Beyond BMI for self-estimates of body size and shape: A new method for developing stimuli correctly calibrated for body composition

Accurate self-assessment of body shape and size plays a key role in the prevention, diagnosis, and treatment of both obesity and eating disorders. These chronic conditions cause significant health problems, reduced quality of life, and represent a major problem for health services. Variation in body shape depends on two aspects of composition: adiposity and muscularity. However, most self-assessment tools are unidimensional. They depict variation in adiposity only, typically quantified by the body mass index. This can lead to substantial, and clinically meaningful, errors in estimates of body shape and size. To solve this problem, we detail a method of creating biometrically valid body stimuli. We obtained high-resolution 3D body shape scans and composition measures from 397 volunteers (aged 18–45 years) and produced a statistical mapping between the two. This allowed us to create 3D computer-generated models of bodies, correctly calibrated for body composition (i.e., muscularity and adiposity). We show how these stimuli, whose shape changes are based on change in composition in two dimensions, can be used to match the body size and shape participants believe themselves to have, to the stimulus they see. We also show how multivariate multiple regression can be used to model shape change predicted by these 2D outcomes, so that participants’ choices can be explained by their measured body composition together with other psychometric variables. Together, this approach should substantially improve the accuracy and precision with which self-assessments of body size and shape can be made in obese individuals and those suffering from eating disorders

Comparison of body mass index (BMI) with the CUN-BAE body adiposity estimator in the prediction of hypertension and type 2 diabetes

Background Obesity is a world-wide epidemic whose prevalence is underestimated by BMI measurements, but CUN-BAE (Clínica Universidad de Navarra - Body Adiposity Estimator) estimates the percentage of body fat (BF) while incorporating information on sex and age, thus giving a better match. Our aim is to compare the BMI and CUN-BAE in determining the population attributable fraction (AFp) for obesity as a cause of chronic diseases. Methods We calculated the Pearson correlation coefficient between BMI and CUN-BAE, the Kappa index and the internal validity of the BMI. The risks of arterial hypertension (AHT) and diabetes mellitus (DM) and the AFp for obesity were assessed using both the BMI and CUN-BAE. Results 3888 white subjects were investigated. The overall correlation between BMI and CUN-BAE was R2 = 0.48, which improved when sex and age were taken into account (R2 > 0.90). The Kappa coefficient for diagnosis of obesity was low (28.7 %). The AFp was 50 % higher for DM and double for AHT when CUN-BAE was used. Conclusions The overall correlation between BMI and CUN-BAE was not good. The AFp of obesity for AHT and DM may be underestimated if assessed using the BMI, as may the prevalence of obesity when estimated from the percentage of BF

Measuring Adiposity in Patients: The Utility of Body Mass Index (BMI), Percent Body Fat, and Leptin

Background: Obesity is a serious disease that is associated with an increased risk of diabetes, hypertension, heart disease, stroke, and cancer, among other diseases. The United States Centers for Disease Control and Prevention (CDC) estimates a 20 % obesity rate in the 50 states, with 12 states having rates of over 30%. Currently, the body mass index (BMI) is most commonly used to determine adiposity. However, BMI presents as an inaccurate obesity classification method that underestimates the epidemic and contributes to failed treatment. In this study, we examine the effectiveness of precise biomarkers and duel-energy x-ray absorptiometry (DXA) to help diagnose and treat obesity. Methodology/Principal Findings: A cross-sectional study of adults with BMI, DXA, fasting leptin and insulin results wer

Association between Variants of the Leptin Receptor Gene (LEPR) and Overweight: A Systematic Review and an Analysis of the CoLaus Study

BACKGROUND: Three non-synonymous single nucleotide polymorphisms (Q223R, K109R and K656N) of the leptin receptor gene (LEPR) have been tested for association with obesity-related outcomes in multiple studies, showing inconclusive results. We performed a systematic review and meta-analysis on the association of the three LEPR variants with BMI. In addition, we analysed 15 SNPs within the LEPR gene in the CoLaus study, assessing the interaction of the variants with sex. METHODOLOGY/PRINCIPAL FINDINGS: We searched electronic databases, including population-based studies that investigated the association between LEPR variants Q223R, K109R and K656N and obesity- related phenotypes in healthy, unrelated subjects. We furthermore performed meta-analyses of the genotype and allele frequencies in case-control studies. Results were stratified by SNP and by potential effect modifiers. CoLaus data were analysed by logistic and linear regressions and tested for interaction with sex. The meta-analysis of published data did not show an overall association between any of the tested LEPR variants and overweight. However, the choice of a BMI cut-off value to distinguish cases from controls was crucial to explain heterogeneity in Q223R. Differences in allele frequencies across ethnic groups are compatible with natural selection of derived alleles in Q223R and K109R and of the ancient allele in K656N in Asians. In CoLaus, the rs10128072, rs3790438 and rs3790437 variants showed interaction with sex for their association with overweight, waist circumference and fat mass in linear regressions. CONCLUSIONS: Our systematic review and analysis of primary data from the CoLaus study did not show an overall association between LEPR SNPs and overweight. Most studies were underpowered to detect small effect sizes. A potential effect modification by sex, population stratification, as well as the role of natural selection should be addressed in future genetic association studies

The relationship between body size and mortality in the linked Scottish Health Surveys: cross-sectional surveys with follow-up

Objective: To investigate the relationship between body mass index (BMI), waist circumference (WC) or waist–hip ratio (WHR) and all-cause mortality or cause-specific mortality. Design: Cross-sectional surveys linked to hospital admissions and death records. Subjects: In total, 20 117 adults (aged 18–86 years) from a nationally representative sample of the Scottish population. Measurements: Cox proportional hazards models were used to estimate hazard ratios (HRs) for all-cause, or cause-specific, mortality. The three anthropometric measurements BMI, WC and WHR were the main variables of interest. The following were adjustment variables: age, gender, smoking status, alcohol consumption, survey year, social class and area of deprivation. Results: BMI-defined obesity (greater than or equal to30 kg m−2) was not associated with increased risk of mortality (HR=0.93; 95% confidence interval=0.80–1.08), whereas the overweight category (25–&#60;30 kg m−2) was associated with a decreased risk (0.80; 0.70–0.91). In contrast, the HR for a high WC (mengreater than or equal to102 cm, womengreater than or equal to88 cm) was 1.17 (1.02–1.34) and a high WHR (mengreater than or equal to1, women&#8805;0.85) was 1.34 (1.16–1.55). There was an increased risk of cardiovascular disease (CVD) mortality associated with BMI-defined obesity, a high WC and a high WHR categories; the HR estimates for these were 1.36 (1.05–1.77), 1.41 (1.11–1.79) and 1.44 (1.12–1.85), respectively. A low BMI (&#60;18.5 kg m−2) was associated with elevated HR for all-cause mortality (2.66; 1.97–3.60), for chronic respiratory disease mortality (3.17; 1.39–7.21) and for acute respiratory disease mortality (11.68; 5.01–27.21). This pattern was repeated for WC but not for WHR. Conclusions: It might be prudent not to use BMI as the sole measure to summarize body size. The alternatives WC and WHR may more clearly define the health risks associated with excess body fat accumulation. The lack of association between elevated BMI and mortality may reflect the secular decline in CVD mortality.</p