BACKGROUND Weight loss is recommended for overweight and obese individuals with type 2 diabetes based on short-term studies, but long-term effects on cardiovascular disease remain unknown. We examined whether intensive lifestyle intervention for weight loss decreased cardiovascular morbidity and mortality in overweight or obese adults with type 2 diabetes. METHODS We randomly assigned 5,145 overweight or obese individuals with type 2 diabetes recruited at 16 US centers to intensive lifestyle intervention (the intervention group), which promoted weight loss through decreased calorie intake and increased physical activity, or diabetes support and education (the control group). The primary outcome was the first post-randomization occurrence of a composite cardiovascular outcome (cardiovascular death, non-fatal myocardial infarction, non-fatal stroke, or hospitalized angina) over a planned maximum follow-up of 13.5 years. RESULTS The trial was stopped early based on a futility analysis when median follow-up was 9.6 years. Weight loss was greater in the intervention group than the control group throughout (8.6% vs. 0.7% at 1 year; 6.0% vs. 3.5% at study end). Intensive lifestyle intervention also produced greater reductions in hemoglobin A1c and greater initial improvements in fitness and all cardiovascular risk factors, except LDL cholesterol. The primary outcome occurred in 403 patients in the intervention group and in 418 in the control group (1.83/100 person-years and 1.92/100 person-years, respectively; hazard ratio 0.95; 95% CI 0.83 to 1.09, p=0.505). CONCLUSION In our study, intensive lifestyle intervention focused on weight loss did not reduce cardiovascular events in overweight or obese adults with type 2 diabetes. (Funded by the Department of Health and Human Services and others; ClinicalTrials.gov number, NCT00017953.)

Many studies have shown that hyperinsulinemia and/or insulin resistance are related to various metabolic and physiological disorders including hypertension, dyslipidemia, and non-insulin-dependent diabetes mellitus. This syndrome has been termed Syndrome X. An important limitation of previous studies has been that they all have been cross sectional, and thus the presence of insulin resistance could be a consequence of the underlying metabolic disorders rather than its cause. We examined the relationship of fasting insulin concentration (as an indicator of insulin resistance) to the incidence of multiple metabolic abnormalities in the 8-yr follow-up of the cohort enrolled in the San Antonio Heart Study, a population-based study of diabetes and cardiovascular disease in Mexican Americans and non-Hispanic whites. In univariate analyses, fasting insulin was related to the incidence of the following conditions: hypertension, decreased high-density lipoprotein cholesterol concentration, increased triglyceride concentration, and non-insulin-dependent diabetes mellitus. Hyperinsulinemia was not related to increased low-density lipoprotein or total cholesterol concentration. In multivariate analyses, after adjustment for obesity and body fat distribution, fasting insulin continued to be significantly related to the incidence of decreased high-density lipoprotein cholesterol and increased triglyceride concentrations and to the incidence of non-insulin-dependent diabetes mellitus. Baseline insulin concentrations were higher in subjects who subsequently developed multiple metabolic disorders. These results were not attributable to differences in baseline obesity and were similar in Mexican Americans and non-Hispanic whites. These results support the existence of a metabolic syndrome and the relationship of that syndrome to multiple metabolic disorders by showing that elevations of insulin concentration precede the development of numerous metabolic disorders.

articles epidemiologyWe summed AS soda, coffee, and tea intakes to estimate AS beverage (ASB) consumption, and-among consumers-identified ASB consumption quartiles. Participants using AS sweeteners and/or cereals-but not ASBs-were included in ASB consumption quartile 1. Participants reporting no AS use were categorized "nonusers. "Dieting status and exercise frequency (2) were recorded at baseline and follow-up. In cohort 1 only, baseline 24-h dietary recalls were performed (2). In cohort 2 only, follow-up AS use (present or absent) was ascertained.Physical measurements and demographic data Standard anthropometric measurements were performed (2). A BMI <25 kg/m 2 was categorized normal weight (NW); ≥ 25 and <30 kg/m 2 , overweight (OW); and ≥ 30 kg/m 2 , obese (OB). The latter categories were combined as OW/OB (BMI ≥ 25 kg/m 2 ). Baseline education and occupation were recorded, and occupation-based Duncan socioeconomic index scores (range: 0-96) assigned. Of 3,682 follow-up participants, 3371 (91.6%) had complete data for all variables reported. statistical analysesIncidence of OW/OB (OW/OB inc ) was defined as the percent of baseline NW participants who had become OW/OB by follow-up. Incidence of obesity (OB inc ) was defined as the percent of baseline NWor-OW participants (BMI < 30 kg/m 2 ) who had become OB by follow-up. Change in BMI (ΔBMI) was calculated as BMI at follow-up minus BMI at baseline. Change in exercise frequency (Δexercise) was calculated as the number of exercise sessions per week at follow-up minus the number of sessions per week at baseline. Participants with Δexercise ≥1/week were categorized as "exercising more"; those ≤−1/ week, as "exercising less"; and all others, as "exercising same. " Excess BMI gains in AS users ("users") were calculated as ΔBMI among users minus ΔBMI among nonusers, divided by ΔBMI among nonusers.Means of continuous variables and percentages of categorical variables are presented by baseline AS consumption status. We used logistic regression to adjust odds ratios (ORs) for baseline BMI, as well as gender and ethnicity; baseline age, education, socioeconomic index, exercise frequency, and smoking status; interim change in exercise level; and interim smoking cessation ("demographic/behavioral covariates"), with ordinal categories of AS doses/day as a predictor variable. Analysis of covariance was used to assess associations between ASB consumption category and ΔBMI. In logistic regression and analysis of covariance models, linear trend was assessed by models using the ordinal category of ASB doses/ day as a continuous measure. All statistical calculations were performed using SAS version 9.1 (SAS Institute, Cary, NC).Analyses of ΔBMI-with adjustment for baseline BMI and demographic/behavioral covariates-were performed for the entire sample. Within cohort 2, they were repeated separately by baseline AS use status (present or absent), with additional adjustment for follow-up AS status. Within cohort 2, these analyses were also repeated among participants whose AS use st...

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We have developed a scale for AN that is easy to use, has high interobserver reliability in Mexican Americans, and correlates well with fasting insulin and BMI. This scale will permit longitudinal and cross-sectional evaluation of AN and will permit the evaluation of AN as a trait in genetic studies.