856 resultados para Etiology metabolic syndrome X risk factors obesity


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Background: The aim was to evaluate the presence of metabolic bone disease (MBD) in patients with Crohn’s disease (CD) and to identify potential etiologic factors. Methods: The case–control study included 99 patients with CD and 56 controls with a similar age and gender distribution. Both groups had dual-energy x-ray absorptionmetry and a nutritional evaluation. Single nucleotide polymorphisms at the IL1, TNF-a, LTa, and IL-6 genes were analyzed in patients only. Statistical analysis was performed using SPSS software. Results: The prevalence of MBD was significantly higher in patients (P ¼ 0.006). CD patients with osteoporosis were older (P < 0.005), small bowel involvement and surgical resections were more frequent (P < 0.005), they more often exhibited a penetrating or stricturing phenotype (P < 0.05), duration of disease over 15 years (P < 0.005), and body mass index (BMI) under 18.5 kg/m2 (P < 0.01) were more often found. No association was found with steroid use. Patients with a Z-score < 2.0 more frequently had chronic active disease (P < 0.05). With regard to diet, low vitamin K intake was more frequent (P ¼ 0.03) and intake of total, monounsaturated, and polyunsaturated fat was higher in patients with Z-score < 2.0 (P < 0.05). With respect to genetics, carriage of the polymorphic allele for LTa252 A/G was associated with a higher risk of osteoporosis (P ¼ 0.02). Regression analysis showed that age over 40 years, chronic active disease, and previous colonic resections were independently associated with the risk of developing MBD. Conclusions: The prevalence of MBD was significantly higher in CD patients. Besides the usual risk factors, we observed that factors related to chronic active and long-lasting disease increased the risk of MBD.

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Background and aim: Cardiorespiratory fitness (CRF) and diet have been involved as significant factors towards the prevention of cardio-metabolic diseases. This study aimed to assess the impact of the combined associations of CRF and adherence to the Southern European Atlantic Diet (SEADiet) on the clustering of metabolic risk factors in adolescents. Methods and Results: A cross-sectional school-based study was conducted on 468 adolescents aged 15-18, from the Azorean Islands, Portugal. We measured fasting glucose, insulin, total cholesterol (TC), HDL-cholesterol, triglycerides, systolic blood pressure, waits circumference and height. HOMA, TC/HDL-C ratio and waist-to-height ratio were calculated. For each of these variables, a Z-score was computed by age and sex. A metabolic risk score (MRS) was constructed by summing the Z scores of all individual risk factors. High risk was considered when the individual had 1SD of this score. CRF was measured with the 20 m-Shuttle-Run- Test. Adherence to SEADiet was assessed with a semi-quantitative food frequency questionnaire. Logistic regression showed that, after adjusting for potential confounders, unfit adolescents with low adherence to SEADiet had the highest odds of having MRS (OR Z 9.4; 95%CI:2.6e33.3) followed by the unfit ones with high adherence to the SEADiet (OR Z 6.6; 95% CI: 1.9e22.5) when compared to those who were fit and had higher adherence to SEADiet.

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INTRODUCTION: Metabolic syndrome (MS) is an independent predictor of acute cardiovascular events. However, few studies have addressed the relationship between MS and stable angiographic coronary artery disease (CAD), which has a different pathophysiological mechanism. We aimed to study the independent predictors for significant CAD, and to analyze the impact of MS (by the AHA/NHLBI definition) on CAD. METHODS: We prospectively included 300 patients, mean age 64±9 years, 59% male, admitted for elective coronary angiography (suspected ischemic heart disease), excluding patients with known cardiac disease. All patients underwent assessment of demographic, anthropometric, and laboratory data and risk factors, and subsequently underwent coronary angiography. RESULTS: In the study population, 23.0% were diabetic, 40.5% had MS (and no diabetes) and 36.7% had neither diagnosis. Significant CAD was present in 51.3% of patients. CAD patients were older and more frequently male and diabetic, with increased triglycerides and glucose and lower HDL cholesterol. Abdominal obesity was also less prevalent. MS was not associated with the presence of CAD (OR 0.94, 95% CI 0.59-1.48, p=0.778). Of the MS components, the most important predictors of CAD were increased glucose and triglycerides. Abdominal obesity was associated with a lower risk of CAD. In a multivariate logistic regression model for CAD, independent predictors of CAD were age, male gender, glucose and triglycerides. Body mass index had a protective effect. CONCLUSIONS: Although MS is associated with cardiovascular events, the same was not found for stable angiographically proven CAD. Age, gender, diabetes and triglycerides are the most influential factors for CAD, with abdominal obesity as a protective factor.

