To examine whether elevated anxiety and/or depressive symptoms are related to all-cause mortality in people with Type 2 diabetes, not using insulin.
948 participants in the community-wide Nord-Trøndelag Health Survey conducted during 1995-97 completed the Hospital Anxiety and Depression Scale with subscales of anxiety (HADS-A) and depression (HADS-D). Elevated symptoms were defined as HADS-A or HADS-D =8. Participants with type 2 diabetes, not using insulin, were followed until November 21, 2012 or death. Cox regression analyses were used to estimate associations between baseline elevated anxiety symptoms, elevated depressive symptoms and mortality, adjusting for sociodemographic factors, HbA1c, cardiovascular disease and microvascular complications.
At baseline, 8% (n = 77/948) reported elevated anxiety symptoms, 9% (n = 87/948) elevated depressive symptoms and 10% (n = 93/948) reported both. After a mean follow-up of 12 years (SD 5.1, range 0-17), 541 participants (57%) had died. Participants with elevated anxiety symptoms only had a decreased mortality risk (unadjusted HR 0.66, 95% CI 0.46-0.96). Adjustment for HbA1c attenuated this relation (HR 0.73, 95% CI 0.50-1.07). Those with elevated depression symptoms alone had an increased mortality risk (fully adjusted model HR 1.39, 95% CI 1.05-1.84). Having both elevated anxiety and depressive symptoms was not associated with increased mortality risk (adjusted HR 1.30, 95% CI 0.96-1.74).
Elevated depressive symptoms were associated with excess mortality risk in people with Type 2 diabetes not using insulin. No significant association with mortality was found among people with elevated anxiety symptoms. Having both elevated anxiety and depressive symptoms was not associated with mortality. The hypothesis that elevated levels of anxiety symptoms leads to behavior that counteracts the adverse health effects of Type 2 diabetes needs further investigation.
Several papers have reported higher prevalence of diabetes mellitus (DM) type 2 in patients suffering from bipolar disorder (BD). The possible links between these 2 disorders include treatment, lifestyle, alterations in signal transduction, and possibly, a genetic link. To study this relation more closely, we investigated whether there are any differences in the clinical characteristics of BD patients with and without DM.
We compared the clinical data of 26 diabetic and 196 nondiabetic subjects from The Maritime Bipolar Registry. Subjects were aged 15 to 82 years, with psychiatric diagnoses of BD I (n = 151), BD II (n = 65), and BD not otherwise specified (n = 6). The registry included basic demographic data and details on the clinical course of bipolar illness, its treatment, and physical comorbidity. In a subsequent analysis using logistic regression, we examined the variables showing differences between groups, with diabetes as an outcome variable.
The prevalence of DM in our sample was 11.7% (n = 26). Diabetic patients were significantly older than nondiabetic patients (P
Persons with type 2 diabetes are at increased risk of cognitive dysfunction. Less is known about which cognitive abilities are affected and how undiagnosed diabetes and impaired fasting glucose relate to cognitive performance. The authors explored this question using data from 1,917 nondemented men and women (average age = 76 years) in the population-based Age, Gene/Environment Susceptibility-Reykjavik Study (2002-2006). Glycemic status groups included diagnosed diabetes (self-reported diabetes or diabetic medication use; n = 163 (8.5%)), undiagnosed diabetes (fasting blood glucose >or=7.0 mmol/L without diagnosed diabetes; n = 55 (2.9%)), and impaired fasting glucose (fasting blood glucose 5.6-6.9 mmol/L; n = 744 (38.8%)). Composites of memory, processing speed (PS), and executive function were constructed from a neuropsychological battery. Linear regression was used to investigate cross-sectional differences in cognitive performance between glycemic groups, adjusted for demographic and health factors. Persons with diagnosed diabetes had slower PS than normoglycemics (beta = -0.12; P or=15 years was associated with significantly poorer PS and executive function. Undiagnosed diabetics had slower PS (beta = -0.22; P
The aim of this study was to assess the performance of the Finnish Diabetes Risk Score as a screening tool for undetected type 2 diabetes (T2D), abnormal glucose tolerance (AGT) and metabolic syndrome in the general population. In a cross-sectional, population-based survey, a total of 4,622 subjects aged 45-74 years were invited to a health examination that included an oral glucose tolerance test. Full data with risk score estimate and glucose tolerance status were available for 2,966 subjects without a prior history of diabetes. The risk score was associated with the presence of previously undiagnosed T2D, AGT, metabolic syndrome and cardiovascular risk factors. The area under the receiver operating curve for the prevalence of undiagnosed diabetes was 0.72 in men and 0.73 in women. The sensitivity using a cutoff risk score of 11 to identify undiagnosed diabetes was 66% in men and 70% in women; the corresponding false-positive rates were 31% and 39%, respectively. The area under the receiver operating curve for detecting the metabolic syndrome was 0.72 in men and 0.75 in women. The Finnish Diabetes Risk Score can be used as a self-administered test to screen subjects at high risk for T2D. It can also be used in the general population and clinical practice to identify undetected T2D, AGT and the metabolic syndrome.
