836 resultados para body mass Index


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OBJECTIVE: Excess body weight, defined by body mass index (BMI), may increase the risk of colorectal cancer. As a prerequisite to the determination of lifestyle attributable risks, we undertook a systematic review and meta-analysis of prospective observational studies to quantify colorectal cancer risk associated with increased BMI and explore for differences by gender, sub-site and study characteristics. METHOD: We searched MEDLINE and EMBASE (to December 2007), and other sources, selecting reports based on strict inclusion criteria. Random-effects meta-analyses and meta-regressions of study-specific incremental estimates were performed to determine the risk ratio (RR) and 95% confidence intervals (CIs) associated with a 5 kg/m(2) increase in BMI. RESULTS: We analysed 29 datasets from 28 articles, including 67,361 incident cases. Higher BMI was associated with colon (RR 1.24, 95% CIs: 1.20-1.28) and rectal (1.09, 1.05-1.14) cancers in men, and with colon cancer (1.09, 1.04-1.12) in women. Associations were stronger in men than in women for colon (P < 0.001) and rectal (P = 0.005) cancers. Associations were generally consistent across geographic populations. Study characteristics and adjustments accounted for only moderate variations of associations. CONCLUSION: Increasing BMI is associated with a modest increased risk of developing colon and rectal cancers, but this modest risk may translate to large attributable proportions in high-prevalence obese populations. Inter-gender differences point to potentially important mechanistic differences, which merit further research.

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Previous studies have sought to associate the Pro12Ala variant of the peroxisome proliferator-activated receptor gamma2 (PPARG2) gene with type 2 diabetes, insulin resistance, and obesity, with controversial results. We have determined the Pro12Ala variant frequency in 370 nondiabetic Mexican Mestizo subjects and in five Mexican Amerindian groups and have investigated its possible association with lipid metabolism, insulin serum levels, and obesity in three of these populations. Two independent case-control studies were conducted in 239 nondiabetic individuals: 135 case subjects (BMI > or = 25 kg/m2) and 104 control subjects (BMI < 25 kg/m2). The PPARG2 Ala12 allele frequency was higher in most Amerindian populations (0.17 in Yaquis, 0.16 in Mazahuas, 0.16 in Mayans, and 0.20 in Triquis) than in Asians, African Americans, and Caucasians. The Pro12Ala and Ala12Ala (X12Ala) genotypes were significantly associated with greater BMI in Mexican Mestizos and in two Amerindian groups. X12Ala individuals had a higher risk of overweight or obesity than noncarriers in Mestizos (OR = 3.67; 95% CI, 1.42-9.48; p = 0.007) and in Yaquis plus Mazahuas (OR = 3.21; 95% CI, 1.27-8.11; p = 0.013). Our results provide further support of the association between the PPARG2 Ala12 allele and risk of overweight or obesity in Mestizos and two Amerindian populations from Mexico.

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Background: Obesity is a growing problem in industrial nations. The aim of this study was to determine the relationship between the body mass index (BMI) and the pattern of injury after polytrauma. Methods: This retrospective study included 651 patients with an injury severity score (ISS) ≥16 and aged ≥16 years who were subdivided into three groups: BMI < 25 kg/m2, BMI 25–30 kg/m2, and BMI > 30 kg/m2. The Abbreviated Injury Scale (AIS) was used to quantify the injuries in the different anatomical regions. The Murray score was assessed at admission and at its maximum during hospitalization to evaluate pulmonary problems. Data are presented as means ± standard errors of the means. One way analysis of variance, χ2 test and Kruskal-Wallis test were used for the analyses and the significance level was set at p < 0.05. Results: The AIS of the thorax was 3.2 ± 0.1 in the BMI < 25 kg/m2 group, 3.3 ± 0.1 in the BMI 25–30 kg/m2 group, and 2.8 ± 0.2 in the BMI > 30 kg/m2 group; p < 0.05. The Murray score at admission increased significantly with increasing BMI (0.8 ± 0.8 for BMI < 25 kg/m2, 0.9 ± 0.9 for BMI 25–30 kg/m2, and 1.0 ± 0.8 for BMI > 30 kg/m2; p < 0.05) as was the maximum Murray score during hospitalization (1.2 ± 0.9 for BMI < 25 kg/m2, 1.6 ± 1.0 for BMI 25–30 kg/m2, and 1.5 ± 0.9 for BMI > 30 kg/m2; p < 0.001). The number of ventilator days was also elevated significantly with increasing BMI (5.9 ± 0.4 for BMI < 25 kg/m2, 7.7 ± 0.8 for BMI 25–30 kg/m2, and 7.9 ± 1.6 for BMI > 30 kg/m2; p < 0.05). Conclusion: Overweight and obesity lead to a higher incidence of thoracic trauma in a polytrauma situation and may additionally handicap ventilation in an obstructive manner.

