scholarly journals Community Based Screening for Diabetes and Prediabetes using the Indian Diabetes Risk Score among Adults in a Semi-Urban Area in Kathmandu, Nepal

2019 ◽  
Vol 21 (1) ◽  
pp. 12-20
Author(s):  
Vinutha Silvanus ◽  
N Dhakal ◽  
A Pokhrel ◽  
BK Baral ◽  
PP Panta
Keyword(s):  
High Risk ◽  
Urban Area ◽  
Risk Score ◽  
Plasma Glucose ◽  
Diabetes Risk ◽  
Low Risk ◽  
Screening Tools ◽  
Community Based ◽  
Family History Of Diabetes ◽  
Diabetes Risk Score

 Diabetes has been recognized as a “global health emergency” with an estimated 9% of adults being affected. However, about half of these adults remain undiagnosed. Conventional screening tools like fasting plasma glucose (FPG), oral glucose tolerance testing (OGTT) and glycosylated haemoglobin (HbA1c) can be inconvenient and expensive in a community-based setting. The Indian Diabetes Risk Score (IDRS) is a simple, non-invasive tool which has been validated for use in the Indian population. Age, abdominal obesity, family history of diabetes and physical activity levels have been weighted for a maximum score of 100. Persons with IDRS of <30 are categorized as low risk, 30-50 as medium risk and those with > 60 as high risk for diabetes. A community based, cross-sectional, analytical study was planned to assess the performance of IDRS among adults in a semi-urban area in Kathmandu, Nepal. A total of 256 (170 female, 86 male) persons without diabetes from 260 households were screened during the study period. A majority (46.09%) were classified as high risk, 44.53% as moderate risk and 9.38% as low risk for developing diabetes. Among them, 162 (63.28%) volunteered for definitive testing. The prevalence of undiagnosed diabetes and prediabetes was 4.32% (95% CI: 1.75% to 8.70%) and 7.14% (95% CI: 3.89% to 12.58%) respectively. IDRS predicted the combined risk of diabetes and prediabetes with sensitivity of 84.21% and specificity of 55.24% in adults with score of 60 and above. The area under the ROC curve (AUC) of IDRS for identifying diabetes and prediabetes was 0.69 as compared to the gold standard (2hour Plasma Glucose) AUC of 0.98. IDRS may be a suitable screening tool for diabetes and prediabetes in the adult Nepalese study population.

scholarly journals Assessment of risk of developing diabetes using Indian diabetes risk score in the urban field practice area of Rajarajeswari Medical College and Hospital, Bangalore

2019 ◽  
Vol 7 (1) ◽  
pp. 170
Author(s):  
Nazia N. Shaik ◽  
Swapna M. Jaswanth ◽  
Shashikala Manjunatha
Keyword(s):  
At Risk ◽  
High Risk ◽  
Risk Score ◽  
Diabetes Risk ◽  
Low Risk ◽  
Risk Category ◽  
Moderate Risk ◽  
Medical College ◽  
Field Practice ◽  
Diabetes Risk Score

Background: Diabetes is one of the largest global health emergencies of the 21st century. As per International Federation of Diabetes some 425 million people worldwide are estimated to have diabetes. The prevalence is higher in urban versus rural (10.2% vs 6.9%). India had 72.9 million people living with diabetes of which, 57.9% remained undiagnosed as per the 2017 data. The objectives of the present study were to identify subjects who at risk of developing Diabetes by using Indian diabetes risk score (IDRS) in the Urban field practice area of Rajarajeswari Medical College and Hospital (RRMCH).Methods: A cross sectional study was conducted using a Standard questionnaire of IDRS on 150 individuals aged ≥20 years residing in the Urban field practice area of RRMCH. The subjects with score <30, 30-50, >or =60 were categorized as having low risk, moderate risk and high risk for developing diabetes type-2 respectively.Results: Out of total 150 participants, 36 (24%) were in high-risk category (IDRS≥60), the majority of participants 61 (41%) were in the moderate-risk category (IDRS 30–50) and 53 (35%) participants were found to be at low-risk (<30) for diabetes. Statistical significant asssociation was found between IDRS and gender, literacy status, body mass index (p<0.0000l).Conclusions: It is essential to implement IDRS which is a simple tool for identifying subjects who are at risk for developing diabetes so that proper intervention can be carried out at the earliest to reduce the burden of diabetes.

scholarly journals Diabetes Risk Score in a Young Student Population in Jordan: A Cross-Sectional Study

