923 resultados para Scaled Mass Index
Resumo:
The problem of obesity is alarming public health authorities around the world. Therefore, it is important to study its determinants. In this paper we explore the empirical relationship between household income and body mass index (BMI) in nine European Union countries. Our findings suggest that the association is negative for women, but we find no statistically significant relationship for men. However, we show that the different relationship for men and women appears to be driven by the negative relationship for women between BMI and individual income from work. We tentatively conclude that the negative relationship between household income and BMI for women may simply be capturing the wage penalty that obese women suffer in the labor market.
Resumo:
In pediatric echocardiography, cardiac dimensions are often normalized for weight, height, or body surface area (BSA). The combined influence of height and weight on cardiac size is complex and likely varies with age. We hypothesized that increasing weight for height, as represented by body mass index (BMI) adjusted for age, is poorly accounted for in Z scores normalized for weight, height, or BSA. We aimed to evaluate whether a bias related to BMI was introduced when proximal aorta diameter Z scores are derived from bivariate models (only one normalizing variable), and whether such a bias was reduced when multivariable models are used. We analyzed 1,422 echocardiograms read as normal in children ≤18 years. We computed Z scores of the proximal aorta using allometric, polynomial, and multivariable models with four body size variables. We then assessed the level of residual association of Z scores and BMI adjusted for age and sex. In children ≥6 years, we found a significant residual linear association with BMI-for-age and Z scores for most regression models. Only a multivariable model including weight and height as independent predictors produced a Z score free of linear association with BMI. We concluded that a bias related to BMI was present in Z scores of proximal aorta diameter when normalization was done using bivariate models, regardless of the regression model or the normalizing variable. The use of multivariable models with weight and height as independent predictors should be explored to reduce this potential pitfall when pediatric echocardiography reference values are evaluated.
Resumo:
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.
Resumo:
Abstract Background. In children, waist-for-height ratio (WHtR) has been proposed to identify subjects at higher risk of cardiovascular diseases. The utility of WHtR to identify children with elevated blood pressure (BP) is unclear. Design. Cross-sectional population-based study of schoolchildren. Methods. Weight, height, waist circumference and BP were measured in all sixth-grade schoolchildren of the canton de Vaud (Switzerland) in 2005/06. WHtR was computed as waist [cm]/height [cm]. Elevated BP was defined according to sex-, age- and height-specific US reference data. The area under the receiver operating characteristic curve (AUC) statistic was computed to compare the ability of body mass index (BMI) z-score and WHtR, alone or in combination, to identify children with elevated BP. Results. 5207 children participated (76% response) [2621 boys, 2586 girls; mean (± SD) age, 12.3 ± 0.5 years; range: 10.1-14.9]. The prevalence of elevated BP was 11%. Mean WHtR was 0.44 ± 0.05 (range: 0.29- 0.77) and 11% had high WHtR (> 0.5). BMI z-score and WHtR were strongly correlated (Spearman correlation coefficient r = 0.76). Both indices were positively associated with elevated BP. AUCs for elevated BP was relatively low for BMI z-score (0.62) or for WHtR (0.62), and was not substantially improved when both indices were considered together (0.63). Conclusions. The ability of BMI z-score or WHtR to identify children aged 10-14 with elevated BP was weak. Adding WHtR did not confer additional discriminative power to BMI alone. These findings do not support the measurement of WHtR in addition to BMI to identify children with elevated BP.
Resumo:
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.
Resumo:
OBJECTIVE: Although dual-energy X-ray absorptiometry (DEXA) is the preferred method to estimate adiposity, body mass index (BMI) is often used as a proxy. However, the ability of BMI to measure adiposity change among youth is poorly evidenced. This study explored which metrics of BMI change have the highest correlations with different metrics of DEXA change. METHODS: Data were from the Quebec Adipose and Lifestyle Investigation in Youth cohort, a prospective cohort of children (8-10 years at recruitment) from Québec, Canada (n=557). Height and weight were measured by trained nurses at baseline (2008) and follow-up (2010). Metrics of BMI change were raw (ΔBMIkg/m(2) ), adjusted for median BMI (ΔBMIpercentage) and age-sex-adjusted with the Centers for Disease Control and Prevention growth curves expressed as centiles (ΔBMIcentile) or z-scores (ΔBMIz-score). Metrics of DEXA change were raw (total fat mass; ΔFMkg), per cent (ΔFMpercentage), height-adjusted (fat mass index; ΔFMI) and age-sex-adjusted z-scores (ΔFMz-score). Spearman's rank correlations were derived. RESULTS: Correlations ranged from modest (0.60) to strong (0.86). ΔFMkg correlated most highly with ΔBMIkg/m(2) (r = 0.86), ΔFMI with ΔBMIkg/m(2) and ΔBMIpercentage (r = 0.83-0.84), ΔFMz-score with ΔBMIz-score (r = 0.78), and ΔFMpercentage with ΔBMIpercentage (r = 0.68). Correlations with ΔBMIcentile were consistently among the lowest. CONCLUSIONS: In 8-10-year-old children, absolute or per cent change in BMI is a good proxy for change in fat mass or FMI, and BMI z-score change is a good proxy for FM z-score change. However change in BMI centile and change in per cent fat mass perform less well and are not recommended.
