AIM: To find the prevalence and prediction factors of undiagnosed diabetes mellitus in an Indonesian adult population. By recognizing the prediction factors, we can make epidemiological modeling and scoring system of undiagnosed diabetes mellitus in Indonesia which can be used as a screening tool in primary health care and health care with minimal diagnostic facility. METHODS: Cross-sectional design was conducted on subjects from National Health Survey, Ministry of Health Republic of Indonesia 2007. Research population was upper than 18th years old. Diabetes mellitus was diagnosed by oral glucose tolerance test based on WHO 1999 standard which has been adapted by Indonesian Society for Endocrinologist. Subjects were categorized undiagnosed if they were newly diagnosed from the survey. RESULTS: From 24417 subjects who undergo oral glucose tolerance test, we choose 20249 subjects who have complete data on important variables. After eliminating subjects bellow 18 years old, we have 18956 subjects included in the study. Prevalence of undiagnosed diabetes mellitus is 4.1% from total 5.6% of diabetic population in Indonesia. Subjects are included in the analysis is undiagnosed diabetes mellitus subjects (778 subjects) and subjects with normal blood glucose or non-diabetes (16011 subjects). From bivariate analysis, variables age, sex, social economic status, education level, obesity, central obesity, hypertension, physical inactivity, and smoking habit have significant association with undiagnosed diabetes mellitus (p < 0.05). From multivariate analysis, we found prediction factors of undiagnosed diabetes mellitus are age, obesity, central obesity, hypertension, and smoking habit. CONCLUSION: Prevalence of undiagnosed diabetes mellitus is 4.1%. Prediction factors of undiagnosed diabetes mellitus in Indonesia are age, obesity, central obesity, hypertension, and smoking habit.
AIM: To find the prevalence and prediction factors of undiagnosed diabetes mellitus in an Indonesian adult population. By recognizing the prediction factors, we can make epidemiological modeling and scoring system of undiagnosed diabetes mellitus in Indonesia which can be used as a screening tool in primary health care and health care with minimal diagnostic facility. METHODS: Cross-sectional design was conducted on subjects from National Health Survey, Ministry of Health Republic of Indonesia 2007. Research population was upper than 18th years old. Diabetes mellitus was diagnosed by oral glucose tolerance test based on WHO 1999 standard which has been adapted by Indonesian Society for Endocrinologist. Subjects were categorized undiagnosed if they were newly diagnosed from the survey. RESULTS: From 24417 subjects who undergo oral glucose tolerance test, we choose 20249 subjects who have complete data on important variables. After eliminating subjects bellow 18 years old, we have 18956 subjects included in the study. Prevalence of undiagnosed diabetes mellitus is 4.1% from total 5.6% of diabetic population in Indonesia. Subjects are included in the analysis is undiagnosed diabetes mellitus subjects (778 subjects) and subjects with normal blood glucose or non-diabetes (16011 subjects). From bivariate analysis, variables age, sex, social economic status, education level, obesity, central obesity, hypertension, physical inactivity, and smoking habit have significant association with undiagnosed diabetes mellitus (p < 0.05). From multivariate analysis, we found prediction factors of undiagnosed diabetes mellitus are age, obesity, central obesity, hypertension, and smoking habit. CONCLUSION: Prevalence of undiagnosed diabetes mellitus is 4.1%. Prediction factors of undiagnosed diabetes mellitus in Indonesia are age, obesity, central obesity, hypertension, and smoking habit.
Authors: Dicky L Tahapary; Karin de Ruiter; Ivonne Martin; Lisette van Lieshout; Bruno Guigas; Pradana Soewondo; Yenny Djuardi; Aprilianto E Wiria; Oleg A Mayboroda; Jeanine J Houwing-Duistermaat; Hengki Tasman; Erliyani Sartono; Maria Yazdanbakhsh; Johannes W A Smit; Taniawati Supali Journal: BMC Infect Dis Date: 2015-03-18 Impact factor: 3.090
Authors: Julia Schröders; Stig Wall; Mohammad Hakimi; Fatwa Sari Tetra Dewi; Lars Weinehall; Mark Nichter; Maria Nilsson; Hari Kusnanto; Ekowati Rahajeng; Nawi Ng Journal: PLoS One Date: 2017-06-20 Impact factor: 3.240