506 resultados para Menopausal obesity
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This study was performed to analyse the prevalence of obesity in children living in six different areas of the north-east of Italy. The study included 1523 children (749 male, 774 female), divided into four age categories (4, 8, 10, 12 +/- 0.5 years of age, respectively). The physical characteristics of the children were measured by trained and standardized examiners. In accordance with the guidelines on the Italian Consensus Conference on Obesity (Rome, 4-6 June 1991), a child was defined as obese when his weight was higher than 120% of the weight predicted for height, as calculated from the Tanner's tables. On average, the prevalence of obesity was higher in males than in females (15.7% vs. 11%). The highest prevalence was seen in 10-year-old males (23.4%). The prevalence increased with age both in males (4 years = 3.6%, 8 years = 11.2%, 10 years = 23.4%, 12 years = 17.3%) and in females (4 years = 2%, 8 years = 13.3%, 10 years = 12.7%, 12 years = 11.9%). This tendency was maintained when calculating the obesity prevalence by other methods, such as BMI, triceps skinfold and fat mass, although the magnitude of the prevalence was different depending on the criteria used to define it. A consensus on more precise criteria to define obesity is needed for a better diagnosis of obesity in childhood and to allow a more reliable measurement and comparison of the prevalence of obesity among populations.
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BACKGROUND: Obesity and African American ethnicity are established independent risk factors for the development of chronic kidney disease. No data exist about the association between obesity and renal hemodynamics in the African region. STUDY DESIGN: Cross-sectional study. SETTING & PARTICIPANTS: 301 nondiabetic participants (97 lean, 108 overweight, and 96 obese) of African descent with a positive family history of hypertension from the Seychelles islands. PREDICTOR: Body mass index (BMI). OUTCOMES: Glomerular hyperfiltration, glomerular filtration rate (GFR), effective renal plasma flow (ERPF), and filtration fraction. MEASUREMENTS: GFR and ERPF were measured using inulin and para-aminohippurate clearances, respectively. Participants' baseline demographics, laboratory data, and blood pressure were measured using standard techniques. RESULTS: The prevalence of glomerular hyperfiltration (defined as GFR >or=140 mL/min) increased across BMI categories (7.2%, 14.8%, and 27.1% for lean, overweight, and obese participants, respectively; P < 0.001). Higher BMI was associated with higher median GFR (99, 110, and 117 mL/min for lean, overweight, and obese participants, respectively; P < 0.001), ERPF (424, 462, and 477 mL/min, respectively; P = 0.01), and filtration fraction (0.23, 0.24, and 0.25; P < 0.001). Multivariate analyses adjusting for age, sex, blood pressure, fasting glucose level, and urinary sodium excretion and accounting for familial correlations confirmed the associations between high BMI (>25 kg/m(2)) and increased GFR, ERPF, and filtration fraction. No association between BMI categories and GFR was found with adjustment for body surface area. LIMITATIONS: Participants had a positive family history of hypertension. CONCLUSION: Overweight and obesity are associated with increased GFR, ERPF, and filtration fraction and a high prevalence of glomerular hyperfiltration in nondiabetic individuals of African descent. The absence of associations between BMI categories and GFR indexed for body surface area raises questions regarding the appropriateness of indexing GFR for body surface area in overweight populations.
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Menopause and premature gonadal steroid deficiency are associated with increases in fat mass and body weight. Ovariectomized (OVX) mice also show reduced locomotor activity. Glucose-dependent-insulinotropic-polypeptide (GIP) is known to play an important role both in fat metabolism and locomotor activity. Therefore, we hypothesized that the effects of estrogen on the regulation of body weight, fat mass, and spontaneous physical activity could be mediated in part by GIP signaling. To test this hypothesis, C57BL/6 mice and GIP-receptor knockout mice (Gipr(-/-)) were exposed to OVX or sham operation (n = 10 per group). The effects on body composition, markers of insulin resistance, energy expenditure, locomotor activity, and expression of hypothalamic anorexigenic and orexigenic factors were investigated over 26 wk in all four groups of mice. OVX wild-type mice developed obesity, increased fat mass, and elevated markers of insulin resistance as expected. This was completely prevented in OVX Gipr(-/-) animals, even though their energy expenditure and spontaneous locomotor activity levels did not significantly differ from those of OVX wild-type mice. Cumulative food intake in OVX Gipr(-/-) animals was significantly reduced and associated with significantly lower hypothalamic mRNA expression of the orexigenic neuropeptide Y (NPY) but not of cocaine-amphetamine-related transcript (CART), melanocortin receptors (MCR-3 and MCR-4), or thyrotropin-releasing hormone (TRH). GIP receptors thus interact with estrogens in the hypothalamic regulation of food intake in mice, and their blockade may carry promising potential for the prevention of obesity in gonadal steroid deficiency.