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Background: Cardiovascular diseases are the current leading causes of death and disability globally. Objective: To assess the effects of a basic educational program for cardiovascular prevention in an unselected outpatient population. Methods: All participants received an educational program to change to a healthy lifestyle. Assessments were conducted at study enrollment and during follow-up. Symptoms, habits, ATP III parameters for metabolic syndrome, and American Heart Association’s 2020 parameters of cardiovascular health were assessed. Results: A total of 15,073 participants aged ≥ 18 years entered the study. Data analysis was conducted in 3,009 patients who completed a second assessment. An improvement in weight (from 76.6 ± 15.3 to 76.4 ± 15.3 kg, p = 0.002), dyspnea on exertion NYHA grade II (from 23.4% to 21.0%) and grade III (from 15.8% to 14.0%) and a decrease in the proportion of current active smokers (from 3.6% to 2.9%, p = 0.002) could be documented. The proportion of patients with levels of triglycerides > 150 mg/dL (from 46.3% to 42.4%, p < 0.001) and LDL cholesterol > 100 mg/dL (from 69.3% to 65.5%, p < 0.001) improved. A ≥ 20% improvement of AHA 2020 metrics at the level graded as poor was found for smoking (-21.1%), diet (-29.8%), and cholesterol level (-23.6%). A large dropout as a surrogate indicator for low patient adherence was documented throughout the first 5 visits, 80% between the first and second assessments, 55.6% between the second and third assessments, 43.6% between the third and fourth assessments, and 38% between the fourth and fifth assessments. Conclusion: A simple, basic educational program may improve symptoms and modifiable cardiovascular risk factors, but shows low patient adherence.

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Background:The risk factors that characterize metabolic syndrome (MetS) may be present in childhood and adolescence, increasing the risk of cardiovascular disease in adulthood.Objective:Evaluate the prevalence of MetS and the importance of its associated variables, including insulin resistance (IR), in children and adolescents in the city of Guabiruba-SC, Brazil.Methods:Cross-sectional study with 1011 students (6–14 years, 52.4% girls, 58.5% children). Blood samples were collected for measurement of biochemical parameters by routine laboratory methods. IR was estimated by the HOMA-IR index, and weight, height, waist circumference and blood pressure were determined. Multivariate logistic regression models were used to examine the associations between risk variables and MetS.Results:The prevalence of MetS, IR, overweight and obesity in the cohort were 14%, 8.5%, 21% and 13%, respectively. Among students with MetS, 27% had IR, 33% were overweight, 45.5% were obese and 22% were eutrophic. IR was more common in overweight (48%) and obese (41%) students when compared with eutrophic individuals (11%; p = 0.034). The variables with greatest influence on the development of MetS were obesity (OR = 32.7), overweight (OR = 6.1), IR (OR = 4.4; p ≤ 0.0001 for all) and age (OR = 1.15; p = 0.014).Conclusion:There was a high prevalence of MetS in children and adolescents evaluated in this study. Students who were obese, overweight or insulin resistant had higher chances of developing the syndrome.

