Risk Assessment for Diabetes Mellitus by Using Indian Diabetes Risk Score among Office Workers of Health Institutions of South India

Background: Diabetes mellitus (DM) is one of the non-communicable diseases plaguing the world and contributes a major part to the total disease burden. Diabetes has been prevalent in all countries throughout the years, with the majority of diabetics living in low- and middle-income countries. Madras Diabetes Research Foundation developed the Indian Diabetes Risk Score (IDRS), a simple and cost-effective method to assess the chances of developing diabetes. Objectives: To assess the diabetes risk profile of office workers using IDRS and to determine the proportion of individual risk factors of diabetes among the participants. Methods: This cross sectional study included 94 non-diabetic office workers working in two health care institutions situated in coastal South India. Data was collected by a study questionnaire consisting of three sections. Section A included details related to participant characteristics, Section B included anthropometric measurements, and Section C consisted of the Indian Diabetes Risk Score. The collected data were coded and entered into Statistical Package for Social Sciences. Results: The mean age of the study participants was 40.88 (±9.761) years, and the mean BMI was 23.8 (±3.6) kg/m2. Majority (n=65, 67%) of the study participants did not have a family history of diabetes. One-third of the study participants had IDRS ≥ 60, which allocated them in the high risk category for type 2 diabetes (n=34, 35.1%). Conclusion: It has been conclusively shown from the study that most of the office workers have moderate to high risk of developing diabetes and are also overweight or obese.

Risk assessment of type-2 diabetes using the Indian diabetes risk score: a cross-sectional study on medical students from a tertiary care hospital

Background: Diabetes mellitus is a major public health problem which affects all age groups and has now been identified in young. Indian diabetes risk score (IDRS), devised and developed by Mohan et al. at the Madras Diabetes Research Foundation, is a validated tool to identify individuals with high risk of developing type 2 diabetes mellitus.Methods: Present cross-sectional study was conducted among medical students of a medical college in Jhansi from June 2021 to September 2021. A semi-structured interview schedule for socio demographic details of subjects like age, gender, education/occupation of parents and physical activity. Written informed consent was taken. Statistical analysis used was SPSS trial version was used for data analysis. P<0.05 was considered as statistically significant.Results: A total of 300 medical students were included in the study. IDRS categorization revealed 10 (3.3%) respondents had score >60 (high risk) and 84 (28%) respondents had score between 30-50 (moderate risk). While 206 (68.6%) respondent had score <30 (low risk).Conclusions: Our study supports the use of IDRS method as screening of diabetes at mass level as it is cost effective as well as time saving procedure.

Correlación del Finnish Diabetes Risk Score y la Hemoglobina Glucosilada en la Identificación de Diabetes y Prediabetes en Docentes Universitarios de Ciencias de la Salud.

Introducción: La Diabetes Mellitus se caracteriza por elevación de glucosa en sangre. En el año 2014 vivían 422 millones de personas con diabetes (8.5%) a nivel mundial. En México, en el 2018 vivían aproximadamente 8.6 millones de personas con diabetes (10.3%) y el 70% de la población adulta presentaba sobrepeso u obesidad. Se ha buscado validar herramientas de bajo costo para ampliar la atención médica de población en riesgo de padecer diabetes. El test de FINDRISC es un instrumento utilizado a nivel mundial para evaluar el riesgo de desarrollar diabetes tipo 2. El objetivo de este estudio fue analizar la correlación entre el puntaje del FINDRISC y el valor de la hemoglobina glucosilada en docentes del área de ciencias de la salud en la Universidad Veracruzana. Métodos: Estudio observacional y transversal. Se aplicó el cuestionario FINDRISC a 92 docentes procedentes de Facultades de Ciencias de la Salud, en los que además se determinó la hemoglobina glucosilada. Resultados: El porcentaje de docentes en riesgo alto fue de 26.1% y de 7.6% en riesgo muy alto. Se identificó un 10% de docentes con prediabetes y 7.1% con diabetes no diagnosticada. Solo 24 docentes (26.1%) presentaron peso normal, 40 con sobrepeso (43.5%) y 28 con obesidad (30.4%). La correlación de Pearson del test FINDRISC con la hemoglobina glucosilada fue de r = 0.50 (I.C. 95% 0.35-0.64). Conclusión: El test FINDRISC junto con la hemoglobina glucosilada son útiles para identificar grupos de riesgo para desarrollar diabetes tipo 2 en población veracruzana.

Trends in the prevalence of metabolic syndrome and its components in Mexican adults, 2006-2018

Objective. To examine trends in the prevalence of metabolic syndrome (MS) and its components. Materials and methods. Data from 27 800 Mexican adults who participated in Ensanut 2006, 2012, 2016 and 2018 were analyzed. Linear regression was used across each Ensanut period to assess temporal linear trends in the prevalence of MS. Logistic regression models were obtained to calculate the percentage change, p-value for the trend and the association between the presence of MS and the risk of developing type 2 diabetes mellitus (T2DM) over 10 years using the Finnish Diabetes Risk Score (FINDRISC) and cardiovascular disease (CVD) using Globorisk. Results. The prevalence of MS in Mexican adults according to the harmonized definition was: 40.2, 57.3, 59.99 and 56.31%, in 2006, 2012, 2016 and 2018 respectively (p for trend <0.0001). In 2018, 7.62% of metabolic syndrome cases had a significant risk for incident DM2 and 11.6% for CVD. Conclusion. It is estimated that there are 36.5 million Mexican adults living with metabolic syndrome, of which 2 million and 2.5 million have a high risk of developing T2DM or cardiovascular disease respectively, over the next 10 years.