2017 ◽  
Vol 2017 ◽  
pp. 1-5 ◽  
Author(s):  
Abdel-Ellah Al-Shudifat ◽  
Amjad Al-Shdaifat ◽  
Ahmad Ali Al-Abdouh ◽  
Mohammad Ibrahim Aburoman ◽  
Sara Mohammad Otoum ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Risk Score ◽  
Plasma Glucose ◽  
Risk Group ◽  
High Risk Group ◽  
Student Population ◽  
Diabetes Risk ◽  
Young Student ◽  
Diabetes Risk Score

Background. The Middle East is the home to the most obese population in the world, and type 2 diabetes mellitus is endemic in the region. However, little is known about risk factors for diabetes in the younger age groups. Methods. The Finnish Diabetes Risk Score (FINDRISC) is a simple, validated tool to identify persons at risk of diabetes. We investigated students at Hashemite University in Jordan with FINDRISC and measured fasting plasma glucose in those who were categorized in the high-risk group. Results. Overall, 1821 students (881 [48.4%] female) were included in the study. Risk factors for diabetes were common: 422 (23.2%) were overweight or obese and 497 (27.3%) had central obesity. Using the FINDRISC score, 94 (5.2%) students were at moderate risk and 32 (1.8%) at high risk of diabetes. The mean FINDRISC score was significantly higher in men than women (5.9 versus 5.4; p=0.002). Twenty-eight students in the high-risk group had a subsequent plasma glucose measurement, and 8 (29%) of them fulfilled the diagnostic criteria for diabetes. Conclusions. Risk factors for diabetes were common in a young student population in Jordan, suggesting that preventive measures should be initiated early in adulthood to turn the diabetes epidemic in the region.

scholarly journals A diabetes risk score for Qatar utilizing a novel mathematical modeling approach to identify individuals at high risk for diabetes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Susanne F. Awad ◽  
Soha R. Dargham ◽  
Amine A. Toumi ◽  
Elsy M. Dumit ◽  
Katie G. El-Nahas ◽  
...  
Keyword(s):  
High Risk ◽  
Sensitivity And Specificity ◽  
Risk Score ◽  
Area Under The Curve ◽  
Diabetes Risk ◽  
Predictive Values ◽  
Predictive Variables ◽  
Comparable Performance ◽  
Representative Random Sample ◽  
Diabetes Risk Score

AbstractWe developed a diabetes risk score using a novel analytical approach and tested its diagnostic performance to detect individuals at high risk of diabetes, by applying it to the Qatari population. A representative random sample of 5,000 Qataris selected at different time points was simulated using a diabetes mathematical model. Logistic regression was used to derive the score using age, sex, obesity, smoking, and physical inactivity as predictive variables. Performance diagnostics, validity, and potential yields of a diabetes testing program were evaluated. In 2020, the area under the curve (AUC) was 0.79 and sensitivity and specificity were 79.0% and 66.8%, respectively. Positive and negative predictive values (PPV and NPV) were 36.1% and 93.0%, with 42.0% of Qataris being at high diabetes risk. In 2030, projected AUC was 0.78 and sensitivity and specificity were 77.5% and 65.8%. PPV and NPV were 36.8% and 92.0%, with 43.0% of Qataris being at high diabetes risk. In 2050, AUC was 0.76 and sensitivity and specificity were 74.4% and 64.5%. PPV and NPV were 40.4% and 88.7%, with 45.0% of Qataris being at high diabetes risk. This model-based score demonstrated comparable performance to a data-derived score. The derived self-complete risk score provides an effective tool for initial diabetes screening, and for targeted lifestyle counselling and prevention programs.

scholarly journals Prediction of the risk of developing diabetes mellitus among Bangladeshi adults by using risk assessment score

2019 ◽  
Vol 10 (1) ◽  
pp. 40-47
Author(s):  
Nazma Akter
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Risk Assessment ◽  
Blood Glucose ◽  
High Risk ◽  
Risk Score ◽  
Diabetes Risk ◽  
High Blood Glucose ◽  
History Of ◽  
Diabetes Risk Score

