277 resultados para Fat mass, blood pressure, aerobics, body mass index, weight
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IMPORTANCE: Depression and obesity are 2 prevalent disorders that have been repeatedly shown to be associated. However, the mechanisms and temporal sequence underlying this association are poorly understood. OBJECTIVE: To determine whether the subtypes of major depressive disorder (MDD; melancholic, atypical, combined, or unspecified) are predictive of adiposity in terms of the incidence of obesity and changes in body mass index (calculated as weight in kilograms divided by height in meters squared), waist circumference, and fat mass. DESIGN, SETTING, AND PARTICIPANTS: This prospective population-based cohort study, CoLaus (Cohorte Lausannoise)/PsyCoLaus (Psychiatric arm of the CoLaus Study), with 5.5 years of follow-up included 3054 randomly selected residents (mean age, 49.7 years; 53.1% were women) of the city of Lausanne, Switzerland (according to the civil register), aged 35 to 66 years in 2003, who accepted the physical and psychiatric baseline and physical follow-up evaluations. EXPOSURES: Depression subtypes according to the DSM-IV. Diagnostic criteria at baseline and follow-up, as well as sociodemographic characteristics, lifestyle (alcohol and tobacco use and physical activity), and medication, were elicited using the semistructured Diagnostic Interview for Genetic Studies. MAIN OUTCOMES AND MEASURES: Changes in body mass index, waist circumference, and fat mass during the follow-up period, in percentage of the baseline value, and the incidence of obesity during the follow-up period among nonobese participants at baseline. Weight, height, waist circumference, and body fat (bioimpedance) were measured at baseline and follow-up by trained field interviewers. RESULTS: Only participants with the atypical subtype of MDD at baseline revealed a higher increase in adiposity during follow-up than participants without MDD. The associations between this MDD subtype and body mass index (β = 3.19; 95% CI, 1.50-4.88), incidence of obesity (odds ratio, 3.75; 95% CI, 1.24-11.35), waist circumference in both sexes (β = 2.44; 95% CI, 0.21-4.66), and fat mass in men (β = 16.36; 95% CI, 4.81-27.92) remained significant after adjustments for a wide range of possible cofounding. CONCLUSIONS AND RELEVANCE: The atypical subtype of MDD is a strong predictor of obesity. This emphasizes the need to identify individuals with this subtype of MDD in both clinical and research settings. Therapeutic measures to diminish the consequences of increased appetite during depressive episodes with atypical features are advocated.
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Marijuana use has been associated with increased appetite, high caloric diet, acute increase in blood pressure, and decreases in high-density lipoprotein cholesterol and triglycerides. Marijuana is the most commonly used illicit drug in the United States, but its long-term effects on body mass index (BMI) and cardiovascular risk factors are unknown. Using 15 years of longitudinal data from 3,617 black and white young adults participating in the Coronary Artery Risk Development in Young Adults (CARDIA) study, we assessed whether marijuana use was associated with caloric intake, BMI, and cardiovascular risk factors. Of the 3,617 participants, 1,365 (38%) reported ever using marijuana. Marijuana use was associated with male gender, tobacco smoking, and other illicit drug use. More extensive marijuana use was associated with a higher caloric intake (2,746 kcal/day in never users to 3,365 kcal/day in those who used marijuana for > or = 1,800 days over 15 years) and alcohol intake (3.6 to 10.8 drinks/week), systolic blood pressure (112.7 to 116.5 mm Hg), and triglyceride levels (84 to 100 mg/dl or 0.95 to 1.13 mmol/L, all p values for trend < 0.001), but not with higher BMI and lipid and glucose levels. In multivariate analysis, the associations between marijuana use and systolic blood pressure and triglycerides disappeared, having been mainly confounded by greater alcohol use in marijuana users. In conclusion, although marijuana use was not independently associated with cardiovascular risk factors, it was associated with other unhealthy behaviors, such as high caloric diet, tobacco smoking, and other illicit drug use, which all have long-term detrimental effects on health.
