According to the network meta- analysis the Mediterranean diet is the most effective and efficacious dietary approach to improve glycaemic control in type 2 diabetes patients
The aim of the present study is to assess the comparative efficacy of different dietary approaches on glycaemic control in patients with type 2 diabetes mellitus using a systematic review of the literature .
The Effects of Low-Carbohydrate versus Conventional Weight Loss Diets in Severely Obese Adults: One-Year Follow-up of a Randomized Trial
Context In 2003 , the authors reported that severely obese adults lost more weight and had better serum lipid patterns after 6 months of a low-carbohydrate diet rather than a conventional low-fat diet . Contribution After 1 year , these same patients still had more favorable triglyceride and high-density lipoprotein cholesterol levels on the low-carbohydrate diet than on the conventional diet . However , weight loss and the other metabolic parameters were similar in the 2 diet groups . Caution s The effect of the modest improvements in high-density lipoprotein cholesterol and triglyceride levels on the development of diabetes and cardiovascular disease is unknown . The Editors The prevalence of obesity and its associated metabolic abnormalities has increased markedly over the past 2 decades ( 1 , 2 ) . Although guidelines to follow a highcomplex carbohydrate , low-fat , energy-deficient diet to achieve weight loss are generally accepted ( 3 ) , considerable public interest has focused on low-carbohydrate diets ( 4 ) . We recently reported that persons with severe obesity lost more weight and had greater improvements in triglyceride levels , insulin sensitivity , and glycemic control after 6 months of a low-carbohydrate diet as compared with a conventional weight loss diet based on calorie and fat restriction ( 5 ) . However , these findings were preliminary because of the short duration of that study ( 6 ) . A simultaneously published study by Foster and colleagues suggested that persons on a low-carbohydrate diet  tended to regain weight by 1 year ( 7 ) . These findings were limited , however , because few participants completed the study and because the study used a self-help approach , which is less effective than direct counseling for maintaining weight loss ( 8) . Foster and colleagues also excluded persons with diabetes , which is highly prevalent in the obese population . During the development of this study , we decided to analyze and report preliminary results at 6 months and final results at 1 year . We thought that the short-term results would be important , given the high-risk nature of our study sample , but that long-term outcomes would provide more information about the sustainability of any diet-related outcomes . We now report our findings 1 year after r and omization to a low-carbohydrate diet versus a low-fat weight loss diet ( conventional diet ) in severely obese adults with a high prevalence of diabetes or the metabolic syndrome . Methods Study Participants The study design has been previously described ( 5 ) . Participants were recruited from the outpatient practice s of the Philadelphia Veterans Affairs Medical Center and included persons 18 years of age and older with a body mass index ( BMI ) of 35 kg/m2 or greater . The exclusion criteria were a serum creatinine level greater than 133 mol/L ( > 1.5 mg/dL ) , hepatic disease , severe life-limiting medical illness , inability to self-monitor glucose levels , or active use of a weight loss program or weight loss medication . Between May 2001 and November 2001 , 132 persons were r and omly assigned to either a low-carbohydrate diet ( n = 64 ) or a conventional diet ( n = 68 ) . The Institutional Review Committee at the Philadelphia Veterans Affairs Medical Center approved the study , and all participants provided written informed consent . Interventions Diet groups met in weekly counseling sessions for 4 weeks , followed by 11 monthly sessions . Participants on the low-carbohydrate diet were instructed only to reduce carbohydrate intake to less than 30 g per day . Participants on the conventional diet were instructed to reduce caloric intake by 500 calories per day , with less than 30 % of calories derived from fat , in accordance with the National Heart , Lung , and Blood Institute guidelines ( 3 ) . Outcome Measures We collected data , including weight ( single calibrated scale , SR Instruments , Inc. , Tonaw and a , New York ) , medical history ( self-reported ) , and blood pressure , at baseline , 6 months , and 1 year . Fasting blood specimens were obtained for glucose , hemoglobin A1c , and serum lipid levels ( Synchron LX20 , Beckman Coulter , Inc. , Fullerton , California ) . Low-density lipoprotein ( LDL ) cholesterol level was calculated by using the Friedewald formula ( 9 ) . We defined the presence of diabetes by a historical fasting blood glucose level greater than 6.94 mmol/L ( > 125 mg/dL ) or use of antidiabetic medications . The metabolic syndrome was considered present if a participant had 3 or more of the following ( 10 ) : central obesity , fasting blood glucose level of 6.11 mmol/L ( 110 mg/dL ) or greater , fasting triglyceride level of 1.70 mmol/L ( 150 mg/dL ) or greater , high-density lipoprotein ( HDL ) cholesterol level less than 1.04 mmol/L ( < 40 mg/dL ) for men or less than 1.30 mmol/L ( < 50 mg/dL ) for women , blood pressure of 130/85 mm Hg or greater , or antihypertensive therapy . We assumed that all participants had central obesity because of the uniform severity of their obesity ( BMI range , 35.0 to 79.4 kg/m2 ) . Serum insulin was measured by radioimmunoassay ( Laboratory Corporation of America Holdings [ LabCorp ] , Burlington , North Carolina ] ) . Insulin resistance in nondiabetic persons was estimated by the quantitative insulin sensitivity check ( QUICK ) index : 1/[(log ( fasting insulin ( U/mL ) ) + ( log fasting glucose(mg/dL ) ) ] . Statistical Analysis Our primary end point was total weight loss at 1 year . Secondary analyses included the change from baseline in serum lipid levels , insulin sensitivity , and glycemic control . We estimated that we would need 100 persons ( 50 per group ) , assuming a 2-sided type I error of 5 % , for the study to have 80 % power to detect a 5-kg greater mean weight loss in the low-carbohydrate group than in the conventional diet group . These calculations were based on an anticipated maximum weight loss by 6 months , with weight stabilization in both diet groups between 6 months and 1 year . To compensate for an anticipated dropout rate of 25 % , we set our enrollment target at 135 persons . R and omization was performed by using a pre-established algorithm generated from a r and om set of numbers that was constructed and held in a separate center and concealed from those enrolling persons during r and omization . We used stratified r and omization , with blocking within strata , to ensure assignment of approximately equal numbers of women , diabetic persons , and severely obese persons ( BMI 40 kg/m2 ) to each study group . Changes in weight , dietary intake , and metabolic data were compared between the 2 diets by r and om-coefficient analysis ( 11 ) . This type of analysis was selected to allow for a variable number of observations for participants and to take into account that the repeated observations of the outcome variables over time for individuals were correlated . The r and om-coefficient analysis model takes these correlations into account by allowing the intercept to vary r and omly among persons . We used a restricted maximum likelihood analysis , which assumed that changes were distributed according to a bivariate normal distribution and that data were missing at r and om . The outcome variables were changes from baseline in weight , dietary macronutrient consumption , and metabolic measurements . For all of these analyses , the covariates included an indicator variable for time ( 6 months and 1 year ) , diet group , and a diet group by time interaction term . This diet group by time interaction term was kept in the model , regardless of its statistical significance ( P = 0.063 for the weight loss analysis ) . Separate analyses to adjust for baseline differences between diet groups were also made by entering the following covariates to each of these models : age ; race ( white or African American ) ; sex ; baseline BMI ; baseline caloric intake ; and the presence or absence of hypertension , use of lipid-lowering therapy , diabetes , active smoking , and sleep apnea ( 12 ) . All variables were assessed for normality before entry into the analyses . Triglyceride , insulin , and glucose levels were skewed and thus were log-transformed before the analyses . Baseline differences between diet groups were compared by chi-square analysis for dichotomous variables and by the unpaired t-test for continuous variables . All P values are 2-sided , and a P value of 0.05 was considered statistically significant . Analyses were performed with SPSS statistical software , version 11.1 ( SPSS , Inc. , Chicago , Illinois ) . Missing Data Of the 132 enrolled persons , follow-up was done at 6 months for 79 persons and at 1 year for 87 persons . For measurements at 6 months , we retrieved weights on an additional 16 persons on the low-carbohydrate diet and 23 persons on the conventional diet ( total , 39 persons at a mean [ SD ] of 6.6 1.2 months ) . For measurements at 1 year , we retrieved weights on 18 persons on the low-carbohydrate diet and 21 persons on the conventional diet ( total , 39 persons at a mean [ SD ] of 13.5 3.2 months ) . Thus , we had 6-month weights on 118 of 132 persons ( 89 % ) and 1-year weights on 126 of 132 persons ( 96 % ) . Of the 18 persons who missed the 6-month visit but returned for the 1-year visit ( 6 in the low-carbohydrate group and 12 in the conventional diet group ) , all but 2 had 6-month weights retrieved from medical records . Of the 6 persons for whom no 1-year weights were available , 2 were in the low-carbohydrate group and 4 in the conventional diet group . The weights retrieved from medical records were obtained on scales that were different from those used for the study and were probably obtained in a nonuniform manner with regard to clothing . We used several approaches to h and le the 45 participants with missing data for diet recall and metabolic measurements . For the primary analysis by r and om-coefficient analysis , we assumed data were missing at r and om . To verify this assumption , we performed sensitivity analyses based on comparisons of baseline characteristics and weight loss differences between those who dropped out and those who completed the study . We also performed 2 additional sensitivity
According to the network meta- analysis the Mediterranean diet is the most effective and efficacious dietary approach to improve glycaemic control in type 2 diabetes patients
The aim of the present study is to assess the comparative efficacy of different dietary approaches on glycaemic control in patients with type 2 diabetes mellitus using a systematic review of the literature .