Validation of simplified Indian Diabetes Risk Score for screening undiagnosed diabetes in an urban setting of Haryana

A meta-analysis of diabetes risk prediction models applied to prediabetes screening

AIM

To provide a systematic overview of diabetes risk prediction models used for prediabetes screening to promote primary prevention of diabetes.

METHODS

The Cochrane, PubMed, Embase, Web of Science and China National Knowledge Infrastructure (CNKI) databases were searched for a comprehensive search period of 30 August 30, 2023, and studies involving diabetes prediction models for screening prediabetes risk were included in the search. The Quality Assessment Checklist for Diagnostic Studies (QUADAS-2) tool was used for risk of bias assessment and Stata and R software were used to pool model effect sizes.

RESULTS

A total of 29 375 articles were screened, and finally 20 models from 24 studies were included in the systematic review. The most common predictors were age, body mass index, family history of diabetes, history of hypertension, and physical activity. Regarding the indicators of model prediction performance, discrimination and calibration were only reported in 79.2% and 4.2% of studies, respectively, resulting in significant heterogeneity in model prediction results, which may be related to differences between model predictor combinations and lack of important methodological information.

CONCLUSIONS

Numerous models are used to predict diabetes, and as there is an association between prediabetes and diabetes, researchers have also used such models for screening the prediabetic population. Although it is a new clinical practice to explore, differences in glycaemic metabolic profiles, potential complications, and methods of intervention between the two populations cannot be ignored, and such differences have led to poor validity and accuracy of the models. Therefore, there is no recommended optimal model, and it is not recommended to use existing models for risk identification in alternative populations; future studies should focus on improving the clinical relevance and predictive performance of existing models.

Risk assessment of diabetes using the Indian Diabetes Risk Score among older adults: Secondary analysis from the Longitudinal Ageing Study in India

BACKGROUND

The Indian Diabetes Risk Score (IDRS) is a simple tool to assess the probability of an individual having type 2 diabetes (T2DM) but its applicability in community-dwelling older adults is lacking. This study aimed to estimate the risk of T2DM and its determinants among older adults without prior diabetes (DM) using the IDRS, while also assessing its sensitivity and specificity in individuals with a history of diabetes.

METHODS

We analyzed cross-sectional data from the Longitudinal Ageing Study in India (LASI) wave-1 (2017-18). IDRS was calculated amongst individuals aged ≥45 years considering waist circumference, physical activity, age and family history of DM. Risk was categorized as high (≥60), moderate (30-50), and low (<30).

RESULTS

Among 64541 individuals, 7.27 % (95 % CI: 6.78, 7.80) were at low risk, 61.80 % (95 % CI: 60.99, 62.61) at moderate risk, and 30.93 % (95 % CI: 30.19, 31.67) at high risk for T2DM. Adjusted analysis showed higher risk of T2DM among men, widowed/divorced, urban residents, minority religions, overweight, obese, and individuals with hypertension. ROC curve yielded an AUC of 0.67 (95 % CI: 0.66, 0.67, P < 0.001). The IDRS cutoff ≥50 had 73.69 % sensitivity and 51.40 % specificity for T2DM detection.

CONCLUSION

More than 9 in 10 older adults in India without history of DM have high-moderate risk of T2DM when assessed with the IDRS risk-prediction tool. However, the low specificity and moderate sensitivity of IDRS in existing DM cases constraints its practical utility as a decision tool for screening.

Effects of a dietary intervention on cardiometabolic risk and food consumption in a workplace

BACKGROUND

Worksite-based health programs have shown positive impacts on employee health and have led to significant improvements in cardiovascular risk factor profiles. We aimed to determine the effect of cafeteria intervention on cardio-metabolic risk factors diet in a worksite setting (Dhulikhel Hospital) in Nepal.

METHODS

In this one-arm pre-post intervention study, we recruited 277 non-pregnant hospital employees aged 18-60 with prediabetes or pre-hypertension. The study was registered in clinicaltrials.gov (NCT03447340; 2018/02/27). All four cafeterias in the hospital premises received cafeteria intervention encouraging healthy foods and discouraging unhealthy foods for six months. We measured blood pressure, fasting glucose level, glycated hemoglobin, cholesterol in the laboratory, and diet intake (in servings per week) using 24-hour recall before and six months after the intervention. The before and after measures were compared using paired-t tests.