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We evaluated the accuracy of skinfold thicknesses, BMI and waist circumference for the prediction of percentage body fat (PBF) in a representative sample of 372 Swiss children aged 6-13 years. PBF was measured using dual-energy X-ray absorptiometry. On the basis of a preliminary bootstrap selection of predictors, seven regression models were evaluated. All models included sex, age and pubertal stage plus one of the following predictors: (1) log-transformed triceps skinfold (logTSF); (2) logTSF and waist circumference; (3) log-transformed sum of triceps and subscapular skinfolds (logSF2); (4) log-transformed sum of triceps, biceps, subscapular and supra-iliac skinfolds (logSF4); (5) BMI; (6) waist circumference; (7) BMI and waist circumference. The adjusted determination coefficient (R² adj) and the root mean squared error (RMSE; kg) were calculated for each model. LogSF4 (R² adj 0.85; RMSE 2.35) and logSF2 (R² adj 0.82; RMSE 2.54) were similarly accurate at predicting PBF and superior to logTSF (R² adj 0.75; RMSE 3.02), logTSF combined with waist circumference (R² adj 0.78; RMSE 2.85), BMI (R² adj 0.62; RMSE 3.73), waist circumference (R² adj 0.58; RMSE 3.89), and BMI combined with waist circumference (R² adj 0.63; RMSE 3.66) (P < 0.001 for all values of R² adj). The finding that logSF4 was only modestly superior to logSF2 and that logTSF was better than BMI and waist circumference at predicting PBF has important implications for paediatric epidemiological studies aimed at disentangling the effect of body fat on health outcomes.
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Objective: to assess the agreement between different anthropometric markers in defining obesity and the effect on the prevalence of obese subjects. Methods: population-based cross-sectional study including 3213 women and 2912 men aged 35-75 years. Body fat percentage (%BF) was assessed using electric bioimpedance. Obesity was defined using established cut-points for body mass index (BMI) and waist, and three population-defined cut-points for %BF. Between-criteria agreement was assessed by the kappa statistic. Results: in men, agreement between the %BF cut-points was significantly higher (kappa values in the range 0.78 - 0.86) than with BMI or waist (0.47 - 0.62), whereas no such differences were found in women (0.41 - 0.69). In both genders, prevalence of obesity varied considerably according to the criteria used: 17% and 24% according to BMI and waist in men, and 14% and 31%, respectively, in women. For %BF, the prevalence varied between 14% and 17% in men and between 19% and 36% in women according to the cut-point used. In the older age groups, a fourfold difference in the prevalence of obesity was found when different criteria were used. Among subjects with at least one criteria for obesity (increased BMI, waist or %BF), only one third fulfilled all three criteria and one quarter two criteria. Less than half of women and 64% of men were jointly classified as obese by the three population-defined cut-points for %BF. Conclusions: the different anthropometric criteria to define obesity show a relatively poor agreement between them, leading to considerable differences in the prevalence of obesity in the general population.
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We assessed the association between several cardiometabolic risk factors (CRFs) (blood pressure, LDL-cholesterol, HDL-cholesterol, triglycerides, uric acid, and glucose) in 390 young adults aged 19-20 years in Seychelles (Indian Ocean, Africa) and body mass index (BMI) measured either at the same time (cross-sectional analysis) or at the age of 12-15 years (longitudinal analysis). BMI tracked markedly between age of 12-15 and age of 19-20. BMI was strongly associated with all considered CRFs in both cross-sectional and longitudinal analyses, with some exceptions. Comparing overweight participants with those having a BMI below the age-specific median, the odds ratios for high blood pressure were 5.4/4.7 (male/female) cross-sectionally and 2.5/3.9 longitudinally (P < 0.05). Significant associations were also found for most other CRFs, with some exceptions. In linear regression analysis including both BMI at age of 12-15 and BMI at age of 19-20, only BMI at age of 19-20 remained significantly associated with most CRFs. We conclude that CRFs are predicted strongly by either current or past BMI levels in adolescents and young adults in this population. The observation that only current BMI remained associated with CRFs when including past and current levels together suggests that weight control at a later age may be effective in reducing CRFs in overweight children irrespective of past weight status.