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BACKGROUND: Only a few small studies investigated the association between postmenopausal breast cancer and metabolic syndrome (MetS) as a single entity. Materials and methods: We analyzed the data of two Italian and Swiss case-control studies conducted between 1983 and 2007, including 3869 postmenopausal women with incident breast cancer and 4082 postmenopausal controls admitted to the same hospitals as cases for acute conditions. MetS was defined as the presence of at least three components among diabetes, drug-treated hypertension, drug-treated hyperlipidemia, and obesity. RESULTS: The odds ratios (ORs) of postmenopausal breast cancer were 1.33 [95% confidence interval (CI) 1.09-1.62] for diabetes, 1.19 (95% CI 1.07-1.33) for hypertension, 1.08 (95% CI 0.95-1.22) for hyperlipidemia, 1.26 (95% CI 1.11-1.44) for body mass index ≥30 kg/m(2), and 1.22 (95% CI 1.09-1.36) for waist circumference ≥88 cm. The risk of postmenopausal breast cancer was significantly increased for women with MetS (OR = 1.75, 95% CI 1.37-2.22, for three or more MetS components, P for trend for increasing number of components < 0.0001) and the risk was higher at older age (OR = 3.04, 95% CI 1.75-5.29, at age ≥70 years for three or more MetS components). CONCLUSIONS: This study supports a direct association between MetS and postmenopausal breast cancer risk.

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Purpose: HIV-infected patients present an increased cardiovascular risk (CVR) of multifactorial origin, usually lower in women than in men. Information by gender about prevalence of modifiable risk factors is scarce. Methods: Coronator is a cross-sectional survey of a representative sample of HIV-infected patients on ART within 10 hospitals across Spain in 2011. Variables include sociodemographics, CVR factors and 10-year CV disease risk estimation (Regicor: Framingham score adapted to the Spanish population). Results: We included 860 patients (76.3% male) with no history of CVD. Median age 45.6 years; 84.1% were Spaniards; 29.9% women were IDUs. Median time since HIV diagnosis for men and women was 10 and 13 years (p=0.001), 28% had an AIDS diagnosis. Median CD4 cell count was 596 cells/mm3, 88% had undetectable viral load. Median time on ART was 91 and 108 months (p=0.017). There was a family history of early CVD in 113 men (17.9%) and 41 women (20.6%). Classical CVR factors are described in the table. Median (IQR) Regicor Score was 3% (2-5) for men and 2% (1-3) for women (p=0.000), and the proportion of subjects with mid-high risk (>5%) was 26.1% for men and 9.4% for women (p=0.000). Conclusions: In this population of HIV-infected patients, women have lower cardiovascular risk than men, partly due to higher levels of HDL cholesterol. Of note is the high frequency of smoking, abdominal obesity and sedentary lifestyle in our population. (Table Presented).

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To estimate the prevalence of metabolically healthy obesity (MHO) according to different definitions. Population-based sample of 2803 women and 2557 men participated in the study. Metabolic abnormalities were defined using six sets of criteria, which included different combinations of the following: waist; blood pressure; total, high-density lipoprotein or low-density lipoprotein-cholesterol; triglycerides; fasting glucose; homeostasis model assessment; high-sensitivity C-reactive protein; personal history of cardiovascular, respiratory or metabolic diseases. For each set, prevalence of MHO was assessed for body mass index (BMI); waist or percent body fat. Among obese (BMI 30 kg/m(2)) participants, prevalence of MHO ranged between 3.3 and 32.1% in men and between 11.4 and 43.3% in women according to the criteria used. Using abdominal obesity, prevalence of MHO ranged between 5.7 and 36.7% (men) and 12.2 and 57.5% (women). Using percent body fat led to a prevalence of MHO ranging between 6.4 and 43.1% (men) and 12.0 and 55.5% (women). MHO participants had a lower odd of presenting a family history of type 2 diabetes. After multivariate adjustment, the odds of presenting with MHO decreased with increasing age, whereas no relationship was found with gender, alcohol consumption or tobacco smoking using most sets of criteria. Physical activity was positively related, whereas increased waist was negatively related with BMI-defined MHO. MHO prevalence varies considerably according to the criteria used, underscoring the need for a standard definition of this metabolic entity. Physical activity increases the likelihood of presenting with MHO, and MHO is associated with a lower prevalence of family history of type 2 diabetes.

