Progress in reducing mortality rates among persons with diabetes has been limited to men. Diabetes continues to greatly increase the risk for death, particularly among women.

National Heart, Lung, and Blood Institute and UnitedHealth Group.

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OBJECTIVE -We sought to study the occurrence of cardiometabolic risk variables, their clustering, and their association with insulin resistance among healthy adolescents in urban south India.RESEARCH DESIGN AND METHODS -School children aged 12-19 years (n ϭ 2,640; 1,323 boys and 1,317 girls) from diverse socioeconomic backgrounds were studied. Demographic, social, and medical details were obtained; anthropometry and blood pressure were measured. Fasting plasma glucose, insulin, and lipid profiles were measured. Clusters of risk variables were identified by factor analysis. Association of insulin resistance (homeostasis model assessment) with individual risk variables and their clusters were assessed.RESULTS -One or more cardiometabolic abnormalities (i.e., low HDL cholesterol, elevated triglycerides, fasting plasma glucose, or blood pressure) was present in 67.7% of children (in 64.8% of normal weight and 85% of overweight children). Insulin resistance was associated with the above abnormalities except HDL cholesterol. It also showed significant positive association with BMI, waist circumference, body fat percentage, and total cholesterol (P Ͻ 0.0001). Factor analysis identified three distinct clusters, with minor differences in the sexes: 1) waist circumference and blood pressure; 2) dyslipidemia, waist circumference, and insulin; and 3) waist circumference, glucose, and plasma insulin, with minor differences in the sexes. Insulin was a component of the lipid and glucometabolic cluster. In girls, it was a component of all three clusters.CONCLUSIONS -Cardiometabolic abnormalities are present in nearly 68% of young, healthy, Asian-Indian adolescents and even among those with normal weight. Insulin resistance is associated with individual cardiometabolic factors, and plasma insulin showed association with clustering of some variables. Diabetes Care 30:1828-1833, 2007I nsulin resistance is associated with obesity, type 2 diabetes, cardiovascular disease, and subclinical cardiometabolic risk markers, such as dyslipidemia, hypertension, and central adiposity (1,2). In fact, many have hypothesized that insulin resistance may be the common pathophysiological factor tying together a "syndrome" of cardiometabolic disturbance, affecting adiposity, glucose intolerance, dyslipidemia, and altered blood pressure control (2-4). On the other hand, the concept that such a syndrome exists has recently been challenged (5).The association between insulin resistance and cardiometabolic risk factors is often confounded once the disease sets in. The ideal population for examining these associations in depth would be one that is: 1) at high risk of insulin resistance, 2) young and has not yet acquired clinical disease, and 3) undergoing rapid environmental and lifestyle change.Asian Indians are at high risk of type 2 diabetes and cardiovascular disease and have an insulin-resistant phenotype, characterized by low muscle mass, upperbody adiposity, and high percentage of body fat (6,7). While insulin resistance runs in families and may h...

Aim To estimate the prevalence of, and assess factors associated with, diabetes and prediabetes in three South Asian cities. Methods Using a multi-stage cluster random sample representative of each city, 16,288 subjects aged ≥20 years (Chennai: 6906, Delhi: 5365 and Karachi: 4017) were recruited to the Centre for cArdiometabolic Risk Reduction in South-Asia (CARRS) Study. Fasting plasma glucose (FPG) and glycosylated hemoglobin (HbA1c) were measured in 13720 subjects. Prediabetes was defined as FPG 100-125mg/dl (5.6-6.9 mmol/l) and/or HbA1c 5.7-6.4% (39-46mmol/mol) and diabetes as self-report and/or drug treatment for diabetes and/or FPG ≥126 mg/dl (≥7.0mmol/l) and/or HbA1c ≥6.5% (48mmol/mol). We assessed factors associated with diabetes and prediabetes using polytomous logistic regression models. Results Overall 47.3-73.1% of the population had either diabetes or prediabetes: Chennai 60.7% [95%CI: 59.0-62.4%] (diabetes-22.8% [21.5-24.1%], prediabetes-37.9% [36.1-39.7%]); Delhi 72.7% [70.6-74.9%] (diabetes-25.2% [23.6-26.8%], prediabetes-47.6% [45.6-49.5%]); and Karachi 47.4% [45.7-49.1%]; (diabetes-16.3% [15.2-17.3%], prediabetes-31.1% [29.5-32.8%], respectively). Proportions of self-reported diabetes were 55.1%, 39.0%, and 48.0% in Chennai, Delhi, and Karachi, respectively. City, age, family history of diabetes, generalized obesity, abdominal obesity, body fat, high cholesterol, high triglyceride, and low HDL cholesterol levels were each independently associated with prediabetes, while the same factors plus waist-to-height ratio and hypertension were associated with diabetes. Conclusion Six in ten adults in large South Asian cities have either diabetes or prediabetes. These data call for urgent action to prevent diabetes in South Asia.