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[cat] Una qüestió clau sobre la producció de salut relativament poc explorada es refereix a la influència dels factors socioeconòmics i mediambientals sobre el pes i l’obesitat. Aquesta problemàtica adquireix particular rellevància quan es comparen dos països Mediterranis com Itàlia i Espanya. És interessant adonar-se que l’obesitat a Espanya és 5 punts percentual més elevada al 2003 mentre que a l’any 1990 era aproximadament la mateixa en ambdós països. Aquesta article presenta una descomposició no lineal dels gaps o diferencials en taxes de sobrepès (índex de massa corporal – IMC- entre 25 i 29.9 9 kg/m2), obesitat classe 1 (IMC≥30 kg/m2) i classe 2 (IMC≥35 kg/m2) entre Espanya i Itàlia per gènere i grups d’edat. En explicar aquests gaps entre països aïllem les influències dels estils de vida, els efectes socioeconòmics i els mediambientals. Els nostres resultats indiquen que quan no es controla pels efectes mediambientals (efectes de grup o ‘peer effects’) els hàbits alimentaris i el nivell educatiu són els principals predictors del gaps totals entre països (36-52%), si bé aquests dos factors exerceixen un impacte diferenciat segons gènere i edat. Un tant paradoxalment, quan controlem pels efectes de grup aquests predictors perden la seva capacitat explicativa i els efectes de grup passen a explicar entre el 46-76% dels gaps en sobrepès i obesitat i mostren un patró creixent amb l’edat.
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BACKGROUND/OBJECTIVES: To assess the distribution of interleukin (IL)-1β, IL-6, tumour necrosis factor (TNF)-α and C-reactive protein (CRP) according to the different definitions of metabolically healthy obesity (MHO). SUBJECTS/METHODS: A total of 881 obese (body mass index (BMI) > or =30 kg/m2) subjects derived from the population-based CoLaus Study participated in this study. MHO was defined using six sets of criteria including different combinations of waist, blood pressure, total high-density lipoprotein cholesterol or low-density lipoprotein -cholesterol, triglycerides, fasting glucose, homeostasis model, high-sensitivity CRP, and personal history of cardiovascular, respiratory or metabolic diseases. IL-1β, IL-6 and TNF-α were assessed by multiplexed flow cytometric assay. CRP was assessed by immunoassay. RESULTS: On bivariate analysis some, but not all, definitions of MHO led to significantly lower levels of IL-6, TNF-α and CRP compared with non-MH obese subjects. Most of these differences became nonsignificant after multivariate analysis. An posteriori analysis showed a statistical power between 9 and 79%, depending on the inflammatory biomarker and MHO definition considered. Further increasing sample size to overweight+obese individuals (BMI > or =25 kg/m2, n=2917) showed metabolically healthy status to be significantly associated with lower levels of CRP, while no association was found for IL-1β. Significantly lower IL-6 and TNF-α levels were also found with some but not all MHO definitions, the differences in IL-6 becoming nonsignificant after adjusting for abdominal obesity or percent body fat. CONCLUSIONS: MHO individuals present with decreased levels of CRP and, depending on MHO definition, also with decreased levels in IL-6 and TNF-α. Conversely, no association with IL-1β levels was found.