A diagnosis of the metabolic syndrome in youth that resolves by adult life is associated with a normalization of high carotid intima-media thickness and type 2 diabetes mellitus risk: the Bogalusa heart and cardiovascular risk in young Finns studies.
The aim of this study was to examine the effect of resolution from metabolic syndrome (MetS) between youth and adulthood on carotid artery intima-media thickness (IMT) and type 2 diabetes mellitus (T2DM).
Published findings demonstrate that youth with MetS are at increased risk of cardio-metabolic outcomes in adulthood. It is not known whether this risk is attenuated in those who resolve their MetS status.
Participants (n = 1,757) from 2 prospective cohort studies were examined as youth (when 9 to 18 years of age) and re-examined 14 to 27 years later. The presence of any 3 components (low high-density lipoprotein cholesterol, high triglycerides, high glucose, high blood pressure, or high body mass index) previously shown to predict adult outcomes defined youth MetS; the harmonized MetS criteria defined adulthood MetS. Participants were classified according to their MetS status at baseline and follow-up and examined for risk of high IMT and T2DM.
Those with MetS in youth and adulthood were at 3.4 times the risk (95% confidence interval: 2.4 to 4.9) of high IMT and 12.2 times the risk (95% confidence interval: 6.3 to 23.9) of T2DM in adulthood compared with those that did not have MetS at either time-point, whereas those that had resolved their youth MetS status by adulthood showed similar risk to those that did not have MetS at either time-point (p > 0.20 for all comparisons).
Although youth with MetS are at increased risk of adult high IMT and T2DM, these data indicate that the resolution of youth MetS by adulthood can go some way to normalize this risk to levels seen in those who have never had MetS.
Previously undetected dysglycaemia is common among patients with acute coronary syndromes (ACSs). The aim of this study was to identify the most reliable method of diagnosing type 2 diabetes mellitus (T2DM) and prediabetes in ACS patients.
Patients admitted to the coronary care unit with ACSs and no previous history of T2DM were consecutively included in the study. Glucose metabolism was measured by glycated haemoglobin (HbA1c), fasting plasma glucose (FPG) and 2-hour plasma glucose (2hPG) with a standard oral glucose tolerance test during hospital admission, and this process was repeated 3 months later. In this study, the diagnosis of T2DM required at least two measurements above the diabetes cut-off point according to current American Diabetes Association and World Health Organization criteria.
A total of 250 patients were included in the study. T2DM was diagnosed in 7.2%. The sensitivities for detecting T2DM were 33.3%, 61.1% and 77.8% during admission and 27.8%, 61.1% and 72.2% at follow-up for HbA1c, FPG and 2hPG, respectively. The positive predictive values (PPVs) for diagnosing T2DM were 100%, 91.7% and 51.9% during admission and 71.4%, 91.7% and 65.0% at follow-up for HbA1c, FPG and 2hPG, respectively. The specificities and negative predictive values were high for all methods. By combining all measurements, the sensitivity was 100% and the PPV was 44.2%, while the combination of all HbA1c and FPG measurements provided 88.9% sensitivity and 80.0% PPV.