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The aim of this study was (1) to examine whether childhood BMI is a significant predictor of restrained eating in preadolescents, (2) to investigate gender differences in restrained and emotional eating, and (3) to determine whether emotional problems, and body esteem were related to eating problems of preadolescents. In this longitudinal study with two measurement points, data from 428 children (50% female) were used. At time 1 (t1) children were on average 5.9 years old. BMI was assessed using objective measures. At time 2 (t2) participants were 12 years old. The adolescents and their parents completed questionnaires assessing restrained and emotional eating, body esteem, emotional problems, and BMI. Multiple regression analysis showed that restrained eating was significantly predicted by t1 BMI, by change in BMI between t1 and t2, and t2 body esteem. Emotional eating was, as expected, not predicted by t1 BMI, but associated with t2 body esteem and t2 emotional problems. Gender was not a significant predictor. The stability of BMI between childhood and preadolescence and its ability to predict restrained eating suggests that it is important to start prevention of overweight, body dissatisfaction and disordered eating at an early age

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Our objective was to determine the effect of body mass index (BMI) on response to bacterial vaginosis (BV) treatment. A secondary analysis was conducted of two multicenter trials of therapy for BV and TRICHOMONAS VAGINALIS. Gravida were screened for BV between 8 and 22 weeks and randomized between 16 and 23 weeks to metronidazole or placebo. Of 1497 gravida with asymptomatic BV and preconceptional BMI, 738 were randomized to metronidazole; BMI was divided into categories: < 25, 25 to 29.9, and > or = 30. Rates of BV persistence at follow-up were compared using the Mantel-Haenszel chi square. Multiple logistic regression was used to evaluate the effect of BMI on BV persistence at follow-up, adjusting for potential confounders. No association was identified between BMI and BV rate at follow-up ( P = 0.21). BMI was associated with maternal age, smoking, marital status, and black race. Compared with women with BMI of < 25, adjusted odds ratio (OR) of BV at follow-up were BMI 25 to 29.9: OR, 0.66, 95% CI 0.43 to 1.02; BMI > or = 30: OR, 0.83, 95% CI 0.54 to 1.26. We concluded that the persistence of BV after treatment was not related to BMI.

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Our objective was to determine the effect of body mass index (BMI) on response to bacterial vaginosis (BV) treatment. A secondary analysis was conducted of two multicenter trials of therapy for BV and TRICHOMONAS VAGINALIS. Gravida were screened for BV between 8 and 22 weeks and randomized between 16 and 23 weeks to metronidazole or placebo. Of 1497 gravida with asymptomatic BV and preconceptional BMI, 738 were randomized to metronidazole; BMI was divided into categories: < 25, 25 to 29.9, and > or = 30. Rates of BV persistence at follow-up were compared using the Mantel-Haenszel chi square. Multiple logistic regression was used to evaluate the effect of BMI on BV persistence at follow-up, adjusting for potential confounders. No association was identified between BMI and BV rate at follow-up ( P = 0.21). BMI was associated with maternal age, smoking, marital status, and black race. Compared with women with BMI of < 25, adjusted odds ratio (OR) of BV at follow-up were BMI 25 to 29.9: OR, 0.66, 95% CI 0.43 to 1.02; BMI > or = 30: OR, 0.83, 95% CI 0.54 to 1.26. We concluded that the persistence of BV after treatment was not related to BMI.

