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)...

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Published inIndian Journal of Medical Research Vol. 157; no. 4; pp. 239 - 249
Main Authors Deepa, Mohan, Elangovan, Nirmal, Venkatesan, Ulagamathesan, Das, Hiranya Kumar, Jampa, Lobsang, Adhikari, Prabha, Joshi, Prashant P., Budnah, Richard O., Suokhrie, Vizolie, John, Mary, Tobgay, Karma Jigme, Subashini, Radhakrishnan, Pradeepa, Rajendra, Anjana, Ranjit Mohan, Mohan, Viswanathan, Kaur, Tanvir, Dhaliwal, Rupinder Singh
Format Journal Article
LanguageEnglish
Published India Medknow Publications & Media Pvt Ltd 01.04.2023
Medknow Publications and Media Pvt. Ltd
Scientific Scholar
Wolters Kluwer - Medknow
Edition2
Subjects
Diabetes
Diagnosis
Evaluation
Health surveys
Medical research
Medical screening
Methods
Performance evaluation
Population-based studies
Programme: Special Report
Risk factors
Surveys
India
screening
type 2 diabetes
undiagnosed diabetes
high-risk group
Indian Diabetes Risk Score
Asian Indians
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Abstract 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 high-, moderate- and low-risk categories of IDRS. The ROC-AUC for the identification of diabetes was 0.697 (95% confidence interval: 0.684-0.709) for urban population and 0.694 (0.684-0.704) for rural, as well as 0.693 (0.682-0.705) for males and 0.707 (0.697-0.718) for females. MDRF-IDRS performed well when the population were sub-categorized by state or by regions. Interpretation & conclusions: Performance of MDRF-IDRS is evaluated across the nation and is found to be suitable for easy and effective screening of diabetes in Asian Indians.
AbstractList 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.Background & objectivesScreening 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.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.MethodsData 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.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 high-, moderate- and low-risk categories of IDRS. The ROC-AUC for the identification of diabetes was 0.697 (95% confidence interval: 0.684-0.709) for urban population and 0.694 (0.684-0.704) for rural, as well as 0.693 (0.682-0.705) for males and 0.707 (0.697-0.718) for females. MDRF-IDRS performed well when the population were sub-categorized by state or by regions.ResultsWe 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 high-, moderate- and low-risk categories of IDRS. The ROC-AUC for the identification of diabetes was 0.697 (95% confidence interval: 0.684-0.709) for urban population and 0.694 (0.684-0.704) for rural, as well as 0.693 (0.682-0.705) for males and 0.707 (0.697-0.718) for females. MDRF-IDRS performed well when the population were sub-categorized by state or by regions.Performance of MDRF-IDRS is evaluated across the nation and is found to be suitable for easy and effective screening of diabetes in Asian Indians.Interpretation & conclusionsPerformance of MDRF-IDRS is evaluated across the nation and is found to be suitable for easy and effective screening of diabetes in Asian Indians.
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 high-, moderate- and low-risk categories of IDRS. The ROC-AUC for the identification of diabetes was 0.697 (95% confidence interval: 0.684-0.709) for urban population and 0.694 (0.684-0.704) for rural, as well as 0.693 (0.682-0.705) for males and 0.707 (0.697-0.718) for females. MDRF-IDRS performed well when the population were sub-categorized by state or by regions. Interpretation & conclusions: Performance of MDRF-IDRS is evaluated across the nation and is found to be suitable for easy and effective screening of diabetes in Asian Indians.
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. 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. 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 high-, moderate- and low-risk categories of IDRS. The ROC-AUC for the identification of diabetes was 0.697 (95% confidence interval: 0.684-0.709) for urban population and 0.694 (0.684-0.704) for rural, as well as 0.693 (0.682-0.705) for males and 0.707 (0.697-0.718) for females. MDRF-IDRS performed well when the population were sub-categorized by state or by regions. Performance of MDRF-IDRS is evaluated across the nation and is found to be suitable for easy and effective screening of diabetes in Asian Indians.
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 high-, moderate- and low-risk categories of IDRS. The ROC-AUC for the identification of diabetes was 0.697 (95% confidence interval: 0.684-0.709) for urban population and 0.694 (0.684-0.704) for rural, as well as 0.693 (0.682-0.705) for males and 0.707 (0.697-0.718) for females. MDRF-IDRS performed well when the population were sub-categorized by state or by regions. Interpretation & conclusions: Performance of MDRF-IDRS is evaluated across the nation and is found to be suitable for easy and effective screening of diabetes in Asian Indians.
Audience Academic
Author Suokhrie, Vizolie
Elangovan, Nirmal
Jampa, Lobsang
Venkatesan, Ulagamathesan
Mohan, Viswanathan
Joshi, Prashant P.
Das, Hiranya Kumar
Dhaliwal, Rupinder Singh
Deepa, Mohan
Pradeepa, Rajendra
John, Mary
Budnah, Richard O.
Adhikari, Prabha
Anjana, Ranjit Mohan
Subashini, Radhakrishnan
Tobgay, Karma Jigme
Kaur, Tanvir
AuthorAffiliation 1 Department of Epidemiology, Diabetes Complications, Chennai, Tamil Nadu, India
11 Deparment of Internal Medicine, Christian Medical College & Hospital, Ludhiana, Punjab, India
4 Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, Chennai, Tamil Nadu, India
13 Division of Non-communicable Diseases, Indian Council of Medical Research, New Delhi, India
7 Department of Epidemiology, Yenepoya Medical College, Yenepoya University Campus, Deralakatte, Karnataka, India
8 Department of General Medicine, All India Institute of Medical Sciences, Nagpur, Maharashtra, India
9 Directorate of Health Services (MI), Shillong, Meghalaya, India
6 Directorate of Health Services, Naharlagun, Arunachal Pradesh, India
12 Department of Health Care, Human Services & Family Welfare, Government of Sikkim, Gangtok, Sikkim, India
3 Department of Biostatistics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India
10 Directorate of Health & Family Welfare, Go
AuthorAffiliation_xml – name: 2 Department of Research Operations & Diabetes Complications, Chennai, Tamil Nadu, India
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/37282387$$D View this record in MEDLINE/PubMed
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Issue 4
Keywords screening
type 2 diabetes
undiagnosed diabetes
high-risk group
Indian Diabetes Risk Score
Asian Indians
Language English
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Snippet Background & objectives: Screening of individuals for early detection and identification of undiagnosed diabetes can help in reducing the burden of diabetic...
Screening of individuals for early detection and identification of undiagnosed diabetes can help in reducing the burden of diabetic complications. This study...
Background & objectives: Screening of individuals for early detection and identification of undiagnosed diabetes can help in reducing the burden of diabetic...
Background & objectives:Screening of individuals for early detection and identification of undiagnosed diabetes can help in reducing the burden of diabetic...
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StartPage 239
SubjectTerms Diabetes
Diagnosis
Evaluation
Health surveys
Medical research
Medical screening
Methods
Performance evaluation
Population-based studies
Programme: Special Report
Risk factors
Surveys
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Title 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)
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