% in adults aged ≥65 years. In univariate analysis age, body mass index, waist circumference, use of antihypertensive medication, history of hyperglycemia, low physical activity, short sleep and family history of diabetes were statistically significant. The final model for the Saudi Diabetes Risk Score constituted sex, age, waist circumference, history of hyperglycemia and family history of diabetes, with the score ranging from 0 to 15. Its fit based on assessment using the receiver operating characteristic curve was good, with an area under the curve of 0.76 (95% confidence interval 0.73–0.79). The proposed cut-point for dysglycemia is 5 or 6, with sensitivity and specificity being approximately 0.7. Conclusion: The Saudi Diabetes Risk Score is a simple tool that can effectively distinguish Saudis at high risk of dysglycemia.
AB - Aims/Introduction: To develop a non-invasive risk score to identify Saudis having prediabetes or undiagnosed type 2 diabetes. Methods: Adult Saudis without diabetes were recruited randomly using a stratified two-stage cluster sampling method. Demographic, dietary, lifestyle variables, personal and family medical history were collected using a questionnaire. Blood pressure and anthropometric measurements were taken. Body mass index was calculated. The 1-h oral glucose tolerance test was carried out. Glycated hemoglobin, fasting and 1-h plasma glucose were measured, and obtained values were used to define prediabetes and type 2 diabetes (dysglycemia). Logistic regression models were used for assessing the association between various factors and dysglycemia, and Hosmer–Lemeshow summary statistics were used to assess the goodness-of-fit. Results: A total of 791 men and 612 women were included, of whom 69 were found to have diabetes, and 259 had prediabetes. The prevalence of dysglycemia was 23%, increasing with age, reaching 71% in adults aged ≥65 years. In univariate analysis age, body mass index, waist circumference, use of antihypertensive medication, history of hyperglycemia, low physical activity, short sleep and family history of diabetes were statistically significant. The final model for the Saudi Diabetes Risk Score constituted sex, age, waist circumference, history of hyperglycemia and family history of diabetes, with the score ranging from 0 to 15. Its fit based on assessment using the receiver operating characteristic curve was good, with an area under the curve of 0.76 (95% confidence interval 0.73–0.79). The proposed cut-point for dysglycemia is 5 or 6, with sensitivity and specificity being approximately 0.7. Conclusion: The Saudi Diabetes Risk Score is a simple tool that can effectively distinguish Saudis at high risk of dysglycemia.
KW - Diabetes risk score
KW - Dysglycemia
KW - Saudi population
UR - http://www.scopus.com/inward/record.url?scp=85079905361&partnerID=8YFLogxK
U2 - 10.1111/jdi.13213
DO - 10.1111/jdi.13213
M3 - Article
C2 - 31957345
AN - SCOPUS:85079905361
SN - 2040-1116
VL - 11
SP - 844
EP - 855
JO - Journal of Diabetes Investigation
JF - Journal of Diabetes Investigation
IS - 4
ER -