Background: Diabetes mellitus (DM) is considered as one of the major health problems worldwide. The rising prevalence of type 2 diabetes mellitus (T2DM) in Bangladesh is primarily attributed to rapid urbanization and associated changes in lifestyle, such as sedentary lifestyle, higher calorie food intake and stressful life. Studies support the utilization of riskassessment scoring systems in quantifying individual’s risk for developing T2DM. Thus, a simple risk-assessment scoring system for early screening of T2DM among Bangladeshi adults will be beneficial to identify the high-risk adults and thus taking adequate preventive measures in combating DM.The purpose of the study was to calculate the risk assessment score of developing T2DM within 10 years among Bangladeshi adults. Methods: The cross-sectional observational study was carried out in the outpatient department (OPD) of Medicine, MARKS Medical College & Hospital, a tertiary care hospital in Dhaka, Bangladesh from February 2018 to July 2018 among randomly sampled 205 adult subjects. Subjects undiagnosed with diabetes mellitus and had previous history of high blood glucose during pregnancy or other health examination (i.e. impaired fasting glucose, impaired glucose tolerance or gestational diabetes mellitus) were included. From a review of literature regarding risk factors of developing DM in Bangladesh, the Finnish Diabetes Risk Score (FINDRISC) system was found to be more useful for the Bangladeshi adults. The Finnish Diabetes Risk Score (FINDRISC) questionnaire was used to collect the data including demographic characteristics and different risk factors and to calculate total risk score for predicting the risk of developing T2DM within 10 years. Results: Among 205 subjects, male and female were 57.1% and 42.9% respectively. The Mean (±SD) age of the study subjects was 37.64±1.07 years. In this study, both non-modifiable and modifiable risk factors showed statistically significant association with the FINDRISC among Bangladeshi adults (p<0.05). There was a significant association among FINDRISC with history of previous high blood glucose, and treated hypertensive Bangladeshi adults.33.65% of the Bangladeshi adults had slightly elevated diabetes risk score (DRS). This study predicts that 17.55% of the Bangladeshi adults may have moderate to high risk to develop T2DM within the consecutive 10 years. Conclusion: This study provides a simple, feasible, non-invasive and convenient screening FINDRISC tool that identifies individuals at risk of having T2DM. People with high risk of DM should be referred for early intervention and changes to a healthy lifestyle and primary prevention to prevent or delay the onset of T2DM. Birdem Med J 2020; 10(1): 40-47

Derivation of a diabetes risk score and validation of existing screening tools in rural Kerala, India

2011 ◽  
Vol 152 ◽  
pp. S32-S33
Author(s):  
Thirunavukkarasu Sathish ◽  
Kannan Srinivasan ◽  
P.S. Sarma ◽  
K.R. Thankappan
Keyword(s):  
Risk Score ◽  
Diabetes Risk ◽  
Screening Tools ◽  
Diabetes Risk Score

scholarly journals Prediction of risk of type 2 diabetes mellitus using Indian diabetes risk score: a cross sectional study in urban field practice area of a medical college, Bagalkot

2018 ◽  
Vol 5 (7) ◽  
pp. 2853
Author(s):  
Basavaraj S. Mannapur ◽  
Bhagyalaxmi S. Sidenur ◽  
Ashok S. Dorle
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cross Sectional Study ◽  
Diabetes Risk ◽  
Risk Category ◽  
Cross Sectional ◽  
Medical College ◽  
High Risk Category ◽  
Field Practice ◽  
Diabetes Risk Score

Background: Diabetes is considered as a global emergency where a person dies from diabetes every 6 seconds and diabetes is seen on 1 in 11 adults. Identification of individuals who are at risk is very much necessary to prevent diabetes in India. IDRS could also help to detect people at risk of having prediabetes. The objective of the study were to estimate the prevalence of diabetes mellitus in the age group of >20 years in urban field practice area of S.N. Medical college, Bagalkot and to identify high risk subjects using Indian diabetes risk score (IDRS).Methods: A cross sectional study was done in urban field practice area of S.N. Medical College among adults >20 years of age with sample size of 207. Systematic random sampling was used to select the subjects. Data was collected using standardised questionnaire which included socio-demographic profile, standard glucometer was used to measure random blood glucose for all participants. IDRS was used to ascertain the risk of developing diabetes. Data was analysed using Pearson’s Chi square test and Fischer exact.Results: The overall prevalence of diabetes was 14.1%. Among 206 subjects, 4.8% were in low risk category. 39.6% and 55.1% were in moderate and high risk category respectively. Total of 11 subjects were newly diagnosed in our study. Among them 10 subjects were in the high risk category and 1 was in the low risk category. Sensitivity of IDRS was 90%, specificity 50%, positive predictive value 43.8% and negative predictive value 96.74%..Conclusions: This study estimates the usefulness of simplified Indian diabetes risk score for identifying high risk diabetic subjects in the community. It can be used routinely in commu­nity-based screening to find out high risk people for diabetes so that proper intervention can be done to reduce the burden of the disease. 

scholarly journals Community-Based Diabetes Screening and Risk Assessment in Rural West Virginia

