Alonso-Moran E.,Basque Institute for Healthcare Innovation |
Orueta J.F.,Astrabudua Health Center |
Esteban J.I.F.,San Miguel Health Center |
Gonzalez M.L.M.,Osakidetza |
And 6 more authors.
BMC Public Health | Year: 2014
Background: Type 2 diabetes mellitus is associated with a diverse range of pathologies. The aim of the study was to determine the incidence of diabetes-related complications, the prevalence of coexistent chronic conditions and to report multimorbidity in people with type 2 diabetes living in the Basque Country.Methods. Administrative databases, in four cross sections (annually from 2007 to 2011) were consulted to analyse 149,015 individual records from patients aged ≥35 years with type 2 diabetes mellitus. The data observed were: age, sex, diabetes-related complications (annual rates of acute myocardial infarction, major amputations and avoidable hospitalisations), diabetes-related pathologies (prevalence of ischaemic heart disease, renal failure, stroke, heart failure, peripheral neuropathy, foot ulcers and diabetic retinopathy) and other unrelated pathologies (44 diseases).Results: The annual incidence for each condition progressively decreased during the four-year period: acute myocardial infarction (0.47 to 0.40%), major amputations (0.10 to 0.08%), and avoidable hospitalisations (5.85 to 5.5%). The prevalence for diabetes-related chronic pathologies was: ischaemic heart disease (11.5%), renal failure (8.4%), stroke (7.0%), heart failure (4.3%), peripheral neuropathy (1.3%), foot ulcers (2.0%) and diabetic retinopathy (7.2%). The prevalence of multimorbidity was 90.4%. The highest prevalence for other chronic conditions was 73.7% for hypertension, 13.8% for dyspepsia and 12.7% for anxiety.Conclusions: In the type 2 diabetes mellitus population living in the Basque Country, incidence rates of diabetes complications are not as high as in other places. However, they present a high prevalence of diabetes related and unrelated diseases. Multimorbidity is very common in this group, and is a factor to be taken into account to ensure correct clinical management. © 2014 Alonso-Morán et al.; licensee BioMed Central Ltd. Source
Gutierrez-Repiso C.,Spanish Biomedical Research Center |
Gutierrez-Repiso C.,Hospital Regional Universitario |
Gutierrez-Repiso C.,Institute Investigacion Biomedica Of Malaga Ibima |
Soriguer F.,Spanish Biomedical Research Center |
And 31 more authors.
Sleep Medicine | Year: 2014
Background: Several recent studies have related short sleep duration with different health problems, though the results related with the risk of obesity and type 2 diabetes (T2D) are far from conclusive. The aim of this study was to investigate the association between night-time sleep duration and the incidence of obesity and T2D in a prospective study with a follow-up of 11 years. Material and methods: The study comprised 1145 people evaluated in 1997-1998 and re-evaluated after 6 years and 11 years. At the three study points, subjects without known diabetes mellitus (KDM) were given an oral glucose tolerance test (OGTT). Anthropometric and biochemical variables were measured. The subjects were asked about their number of hours of night-time sleep. Results: After adjustment, the OR of becoming obese was significantly higher in subjects who slept ≤7 hours per night, at both the 6-year follow-up (OR = 1.99; 95% CI = 1.12-3.55) and the 11-year follow-up (OR = 2.73; 95% CI = 1.47-5.04). The incidence of T2D at the 6-year follow-up in subjects without T2D at baseline was higher in those who slept ≤7 hours per night (OR = 1.96; 95% CI = 1.10-3.50). However, this association was not independent of obesity, weight gain or abnormal glucose regulation at baseline. At the 11-year follow-up however there was no association between night-time sleep duration and the incidence of T2D. Conclusions: The incidence of obesity over the 11-year follow-up increased in subjects with fewer hours of night-time sleep. The incidence of T2D according to the hours of night-time sleep depended on obesity and the carbohydrate metabolism phenotype. © 2014 Elsevier B.V. Source
Canellas N.,Rovira i Virgili University |
Canellas N.,Spanish Biomedical Research Center |
Sola-Alberich R.,St Joan University Hosp |
Sola-Alberich R.,Spanish Biomedical Research Center |
And 15 more authors.
Chemometrics and Intelligent Laboratory Systems | Year: 2013
The study of nutritional interventions in humans is difficult to assess because the induced metabolic changes are lower than the natural biological variability between subjects. Due to its holistic approach, 1H NMR is one of the preferred technologies for this type of studies, even though it has a very low sensitivity. This work shows how the use of several chemometric algorithms on the measured data compensates for these drawbacks and allows the study of the effects of the nutritional intervention isolating them from the natural variability inherent to human studies. Mild to moderate hypercholesterolemic patients received either placebo or soluble fiber in a low saturated fat diet. Plasma samples were collected at week 0 and week 8. Spectra obtained with NMR equipment were processed with ANOVA simultaneous component analysis (ASCA). The application of clustering techniques revealed different responses based on the patient's basal state, which allowed the identification of responders from non-responders. Results showed a triglyceride level reduction of up to 15% (p=0.0032), with a higher reduction for those patients with a higher initial lipid profile. Moreover, line-shape fitting techniques applied to the NMR spectra allowed the conclusion that LDL (and VLDL) lipoprotein particles, and more noticeably triglycerides, moved to a profile configuration associated with lower cardiovascular risk. Results shed light on some of the metabolic modifications that husk fiber induces in humans which could not be seen with more conventional data analysis approaches. Our conclusion is that by using the right chemometric techniques it is possible to assess nutritional intervention effects in human NMR human studies despite the low sensitivity and selectivity that the technique offers today. © 2012 Elsevier B.V. Source