Resumo:
The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.
Resumo:
The aim of this study was to determine the prevalence of low fat-free mass index (FFMI) and high and very high body fat mass index (BFMI) after lung transplantation (LTR). A total of 37 LTR patients were assessed prior to and at 1 month, 1 year and 2 years for FFM and compared to 37 matched volunteers (VOL). FFM was calculated by the Geneva equation and normalized for height (kg/m(2)). Subjects were classified as FFMI "low", <or=17.4 in men and <or=15.0 in women; BFMI "high", 5.2-8.1 in men and 8.3-11.7 in women; or "very high" >8.2 kg/m(2) in men and >11.8 kg/m(2) in women. In 23 M/14 F, body mass index (BMI) was 22.3+/-4.4 and 20.1+/-4.9 kg/m(2), respectively. The prevalence of low FFMI was 80% at 1 month and 33% at 2 years after LTR. Prevalence of very high BFMI increased and was higher in patients than VOL after LTR. The prevalence of low FFMI was high prior to and remained important 2 years after LTR, whereas BFMI was lower prior to and higher 2 years after LTR.
Resumo:
There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
Resumo:
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.
Resumo:
OBJECTIVE: Body mass index does not discriminate body fat from fat-free mass or determine changes in these parameters with physical activity and aging. Body fat mass index (BFMI) and fat-free mass index (FFMI) permit comparisons of subjects with different heights. This study evaluated differences in body mass index, BFMI, and FFMI in physically active and sedentary subjects younger and older than 60 y and determined the association between physical activity, age, and body composition parameters in a healthy white population between ages 18 and 98 y. METHODS: Body fat and fat-free mass were determined in healthy white men (n = 3549) and women (n = 3184), between ages 18 and 98 y, by bioelectrical impedance analysis. BFMI and FFMI (kg/m2) were calculated. Physical activity was defined as at least 3 h/wk of endurance-type activity for at least 2 mo. RESULTS: Physically active as opposed to sedentary subjects were more likely to have a low BFMI (men: odds ratio [OR], 1.4; confidence interval [CI], 0.7-2.5; women: OR 1.9, CI 1.6-2.2) and less likely to have very high BFMI (men: OR, 0.2; CI, 0.1-0.2; women: OR, 0.1; CI, 0.02-0.2), low FFMI (men: OR, 0.5; CI, 0.3-0.9; women: OR, 0.7; CI, 0.6-0.9), or very high FFMI (men: OR, 0.6; CI, 0.4-0.8; women: OR, 0.7; CI, 0.5-1.0). Compared with subjects younger than 60 y, those older than 60 y were more like to have very high BFMI (men: OR, 6.5; CI, 4.5-9.3; women: OR, 14.0; CI, 9.6-20.5), and women 60 y and older were less likely to have a low BFMI (OR, 0.4; CI, 0.2-0.5). CONCLUSIONS: A clear association was found between low physical activity or age and height-normalized body composition parameters (BFMI and FFMI) derived from bioelectrical impedance analysis. Physically active subjects were more likely to have high or very high or low FFMI. Older subjects had higher body weights and BFMI.
Resumo:
BACKGROUND: Head and neck cancer (HNC) risk is elevated among lean people and reduced among overweight or obese people in some studies; however, it is unknown whether these associations differ for certain subgroups or are influenced by residual confounding from the effects of alcohol and tobacco use or by other sources of biases. METHODS: We pooled data from 17 case-control studies including 12 716 cases and the 17 438 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for associations between body mass index (BMI) at different ages and HNC risk, adjusted for age, sex, centre, race, education, tobacco smoking and alcohol consumption. RESULTS: Adjusted ORs (95% CIs) were elevated for people with BMI at reference (date of diagnosis for cases and date of selection for controls) 25.0-30.0 kg/m(2) (0.52, 0.44-0.60) and BMI >/=30 kg/m(2) (0.43, 0.33-0.57), compared with BMI >18.5-25.0 kg/m(2). These associations did not differ by age, sex, tumour site or control source. Although the increased risk among people with BMI 25 kg/m(2) was present only in smokers and drinkers. CONCLUSIONS: In our large pooled analysis, leanness was associated with increased HNC risk regardless of smoking and drinking status, although reverse causality cannot be excluded. The reduced risk among overweight or obese people may indicate body size is a modifier of the risk associated with smoking and drinking. Further clarification may be provided by analyses of prospective cohort and mechanistic studies.
Resumo:
Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.