Diagnosis of T2DM can be reliably carried out by repeated measurements of FPG and HbA1c in ACS patients, with limited added value of an oral glucose tolerance test.
Although type 2 diabetes mellitus is a risk factor for developing congestive heart failure, the mechanism leading to heart failure is unclear. We examined the prevalence of left ventricular (LV) systolic and diastolic dysfunction in patients with type 2 diabetes mellitus in relation to vascular function and myocardial perfusion.
A prospective observational study of 305 patients with type 2 diabetes mellitus (diabetes duration, 4.5+/-5.3 years) referred consecutively to a diabetes clinic were screened for LV systolic and diastolic function by echocardiography. Vascular function was estimated using noninvasive estimation of pulse pressure, carotid arterial compliance, total arterial compliance, and valvulo-arterial impedance. The prevalences of LV diastolic dysfunction and left atrial (LA) volume index >32 mL/m(2) were 40% and 32%, respectively. The prevalence of myocardial ischemia on myocardial perfusion scintigraphy was more frequent in patients with grade 2 diastolic dysfunction and LA volume index >32 mL/m(2) compared with those having normal or grade 1 diastolic dysfunction (P=0.002) or LA volume index
To investigate methods for the detection of different clusterings of the insulin-resistant abnormalities consistent with the concept of the 'metabolic syndrome' in clinical practice, and to research the occurrence of these clusters in a middle-aged Finnish population.
We studied a random sample of 207 middle-aged subjects in the city of Tampere, and all 1148 subjects of four middle-aged age groups in Pieksamaki town, in central Finland. Clusterings of the following eight markers of insulin resistance were recorded as the main outcome measures: 1) at least one first-degree relative with non-insulin-dependent diabetes (NIDDM); 2) obesity: body mass index (BMI) > or = 30 kg/m2; 3) central adiposity: waist-to-hip ratio (WHR) > or = 1.00 in men and > or = 0.88 in women; 4) hypertension: systolic blood pressure > or = 160 mmHg or diastolic blood pressure > or = 95 mmHg, or receiving drug treatment for hypertension; 5) hypertriglyceridaemia > or = 1.70 mmol/l; 6) low high-density lipoprotein (HDL) cholesterol: or = 13.0 mU/l.
The metabolic syndrome, defined as a clustering of dyslipidaemia (hypertriglyceridaemia, low HDL cholesterol, or both) and insulin resistance (abnormal glucose tolerance, hyperinsulinaemia, or both) was present in 17% of men and in 8% of women; this sex difference was statistically significant (P
To predict mortality risk and life expectancy for patients with type 2 diabetes after a major diabetes-related complication.
The study sample, taken from the Swedish National Diabetes Register, consisted of 20 836 people with type 2 diabetes who had their first major complication (myocardial infarction, stroke, heart failure, amputation or renal failure) between January 2001 and December 2007. A Gompertz proportional hazards model was derived which determined significant risk factors associated with mortality and was used to estimate life expectancies.
Risk of death changed over time according to type of complication, with myocardial infarction initally having the highest initial risk of death, but after the first month, the risk was higher for heart failure, renal failure and amputation. Other factors that increased the risk of death were male gender (hazard ratio 1.06, 95% CI 1.02-1.12), longer duration of diabetes (hazard ratio 1.07 per 10 years, 95% CI 1.04-1.10), smoking (hazard ratio 1.51, 95% CI 1.40-1.63) and macroalbuminuria (hazard ratio 1.14, 95% CI 1.06-1.22). Low BMI, low systolic blood pressure and low estimated GFR also increased mortality risk. Life expectancy was highest after a stroke, myocardial infarction or heart failure, lower after amputation and lowest after renal failure. Smoking and poor renal function were the risk factors which had the largest impact on reducing life expectancy.
Risk of death and life expectancy differs substantially among the major complications of diabetes, and factors significantly increasing risk included smoking, low estimated GFR and albuminuria.