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Western societies can reduce avoidable mortality and morbidity by better understanding the relationship between obesity and chronic disease. This paper examines the joint determinants of obesity and of heart disease, diabetes, hypertension, and elevated cholesterol. It analyzes a broadly representative Spanish dataset, the 1999 Survey on Disabilities, Impairments and Health Status, using a health production theoretical framework together with a seemingly unrelated probit model approach that controls for unobserved heterogeneity and endogeneity. Its findings provide suggestive evidence of a positive and significant, although specification-dependent, association between obesity and the prevalence of chronic illness
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Obesity has progressively become a global epidemic that constitutes one of the biggest current health problems worldwide. Pregnancy is a risk factor for excessive weight gain. Factors that may predict development of obesity in later life mainly include gestational weight gain, pre-pregnancy nutritional status, age, parity and race. Change in lifestyle factors, such as eating habits, enrollment in physical activity, smoking and duration of lactation, in addition to the above factors, may also contribute to the development of obesity but are still not fully understood. Women who retain more body weight after pregnancy have, in general, larger pregnancy body weight gain, higher pre-pregnancy body mass index, marked weight changes in previous pregnancies, lactate slightly less and stop smoking during pregnancy to a larger extent. In addition, irregular eating habits and decreased leisure time activity after delivery influence postpartum weight retention. Taking into consideration the epidemic of obesity, with all its adverse long-term consequences, there is an increasing need to promote counseling before, during and after pregnancy on the role of diet and physical activity in reproductive health.
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BACKGROUND AND AIMS: Obesity increases the risk for cardiovascular risk factors (CVRFs), including hypertension, dyslipidaemia and type 2 diabetes. In this study, we assessed the burden of overweight and obesity on CVRFs in Switzerland, using Swiss-specific population attributable fractions (PAFs). METHODS AND RESULTS: The number of cases of CVRFs that could have been prevented if the increase in overweight and obesity in Switzerland had been contained was estimated using gender-specific, age- and smoking-adjusted PAFs for overweight and obesity. PAFs were estimated from the Swiss Health Survey 2007 (self-reported) and the CoLaus study (measured) data. PAFs from self-reported were lower than from measured data. Using measured data, overweight and obesity contributed to 38% of hypertension cases in men (32% in women). In men, overweight had a larger impact than obesity (22.2% and 15.6%, respectively), while the opposite was observed for women (13.6% and 18.1%, respectively). In men, 37% of dyslipidaemia (30% in women) could be attributed to overweight and obesity; overweight had a higher contribution than obesity in both sexes. In men, 57% of type 2 diabetes (62% in women) was attributable to overweight and obesity; obesity had a larger impact than overweight in both sexes. Overall, approximately 27,000 cases of type 2 diabetes, 63,000 cases of high blood pressure and 37,000 cases of dyslipidaemia could have been avoided if overweight and obesity levels were maintained at 1992 levels. CONCLUSION: A large proportion of CVRFs is attributable to overweight and/or obesity and could have been prevented by containing the overweight/obesity epidemic.
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Rapport de synthèse : Le traitement des leucémies aiguës chez l'enfant représente un des succès de la médecine moderne avec des taux de guérison avoisinant les 80% ce qui implique la nécessité de suivre les effets secondaires à long terme des traitements chez cette population de patients. Récemment plusieurs études internationales ont relevé une prévalence plus importante de surpoids et d'obésité chez les enfants traités pour une leucémie aiguë. L'origine de ce processus reste incertaine :aux effets secondaires bien connus et décrits des traitements (stéroïdes et radiothérapie) semblent s'ajouter des facteurs génétiques, familiaux (age, BMI au diagnostic, BMI parents et fratrie), environnementaux. L'objectif de ce travail est d'estimer la prévalence et les facteurs de risque pour le surpoids et l'obésité chez les enfants traités et guéris d'une leucémie aiguë en Suisse romande et de comparer ces résultats à ceux d'études internationales. Pour répondre à ces questions nous avons inclus 54 patients (40 de Lausanne et 14 de Genève) traités pour une leucémie aiguë. Seuls les enfants à 5 ans de leur première rémission clinique, sans atteinte du système nerveux central, testiculaire ou médullaire et traités par chimiothérapie seule sont retenus. Leur poids, taille sont enregistrés durant les phases précises de traitement (au diagnostic, à la rémission, fin de consolidation, milieumaintenance et en fin de traitement) puis annuellement jusqu'à 12 ans post fin de traitement. Le BMI (kg/ml) et sa déviation standard BMI-SDS (spécifique pour Page et le sexe) pour les patients et leurs parents sont calculés selon les valeurs internationales (IOTF) respectivement BMI-SDS >1.645 (p<0.05) pour le surpoids et> 1.96 (p<0.025) pour