Urban-Rural Differences in the Prevalence of Diabetes Among Adults in Haryana, India: The ICMR-INDIAB Study (ICMR-INDIAB-18).

INTRODUCTION: Diabetes is a multifactorial disease with far-reaching consequences. Environmental factors, such as urban or rural residence, influence its prevalence and associated comorbidities. Haryana-a north Indian state-has undergone rapid urbanisation, and part of it is included in the National Capital Region (NCR). The primary aim of the study is to estimate the prevalence of diabetes in Haryana with urban-rural, NCR and non-NCR regional stratification and assess the factors affecting the likelihood of having diabetes among adults. METHODS: This sub-group analysis of the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study (a nationally representative cross-sectional population-based survey) was done for Haryana using data from 3722 participants. The dependent variable was diabetes, while residence in NCR/non-NCR and urban-rural areas were prime independent variables. Weighted prevalence was estimated using state-specific sampling weights and standardized using National Family Health Survey-5 (NFHS-5) study weights. Associations were depicted using bivariate analysis, and factors describing the likelihood of living with diabetes were explored using a multivariable binary logistic regression analysis approach. RESULTS: Overall, the weighted prevalence of diabetes in Haryana was higher than the national average (12.4% vs. 11.4%). The prevalence was higher in urban (17.9%) than in rural areas (9.5%). The prevalence of diabetes in rural areas was higher in the NCR region, while that of prediabetes was higher in rural non-NCR region. Urban-rural participants' anthropometric measurements and biochemical profiles depicted non-significant differences. Urban-rural status, age and physical activity levels were the most significant factors that affected the likelihood of living with diabetes. CONCLUSIONS: The current analysis provides robust prevalence estimates highlighting the urban-rural disparities. Urban areas continue to have a high prevalence of diabetes and prediabetes; rural areas depict a much higher prevalence of prediabetes than diabetes. With the economic transition rapidly bridging the gap between urban and rural populations, health policymakers should plan efficient strategies to tackle the diabetes epidemic.

Performance of European prediction models for classification of type 1 and type 2 diabetes in Indians.

AIM: We aimed to determine the performance of European prediction models in an Indian population to classify type 1 diabetes(T1D) and type 2 diabetes(T2D). METHODS: We assessed discrimination and calibration of published models of diabetes classification, using retrospective data from electronic medical records of 83309 participants aged 18-50 years living in India. Diabetes type was defined based on C-peptide measurement and early insulin requirement. Models assessed combinations of clinical measurements: age at diagnosis, body mass index(mean = 26.6 kg/m2), sex(male = 64.9 %), Glutamic acid decarboxylase(GAD) antibody, serum cholesterol, serum triglycerides, and high-density lipoprotein(HDL) cholesterol. RESULTS: 67955 participants met inclusion criteria, of whom 0.8 % had T1D, which was markedly lower than model development cohorts. Model discrimination for clinical features was broadly similar in our Indian cohort compared to the European cohort: area under the receiver operating characteristic curve(AUC ROC) was 0.90 vs. 0.90 respectively, but was lower in the subset of young participants with measured GAD antibodies(n = 2404): and an AUC ROC of 0.87 when clinical features, sex, lipids and GAD antibodies were combined. All models substantially overestimated the likelihood of T1D, reflecting the lower prevalence of T1D in the Indian population. However, good model performance was achieved after recalibration by updating the model intercept and slope. CONCLUSION: Models for diabetes classification maintain the discrimination of T1D and T2D in this Indian population, where T2D is far more common, but require recalibration to obtain appropriate model probabilities. External validation and recalibration are needed before these tools can be used in non-European populations.

Accuracy of 1-Hour Plasma Glucose During the Oral Glucose Tolerance Test in Diagnosis of Type 2 Diabetes in Adults: A Meta-analysis.

OBJECTIVE: One-hour plasma glucose (1-h PG) during the oral glucose tolerance test (OGTT) is an accurate predictor of type 2 diabetes. We performed a meta-analysis to determine the optimum cutoff of 1-h PG for detection of type 2 diabetes using 2-h PG as the gold standard. RESEARCH DESIGN AND METHODS: We included 15 studies with 35,551 participants from multiple ethnic groups (53.8% Caucasian) and 2,705 newly detected cases of diabetes based on 2-h PG during OGTT. We excluded cases identified only by elevated fasting plasma glucose and/or HbA1c. We determined the optimal 1-h PG threshold and its accuracy at this cutoff for detection of diabetes (2-h PG ≥11.1 mmol/L) using a mixed linear effects regression model with different weights to sensitivity/specificity (2/3, 1/2, and 1/3). RESULTS: Three cutoffs of 1-h PG, at 10.6 mmol/L, 11.6 mmol/L, and 12.5 mmol/L, had sensitivities of 0.95, 0.92, and 0.87 and specificities of 0.86, 0.91, and 0.94 at weights 2/3, 1/2, and 1/3, respectively. The cutoff of 11.6 mmol/L (95% CI 10.6, 12.6) had a sensitivity of 0.92 (0.87, 0.95), specificity of 0.91 (0.88, 0.93), area under the curve 0.939 (95% confidence region for sensitivity at a given specificity: 0.904, 0.946), and a positive predictive value of 45%. CONCLUSIONS: The 1-h PG of ≥11.6 mmol/L during OGTT has a good sensitivity and specificity for detecting type 2 diabetes. Prescreening with a diabetes-specific risk calculator to identify high-risk individuals is suggested to decrease the proportion of false-positive cases. Studies including other ethnic groups and assessing complication risk are warranted.

Contrasting Associations Between Diabetes and Cardiovascular Mortality Rates in Low-, Middle-, and High-Income Countries: Cohort Study Data From 143,567 Individuals in 21 Countries in the PURE Study.

OBJECTIVE: We aimed to compare cardiovascular (CV) events, all-cause mortality, and CV mortality rates among adults with and without diabetes in countries with differing levels of income. RESEARCH DESIGN AND METHODS: The Prospective Urban Rural Epidemiology (PURE) study enrolled 143,567 adults aged 35-70 years from 4 high-income countries (HIC), 12 middle-income countries (MIC), and 5 low-income countries (LIC). The mean follow-up was 9.0 ± 3.0 years. RESULTS: Among those with diabetes, CVD rates (LIC 10.3, MIC 9.2, HIC 8.3 per 1,000 person-years, P < 0.001), all-cause mortality (LIC 13.8, MIC 7.2, HIC 4.2 per 1,000 person-years, P < 0.001), and CV mortality (LIC 5.7, MIC 2.2, HIC 1.0 per 1,000 person-years, P < 0.001) were considerably higher in LIC compared with MIC and HIC. Within LIC, mortality was higher in those in the lowest tertile of wealth index (low 14.7%, middle 10.8%, and high 6.5%). In contrast to HIC and MIC, the increased CV mortality in those with diabetes in LIC remained unchanged even after adjustment for behavioral risk factors and treatments (hazard ratio [95% CI] 1.89 [1.58-2.27] to 1.78 [1.36-2.34]). CONCLUSIONS: CVD rates, all-cause mortality, and CV mortality were markedly higher among those with diabetes in LIC compared with MIC and HIC with mortality risk remaining unchanged even after adjustment for risk factors and treatments. There is an urgent need to improve access to care to those with diabetes in LIC to reduce the excess mortality rates, particularly among those in the poorer strata of society.