The dynamic behaviour of metabolic syndrome and its components in an eight-year population-based cohort from the Mediterranean

Síndrome X de resistència a la insulina; Síndrome metabòlica; ObesitatSíndrome X de resistencia a la insulina; Síndrome metabólico; ObesidadInsulin Resistance Syndrome X; Metabolic syndrome; ObesityBACKGROUND The significant rise in the prevalence of obesity coincides with the considerable increase in the prevalence of metabolic syndrome (MS) currently being observed worldwide. The components of MS are not static and their dynamics, such as the order of their occurrence, or the time of exposure to them are, as yet, unknown but could well be clinically relevant. Our objective was to study the dynamic behaviour of MS and its components in a large population-based cohort from a Mediterranean region. METHODS AND FINDINGS Our study employed a retrospective cohort (between January 1, 2005 and December 31, 2012) made up of individuals from the general population in a region in the northeast of Catalonia, Spain. Given that most of the explicative variables of the risk of having MS were time dependent and, therefore, the risk was not proportional, we used the Andersen-Gill (AG) model to perform a multivariate survival analysis and inferences were performed using a Bayesian framework. Thirty-nine percent of the participants developed MS; 44.6% of them with a single limited episode. Triglycerides and low HDL cholesterol, together with obesity, are components associated with the first occurrence of MS. Components related to the metabolism of glucose are associated with a medium risk of having a first episode of MS, and those related to blood pressure are associated with a lower risk. When the components related to blood pressure and the metabolism of glucose appear first, they determine the appearance of the first episode of MS. The variables concerning the persistence of MS are those that correspond to clinical conditions that do not have well-established drug treatment criteria. CONCLUSIONS Our results suggest that the components related to the metabolism of glucose and to high blood pressure appear early on and act as biomarkers for predicting MS, while the components related to obesity and dyslipidaemia, although essential for the development of MS, appear later. Making lifestyle changes reduces the conditions associated with the persistence of MS

Chronic kidney disease in the type 2 diabetic patients: prevalence and associated variables in a random sample of 2642 patients of a Mediterranean area

Background: Kidney disease is associated with an increased total mortality and cardiovascular morbimortality in the general population and in patients with Type 2 diabetes. The aim of this study is to determine the prevalence of kidney disease and different types of renal disease in patients with type 2 diabetes (T2DM). Methods: Cross-sectional study in a random sample of 2,642 T2DM patients cared for in primary care during 2007. Studied variables: demographic and clinical characteristics, pharmacological treatments and T2DM complications (diabetic foot, retinopathy, coronary heart disease and stroke). Variables of renal function were defined as follows: 1) Microalbuminuria: albumin excretion rate & 30 mg/g or 3.5 mg/mmol, 2) Macroalbuminuria: albumin excretion rate & 300 mg/g or 35 mg/mmol, 3) Kidney disease (KD): glomerular filtration rate according to Modification of Diet in Renal Disease < 60 ml/min/1.73 m2 and/or the presence of albuminuria, 4) Renal impairment (RI): glomerular filtration rate < 60 ml/min/1.73 m2, 5) Nonalbuminuric RI: glomerular filtration rate < 60 ml/min/1.73 m2 without albuminuria and, 5) Diabetic nephropathy (DN): macroalbuminuria or microalbuminuria plus diabetic retinopathy. Results: The prevalence of different types of renal disease in patients was: 34.1% KD, 22.9% RI, 19.5% albuminuria and 16.4% diabetic nephropathy (DN). The prevalence of albuminuria without RI (13.5%) and nonalbuminuric RI (14.7%) was similar. After adjusting per age, BMI, cholesterol, blood pressure and macrovascular disease, RI was significantly associated with the female gender (OR 2.20; CI 95% 1.86-2.59), microvascular disease (OR 2.14; CI 95% 1.8-2.54) and insulin treatment (OR 1.82; CI 95% 1.39-2.38), and inversely associated with HbA1c (OR 0.85 for every 1% increase; CI 95% 0.80-0.91). Albuminuria without RI was inversely associated with the female gender (OR 0.27; CI 95% 0.21-0.35), duration of diabetes (OR 0.94 per year; CI 95% 0.91-0.97) and directly associated with HbA1c (OR 1.19 for every 1% increase; CI 95% 1.09-1.3). Conclusions: One-third of the sample population in this study has KD. The presence or absence of albuminuria identifies two subgroups with different characteristics related to gender, the duration of diabetes and metabolic status of the patient. It is important to determine both albuminuria and GFR estimation to diagnose KD

The dynamic behaviour of metabolic syndrome and its components in an eight-year population-based cohort from the Mediterranean

Síndrome X de resistència a la insulina; Síndrome metabòlica; ObesitatSíndrome X de resistencia a la insulina; Síndrome metabólico; ObesidadInsulin Resistance Syndrome X; Metabolic syndrome; ObesityBACKGROUND The significant rise in the prevalence of obesity coincides with the considerable increase in the prevalence of metabolic syndrome (MS) currently being observed worldwide. The components of MS are not static and their dynamics, such as the order of their occurrence, or the time of exposure to them are, as yet, unknown but could well be clinically relevant. Our objective was to study the dynamic behaviour of MS and its components in a large population-based cohort from a Mediterranean region. METHODS AND FINDINGS Our study employed a retrospective cohort (between January 1, 2005 and December 31, 2012) made up of individuals from the general population in a region in the northeast of Catalonia, Spain. Given that most of the explicative variables of the risk of having MS were time dependent and, therefore, the risk was not proportional, we used the Andersen-Gill (AG) model to perform a multivariate survival analysis and inferences were performed using a Bayesian framework. Thirty-nine percent of the participants developed MS; 44.6% of them with a single limited episode. Triglycerides and low HDL cholesterol, together with obesity, are components associated with the first occurrence of MS. Components related to the metabolism of glucose are associated with a medium risk of having a first episode of MS, and those related to blood pressure are associated with a lower risk. When the components related to blood pressure and the metabolism of glucose appear first, they determine the appearance of the first episode of MS. The variables concerning the persistence of MS are those that correspond to clinical conditions that do not have well-established drug treatment criteria. CONCLUSIONS Our results suggest that the components related to the metabolism of glucose and to high blood pressure appear early on and act as biomarkers for predicting MS, while the components related to obesity and dyslipidaemia, although essential for the development of MS, appear later. Making lifestyle changes reduces the conditions associated with the persistence of MS

Risk of the first episode of metabolic syndrome in relation to the occurrence of the first two components.

<p>Multivariate analysis.</p

Variables related to the risk of persistent or non-persistent metabolic syndrome.

<p>Multivariate analysis.</p

Survival curves.

<p><b>Survival rate (percentage of subjects without MS episode) from the occurrence of the component, in accordance with the first occurrence of components related to glucose metabolism, combined with dyslipidaemia.</b> The horizontal line represents a 50% probability (of the first MS episode occurring).</p

Baseline characteristics of participants who developed one or more than one metabolic syndrome episode.

<p>Baseline characteristics of participants who developed one or more than one metabolic syndrome episode.</p

Variables related to the risk of the occurrence of the first episode of metabolic syndrome and to the risk of the occurrence of any episode of metabolic syndrome.

<p>Multivariate analyses.</p

Order in which the components appear and risk first metabolic syndrome episode.

<p>Order in which the components appear and risk first metabolic syndrome episode.</p