l'obésité. Les résultats de ce travail confirment une prévalence double de surpoids (30% versus 17%) et quadruple d'obésité (18% versus 4%) au sein de la population d'enfants traités pour une leucémie aiguë comparées à la population suisse standard. Les facteurs de risque impliqués sont le BMI initial au diagnostic et le BMI maternel contrairement à Page, sexe, stéroïdes et au BMI paternel. Ces données confirment une prévalence significative d'enfants en surpoids/obèses au sein de cette population avec des résultats similaires à ceux retrouvés dans des études internationales récentes. Les facteurs de risque identifiés semblent plutôt liés à l'environnement familial qu'aux traitements. Ces constatations pourraient être le résultat d'interactions complexes entre "le background génétique", les facteurs environnementaux, les habitudes socioculturelles (activité physique, status nutritionnel) paramètres non évalués dans cette revue. Des études plus larges, prospectives sont nécessaires pour clarifier les rôles des différents facteurs de risque et de leurs interactions ;celles-ci devraient inclure des données génétiques (LEPR), taux de leptine, activité physique et le status nutritionnel. Enfin, l'identification des patients à risque est cruciale afin de prévenir les effets secondaires cardio-vasculaires, métaboliques bien connus liés au surpoids et à l'obésité.
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Introduction: The latest data on prevalence of overweight (OW) and obesity (OB) in the general Swiss resident population rely on the Swiss Health Survey (SHS), a telephonic interview performed in 2007. However, body mass index (BMI) is underestimated when self-reported, leading to a misclassification of up to 60% of obese subjects. The last survey with measured BMI performed in the 3 linguistic regions of Switzerland dates back to 1977. We explored the regional prevalences of OW and OB by measured BMI in the general Swiss resident population. Methods: Cross-sectional population-based survey in the 3 linguistic regions of Switzerland in 2010-2011. Data on 1471 participants aged 15-95 years (712 men, 759 women) were available for the analysis. BMI was calculated from measured height and weight and categorized into 3 groups according to WHO classification: lean (<25 kg/m2), overweight (25-30 kg/m2) and obese (>= 30 kg/m2). Data on medication, smoking, education, physical activity and dietary habitudes were collected using a questionnaire. Results: The overall prevalence of OW and OB was 32.1% and 13.9%, respectively. OB prevalence was similar across the 3 linguistic regions (13.5% in German-, 15.6% in French- and 12.0% in Italian-speaking Switzerland, p = 0.40), unlike OW prevalence, which significantly differed in unadjusted analyses (35.4%, 29.1% and 25.4%, respectively, p = 0.005). In analyses including age, sex, smoking, physical activity and education as covariates, living in the Italian-speaking region was associated neither with BMI (linear regression) nor with OW or OB (logistic regressions) . Age (beta coefficient [SE]: 0.064[0.006] kg/m2 per year, p <0.001) and sex (-1.76 [0.23] kg/m2 in women, p <0.001) were significantly associated with BMI. Conclusions: Overweight and obesity affect nearly half of the Swiss population aged >15 years. We observed no significant differences across regions once we accounted for age, sex, education and lifestyle. Public health interventions addressing modifiable behavioral factors to reduce overweight and obesity in Switzerland can be expected to have substantial benefits.
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The objective was to analyze the situation in Switzerland regarding the prevalence of overweight or obesity in children, adolescents and adults. The data were compared with France, an adjacent much larger country. The results showed that there is a definitive lack of objective information in Switzerland on the prevalence of obesity at different ages. As in other European studies, the fact that many national surveys are classically based on subject interviews (self-reported weights and heights rather than measured values) implies that the overweight/obesity prevalence is largely underestimated in adulthood. For example, in a recent Swiss epidemiological study, the prevalence of obesity (BMI greater than 30 kg/m(2)) averaged 6-7% in young men and women (25-34 y), the prevalence being underestimated by a factor of two to three when body weight was self-reported rather than measured. This phenomenon has already been observed in previous European studies. It is concluded that National Surveys based on telephone interviews generally produce biased obesity prevalence results, although the direction of the changes in prevalence of obesity and its evolution with repeated surveys using strict standardized methodology may be evaluated correctly. Therefore, these surveys should be complemented by large-scale epidemiological studies (based on measured anthropomeric variables rather than declared) covering the different linguistic areas of Switzerland. An epidemiological body weight (BMI) monitoring surveillance system, using a harmonized methodology among European countries, would help to accurately assess differences in obesity prevalence across Europe without methodological bias. It will permit monitoring of the dynamic evolution of obesity prevalence as well as the development of appropriate strategies (taking into account the specificity of each country) for obesity prevention and treatment.