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BACKGROUND: Community-based diabetes screening programs can help sensitize the population and identify new cases. However, the impact of such programs is rarely assessed in high-income countries, where concurrent health information and screening opportunities are common place. INTERVENTION AND METHODS: A 2-week screening and awareness campaign was organized as part of a new diabetes program in the canton of Vaud (population of 697,000) in Switzerland. Screening was performed without appointment in 190 out of 244 pharmacies in the canton at the subsidized cost of 10 Swiss Francs per participant. Screening included questions on risk behaviors, measurement of body mass index, blood pressure, blood cholesterol, random blood glucose (RBG), and A1c if RBG was >/=7.0 mmol/L. A mass media campaign promoting physical activity and a healthy diet was channeled through several media, eg, 165 spots on radio, billboards in 250 public places, flyers in 360 public transport vehicles, and a dozen articles in several newspapers. A telephone survey in a representative sample of the population of the canton was performed after the campaign to evaluate the program. RESULTS: A total of 4222 participants (0.76% of all persons aged >/=18 years) underwent the screening program (median age: 53 years, 63% females). Among participants not treated for diabetes, 3.7% had RBG >/= 7.8 mmol/L and 1.8% had both RBG >/= 7.0 mmol/L and A1c >/= 6.5. Untreated blood pressure >/=140/90 mmHg and/or untreated cholesterol >/=5.2 mmol/L were found in 50.5% of participants. One or several treated or untreated modifiable risk factors were found in 78% of participants. The telephone survey showed that 53% of all adults in the canton were sensitized by the campaign. Excluding fees paid by the participants, the program incurred a cost of CHF 330,600. CONCLUSION: A community-based screening program had low efficiency for detecting new cases of diabetes, but it identified large numbers of persons with elevated other cardiovascular risk factors. Our findings suggest the convenience of A1c for mass screening of diabetes, the usefulness of extending diabetes screening to other cardiovascular risk factors, and the importance of a robust background communication campaign.

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BACKGROUND: We assessed the prevalence of risk factors for cardiovascular disease (CVD) in a middle-income country in rapid epidemiological transition and estimated direct costs for treating all individuals at increased cardiovascular risk, i.e. following the so-called "high risk strategy". METHODS: Survey of risk factors using an age- and sex-stratified random sample of the population of Seychelles aged 25-64 in 2004. Assessment of CVD risk and treatment modalities were in line with international guidelines. Costs are expressed as USD per capita per year. RESULTS: 1255 persons took part in the survey (participation rate of 80.2%). Prevalence of main risk factors was: 39.6% for high blood pressure (> or =140/90 mmHg or treatment) of which 59% were under treatment; 24.2% for high cholesterol (> or =6.2 mmol/l); 20.8% for low HDL-cholesterol (<1.0 mmol/l); 9.3% for diabetes (fasting glucose > or =7.0 mmol/l); 17.5% for smoking; 25.1% for obesity (body mass index > or =30 kg/m2) and 22.1% for the metabolic syndrome. Overall, 43% had HBP, high cholesterol or diabetes and substantially increased CVD risk. The cost for medications needed to treat all high-risk individuals amounted to USD 45.6, i.e. 11.2 dollars for high blood pressure, 3.8 dollars for diabetes, and 30.6 dollars for dyslipidemia (using generic drugs except for hypercholesterolemia). Cost for minimal follow-up medical care and laboratory tests amounted to 22.6 dollars. CONCLUSION: High prevalence of major risk factors was found in a rapidly developing country and costs for treatment needed to reduce risk factors in all high-risk individuals exceeded resources generally available in low or middle income countries. Our findings emphasize the need for affordable cost-effective treatment strategies and the critical importance of population strategies aimed at reducing risk factors in the entire population.

