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The aim of the study was to examine the association of dietary carbohydrates and glycaemic load with the risk of type 2 diabetes among an urban adult Asian Indian population. Adult subjects aged .20 years (n 1843) were randomly selected from the Chennai Urban Rural Epidemiology Study, in Chennai city in southern India. Dietary carbohydrates, glycaemic load and food groups were assessed using FFQ. Oral glucose tolerance tests were performed using 75 g glucose in all subjects. Diagnosis of diabetes was based on WHO Consulting Group criteria. OR for newly detected diabetes were calculated for carbohydrates, glycaemic load and specific food groups comparing subjects in the highest with those in the lowest quartiles, after adjustment for potential confounders such as age, sex, BMI, family history of diabetes, physical activity, current smoking, alcohol consumption and relevant dietary factors. We identified 156 (8·5 %) newly diagnosed cases of type 2 diabetes. Refined grain intake was positively associated with the risk of type 2 diabetes (OR 5·31 (95 % CI 2·98, 9·45); P,0·001). In the multivariate model, after adjustment for potential confounders, total carbohydrate (OR 4·98 (95 % CI 2·69, 9·19), P,0·001), glycaemic load (OR 4·25 (95 % CI 2·33, 7·77); P, 0·001) and glycaemic index (OR 2·51 (95 % CI 1·42, 4·43); P¼ 0·006) were associated with type 2 diabetes. Dietary fibre intake was inversely associated with diabetes (OR 0·31 (95 % CI 0·15, 0·62); P, 0·001). In urban south Indians, total dietary carbohydrate and glycaemic load are associated with increased, and dietary fibre with decreased, risk of type 2 diabetes.

We report on the reproducibility and validity of a food frequency questionnaire (FFQ) developed for southern India. One hundred and two adult subjects aged > or =20 years drawn from the Chennai Urban Rural Epidemiology Study participated. The FFQ was developed based on local foods and habits, and was administered three times at 0, 6 and 12 month periods (called FFQ1, FFQ2 and FFQ3) to assess the reproducibility. To test the validity of the FFQ, multiple 24-h recalls collected at 2-monthly intervals for a period of 1 year and the estimated energy intake/basal metabolic rate (EI/BMR) ratio were used. The 'EpiNu' in-house food and nutrient database was used to compile dietary intakes, which were analyzed for statistical analysis. The intraclass correlation coefficient for all three FFQs ranged from 0.72 for carbohydrates to 0.45 for folate. The de-attenuated Pearson correlation for the energy adjusted nutrients between FFQ3 and 24-h recalls ranged from 0.73 for carbohydrates to 0.35 for calcium. Bland and Altman plots for energy intake between the two methods showed the limits of agreement ranged from 768 to -1358 calories/day (+/-2 standard deviations). Misclassification was low for most of the nutrients. Under-reporting of the energy intake (EI/BMR ratio<1.2) was higher in females than males. This FFQ appears to be a robust tool to measure dietary intakes in southern India.

OBJECTIVETo determine A1C cut points for glucose intolerance in Asian Indians.RESEARCH DESIGN AND METHODSA total of 2,188 participants without known diabetes were randomly selected from the Chennai Urban Rural Epidemiology Study. All had fasting plasma glucose (FPG) and 2-h postload plasma glucose measurements after a 75-g load and were classified as having impaired fasting glucose (IFG) (American Diabetes Association [ADA] criteria, FPG ≥5.5 and <7 mmol/l, and World Health Organization [WHO] criteria, FPG ≥6.1 and <7 mmol/l), impaired glucose tolerance (IGT) (2-h postload plasma glucose ≥7.8 and <11.1 mmol/l), or diabetes (FPG ≥7 mmol/l and/or 2-h postload plasma glucose ≥11.1 mmol/l). A1C was measured using the Bio-Rad Variant machine. Based on receiver operating characteristic curves, optimum sensitivity and specificity were derived for defining A1C cut points for diabetes, IGT, and IFG.RESULTSMean ± SD values of A1C among subjects with normal glucose tolerance, IGT, and diabetes were 5.5 ± 0.4, 5.9 ± 0.6, and 8.3 ± 2.0%, respectively (Ptrend < 0.001) with considerable overlap. To identify diabetes based on 2-h postload plasma glucose, the A1C cut point of 6.1% had an area under the curve (AUC) of 0.941 with 88.0% sensitivity and 87.9% specificity. When diabetes was defined as FPG ≥7.0 mmol/l, the A1C cut point was 6.4% (AUC = 0.966, sensitivity 93.3%, and specificity 92.3%). For IGT, AUC = 0.708; for IFG, AUC = 0.632 (WHO criteria) and 0.708 (ADA criteria), and the A1C cut point was 5.6%.CONCLUSIONSIn Asian Indians, A1C cut points of 6.1 and 6.4% defined diabetes by 2-h postload plasma glucose or FPG criteria, respectively. A value of 5.6% optimally identified IGT or IFG but was <70% accurate.