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Many persons in the U.S. gain weight during young adulthood, and the prevalence of obesity has been increasing among young adults. Although obesity and physical inactivity are generally recognized as risk factors for coronary heart disease (CHD), the magnitude of their effect on risk may have been seriously underestimated due to failure to adequately handle the problem of cigarette smoking. Since cigarette smoking causes weight loss, physically inactive cigarette smokers may remain relatively lean because they smoke cigarettes. We hypothesize cigarette smoking modifies the association between weight gain during young adulthood and risk of coronary heart disease during middle age, and that the true effect of weight gain during young adulthood on risk of CHD can be assessed only in persons who have not smoked cigarettes. Specifically, we hypothesize that weight gain during young adulthood is positively associated with risk of CHD during middle-age in nonsmokers but that the association is much smaller or absent entirely among cigarette smokers. The purpose of this study was to test this hypothesis. The population for analysis was comprised of 1,934 middle-aged, employed men whose average age at the baseline examination was 48.7 years. Information collected at the baseline examinations in 1958 and 1959 included recalled weight at age 20, present weight, height, smoking status, and other CHD risk factors. To decrease the effect of intraindividual variation, the mean values of the 1958 and 1959 baseline examinations were used in analyses. Change in body mass index ($\Delta$BMI) during young adulthood was the primary exposure variable and was measured as BMI at baseline (kg/m$\sp2)$ minus BMI at age 20 (kg/m$\sp2).$ Proportional hazards regression analysis was used to generate relative risks of CHD mortality by category of $\Delta$BMI and cigarette smoking status after adjustment for age, family history of CVD, major organ system disease, BMI at age 20, and number of cigarettes smoked per day. Adjustment was not performed for systolic blood pressure or total serum cholesterol as these were regarded as intervening variables. Vital status was known for all men on the 25th anniversary of their baseline examinations. 705 deaths (including 319 CHD deaths) occurred over 40,136 person-years of experience. $\Delta$BMI was positively associated with risk of CHD mortality in never-smokers, but not in ever-smokers (p for interaction = 0.067). For never-smokers with $\Delta$BMI of stable, low gain, moderate gain, and high gain, adjusted relative risks were 1.00, 1.62, 1.61, and 2.78, respectively (p for trend = 0.010). For ever-smokers, with $\Delta$BMI of stable, low gain, moderate gain, and high gain, adjusted relative risks were 1.00, 0.74, 1.07, and 1.06, respectively (p for trend = 0.422). These results support the research hypothesis that cigarette smoking modifies the association between weight gain and CHD mortality. Current estimates of the magnitude of effect of obesity and physical inactivity on risk of coronary mortality may have been seriously underestimated due to inadequate handling of cigarette smoking. ^

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BACKGROUND Rising levels of overweight and obesity are important public-health concerns worldwide. The purpose of this study is to elucidate their prevalence and trends in Switzerland by analyzing variations in Body Mass Index (BMI) of Swiss conscripts. METHODS The conscription records were provided by the Swiss Army. This study focussed on conscripts 18.5-20.5 years of age from the seven one-year birth cohorts spanning the period 1986-1992. BMI across professional status, area-based socioeconomic position (abSEP), urbanicity and regions was analyzed. Two piecewise quantile regression models with linear splines for three birth-cohort groups were used to examine the association of median BMI with explanatory variables and to determine the extent to which BMI has varied over time. RESULTS The study population consisted of 188,537 individuals. Median BMI was 22.51 kg/m2 (22.45-22.57 95% confidence interval (CI)). BMI was lower among conscripts of high professional status (-0.46 kg/m2; 95% CI: -0.50, -0.42, compared with low), living in areas of high abSEP (-0.11 kg/m2; 95% CI: -0.16, -0.07 compared to medium) and from urban communities (-0.07 kg/m2; 95% CI: -0.11, -0.03, compared with peri-urban). Comparing with Midland, median BMI was highest in the North-West (0.25 kg/m2; 95% CI: 0.19-0.30) and Central regions (0.11 kg/m2; 95% CI: 0.05-0.16) and lowest in the East (-0.19 kg/m2; 95% CI: -0.24, -0.14) and Lake Geneva regions (-0.15 kg/m2; 95% CI: -0.20, -0.09). Trajectories of regional BMI growth varied across birth cohorts, with median BMI remaining high in the Central and North-West regions, whereas stabilization and in some cases a decline were observed elsewhere. CONCLUSIONS BMI of Swiss conscripts is associated with individual and abSEP and urbanicity. Results show regional variation in the levels and temporal trajectories of BMI growth and signal their possible slowdown among recent birth cohorts.