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OBJECTIVE: Few studies have assessed secular changes in the levels of cardiovascular risk factors (CV-RF) in populations of low or middle income countries. The systematic collection of a broad set of both traditional and metabolic CV-RF in 1989 and 2004 in the population of the Seychelles islands provides a unique opportunity to examine trends at a fairly early stage of the "diabesity" era in a country in the African region. METHODS: Two examination surveys were conducted in independent random samples of the population aged 25-64 years in 1989 and 2004, attended by respectively 1081 and 1255 participants (participation rates >80%). All results are age-standardized to the WHO standard population. RESULTS: In 2004 vs. 1989, the levels of the main traditional CV-RF have either decreased, e.g. smoking (17% vs. 30%, p < 0.001), mean blood pressure (127.8/84.8 vs. 130.0/83.4 mmHg, p < 0.05), or only moderately increased, e.g. median LDL-cholesterol (3.58 vs. 3.36 mmol/l, p < 0. 01). In contrast, marked detrimental trends were found for obesity (37% vs. 21%, p < 0.001) and several cardiometabolic CVD-RF, e.g. mean HDL-cholesterol (1.36 vs. 1.40 mmol/l, p < 0.05), median triglycerides (0.80 vs. 0.78 mmol/l, p < 0.01), mean blood glucose (5.89 vs. 5.22 mmol/l, p < 0.001), median insulin (11.6 vs. 8.3 micromol/l, p < 0.001), median HOMA-IR (2.9 vs. 1.8, p < 0.001) and diabetes (9.4% vs. 6.2%, p < 0.001). At age 40-64, the prevalence of elevated total cardiovascular risk tended to decrease (e.g. WHO-ISH risk score > or =10; 11% vs. 13%, ns), whereas the prevalence of the metabolic syndrome (which integrates several cardiometabolic CVD-RF) nearly doubled (36% vs. 20%, p < 0.001). Data on physical activity and on intake of alcohol, fruit and vegetables are also provided. Awareness and treatment rates improved substantially for hypertension and diabetes, but control rates improved for the former only. Median levels of the cardiometabolic CVD-RF increased between 1989 and 2004 within all BMI strata, suggesting that the worsening levels of cardiometabolic CVD-RF in the population were not only related to increasing BMI levels in the interval. CONCLUSION: The levels of several traditional CVD-RF improved over time, while marked detrimental trends were observed for obesity, diabetes and several cardiometabolic factors. Thus, in this population, the rapid health transition was characterized by substantial changes in the patterns of CVD-RF. More generally, this analysis suggests the importance of surveillance systems to identify risk factor trends and the need for preventive strategies to promote healthy lifestyles and nutrition.

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STUDY OBJECTIVES: To evaluate the association between objective sleep measures and metabolic syndrome (MS), hypertension, diabetes, and obesity. DESIGN: Cross-sectional study. SETTING: General population sample. PARTICIPANTS: There were 2,162 patients (51.2% women, mean age 58.4 ± 11.1). INTERVENTIONS: Patients were evaluated for hypertension, diabetes, overweight/obesity, and MS, and underwent a full polysomnography (PSG). MEASUREMENTS AND RESULTS: PSG measured variables included: total sleep time (TST), percentage and time spent in slow wave sleep (SWS) and in rapid eye movement (REM) sleep, sleep efficiency and arousal index (ArI). In univariate analyses, MS was associated with decreased TST, SWS, REM sleep, and sleep efficiency, and increased ArI. After adjustment for age, sex, smoking, alcohol, physical activity, drugs that affect sleep and depression, the ArI remained significantly higher, but the difference disappeared in patients without significant sleep disordered breathing (SDB). Differences in sleep structure were also found according to the presence or absence of hypertension, diabetes, and overweight/obesity in univariate analysis. However, these differences were attenuated after multivariate adjustment and after excluding subjects with significant SDB. CONCLUSIONS: In this population-based sample we found significant associations between sleep structure and MS, hypertension, diabetes, and obesity. However, these associations were cancelled after multivariate adjustment. We conclude that normal variations in sleep contribute little if any to MS and associated disorders.