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Objective: to assess the diagnostic accuracy of different anthropometric markers in defining low aerobic fitness among adolescents. Methods: cross-sectional study on 2,331 boys and 2,366 girls aged 10 - 18 years. Body mass index (BMI) was measured using standardized methods; body fat (BF) was assessed by bioelectrical impedance. Low aerobic fitness was assessed by the 20-meter shuttle run using the FITNESSGRAMR criteria. Waist was measured in a subsample of 1,933 boys and 1,897 girls. Overweight, obesity and excess fat were defined according to the International Obesity Task Force (IOTF) or FITNESSGRAMR criteria. Results: 38.5% of boys and 46.5% of girls were considered as unfit according to the FITNESSGRAMR criteria. In boys, the area under the ROC curve (AUC) and 95% confidence interval were 66.7 (64.1 - 69.3), 67.1 (64.5 - 69.6) and 64.6 (61.9 - 67.2) for BMI, BF and waist, respectively (P<0.02). In girls, the values were 68.3 (65.9 - 70.8), 63.8 (61.3 - 66.3) and 65.9 (63.4 - 68.4), respectively (P<0.001). In boys, the sensitivity and specificity to diagnose low fitness were 13% and 99% for obesity (IOTF); 38% and 86% for overweight + obesity (IOTF); 28% and 94% for obesity (FITNESSGRAMR) and 42% and 81% for excess fat (FITNESSGRAMR). For girls, the values were 9% and 99% for obesity (IOTF); 33% and 82% for overweight + obesity (IOTF); 22% and 94% for obesity (FITNESSGRAMR) and 26% and 90% for excess fat (FITNESSGRAMR). Conclusions: BMI, not body fat or waist, should be used to define low aerobic fitness. The IOTF BMI cut-points to define obesity have a very low screening capacity and should not be used.
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In recent decades the percentage of energy derived from dietary fat has increased. The aim of this study was to explore the relationship between food taste preferences, BMI, age, gender and smoking habits. A computerized questionnaire using a hedonic scale (range 0 to 8) to quantify the liking for sweet and savoury, lean and fat foods, was filled by 233 adults: 171 normal weight (131 women, 40 men) and 62 overweight subjects (BMI > 25 kg/m2 42 women, 20 men). The majority of the subjects had a general preference for savoury lean food irrespective of their BMI or gender. Similarly, preference for sweet lean food was not influenced by the magnitude of the BMI. In contrast, overweight subjects had a preference for sweet fat food (p = 0.05) as well as for savoury fat food (p < 0.05). At any age or BMI, men preferred sweet fat food (p < 0.01). This was not the case for women. Overweight men over forty preferred savoury fat food, in contrast to overweight women of the same age (p < 0.01). The same difference existed between normal weight smokers and non-smokers. This study demonstrates that fat food preference plays a potential role in the development of obesity.
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Energy expenditure was measured by means of a respiratory chamber in two groups of adult rural Gambian men. The first group (n = 29) had a low body mass index (BMI; in kg/m2) < 18.5), whereas the control group (n = 29) had a higher BMI (> 22). This study shows that the energy expenditure of Gambian men with low BMI is not different from that of Gambian men with normal BMI when the results are normalized for fat-free mass or for weight by analysis of covariance. In Gambian men the nutritional status thus does not seem to affect energy metabolism notably. No differences in respiratory quotient, diet-induced thermogenesis, net work efficiency, spontaneous physical activity, heart rate, or urinary catecholamine excretion were observed between the two groups. It is, however, interesting to note that the basal metabolic rate of Gambian men, regardless of their nutritional status, is approximately 10% (range 4-12% depending on the reference value used) lower than that predicted for individuals living in industrialized countries.
