ABSTRACT
OBJECTIVE: To describe the measurement challenges faced and to evaluate the measurement quality obtained with massively obese individuals. METHOD: A cross-sectional analysis of 107 individuals with body mass indices (kg/m2) > or = 50 was conducted. Individuals had their body fat measured via bioimpedance analysis (BIA), their serum leptin levels measured via radioimmunoassay (RIA), and height and weight measured via both laboratory scales and self-report. RESULTS: Serum leptin appeared to be measured accurately, provided the serum was diluted prior to conducting the RIA. Difficulties remained, however, in evaluating what was an unusual or expected value of leptin among individuals this large. Measures of impedance appeared to provide reasonable ordinal indications of body fatness. However, currently available equations for converting measures of impedance to estimates of percent body fat were highly inaccurate. Self-reported height and weight were reasonably good proxies of measured height and weight among individuals who reported their height and weight. However, a substantial proportion were unable to provide estimates. DISCUSSION: The above results suggest there are substantial challenges when trying to obtain meaningful measurements regarding obesity-related variables among massively obese individuals. Other logistic challenges also are discussed. It is hoped future research is directed at overcoming some of these challenges.
Subject(s)
Body Weight , Obesity, Morbid/pathology , Adipose Tissue/pathology , Adult , Body Height , Body Mass Index , Female , Humans , Leptin , Male , Proteins/analysisABSTRACT
OBJECTIVE: Risch's lambda statistic (lambda R) is related to the heritability of traits and can be useful in several contexts, including the conduct of power analyses to determine sample size for gene mapping studies. However, values of lambda R have not been presented for human obesity. DESIGN AND RESULTS: Using both analytic and empirical approaches, the present study calculates estimates of lambda R. Examples are provided to illustrate the use of these estimates for determining sample size for genetic mapping studies.
