Determination of Prevalence of Type 2 Diabetes Mellitus by Screening Tests using a Mathematical Formula in Place of Invasive Blood Tests LC05-LC09
Dr. Jugal Kishore,
Professor, Department of Community Medicine, VMMC, Delhi, India.
E-mail : email@example.com
Introduction: True prevalence rate of diabetes mellitus in a population can be obtained by using invasive tests but it is practically difficult on large scale.
Aim: To find out the feasibility of mass non-invasive screening test to detect the prevalence of diabetes mellitus in rural population of India with the help of a mathematical formula.
Materials and Methods: From population of 18800 residing in two adjacent rural areas of Delhi, a systematic random sample of 1005 adult subjects was screened for diabetes by using urine benedicts test, Canrisk questionnaire, Madras Diabetes Research Foundation-Indian Diabetic Risk Score (MDRF-IDRS) and determined prevalence of diabetes (pA) gauzed by each of these screening tests. Simultaneously, each subject’s glycaemic status was confirmed by standard fasting Plasma glucose (FPG) and postprandial plasma glucose (PPPG) levels. The blood test was also used to determine true prevalence which was cross-checked with the prevalence estimated (Pe) by the above stated screening tests using a mathematical formula.
Results: The true prevalence of T2DM in more than 18 years of population by Fasting Plasma Sugar (FPS) was 4.5% while that by using mathematical formulae that estimated by urine test, Canrisk test and MDRF-IDRS was 4.4%, 4.4 and 4.3% respectively. When more than 35 years age-group was selected, true prevalence was 7.4% and estimated prevalence by Canrisk test was 7.1% (as against gold standard of Fasting) and 6.9% (as against PP). By fasting urine test it came out to be 7.2% and by PP urine test it was 7.4%. In population l8-35 years, the prevalence of diabetes was 1.1% by plasma glucose test. By using Canrisk, it came out to be 1.04%.
Conclusion: Individual screening tests such as urine, Canrisk and MDRF-IDRS can be used to estimate prevalence rates of diabetes in rural areas by means of mathematical formula which would be close to true estimates.