FNASCOBJECTIVE -The objective of the study was to examine body fat distribution using computed tomography (CT), dual-energy X-ray absorptiometry (DEXA), and anthropometry in relation to type 2 diabetes in urban Asian Indians. RESEARCH DESIGN AND METHODS-This is a case-control study of 82 type 2 diabetic and 82 age-and sex-matched nondiabetic subjects from the Chennai Urban Rural Epidemiology Study, an ongoing epidemiological study in southern India. Visceral, subcutaneous, and total abdominal fat were measured using CT, while DEXA was used to measure central abdominal and total body fat. Anthropometric measures included BMI, waist circumference, sagittal abdominal diameter (SAD), and waist-to-hip ratio.RESULTS -Visceral and central abdominal fat showed a strong correlation with each other (P Ͻ 0.0001), and analysis revealed a fairly good agreement between tertiles of visceral and central abdominal fat ( ϭ 0.44, P Ͻ 0.0001). Diabetic subjects had significantly higher visceral (P ϭ 0.005) and central abdominal (P ϭ 0.011) fat compared with nondiabetic subjects. Waist circumference and SAD showed a strong correlation with visceral (P Ͻ 0.01) and central abdominal (P Ͻ 0.0001) fat in both diabetic and nondiabetic subjects. Logistic regression analysis revealed visceral (odds ratio [OR] 1.011, P ϭ 0.004) and central abdominal (OR 1.001, P ϭ 0.013) fat to be associated with diabetes, even after adjusting for age and sex.CONCLUSIONS -Visceral and central abdominal fat showed a strong association with type 2 diabetes. Both measures correlated well with each other and with waist circumference and SAD in diabetic and nondiabetic urban Asian Indians. Diabetes Care 27:2948 -2953, 2004A sian Indians have an increased susceptibility to type 2 diabetes and insulin resistance compared with Europeans (1-4). Recent studies indicate a rising prevalence of diabetes and insulin resistance in India (5-7). Although obesity is a major contributing factor to diabetes, Asian Indians are known to have lower BMIs than Europeans (8). However, for any given BMI, Asian Indians have greater waist-to-hip ratios and abdominal fat (8,9) than Europeans. There are very few studies on fat distribution in Indians (10,11) and virtually none comparing diabetic and nondiabetic subjects. Thus, the first objective of this study was to measure body fat distribution in Asian Indians in relation to type 2 diabetes.Computed tomography (CT) is widely used to assess visceral fat (12-14). Dual-energy X-ray absorptiometry (DEXA) is usually used to measure total body fat (15) but recently has also been used to measure central abdominal fat (16). The association of visceral fat measured by CT and central abdominal fat measured by DEXA has not been studied in an Asian-Indian population, and their relationship with anthropometric variables is also not clear. Thus, the second objective of our study was to correlate visceral and central abdominal fat with each other and with anthropometric parameters. RESEARCH DESIGN ANDMETHODS -This is a case-control study of diabetic...

Recent evidence suggests that lifestyle factors influence the association between the Melanocortin 4 receptor (MC4R) and Transcription Factor 7-Like 2 (TCF7L2) gene variants and cardio-metabolic traits in several populations; however, the available research is limited among the Asian Indian population. Hence, the present study examined whether the association between the MC4R single nucleotide polymorphism (SNP) (rs17782313) and two SNPs of the TCF7L2 gene (rs12255372 and rs7903146) and cardio-metabolic traits is modified by dietary factors and physical activity. This cross sectional study included a random sample of normal glucose tolerant (NGT) (n = 821) and participants with type 2 diabetes (T2D) (n = 861) recruited from the urban part of the Chennai Urban Rural Epidemiology Study (CURES). A validated food frequency questionnaire (FFQ) was used for dietary assessment and self-reported physical activity measures were collected. The threshold for significance was set at P = 0.00023 based on Bonferroni correction for multiple testing [(0.05/210 (3 SNPs x 14 outcomes x 5 lifestyle factors)]. After Bonferroni correction, there was a significant interaction between the TCF7L2 rs12255372 SNP and fat intake (g/day) (Pinteraction = 0.0001) on high-density lipoprotein cholesterol (HDL-C), where the ‘T’ allele carriers in the lowest tertile of total fat intake had higher HDL-C (P = 0.008) and those in the highest tertile (P = 0.017) had lower HDL-C compared to the GG homozygotes. In a secondary analysis of SNPs with the subtypes of fat, there was also a significant interaction between the SNP rs12255372 and polyunsaturated fatty acids (PUFA, g/day) (Pinteraction<0.0001) on HDL-C, where the minor allele carriers had higher HDL-C in the lowest PUFA tertile (P = 0.024) and those in the highest PUFA tertile had lower HDL-C (P = 0.028) than GG homozygotes. In addition, a significant interaction was also seen between TCF7L2 SNP rs12255372 and fibre intake (g/day) on HDL-C (Pinteraction<0.0001). None of the other interactions between the SNPs and lifestyle factors were statistically significant after correction for multiple testing. Our findings indicate that the association between TCF7L2 SNP rs12255372 and HDL-C may be modified by dietary fat intake in this Asian Indian population.

Objective: To evaluate whether polymorphisms in the peroxisome proliferator-activated receptor-gamma coactivator-1 alpha (PPARGC1A) gene were related to body fat in Asian Indians. Methods: Three polymorphisms of PPARGC1A gene, the Thr394Thr, Gly482Ser and þ A2962G, were genotyped on 82 type 2 diabetic and 82 normal glucose tolerant (NGT) subjects randomly chosen from the Chennai Urban Rural Epidemiology Study using PCR-RFLP, and the nature of the variants were confirmed using direct sequencing. Linkage disequilibrium (LD) was estimated from the estimates of haplotypic frequencies using an expectation-maximization algorithm. Visceral, subcutaneous and total abdominal fat were measured using computed tomography, whereas dual X-ray absorptiometry was used to measure central abdominal and total body fat. Results: None of the three polymorphisms studied were in LD. The genotype (0.59 vs 0.32, P ¼ 0.001) and allele (0.30 vs 0.17, P ¼ 0.007) frequencies of Thr394Thr polymorphism were significantly higher in type 2 diabetic subjects compared to those in NGT subjects. The odds ratio for diabetes (adjusted for age, sex and body mass index) for the susceptible genotype, XA (GA þ AA) of Thr394Thr polymorphism, was 2.53 (95% confidence intervals: 1.30-5.04, P ¼ 0.009). Visceral and subcutaneous fat were significantly higher in NGT subjects with XA genotype of the Thr394Thr polymorphism compared to those with GG genotype (visceral fat: XA 148.2746.9 vs GG 106.5751.9 cm 2 , P ¼ 0.001; subcutaneous fat: XA 271.87167.1 vs GG 181.5778.5 cm 2 , P ¼ 0.001). Abdominal (XA 4521.971749.6 vs GG 3445.271443.4 g, P ¼ 0.004), central abdominal (XA 1689.07524.0 vs GG 1228.57438.7 g, Po0.0001) and non-abdominal fat (XA 18763.878789.4 vs GG 13160.474255.3 g, Po0.0001) were also significantly higher in the NGT subjects with XA genotype compared to those with GG genotype. The Gly482Ser and þ A2962G polymorphisms were not associated with any of the body fat measures. Conclusion: Among Asian Indians, the Thr394Thr (G-A) polymorphism is associated with increased total, visceral and subcutaneous body fat.