Soort document: Journal Article
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Meer over auteurs/freelancers verbonden aan het LBI :
Dr. Herman van Wietmarschen
Taal van het document: Engels
Title in English: Predictors of Diet-Induced Weight Loss in Overweight Adults with Type 2 Diabetes
Abstract / summary in English:
A very low calorie diet improves the metabolic regulation of obesity related type 2 diabetes, but not for all patients, which leads to frustration in patients and professionals alike. The aim of this study was to develop a prediction model of diet-induced weight loss in type 2 diabetes.
192 patients with type 2 diabetes and BMI>27 kg/m2 from the outpatient diabetes clinic of the Erasmus Medical Center underwent an 8-week very low calorie diet. Baseline demographic, psychological and physiological parameters were measured and the C-index was calculated of the model with the largest explained variance of relative weight loss using backward linear regression analysis. The model was internally validated using bootstrapping techniques.
Weight loss after the diet was 7.8±4.6 kg (95%CI 7.2–8.5; p<0.001) and was independently associated with the baseline variables fasting glucose (B = -0.33 (95%CI -0.49, -0.18), p =0.001), anxiety (HADS; B = -0.22 (95%CI -0.34, -0.11), p = 0.001), numb feeling in extremities (B = 1.86 (95%CI 0.85, 2.87), p = 0.002), insulin dose (B = 0.01 (95%CI 0.00, 0.02), p =0.014) and waist-to-hip ratio (B = 6.79 (95%CI 2.10, 11.78), p = 0.003). This model explained 25% of the variance in weight loss. The C-index of this model to predict successful (5%) weight loss was 0.74 (95%CI 0.67–0.82), with a sensitivity of 0.93 (95% CI 0.89–0.97) and specificity of 0.29 (95% CI 0.16–0.42). When only the obese T2D patients (BMI30 kg/m2; n = 181) were considered, age also contributed to the model (B = 0.06 (95%CI 0.02, 0.11), p = 0.008), whereas waist-to-hip ratio did not.
Diet-induced weight loss in overweight adults with T2D was predicted by five baseline parameters, which were predominantly diabetes related. However, failure seems difficult to predict. We propose to test this prediction model in future prospective diet intervention studies in patients with type 2 diabetes.
Keywords in English: Weight loss, insulin, diet, diabetes mellitus, obesity, depression, dose prediction methods, eating disorders