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BACKGROUND The factors that contribute to increasing obesity rates in human immunodeficiency virus (HIV)-positive persons and to body mass index (BMI) increase that typically occurs after starting antiretroviral therapy (ART) are incompletely characterized. METHODS We describe BMI trends in the entire Swiss HIV Cohort Study (SHCS) population and investigate the effects of demographics, HIV-related factors, and ART on BMI change in participants with data available before and 4 years after first starting ART. RESULTS In the SHCS, overweight/obesity prevalence increased from 13% in 1990 (n = 1641) to 38% in 2012 (n = 8150). In the participants starting ART (n = 1601), mean BMI increase was 0.92 kg/m(2) per year (95% confidence interval, .83-1.0) during year 0-1 and 0.31 kg/m(2) per year (0.29-0.34) during years 1-4. In multivariable analyses, annualized BMI change during year 0-1 was associated with older age (0.15 [0.06-0.24] kg/m(2)) and CD4 nadir <199 cells/µL compared to nadir >350 (P < .001). Annualized BMI change during years 1-4 was associated with CD4 nadir <100 cells/µL compared to nadir >350 (P = .001) and black compared to white ethnicity (0.28 [0.16-0.37] kg/m(2)). Individual ART combinations differed little in their contribution to BMI change. CONCLUSIONS Increasing obesity rates in the SHCS over time occurred at the same time as aging of the SHCS population, demographic changes, earlier ART start, and increasingly widespread ART coverage. Body mass index increase after ART start was typically biphasic, the BMI increase in year 0-1 being as large as the increase in years 1-4 combined. The effect of ART regimen on BMI change was limited.

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Purpose The aim was to test the impact of body mass index (BMI) and gender on infectious complications after polytrauma. Methods A total of 651 patients were included in this retrospective study, with an Injury Severity Score (ISS) C16 and age C16 years. The sample was subdivided into three groups: BMI\25 kg/m2, BMI 25–30 kg/m2, and BMI[30 kg/m2, and a female and a male group. Infectious complications were observed for 31 days after admission. Data are given as mean ± standard errors of the means. Analysis of variance, Kruskal–Wallis test, v2 tests, and Pearson’s correlation were used for the analyses and the significance level was set at P\0.05. Results The overall infection rates were 31.0 % in the BMI\25 kg/m2 group, 29.0 % in the BMI 25–30 kg/m2 group, and 24.5 % in the BMI[30 kg/m2 group (P = 0.519). The female patients developed significantly fewer infectious complications than the male patients (26.8 vs. 73.2 %; P\0.001). The incidence of death was significantly decreased according to the BMI group (8.8 vs. 7.2 vs. 1.5 %; P\0.0001) and the female population had a significantly lower mortality rate (4.1 vs. 13.4 %; P\0.0001). Pearson’s correlations between the Abbreviated Injury Scale (AIS) score and the corresponding infectious foci were not significant. Conclusion Higher BMI seems to be protective against polytrauma-associated death but not polytrauma-associated infections, and female gender protects against both polytrauma- associated infections and death. Understanding gender-specific immunomodulation could improve the outcome of polytrauma patients.

