Rafael Gabriel

A Single Factor Underlies the Metabolic Syndrome: A confirmatory factor analysis

OBJECTIVE Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. RESEARCH DESIGN AND METHODS Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. RESULTS The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. CONCLUSIONS These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Prevalence of PD and other types of parkinsonism in three elderly populations of central Spain.

The prevalence of Parkinsons disease (PD) and other types of parkinsonism in three elderly populations of central Spain was investigated using a door‐to‐door, two‐phase approach. This design called for the administration of a brief questionnaire to subjects 65 years of age or older taken from the census of one urban municipality of Greater Madrid (Margaritas, Getafe), one rural site (Arévalo County, Ávila), and one urban district of Madrid (Lista) in Spain (N = 5,278). Study neurologists extensively investigated those subjects who screened positively. The diagnoses, based on specified criteria, were reviewed to increase reliability across neurologists. We found 118 subjects with parkinsonism: 81 affected by PD (68.6%), 26 drug‐induced parkinsonism (22.0%), 6 parkinsonism in dementia (5.1%), 3 vascular parkinsonism (2.5%), and 2 unspecified parkinsonism (1.7%). The prevalence was 2.2% (95% confidence interval [CI], 1.8–2.6) for all types of parkinsonism and 1.5% (95% CI, 1.2–1.8) for PD. The prevalence estimates of parkinsonism and PD increased with age, declining at 85 years and over. Age prevalence ratios were higher for men. Twenty‐three subjects (28.4%) of the subjects with PD were detected through the screening and had not been diagnosed previously. Overall prevalence estimates of PD and other types of parkinsonism in central Spain rank at levels similar to those recently reported for other European and non‐European elderly populations. Despite improvement in access to health services, an important proportion of PD patients may never seek neurological attention.

Prevalencia, distribución y variabilidad geográfica de los principales factores de riesgo cardiovascular en España. Análisis agrupado de datos individuales de estudios epidemiológicos poblacionales: estudio ERICE

Introduccion y objetivos Estimar la prevalencia y la distribucion geografica de los principales factores de riesgo cardiovascular en la poblacion espanola. Investigar la existencia de diferencias geograficas. Metodos Agregacion de ocho estudios epidemiologicos transversales, realizados en Espana entre 1992 y 2001, que superaron criterios de calidad metodologica. Reanalisis conjunto de los datos individuales por grupos de edad (20-44, 45-64 y ≥ 65 anos), sexo y grandes areas geograficas. Poblacion de estudio: 19.729 sujetos. Estimacion de valores medios y prevalencias crudas y ajustadas. Resultados Por orden decreciente, los factores de riesgo cardiovascular mas frecuentes en la poblacion espanola fueron la hipercolesterolemia (colesterol total > 200 mg/dl, 46,7%), hipertension arterial (37,6%), tabaquismo (32,2%), obesidad (22,8%) y diabetes mellitus (6,2%). Los valores medios de presion arterial, indice de masa corporal, colesterol de las lipoproteinas de alta densidad y glucemia varian ampliamente con la edad, el sexo y las areas geograficas. La mayor carga de factores de riesgo cardiovascular se observa en las zonas sureste y mediterranea y la menor, en las areas norte y centro. Conclusiones En Espana la prevalencia de los principales factores de riesgo cardiovascular es elevada. Hay marcadas diferencias geograficas en su distribucion.

Prevalence, Geographic Distribution, and Geographic Variability of Major Cardiovascular Risk Factors in Spain. Pooled Analysis of Data From Population-Based Epidemiological Studies: The ERICE Study

INTRODUCTION AND OBJECTIVES To determine the prevalence and geographic distribution of major cardiovascular risk factors in the Spanish population. To investigate whether geographic variability exists. METHODS Data were pooled from eight cross-sectional epidemiologic studies carried out in Spain between 1992 and 2001 whose methodological quality satisfied predefined criteria. Individual data were reassessed and analyzed by age group (20-44 years, 45-64 years, and 365 years), sex and geographic area. The study population included 19,729 individuals. Mean values and unadjusted and adjusted prevalence rates were derived for various risk factors. RESULTS The most common cardiovascular risk factors in the Spanish population were, in descending order: hypercholesterolemia (i.e., total cholesterol >200 mg/dL) in 46.7%, hypertension in 37.6%, smoking in 32.2%, obesity in 22.8%, and diabetes mellitus in 6.2%. The mean values for blood pressure, body mass index, high-density lipoprotein cholesterol and glycemia varied considerably with age, sex and geographic area. The highest levels of cardiovascular risk factors were observed in Mediterranean and south-eastern areas of the country and the lowest, in northern and central areas. CONCLUSIONS The prevalence of major cardiovascular risk factors in Spain was high. Their distribution varied considerably with geographic area.

Prevalence of Stroke and Transient Ischemic Attack in Three Elderly Populations of Central Spain

Objective: Our aim was to assess prevalence rates of cerebrovascular disease (CVD; stroke and transient ischemic attacks) according to age and gender in three populations in central Spain using data from the Neurological Disorders in Central Spain (NEDICES) study, a population-based survey of elderly participants. Methods: Individuals from one suburban municipality of Greater Madrid (Las Margaritas neighborhood, Getafe), one urban district of Madrid (Lista) and one rural site (Arévalo county, Avila) were evaluated at baseline (n = 5,278). The evaluation included a screening questionnaire and a neurological assessment when possible. We used point prevalence with a reference date of May 1, 1994. Results: Of the 5,278 subjects, there were 186 prevalent stroke cases and 71 cases of transient ischemic attacks. Prevalence rates, adjusted to the standard European populations, were 4.9% for CVD (95% confidence interval [CI] = 4.3–5.4), 3.4% for stroke (95% CI = 2.9–3.9) and 1.3% for transient ischemic attacks (95% CI = 1.0–1.6) in the total population. Age-specific prevalence rates of CVD, stroke and transient ischemic attacks increased exponentially with advancing age. The prevalence rates of CVD, stroke and transient ischemic attacks were higher for men than for women. Prevalence figures were higher in the suburban area of Margaritas compared to the rural region. Conclusions: In this study, the prevalence of stroke and transient ischemic attacks were higher in men and in urban areas. Central Spain would be a medium stroke prevalence zone.

Which Obesity Index Best Explains Prevalence Differences in Type 2 Diabetes Mellitus

Objective: Obesity drives the diabetes epidemic. However, it is not known which obesity index best explains variations in type 2 diabetes mellitus prevalence across populations.

Low-Grade Chronic Inflammation in the Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC) Population: Associations with insulin resistance and cardiometabolic risk profile

OBJECTIVE Low-grade chronic inflammation has been hypothesized to underlie the constellation of cardiometabolic risk factors, possibly by inducing insulin resistance. In the present study, we investigated associations between inflammation markers, insulin sensitivity (expressed as the ratio of the M value to the mean plasma insulin concentrations measured during the final 40 min of the clamp [M/I]), and a range of cardiometabolic risk factors in a large, healthy population. RESEARCH DESIGN AND METHODS The Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC) cohort includes 1,326 nondiabetic European men and women, aged between 30 and 60 years. We measured cardiometabolic risk factors and performed a hyperinsulinemic-euglycemic clamp. We determined total white blood cell count (WBC) and erythrocyte sedimentation rate (ESR) as markers of chronic inflammation. RESULTS WBC and ESR were both strongly associated with M/I. WBC and ESR were further associated with a range of cardiometabolic risk factors. Associations between WBC and HDL cholesterol, triglycerides, heart rate, fasting C-peptide, and insulin and 2-h insulin in men and women and between WBC and 2-h glucose in women remained significant after adjustment for both M/I and waist circumference. Associations between ESR and HDL cholesterol, heart rate, fasting, and 2-h insulin in men and women and between ESR and fat mass in women remained significant after adjustment for M/I and waist circumference. CONCLUSIONS This study showed that low-grade chronic inflammation is associated with the cardiometabolic risk profile of a healthy population. Insulin resistance, although strongly associated with inflammation, does not seem to play a large intermediary role.

Dementia, stroke and Parkinson's disease in spanish populations: A review of door-to-door prevalence surveys

We identified 14 door-to-door prevalence surveys on dementia, parkinsonism or stroke in Spanish populations fulfilling specific criteria and combined selected age- and sex-specific data using logistic regression and taking Pamplona as a reference. The prevalence of dementia and of Alzheimer’s disease varied significantly with space. However, the largest variation was seen for vascular dementia: odds ratio (OR) and 95% confidence interval (CI) for Gerona were 6.42 (3.23–12.3) in women and 2.30 (1.10–4.79) in men. Stroke was particularly frequent among Arevalo’s women, with OR 2.10 and 95% CI 1.26–3.49. The prevalence of Parkinson’s disease was twofold higher in Cantalejo. Although differences in methodology make the interpretation of results problematic, the prevalence of stroke and vascular dementia in Spain seems to vary spatially, indicating a space for prevention.

Metabolic normality in overweight and obese subjects. Which parameters? Which risks?

Objectives:The objective of this study was to define metabolic normality and to investigate the cardiometabolic profile of metabolically normal obese.Design:Cross-sectional study conducted at 21 research centers in Europe.Subjects:Normal body weight (nbw, n=382) and overweight or obese (ow/ob, n=185) subjects free from metabolic syndrome and with normal glucose tolerance, were selected among the Relationship between Insulin Sensitivity and Cardiovascular Disease study participants.Main outcome measures:Insulin sensitivity was assessed by the clamp technique. On the basis of quartiles in nbw subjects, the limits of normal insulin sensitivity and of normal fasting insulinemia were established. Subjects with normal insulin sensitivity and fasting insulin were defined as metabolically normal.Results:Among ow/ob subjects, 11% were metabolically normal vs 37% among nbw, P<0.0001. Ow/ob subjects showed increased fasting insulin (P=0.0009), low-density lipoprotein cholesterol (LDL-cholesterol) (P=0.004), systolic (P=0.0007) and diastolic (P=0.001) blood pressure, as compared with nbw. When evaluating the contribution of body mass index (BMI), hyperinsulinemia and insulin resistance, BMI showed an isolated effect on high-density lipoprotein (P=0.007), high-sensitivity C-reactive protein (P<0.0001), systolic (P=0.002) and diastolic (P=0.008) blood pressures. BMI shared its influence with insulinemia on total cholesterol (P=0.04 and 0.003, respectively), LDL-cholesterol (P=0.003 and 0.006, respectively) and triglycerides (P=0.02 and 0.001, respectively).Conclusion:In obese subjects, fasting insulin should be taken into account in the definition of metabolic normality. Even when metabolically normal, obese subjects could be at increased risk for cardiometabolic diseases. Increased BMI, alone or with fasting insulin, is the major responsible for the less favorable cardio-metabolic profile.

The association between leptin and left ventricular hypertrophy: a population-based cross-sectional study

Background and objectives Plasma leptin levels have been shown to be an independent risk factor for cardiovascular disease. Leptin has been shown to have sympathetic and vascular effects, and may increase cardiovascular risk through increased blood pressure, left ventricular hypertrophy, or atherosclerotic mechanisms. This study examines whether leptin levels, independent of body mass and insulin resistance, are a risk factor for hypertension and left ventricular hypertrophy. Methods and participants A population-based, cross-sectional sample of 410 adults from rural Spain was studied. The correlations between plasma leptin levels and left ventricular mass index, sum of wall thicknesses, and blood pressure were calculated. Multiple linear regression analysis was used to adjust for other cardiovascular risk factors. Results After adjusting for age, body mass index, systolic blood pressure, sex, and insulin resistance, leptin was inversely associated with left ventricular mass index (β = −0.20, P < 0.01). Leptin was also inversely related to the sum of wall thicknesses; however, this association did not reach statistical significance (β = −0.12, P = 0.063). Leptin was not statistically associated with blood pressure after adjusting for body mass index. Conclusions The results do not support the hypothesis that leptin increases cardiovascular risk by increasing left ventricular mass index or blood pressure. Other mechanisms, related to atherosclerosis, could explain the increased risk of cardiovascular diseases observed with high leptin levels.