Background: The oxidative balance score (OBS) is a composite estimate of the overall pro- and antioxidant exposure status in an individual. The aim of this study was to determine the association between OBS and renal disease. Methods: Using the Reasons for Geographic and Racial Differences in Stroke cohort study, OBS was calculated by combining 13 a priori-defined pro- and antioxidant factors by using baseline dietary and lifestyle assessment. OBS was divided into quartiles (Q1-Q4) with the lowest quartile, Q1 (predominance of pro-oxidants), as the reference. Multivariable logistic regression and Cox proportional hazards models were used to estimate adjusted ORs for albuminuria defined as urine albumin/creatinine ratio (ACR) >30 mg/g, macroalbuminuria defined as ACR >300 mg/g and chronic kidney disease (CKD) defined as estimated glomerular filtration rate <60 ml/min/1.73 m² according to the Chronic Kidney Disease Epidemiology Collaboration and hazards ratios for end-stage renal disease (ESRD), respectively. Results: Of the 19,461 participants analyzed, 12.9% had albuminuria and 10.1% had CKD at baseline; over a median follow-up of 3.5 years (range 2.14-4.32 years), 0.46% developed ESRD. Higher OBS quartiles were associated with lower prevalence of CKD (OR vs. Q1: Q2 = 0.93 [95% CI 0.80-1.08]; Q3 = 0.90 [95% CI 0.77-1.04] and Q4 = 0.79 [95% CI 0.67-0.92], p for trend <0.01). The associations between OBS and albuminuria (p for trend 0.31) and incident ESRD (p for trend 0.56) were not significant in the fully adjusted models. Conclusions: These findings suggest that higher OBS is associated with lower prevalence of CKD. Lack of association with ESRD incidence in the multivariable analyses indicates that temporal relation between OBS and renal damage remains unclear.

Among Asian Indians, β-cell dysfunction appears to be more strongly associated with T2DM-Y than insulin resistance.

IntroductionWe conducted a systematic review and meta-analysis to evaluate the updated evidence regarding prediabetes for predicting mortality, macrovascular and microvascular outcomes.Research design and methodsWe identified English language studies from MEDLINE, PubMed, OVID and Cochrane database indexed from inception to January 31, 2020. Paired reviewers independently identified 106 prospective studies, comprising nearly 1.85 million people, from 27 countries. Primary outcomes were all-cause mortality (ACM), cardiovascular mortality (CVDM), cardiovascular disease (CVD), coronary heart disease (CHD) and stroke. Secondary outcomes were heart failure, chronic kidney disease (CKD) and retinopathy.ResultsImpaired glucose tolerance was associated with ACM; HR 1.19, 95% CI (1.15 to 1.24), CVDM; HR 1.21, 95% CI (1.10 to 1.32), CVD; HR 1.18, 95% CI (1.11 to 1.26), CHD; HR; 1.13, 95% CI (1.05 to 1.21) and stroke; HR 1.24, 95% CI (1.06 to 1.45). Impaired fasting glucose (IFG) 110–125 mg/dL was associated with ACM; HR 1.17, 95% CI (1.13 to 1.22), CVDM; HR 1.20, 95% CI (1.09 to 1.33), CVD; HR 1.21, 95% CI (1.09 to 1.33), CHD; HR; 1.14, 95% CI (1.06 to 1.22) and stroke; HR 1.22, 95% CI (1.07 to 1.40). IFG 100–125 mg/dL was associated with ACM; HR 1.11, 95% CI (1.04 to 1.19), CVDM; HR 1.14, 95% CI (1.03 to 1.25), CVD; HR 1.15, 95% CI (1.05 to 1.25), CHD HR; 1.10, 95% CI (1.02 to 1.19) and CKD; HR; 1.09, 95% CI (1.01 to 1.18). Glycosylated hemoglobin A1c (HbA1c) 6.0%–6.4% was associated with ACM; HR 1.30, 95% CI (1.03 to 1.66), CVD; HR 1.32, 95% CI (1.00 to 1.73) and CKD; HR 1.50, 95% CI (1.32 to 1.70). HbA1c 5.7%–6.4% was associated with CVD HR 1.15, 95% CI (1.02 to 1.30), CHD; HR 1.28, 95% CI (1.13 to 1.46), stroke; HR 1.23, 95% CI (1.04 to 1.46) and CKD; HR 1.32, 95% CI (1.16 to 1.50).ConclusionPrediabetes is an elevated risk state for macrovascular and microvascular outcomes. The prevention and management of prediabetes should be considered.