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BACKGROUND An increased body mass index (BMI) is associated with a high risk of cardiovascular disease and reduction in life expectancy. However, several studies reported improved clinical outcomes in obese patients treated for cardiovascular diseases. The aim of the present study is to investigate the impact of BMI on long-term clinical outcomes after implantation of zotarolimus eluting stents. METHODS Individual patient data were pooled from the RESOLUTE Clinical Program comprising five trials worldwide. The study population was sorted according to BMI tertiles and clinical outcomes were evaluated at 2-year follow-up. RESULTS Data from a total of 5,127 patients receiving the R-ZES were included in the present study. BMI tertiles were as follow: I tertile (≤ 25.95 kg/m(2) -Low or normal weight) 1,727 patients; II tertile (>25.95 ≤ 29.74 kg/m(2) -overweight) 1,695 patients, and III tertile (>29.74 kg/m(2) -obese) 1,705 patients. At 2-years follow-up no difference was found for patients with high BMI (III tertile) compared with patients with normal or low BMI (I tertile) in terms of target lesion failure (I-III tertile, HR [95% CI] = 0.89 [0.69, 1.14], P = 0.341; major adverse cardiac events (I-III tertile, HR [95% CI] = 0.90 [0.72, 1.14], P = 0.389; cardiac death (I-III tertile, HR [95% CI] = 1.20 [0.73, 1.99], P = 0.476); myocardial infarction (I-III tertile, HR [95% CI] = 0.86 [0.55, 1.35], P = 0.509; clinically-driven target lesion revascularization (I-III tertile, HR [95% CI] = 0.75 [0.53, 1.08], P = 0.123; definite or probable stent thrombosis (I-III tertile, HR [95% CI] = 0.98 [0.49, 1.99], P = 0.964. CONCLUSIONS In the present study, the patients' body mass index was found to have no impact on long-term clinical outcomes after coronary artery interventions.

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A variety of studies indicate that the process of athrosclerosis begins in childhood. There was limited information on the association of the changes in anthropometric variables to blood lipids in school age children and adolescents. Previous longitudinal studies of children typically with insufficient frequency of observation could not provide sound inference on the dynamics of change in blood lipids. The aims of this analysis are (1) to document the sex- and ethnic-specific trajectory and velocity curves of blood lipids (TC, LDL-C, HDL-C and TG); (2) to evaluate the relationship of changes in anthropometric variables, such as height, weight and BMI, to blood lipids from age 8 to 18 years. ^ Project HeartBeat! is a longitudinal study designed to examine the patterns of serial change in major cardiovascular risk factors. Cohort of three different age levels, 8, 11 and 14 years at baseline, with a total of 678 participants were enrolled. Each member of these cohorts was examined three times per year for up to four years. ^ Sex- and ethnic-specific trajectory and velocity curves of blood lipids; demonstrated the complex and polyphasic changes in TC, LDL-C, HDL-C and TG longitudinally. The trajectory curves of TC, LDL-C and HDL-C with age showed curvilinear patterns of change. The velocity change in TC, HDL-C and LDL-C showed U-shaped curves for non-Blacks, and nearly linear lines in velocity of TG for both Blacks and non-Blacks. ^ The relationship of changes in anthropometric variables to blood lipids was evaulated by adding height, weight, or BMI and associated interaction terms separately to the basic age-sex models. Height or height gain had a significant negative association with changes in TC, LDL-C and HDL-C. Weight or BMI gain showed positive associations with TC, LDL-C and TC, and a negative relationship with HDL-C. ^ Dynamic changes of blood lipids in school age children and adolescents observed from this analysis suggested that using fixed screening criteria under the current NCEP guidelines for all ages 2–19 may not be appropriate for this age group. The association of increasing BMI or weight to an adverse blood lipid profile found in this analysis also indicated that weight or BMI monitoring could be a future intervention to be implemented in the pediatric population. ^