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Dynamic changes in body weight have long been recognized as important indicators of risk for debilitating diseases. While weight loss or impaired growth can lead to muscle wastage, as well as to susceptibility to infections and organ dysfunctions, the development of excess fat predisposes to type 2 diabetes and cardiovascular diseases, with insulin resistance as a central feature of the disease entities of the metabolic syndrome. Although widely used as the phenotypic expression of adiposity in population and gene-search studies, body mass index (BMI), that is, weight/height(2) (H(2)), which was developed as an operational definition for classifying both obesity and malnutrition, has considerable limitations in delineating fat mass (FM) from fat-free mass (FFM), in particular at the individual level. After an examination of these limitations within the constraints of the BMI-FM% relationship, this paper reviews recent advances in concepts about health risks related to body composition phenotypes, which center upon (i) the partitioning of BMI into an FM index (FM/H(2)) and an FFM index (FFM/H(2)), (ii) the partitioning of FFM into organ mass and skeletal muscle mass, (iii) the anatomical partitioning of FM into hazardous fat and protective fat and (iv) the interplay between adipose tissue expandability and ectopic fat deposition within or around organs/tissues that constitute the lean body mass. These concepts about body composition phenotypes and health risks are reviewed in the light of race/ethnic variability in metabolic susceptibility to obesity and the metabolic syndrome.

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NlmCategory="UNASSIGNED">Metabolic syndrome after transplantation is a major concern following solid organ transplantation (SOT). The CREB-regulated transcription co-activator 2 (CRTC2) regulates glucose metabolism. The effect of CRTC2 polymorphisms on new-onset diabetes after transplantation (NODAT) was investigated in a discovery sample of SOT recipients (n1=197). Positive results were tested for replication in two samples from the Swiss Transplant Cohort Study (STCS, n2=1294 and n3=759). Obesity and other metabolic traits were also tested. Associations with metabolic traits in population-based samples (n4=46'186, n5=123'865, n6>100,000) were finally analyzed. In the discovery sample, CRTC2 rs8450-AA genotype was associated with NODAT, fasting blood glucose and body mass index (Pcorrected<0.05). CRTC2 rs8450-AA genotype was associated with NODAT in the second STCS replication sample (odd ratio (OR)=2.01, P=0.04). In the combined STCS replication samples, the effect of rs8450-AA genotype on NODAT was observed in patients having received SOT from a deceased donor and treated with tacrolimus (n=395, OR=2.08, P=0.02) and in non-kidney transplant recipients (OR=2.09, P=0.02). Moreover, rs8450-AA genotype was associated with overweight or obesity (n=1215, OR=1.56, P=0.02), new-onset hyperlipidemia (n=1007, OR=1.76, P=0.007), and lower high-density lipoprotein-cholesterol (n=1214, β=-0.08, P=0.001). In the population-based samples, a proxy of rs8450G>A was significantly associated with several metabolic abnormalities. CRTC2 rs8450G>A appears to have an important role in the high prevalence of metabolic traits observed in patients with SOT. A weak association with metabolic traits was also observed in the population-based samples.The Pharmacogenomics Journal advance online publication, 8 December 2015; doi:10.1038/tpj.2015.82.

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Metabolic syndrome (MetS) is a disease composed of different risk factors such as obesity, type 2 diabetes or dyslipidemia. The prevalence of this syndrome is increasing worldwide in parallel with the rise in obesity. Nonalcoholic fatty liver disease (NAFLD) is now the most frequent chronic liver disease in western countries, affecting more than 30% of the general population. NAFLD encompasses a spectrum of liver manifestations ranging from simple steatosis to nonalcoholic steatohepatitis (NASH), fibrosis and cirrhosis, which may ultimately progress to hepatocellular carcinoma. There is accumulating evidence supporting an association between NAFLD and MetS. Indeed, NAFLD is recognized as the liver manifestation of MetS. Insulin resistance is increasingly recognized as a key factor linking MetS and NAFLD. Insulin resistance is associated with excessive fat accumulation in ectopic tissues, such as the liver, and increased circulating free fatty acids, which can further promote inflammation and endoplasmic reticulum stress. This in turn aggravates and maintains the insulin resistant state, constituting a vicious cycle. Importantly, evidence shows that most of the patients developing NAFLD present at least one of the MetS traits. This review will define MetS and NAFLD, provide an overview of the common pathophysiological mechanisms linking MetS and NAFLD, and give a perspective regarding treatment of these ever growing metabolic diseases.