OBJECTIVE -To determine random capillary blood glucose (RCBG) cut points that discriminate diabetic and pre-diabetic subjects from normal individuals.RESEARCH DESIGN AND METHODS -RCBG was performed in 1,333 individuals randomly chosen from 63,305 individuals who had participated in an opportunistic screening program. An oral glucose tolerance test was also performed by venous plasma glucose on an autoanalyzer. RCBG cut points that discriminate diabetes, impaired glucose tolerance (IGT), and impaired fasting glucose (IFG) were determined using receiver operating characteristic curves.RESULTS -Using 2-h plasma glucose Ն200 mg/dl (11.1 mmol/l) criterion, the RCBG cut point of 140 mg/dl (7.7 mmol/l) gave the highest sensitivity and specificity. For 2-h plasma glucose Ն200 mg/dl (11.1 mmol/l) and fasting plasma glucose (FPG) Ն126 mg/dl (7.0 mmol/l) criteria, either 2-h plasma glucose Ն200 mg/dl (11.1 mmol/l) or FPG Ն126 mg/dl (7.0 mmol/l) criterion, and the FPG Ն126 mg/dl (7.0 mmol/l) criterion, RCBG cut point was 143 mg/dl (7.9 mmol/l). RCBG cut points for IGT, IFG according to World Health Organization criterion, and IFG according to American Diabetes Association criterion were 119 mg/dl (6.6 mmol/l), 118 mg/dl (6.6 mmol/l), and 113 mg/dl (6.3 mmol/l), respectively.CONCLUSIONS -Asian Indians with RCBG Ͼ110 mg/dl at screening can be recommended to undergo definitive testing.

In South Indian Type 2 diabetic subjects, duration of diabetes, HbA1c, male gender, macroalbuminuria and insulin therapy were independent risk factors for severity of DR. Postprandial hyperglycaemia indicated a higher risk for DR compared with elevated fasting plasma glucose levels.

The study examines the relationship between fruit and vegetable intake (g/d) and CVD risk factors in urban south Indians. The study population comprised of 983 individuals aged $ 20 years selected from the Chennai Urban Rural Epidemiological Study (CURES), a population-based crosssectional study on a representative population of Chennai in southern India. Fruit and vegetable intake (g/d) was measured using a validated semiquantitative FFQ. Linear regression analysis revealed that after adjusting for potential confounders such as age, sex, smoking, alcohol, BMI and total energy intake, the highest quartile of fruit and vegetable intake (g/d) showed a significant inverse association with systolic blood pressure (b ¼ 2 2·6 (95 % CI 2 5·92, 21·02) mmHg; P¼0·027), BMI (b ¼ 2 2·3 (95 % CI 2 2·96, 21·57) kg/m 2 ; P, 0·0001), waist circumference (b ¼ 2 2·6 (95 % CI 23·69, 2 1·46) cm; P, 0·0001), total cholesterol (b ¼ 250 (95 % CI 2 113·9, 213·6) mg/l; P¼0·017) and LDL-cholesterol concentration (b ¼ 2 55 (95 % CI 2 110·8, 2 11·1) mg/l; P¼0·039) when compared with the lowest quartile. A higher intake of fruit and vegetables explained 48 % of the protective effect against CVD risk factors. Increased intake of fruits and vegetables could play a protective role against CVD in Asian Indians who have high rates of premature coronary artery disease.