Diabetes mellitus is a common metabolic disorder that restricts the quality of life of involved patients worldwide. As per National Non-Communicable Disease (NCD) Monitoring Survey in March 2022, in India, the prevalence of diabetes in adults has increased up to 9.3% with only 45.8% of the population aware of their diabetic status [1].

Now a days, non-invasive risk scores are more widely accepted by the public compared to invasive procedures for screening purposes as they are more cost-effective and feasible for widespread usage [2].

Indian Diabetic Risk Score (IDRS) is one such risk score developed by Dr. Mohan V and his colleagues at Madras Diabetes Research Foundation (MDRF), Chennai in the year 2005 from their ongoing cohort Chennai Urban Rural Epidemiology Study (CURES) [3].

IDRS uses 2 modifiable (waist circumference and physical activity) and 2 non-modifiable (age and family history) parameters to identify the undetected and high-risk individuals. The score ranges from a minimum score of 0 to a maximum score of 100. Study patients with a score of 60 or above are at high risk of developing diabetes (Figure 1) [4].

Early detection, initiation of appropriate intervention and monitoring for good diabetic control can help in delaying the course of diabetes and related complications. The current study is undertaken in a tertiary care hospital in Bangalore, to study the correlation of glycaemic index and Indian Diabetic Risk Score in Type 2 DM.

Figure 1: Indian Diabetic Risk Score [4]

In this cross-sectional observational study, newly diagnosed patients who came to the outpatient or inpatient department of tertiary care hospital and fulfilled the inclusion criteria were enrolled in the study from November 2021 to April 2022. Detailed history and thorough general examination including anthropometric measurements and systemic examination of the individual was done. Risk factor profile was found using the Indian Diabetic Risk Score. Glycaemic index was measured by testing HbA1c levels.

Inclusion Criteria

• Individuals aged above 25 years

• Individuals who have given consent for study

Exclusion Criteria 

• Previously known cases of diabetes

• Individuals on long term Steroids

• Known cases of hypothyroidism (both clinical and subclinical)

• Women with history of gestational Diabetes

• Pregnant females

• Individuals who denied for giving consent

Anthropometric Measurements

Waist circumference was measured in the standing position by placing a plastic tape horizontally midway between the 12th rib and iliac crest on the mid-axillary line. The measurements were repeated twice by using the same device and the mean value was recorded.

Body mass index estimation: Weight was recorded in kilogram (kg) with the subject standing on the weighing machine without shoes. The same weighing machine was used for all the study patients. Height was recorded in centimetres with the subject standing erect, barefooted with both feet together and looking straight ahead. BMI was calculated from the formula: 

BMI = weight in kilogram/square of height in meters

Categorisation of patients: Patients were classified according to the Indian Diabetic Risk score as [5]:

• High Risk- IDRS Score >60 

• Moderate Risk- IDRS Score 30-50 

• Low Risk- IDRS Score 0-20

Study Design

Cross-sectional study.

Statistical Analysis

Analysis of data was done using Statistical package for social science 22.00 (SPSS 22.00 for windows; SPSS Inc., Chicago, USA). For each assessment point, data were statistically analysed using factorial ANOVA. Difference between two groups were determined using chi square test and the level of significance was set at p<0.05.

A total of 88 newly diagnosed diabetics aged above 25 years were included in the study.  Out of them, 37 (42.04%) were females and 51 (57.96%) were males. Mean age of study subjects was found to be 53.11±13.21 years. In the present study, we found that 8 patients (9.09%) were aged <35 years, 27 patients (30.68%) were aged between 35-49 years and 53 patients (39.99%) were more than 50 years old. 

Out of 88 patients, 25 (28.41%) were smokers, 63 (71.59%) were non-smokers and 37 (42.05%) had history of consumption of alcohol and 51 (57.95%) patients never consumed alcohol. A total of 12 patients (13.63%) were found to have family history of diabetes in both parents, 19 patients (21.59%) had history of diabetes in either parent and 57 (64.78%) had no history of diabetes in parents. History of hypertension was found in 20 patients (22.72%).

In our study, out of 88 diabetics, 77 patients (87.51%) had normal BMI, 5 patients (5.68%) were overweight and 6 patients (6.81%) were in the obese category. None of the patient in this study population was found to be in underweight category. Overall, 3 patients (3.41%) had low risk, 43 (48.87%) had moderate risk and 42 (47.72%) had high risk of development of diabetes according to Indian Diabetic Risk Score (Table 1).

Table 1: Distribution of Indian Diabetic Risk Score (IDRS) in Study Population

Association between Different Variables of Indian Diabetic Risk Score and Diabetes 

According to Indian Diabetic Risk Score, the study population was divided into low, moderate or high-risk category depending on age, family history, waist circumference and physical activity (Table 2).

Table 2: Association between different Variables of Indian Diabetic Risk Score and Diabetes

The results of the present study found a significant association between Indian Diabetes Risk Score, family history of diabetes, higher waist circumference and sedentary lifestyle (p<0.001). However, when age was compared to diabetes risk, it was found to be statistically insignificant in our study.

Out of the total 88 newly diagnosed diabetes patients, 42 patients (47.72%) and 85 patients (96.59%) had IDRS score >60 and >30 respectively. When the HbA1c level was analysed for diabetes control, it was found that all 42 patients (100%) under high risk IDRS category had poor glycaemic control (HbA1C levels >8%). Among the 42 patients with moderate risk, 24 patients (57.14%) had HbA1c levels >8%, 16 patients (38.09%) had HbA1c levels between 7-8% and rest 2 patients (4.77%) had HbA1c between 6.5-7%. Among the 4 patients with low IDRS score, 25% had HbA1c levels between 6.5-7% and rest 3 patients (75%) had HbA1c levels between 6.5-7% (Table 3 and Figure 2). The results indicated that the patients with higher IDRS score had poorer glycaemic control compared to those with lower IDRS score (p value <0.01).