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Ranjita Misra ◽  
Cindy Fitch ◽  
David Roberts ◽  
Dana Wright
Keyword(s):  
Risk Assessment ◽  
Family History ◽  
High Risk ◽  
West Virginia ◽  
Diabetes Risk ◽  
Older Age ◽  
Community Based ◽  
Family History Of Diabetes ◽  
History Of ◽  
Rural West Virginia

This project utilized a cross-sectional study design to assess diabetes risk among 540 individuals from 12 counties using trained extension agents and community organizations in West Virginia. Individuals were screened for diabetes using (1) the validated 7-item diabetes risk assessment survey and (2) hemoglobin A1c tests. Demographic and lifestyle behaviors were also collected. The average age, body mass index, and A1c were51.2±16.4,31.1±7.5, and5.8±0.74, respectively. The majority were females, Non-Hispanic Whites with no prior diagnosis of diabetes. Screenings showed that 61.8% of participants were at high risk for diabetes. Family history of diabetes (siblings or parents), overweight or obese status, sedentary lifestyle, and older age were commonly prevalent risk factors. Higher risk scores computed from the 7-item questions correlated positively with higher A1c (r=0.221,P<0.001). In multivariate logistic regression analyses, higher diabetes risk was predicted by obesity, older age, family history of hypertension, and gestational diabetes. Females were 4 times at higher risk than males. The findings indicated that community-based screenings were an effective way to assess diabetes risk in rural West Virginia. Linking diabetes screenings with referrals to lifestyle programs for high risk individuals can help reduce the burden of diabetes in the state.

A Mobile App for Identifying Individuals With Undiagnosed Diabetes and Prediabetes and for Promoting Behavior Change: 2-Year Prospective Study (Preprint)

2018 ◽  
Author(s):  
Angela YM Leung ◽  
Xin Yi Xu ◽  
Pui Hing Chau ◽  
Yee Tak Esther Yu ◽  
Mike KT Cheung ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Risk Group ◽  
Mobile App ◽  
Diabetes Risk ◽  
Undiagnosed Diabetes ◽  
Risk Level ◽  
Optimal Cutoff ◽  
Diabetes Risk Score

BACKGROUND To decrease the burden of diabetes in society, early screening of undiagnosed diabetes and prediabetes is needed. Integrating a diabetes risk score into a mobile app would provide a useful platform to enable people to self-assess their risk of diabetes with ease. OBJECTIVE The objectives of this study were to (1) assess the profile of Diabetes Risk Score mobile app users, (2) determine the optimal cutoff value of the Finnish Diabetes Risk Score to identify undiagnosed diabetes and prediabetes in the Chinese population, (3) estimate users’ chance of developing diabetes within 2 years of using the app, and (4) investigate high-risk app users’ lifestyle behavior changes after ascertaining their risk level from the app. METHODS We conducted this 2-phase study among adults via mobile app and online survey from August 2014 to December 2016. Phase 1 adopted a cross-sectional design, with a descriptive analysis of the app users’ profile. We used a Cohen kappa score to show the agreement between the risk level (as shown in the app) and glycated hemoglobin test results. We used sensitivity, specificity, and area under the curve to determine the optimal cutoff value of the diabetes risk score in this population. Phase 2 was a prospective cohort study. We used a logistic regression model to estimate the chance of developing diabetes after using the app. Paired t tests compared high-risk app users’ lifestyle changes. RESULTS A total of 13,289 people used the app in phase 1a. After data cleaning, we considered 4549 of these as valid data. Most users were male, and 1811 (39.81%) had tertiary education or above. Among them, 188 (10.4%) users agreed to attend the health assessment in phase 1b. We recommend the optimal value of the diabetes risk score for identifying persons with undiagnosed diabetes and prediabetes to be 9, with an area under the receiver operating characteristic curve of 0.67 (95% CI 0.60-0.74), sensitivity of 0.70 (95% CI 0.58-0.80), and specificity of 0.57 (95% CI 0.47-0.66). At the 2-year follow-up, people in the high-risk group had a higher chance of developing diabetes (odds ratio 4.59, P=.048) than the low-risk group. The high-risk app users improved their daily intake of vegetables (baseline: mean 0.76, SD 0.43; follow-up: mean 0.93, SD 0.26; t81=–3.77, P<.001) and daily exercise (baseline: mean 0.40, SD 0.49; follow-up: mean 0.54, SD 0.50; t81=–2.08, P=.04). CONCLUSIONS The Diabetes Risk Score app has been shown to be a feasible and reliable tool to identify persons with undiagnosed diabetes and prediabetes and to predict diabetes incidence in 2 years. The app can also encourage high-risk people to modify dietary habits and reduce sedentary lifestyle.

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