Development and Validation of a Risk Score for Diabetes Screening in Oman

Objective: To develop and validate a diabetic risk score model, as a non-invasive and selfadministered screening tool, to be used in the general Omani population. Methods: The World Health Survey (WHS) 2008 data from Oman (n=2,720) was used to develop the risk score model. Multivariable logistic regression with backward stepwise method was implemented to obtain risk factors regression coefficients for gender, age, educational attainment, marital status, place of residence, hypertension, body mass index, waist circumference, tobacco use, daily fruits and vegetables intake and weekly physical activity. The model coefficients were multiplied by a factor of five to allocate each variable category a risk score. The total score was calculated as the sum of these individual scores. The score was validated using another Omani cohort (Sur Survey 2006 dataset, n=1,355) Page 2 of 24 by calculating the area under the receiver-operating characteristic (ROC) curve (AUC) and optimal score sensitivity and specificity were determined. Results: A robust diabetes risk score model was produced, which composed of eight variables (age, gender, education level, marital status, place of residence, hypertension, smoking status and body mass index) with an optimal cutoff point of ≥15 to classify persons with possible prevalent T2DM. At this cutoff point, the model had a sensitivity of 71.1%, specificity of 74.4% and AUC of 0.80 (95% CI) 0.7–0.82, when internally validated (in the WHS 2008 cohort). When the model was externally validated (using the Sur 2006 cohort), the optimal cutoff point for the score was ≥13, with a lower sensitivity (54%), higher specificity (79%) and an AUC of 0.74 (95% CI 0.70–0.78). In contrast, test of the old Omani, Kuwaiti, Saudi and Finnish diabetes risk scores, in both of our study populations, showed poor performance of these models among Omanis with poor sensitivity (29% to 63.5%) and reasonable specificity (70% to 80%). Conclusion: The developed diabetes risk score for screening prevalent T2DM, provides an easy-to-use self-administered tool to identify most individuals at risk of this condition in Oman. The score incorporates eight diabetes-associated risk factors that can also act as a tool to increase people’s awareness about the importance of diabetes-related risk factors and provide information for policy makers to establish a diabetes prevention programs.

158Prediction of diabetes and hypertension by opportunistic screening: A facility based study from rural Jodhpur

Background Nearly half of population with Diabetes and Hypertension is estimated to be undetected in India. The objectives of this study were to conduct opportunistic screening for Diabetes and Hypertension coming to OPD of health centres under Department of Community Medicine and Family Medicine, AIIMS Jodhpur, India and to develop the models for prediction of Diabetes and Hypertension. Methods Time bound study was conducted at three rural health centres between 2018-19. A total of 942 patients aged ≥30 years were screened. Data was recorded using Epicollect5. Risk assessment was done by using Indian Diabetes risk score (IDRS), Community based assessment checklist (CBAC), Waist Hip Ratio, & BMI. Random and fasting capillary blood sugar and BP was measured. Results The mean age of the participants was 52.4 ± 13.5 years. As much as 446 (47.4%) had IDRS score of ≥ 60 and 276 (29.3%) had CBAC score of ≥ 4. RBS level of ≥ 140mg/dl was found among 223 participants, of these, 42.5% were diagnosed to be diabetic on FBS. One-fourth (25.6%) were estimated to be hypertensive. Physical activity and hypertension were best predicting the diabetes (r2= 90.8), while hypertension was best predicted by age and BMI (r2= 74.3). Conclusions Prevalence of diabetes and hypertension was in accordance with the reported prevalence in the country. As compared to existing models, less number of prediction variables were identified for NCDs. Key messages The study highlights the need for implementation of hospital based opportunistic screening and point out the necessity to revise the existing prediction models for NCDs.

Comparing non-invasive diabetes risk scores for detecting patients in clinical practice: a cross-sectional validation study

Background: Type 2 diabetes (T2DM) is a significant cause of morbidity and mortality, thus early identification is of paramount importance. A high proportion of T2DM cases are undiagnosed highlighting the importance of effective detection methods such as non-invasive diabetes risk scores (DRSs). Thus far, no DRS has been validated in an Irish population. Therefore, the aim of this study was to compare the ability of nine DRSs to detect T2DM cases in an Irish population. Methods: This was a cross-sectional study of 1,990 men and women aged 46–73 years. Data on DRS components were collected from questionnaires and clinical examinations. T2DM was determined according to a fasting plasma glucose level ≥7.0 mmol/l or a glycated haemoglobin A1c level ≥6.5% (≥48 mmol/mol). Receiver operating characteristic curve analysis assessed the ability of DRSs and their components to discriminate T2DM cases. Results: Among the examined scores, area under the curve (AUC) values ranged from 0.71–0.78, with the Cambridge Diabetes Risk Score (AUC=0.78, 95% CI: 0.75–0.82), Leicester Diabetes Risk Score (AUC=0.78, 95% CI: 0.75–0.82), Rotterdam Predictive Model 2 (AUC=0.78, 95% CI: 0.74–0.82) and the U.S. Diabetes Risk Score (AUC=0.78, 95% CI: 0.74–0.81) demonstrating the largest AUC values as continuous variables and at optimal cut-offs. Regarding individual DRS components, anthropometric measures displayed the largest AUC values. Conclusions: The best performing DRSs were broadly similar in terms of their components; all incorporated variables for age, sex, BMI, hypertension and family diabetes history. The Cambridge Diabetes Risk Score, had the largest AUC value at an optimal cut-off, can be easily accessed online for use in a clinical setting and may be the most appropriate and cost-effective method for case-finding in an Irish population.