Abdominal obesity and myocardial infarction risk-We demonstrate the anthropometric and mathematical reasons that justify the association bias of the waist-to-hip ratio Obesidad abdominal y riesgo de infarto de miocardio: demostramos las razones antropométricas y matemáticas que justifican el sesgo de asociación del índice cintura-cadera

OBJECTIVEMedical nutrition therapy based on the control of the amount and distribution of carbohydrates (CHO) is the initial treatment for gestational diabetes mellitus (GDM), but there is a need for randomized controlled trials comparing different dietary strategies. The purpose of this study was to test the hypothesis that a low-CHO diet for the treatment of GDM would lead to a lower rate of insulin treatment with similar pregnancy outcomes compared with a control diet.RESEARCH DESIGN AND METHODSA total of 152 women with GDM were included in this open, randomized controlled trial and assigned to follow either a diet with low-CHO content (40% of the total diet energy content as CHO) or a control diet (55% of the total diet energy content as CHO). CHO intake was assessed by 3-day food records. The main pregnancy outcomes were also assessed.RESULTSThe rate of women requiring insulin was not significantly different between the treatment groups (low CHO 54.7% vs. control 54.7%; P = 1). Daily food records confirmed a difference in the amount of CHO consumed between the groups (P = 0.0001). No differences were found in the obstetric and perinatal outcomes between the treatment groups.CONCLUSIONSTreatment of women with GDM using a low-CHO diet did not reduce the number of women needing insulin and produced similar pregnancy outcomes. In GDM, CHO amount (40 vs. 55% of calories) did not influence insulin need or pregnancy outcomes.

Fasting C-peptide and derived parameters help to differentiate type 1 from type 2 diabetes, but there is a range of C-peptide concentrations that does not help discriminate. Relating C-peptide to glucose did not improve diagnostic accuracy. C-peptide does not help predicting a need for insulin treatment in patients with type 2 diabetes.

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