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The association between adiposity measures and dyslipidemia has seldom been assessed in a multipopulational setting. 27 populations from Europe, Australia, New Zealand and Canada (WHO MONICA project) using health surveys conducted between 1990 and 1997 in adults aged 35-64 years (n = 40,480). Dyslipidemia was defined as the total/HDL cholesterol ratio >6 (men) and >5 (women). Overall prevalence of dyslipidemia was 25% in men and 23% in women. Logistic regression showed that dyslipidemia was strongly associated with body mass index (BMI) in men and with waist circumference (WC) in women, after adjusting for region, age and smoking. Among normal-weight men and women (BMI<25 kg/m(2)), an increase in the odds for being dyslipidemic was observed between lowest and highest WC quartiles (OR = 3.6, p < 0.001). Among obese men (BMI ≥ 30), the corresponding increase was smaller (OR = 1.2, p = 0.036). A similar weakening was observed among women. Classification tree analysis was performed to assign subjects into classes of risk for dyslipidemia. BMI thresholds (25.4 and 29.2 kg/m(2)) in men and WC thresholds (81.7 and 92.6 cm) in women came out at first stages. High WC (>84.8 cm) in normal-weight men, menopause in women and regular smoking further defined subgroups at increased risk. standard categories of BMI and WC, or their combinations, do not lead to optimal risk stratification for dyslipidemia in middle-age adults. Sex-specific adaptations are necessary, in particular by taking into account abdominal obesity in normal-weight men, post-menopausal age in women and regular smoking in both sexes.
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Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and β-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 × 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.
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There is evidence that obesity-related disorders are increased among people with depression. Variation in the FTO (fat mass and obesity associated) gene has been shown to contribute to common forms of human obesity. This study aimed to investigate the genetic influence of polymorphisms in FTO in relation to body mass index (BMI) in two independent samples of major depressive disorder (MDD) cases and controls. We analysed 88 polymorphisms in the FTO gene in a clinically ascertained sample of 2442 MDD cases and 809 controls (Radiant Study). In all, 8 of the top 10 single-nucleotide polymorphisms (SNPs) showing the strongest associations with BMI were followed-up in a population-based cohort (PsyCoLaus Study) consisting of 1292 depression cases and 1690 controls. Linear regression analyses of the FTO variants and BMI yielded 10 SNPs significantly associated with increased BMI in the depressive group but not the control group in the Radiant sample. The same pattern was found in the PsyCoLaus sample. We found a significant interaction between genotype and affected status in relation to BMI for seven SNPs in Radiant (P<0.0057), with PsyCoLaus giving supportive evidence for five SNPs (P-values between 0.03 and 0.06), which increased in significance when the data were combined in a meta-analysis. This is the first study investigating FTO and BMI within the context of MDD, and the results indicate that having a history of depression moderates the effect of FTO on BMI. This finding suggests that FTO is involved in the mechanism underlying the association between mood disorders and obesity.
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Serum uric acid (SUA) concentration is independently associated with blood pressure (BP) in adults. We examined this association in young adults at an age where anti-hypertension treatment, other potential confounding factors and co-morbidity are unlikely to occur. We assessed BP, anthropometric variables including weight, height, waist circumference (WC), body fat percent (using bioimpedance), lifestyle behaviors, SUA and blood lipids in 549 participants aged 19-20 years from a population-based cohort study (Seychelles Child Development Study). Mean (s.d.) SUA was higher in males than females, 0.33 (0.08) and 0.24 (0.07) mmol l(-1), respectively. Body mass index (BMI) was higher in females than males but BP was markedly higher in males than in females. SUA was associated with both systolic and diastolic BP. However, the magnitude of the linear regression coefficients relating BP and SUA decreased by up to 50% upon adjustment for BMI, WC or body fat percent. The association between SUA and BP was not altered upon further adjustment for alcohol intake, smoking, triglycerides or renal function. In fully adjusted models, SUA remained associated with BP (P<0.05) in females. In conclusion, adiposity substantially decreased the association between SUA and BP in young adults, and BP was independently associated with SUA in females. These findings suggest a role of adiposity in the link between hyperuricemia and hypertension.
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FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177,330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m(2), P = 1.9 × 10(-105)), and all participants (0.30 [0.30, 0.35] kg/m(2), P = 3.6 × 10(-107)). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10(-16)), and relative weak associations with lower total energy intake (-6.4 [-10.1, -2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (-0.07 [-0.11, -0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10(-9)) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity.