Evaluation of Madras Diabetes Research Foundation-Indian Diabetes Risk Score in detecting undiagnosed diabetes in the Indian population: Results from the Indian Council of Medical Research-INdia DIABetes population-based study (INDIAB-15)

Background & objectives: Screening of individuals for early detection and identification of undiagnosed diabetes can help in reducing the burden of diabetic complications. This study aimed to evaluate the performance of Madras Diabetes Research Foundation (MDRF)-Indian Diabetes Risk Score (IDRS) to screen for undiagnosed type 2 diabetes in a large representative population in India. Methods: Data were acquired from the Indian Council of Medical Research–INdia DIABetes (ICMR–INDIAB) study, a large national survey that included both urban and rural populations from 30 states/union territories in India. Stratified multistage design was followed to obtain a sample of 113,043 individuals (94.2% response rate). MDRF-IDRS used four simple parameters, viz. age, waist circumference, family history of diabetes and physical activity to detect undiagnosed diabetes. Receiver operating characteristic (ROC) with area under the curve (AUC) was used to assess the performance of MDRF-IDRS. Results: We identified that 32.4, 52.7 and 14.9 per cent of the general population were under high-, moderate- and low-risk category of diabetes. Among the newly diagnosed individuals with diabetes [diagnosed by oral glucose tolerance test (OGTT)], 60.2, 35.9 and 3.9 per cent were identified under

Geographic information system-based mapping of air pollution & emergency room visits of patients for acute respiratory symptoms in Delhi, India (March 2018-February 2019)

Background & objectives: Studies assessing the spatial and temporal association of ambient air pollution with emergency room visits of patients having acute respiratory symptoms in Delhi are lacking. Therefore, the present study explored the relationship between spatio-temporal variation of particulate matter (PM)2.5 concentrations and air quality index (AQI) with emergency room (ER) visits of patients having acute respiratory symptoms in Delhi using the geographic information system (GIS) approach. Methods: The daily number of ER visits of patients having acute respiratory symptoms (less than or equal to two weeks) was recorded from the ER of four hospitals of Delhi from March 2018 to February 2019. Daily outdoor PM2.5 concentrations and air quality index (AQI) were obtained from the Delhi Pollution Control Committee. Spatial distribution of patients with acute respiratory symptoms visiting ER, PM2.5 concentrations and AQI were mapped for three seasons of Delhi using ArcGIS software. Results: Of the 70,594 patients screened from ER, 18,063 eligible patients were enrolled in the study. Winter days had poor AQI compared to moderate and satisfactory AQI during summer and monsoon days, respectively. None of the days reported good AQI (<50). During winters, an increase in acute respiratory ER visits of patients was associated with higher PM2.5 concentrations in the highly polluted northwest region of Delhi. In contrast, a lower number of acute respiratory ER visits of patients were seen from the ‘moderately polluted’ south-west region of Delhi with relatively lower PM2.5 concentrations. Interpretation & conclusions: Acute respiratory ER visits of patients were related to regional PM2.5 concentrations and AQI that differed during the three seasons of Delhi. The present study providessupport for identifying the hotspots and implementation of focused, intensive decentralized strategies to control ambient air pollution in worst-affected areas, in addition to the general city-wise strategies.