RESULTS

After six months of cafeteria intervention, the median consumption of whole grains, mono/polyunsaturated fat, fruits, vegetable and nuts servings per week increased by 2.24(p<0.001), 2.88(p<0.001), 0.84(p<0.001) 2.25(p<0.001) and nuts 0.55 (p<0.001) servings per week respectively. The median consumption of refined grains decreased by 5.07 servings per week (p<0.001). Mean systolic and diastolic blood pressure decreased by 2 mmHg (SE = 0.6; p = 0.003) and 0.1 mmHg (SE = 0.6; p = 0.008), respectively. The low-density lipoprotein (LDL) was significantly reduced by 6 mg/dL (SE = 1.4; p<0.001).

CONCLUSION

Overall, we found a decrease in consumption of refined grains and an increase in consumption of whole grains, unsaturated fats, fruits, and nuts observed a modest reduction in blood pressure and LDL cholesterol following a 6-month cafeteria-based worksite intervention incorporating access to healthy foods.

Targeted screening for prediabetes and undiagnosed diabetes in a community setting in India

BACKGROUND AND OBJECTIVES

Data to support the use of risk scores in screening programs to detect people with prediabetes and undiagnosed diabetes in low- and middle-income countries are limited. We evaluated a targeted screening program involving a diabetes risk score in a community setting in India in terms of its uptake, yield, and costs.

METHODS

In the Kerala Diabetes Prevention Program, 2586 individuals (age 30-60 years) without known diabetes were screened using a two-step procedure. Step 1: screening with the Indian Diabetes Risk Score at participants' homes by trained non-medical staff. Step 2: oral glucose tolerance test (OGTT) among those with IDRS score ≥60 ("screen-positive") at community-based clinics. Screening costs were expressed in 2013 US dollars.

RESULTS

96.3% of those invited for the IDRS screening consented and 79.1% of screen-positives attended clinics for an OGTT. Older age and male gender were associated with higher IDRS uptake. Female gender, higher monthly household expenditure, and higher IDRS score were associated with higher OGTT uptake. The number needed to screen (yield) to detect one person with prediabetes and undiagnosed diabetes was two and six, respectively. The average screening cost of identifying one person with prediabetes and undiagnosed diabetes was $33.8 and $116.5, respectively.

CONCLUSION

This targeted screening program had a high uptake and high yield for prediabetes and undiagnosed diabetes in a community setting in India. Alternative strategies are likely required to enhance the uptake of screening in certain groups.

Risk of developing Diabetes Mellitus among urban poor South Indian population using Indian Diabetes Risk Score

Background:

Diabetes mellitus is increasing its share of burden to the health-related problems in developing countries such as India. Urban slum residents constitute the “vulnerable population” who lack the basic health amenities. Lack of effective screening for primary prevention has been one of the reasons for the rising burden.

Materials and Methods:

The cross-sectional study was conducted among 400 adults aged between 30 and 60 years residing in a settled slum of Rukmini Nagar area of Belagavi city, Karnataka. Data were collected after taking written informed consent from each participant using a pretested questionnaire that included demographic information and details of the risk factors. Risk of developing diabetes was assessed by using Indian Diabetes Risk Score. Results are expressed as proportions, and analysis was done using Chi-square test and multiple logistic regression analysis.

Results:

The mean age of participants was 44.3 ± 8.7 years. The proportion of low, moderate, and high risk of developing diabetes mellitus was 7%, 63%, and 30%, respectively. The prevalence of newly diagnosed cases was 10.25%. Moreover, 57.1% of them with positive family history were in the high risk category; 76.9% of the sedentary workers were at higher risk; overweight and obese individuals had higher proportion of the high and moderate risk (P < 0.0001). Correlation coefficient (R) was 0.782, and coefficient of determination (R²) was 0.61.

Conclusions:

Our study demonstrated that advancing age, low physical activity, family history, overweight, and obesity were the prominent factors that predicted the risk of diabetes in the near future. Hence, focused interventions for urban slum dwellers are imperative and draw special attention.