Table 3: Correlation between Indian Diabetic Risk Score and Glycaemic Index

Figure 2: Correlation between Indian Diabetic Risk Score and Glycaemic Index

In a developing country like India, where there are a large number of diabetics and many of the cases remaining undiagnosed, risk scores would render great help in the early detection and management of prediabetes and diabetes [6]. Early interventions can further help in delaying the course of diabetes and development of its complications. 

The present study is conducted to study the correlation of glycaemic index and Indian Diabetic Risk Score in newly diagnosed Type 2 diabetics. 

In our study, high diabetes risk is found among 50% of patients aged 25-35 years, 44.44% of patients aged between 36-49 years and 50.94% of the patients aged more than 50 years respectively, indicating that there is no association between diabetes risk and age.

In our study, among the 88 diabetic patients, 51 patients (57.96%) are males. Out of these 51 patients, 10 patients (19.61%) have waist circumference more than 100 cm and all these 10 patients (100%) are found to have high diabetes risk as per IDRS compared to 25 male patients with waist circumference of <90 cm, among whom only 5 patients (20%) have high IDRS. Among the 37 females, 8 patients (21.62%) have waist circumference more than 100 cm and all these 8 patients (100%) are found to have high diabetes risk as per IDRS compared to 17 patients with waist circumference of <80 cm, among whom only 2 patients (11.76%) have high IDRS. This indicates that increasing waist circumference is significantly associated with increased risk of developing diabetes both in males and females (p value <0.003 and <0.004 respectively).

Similar results are obtained in the study conducted by Khan et al. [7] on the validity of Indian Diabetic risk score among 405 study participants in which it is found that the maximum number i.e. 194 (47.9%) of the patients are having waist circumference 80-89 cm in females and 90-99 cm in males, followed by 162 patients (40%) with waist circumference ≥90 cm in females and ≥100 cm in males. Only 49 (12.1%) individuals are normal. Out of 198 (48.88%) patients who are obese, 79.3% are found at high risk for diabetes. The results of their study showed a statistically significant association between higher waist circumference and diabetes risk.

In our study, 83.33% patients with history of diabetes in both parents and 63.63% patients with history of diabetes in either parent have high risk. Among those with no family history, 25.58% are at high risk of diabetes as per IDRS indicating family history of diabetes increases the risk of developing diabetes (p value <0.001). Similar results are obtained in a study done by Dudeja et al. [3] where out of 155 patients included, 41 patients were newly diagnosed diabetes and among these, 51.21% family history of diabetes in both parents (p value 0.007).

A sedentary lifestyle increases the risk of developing diabetes. Being physically active has various advantageous effects as it helps in reducing body fat, increases body muscle mass, relieves stress and promotes overall well-being. It also helps in the prevention of diabetes and delaying complications [8]. In the present study, only 4 patients (4.54%) did regular exercise and strenuous work and all of them are found to have low risk. Among those with sedentary lifestyle, 66.66% had high risk of diabetes indicating that sedentary lifestyle increases diabetes risk (p value <0.0001).

Similar results are obtained in a study done by Patil et al. [9] in the slums of Maharashtra among 425 patients, in which among the 255 patients with a sedentary lifestyle, 236 patients (92.6%) have a moderate to high risk of developing diabetes (p value <0.0001).

When the HbA1c level is analysed for diabetes control, it is found that all 42 patients (100%) under high risk IDRS category have poor glycaemic control (HbA1C levels >8%). 57.14% patients in moderate risk category have HbA1c levels >8%. The results indicated that higher the IDRS score, poorer is the glycaemic control (p value <0.01).

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3. Dudeja, P. et al. “Performance of Indian Diabetes Risk Score (IDRS) as a screening tool for diabetes in an urban slum.” Medical Journal Armed Forces India, vol. 73, no. 2, 2017, pp. 123–128.

4. Joshi, S.R. “Indian diabetes risk score.” Journal of the Association of Physicians of India, vol. 53, 2005, pp. 755–757.

5. Low, S. et al. “Effect of long-term glycemic variability on estimated glomerular filtration rate decline among patients with type 2 diabetes mellitus: insights from the diabetic nephropathy cohort in Singapore.” Journal of Diabetes, vol. 9, no. 10, 2017, pp. 908–919.

6. Namdev, G. and V. Narkhede. “A study on validity of Indian diabetes risk score for screening of diabetes mellitus among rural adult population at a rural health training Centre.” International Journal of Community Medicine and Public Health, vol. 5, no. 12, 2018, pp. 5295.

7. Sonkar, S. et al. “Validity of Indian diabetes risk score and its association with body mass index and glycosylated hemoglobin for screening of diabetes in and around areas of Lucknow.” Journal of Family Medicine and Primary Care, vol. 6, no. 2, 2017, pp. 366.

8. Ram, R. et al. “An Epidemiological study on risk factors of diabetes mellitus among patients attending a medical college Hospital in Kolkata, West Bengal.” Journal of the Indian Medical Association, vol. 104, no. 8, 2006, pp. 428–430.

9. Patil, R. and J. Gothankar. “Assessment of risk of type 2 diabetes using the Indian Diabetes Risk Score in an Urban Slum of Pune, Maharashtra, India: A Cross-Sectional Study.” WHO South-East Asia Journal of Public Health, vol. 5, no. 1, 2016, pp. 53.