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BACKGROUND: Although smokers tend to have a lower body-mass index (BMI) than non-smokers, smoking may affect body fat (BF) distribution. Some studies have assessed the association between smoking, BMI and waist circumference (WC), but, to our knowledge, no population-based studies assessed the relation between smoking and BF composition. We assessed the association between amount of cigarette smoking, BMI, WC and BF composition. METHODS: Data was analysed from a cross-sectional population-based study including 6187 Caucasians aged 32-76 and living in Switzerland. Height, weight and WC were measured. BF, expressed in percent of total body weight, was measured by electrical bioimpedance. Obesity was defined as a BMI>=30 kg/m2 and normal weight as a BMI<25 kg/m2. Abdominal obesity was defined as a WC>=102 cm for men and >=88 cm for women and normal WC as <94 cm for men and <80 cm for women. In men, excess BF was defined as %BF >=28.1, 28.7, 30.6 and 32.6 for age groups 32-44, 45-54, 55-64 and 65-76, respectively; the corresponding values for women were 35.9, 36.5, 40.5 and 44.4. Cigarette smoking was assessed using a self-reported questionnaire. RESULTS: 29.3% of men and 25.0% of women were smokers. Prevalence of obesity, abdominal obesity, and excess of BF was 16.9% and 26.6% and 14.2% in men and 15.0%, 33.0% and 27.5% in women, respectively. Smokers had lower age-adjusted mean BMI, WC and percent of BF compared to non-smokers. However, among smokers,mean age-adjusted BMI,WC and BF increased with the number of cigarettes smoked per day: among light (1-10 cig/day), moderate (11-20) and heavy smokers (>20), mean +/-SE %BF was 22.4 +/−0.3, 23.1+/−0.3 and 23.5+/−0.4 for men, and 31.9+/−0.3, 32.6+/−0.3 and 32.9+/−0.4 for women, respectively. Mean WC was 92.9+/−0.6, 94.0+/−0.5 and 96.0+/−0.6 cm for men, and 80.2+/−0.5, 81.3+/−0.5 and 83.3+/−0.7 for women, respectively. Mean BMI was 25.7+/−0.2, 26.0+/−0.2, and 26.1+/−0.2 kg/m2 for men; and 23.6+/−0.2, 24.0+/−0.2 and 24.1+/−0.3 for women, respectively. Compared with light smokers, the age-adjusted odds ratio (95% Confidence Interval) for excess of BF was 1.04 (0.58 to 1.85) formoderatesmokers and 1.06 (0.57 to 1.99) for heavy smokers in men (p-trend = 0.9), and 1.35 (0.92 to 1.99) and 2.26 (1.38 to 3.72), respectively, in women (p-trend = 0.04). Odds ratio for abdominal obesity vs. normal WC was 1.32 (0.81 to 2.15) for moderate smokers and 1.95 (1.16 to 3.27) for heavy smokers in men (p-trend < 0.01), and 1.15 (0.79 to 1.69) and 2.36 (1.41 to 3.93) in women (p-trend = 0.03). Odds ratio for obesity vs. normal weight was 1.35 (0.76 to 2.41) for moderate smokers and 1.33 (0.71 to 2.49) for heavy smokers in men (p-trend = 0.9) and 0.78 (0.45 to 1.35) and 1.44 (0.73 to 2.85), in women (p-trend = 0.08). CONCLUSIONS: WC and BF were positively and dose-dependently associated with the number of cigarettes smoked per day in women, whereas onlyWC was dose dependently and significantly associated with the amount of cigarettes smoked per day in men. This suggests that heavy smokers, especially women, are more likely to have an excess of BF and to accumulate BF in the abdomen compared to lighter smokers.