OBJECTIVEEmotional distress is common in outpatients with diabetes, affecting ∼20–40% of the patients. The aim of this study was to determine the effectiveness of group therapy with Mindfulness-Based Cognitive Therapy (MBCT), relative to usual care, for patients with diabetes with regard to reducing emotional distress and improving health-related quality of life and glycemic control.RESEARCH DESIGN AND METHODSIn the present randomized controlled trial, 139 outpatients with diabetes (type 1 or type 2) and low levels of emotional well-being were randomized to MBCT (n = 70) or a waiting list group (n = 69). Primary outcomes were perceived stress (Perceived Stress Scale), anxiety and depressive symptoms (Hospital Anxiety and Depression Scale), mood (Profiles of Mood States), and diabetes-specific distress (Problem Areas In Diabetes). Secondary outcomes were health-related quality of life (12-Item Short-Form Health Survey), and glycemic control (HbA1c). Assessments were conducted at baseline and at 4 and 8 weeks of follow-up.RESULTSCompared with control, MBCT was more effective in reducing stress (P < 0.001, Cohen d = 0.70), depressive symptoms (P = 0.006, d = 0.59), and anxiety (P = 0.019, d = 0.44). In addition, MBCT was more effective in improving quality of life (mental: P = 0.003, d = 0.55; physical: P = 0.032, d = 0.40). We found no significant effect on HbA1c or diabetes-specific distress, although patients with elevated diabetes distress in the MBCT group tended to show a decrease in diabetes distress (P = 0.07, d = 0.70) compared with the control group.CONCLUSIONSCompared with usual care, MBCT resulted in a reduction of emotional distress and an increase in health-related quality of life in diabetic patients who had lower levels of emotional well-being.

In diabetic pregnancy, use of intermittent retrospective CGM did not reduce the risk of macrosomia. CGM provides detailed information concerning glycaemic fluctuations but, as a treatment strategy, does not translate into improved pregnancy outcome.

Dutch Trial Register NTR2145, http://www.trialregister.nl.

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BackgroundType 2 diabetes is a major healthcare problem. Glucose-, lipid-, and blood pressure-lowering strategies decrease the risk of micro- and macrovascular complications. However, a substantial residual risk remains. To unravel the etiology of type 2 diabetes and its complications, large-scale, well-phenotyped studies with prospective follow-up are needed. This is the goal of the DiaGene study. In this manuscript, we describe the design and baseline characteristics of the study.MethodsThe DiaGene study is a multi-centre, prospective, extensively phenotyped type 2 diabetes cohort study with concurrent inclusion of diabetes-free individuals at baseline as controls in the city of Eindhoven, The Netherlands. We collected anthropometry, laboratory measurements, DNA material, and detailed information on medication usage, family history, lifestyle and past medical history. Furthermore, we assessed the prevalence and incidence of retinopathy, nephropathy, neuropathy, and diabetic feet in cases. Using logistic regression models, we analyzed the association of 11 well known genetic risk variants with type 2 diabetes in our study.ResultsIn total, 1886 patients with type 2 diabetes and 854 controls were included. Cases had worse anthropometric and metabolic profiles than controls. Patients in outpatient clinics had higher prevalence of macrovascular (41.9% vs. 34.8%; P = 0.002) and microvascular disease (63.8% vs. 20.7%) compared to patients from primary care. With the exception of the genetic variant in KCNJ11, all type 2 diabetes susceptibility variants had higher allele frequencies in subjects with type 2 diabetes than in controls.ConclusionsIn our study population, considerable rates of macrovascular and microvascular complications are present despite treatment. These prevalence rates are comparable to other type 2 diabetes populations. While planning genomics, we describe that 11 well-known type 2 diabetes genetic risk variants (in TCF7L2, PPARG-P12A, KCNJ11, FTO, IGF2BP2, DUSP9, CENTD2, THADA, HHEX, CDKAL1, KCNQ1) showed similar associations compared to literature. This study is well-suited for multiple omics analyses to further elucidate disease pathophysiology. Our overall goal is to increase the understanding of the underlying mechanisms of type 2 diabetes and its complications for developing new prediction, prevention, and treatment strategies.Electronic supplementary materialThe online version of this article (doi:10.1186/s13098-017-0245-x) contains supplementary material, which is available to authorized users.