Scott B Going

PMID: 15655038;Abstract:

Prompted by the large heterogeneity of individual results in obesity treatment, many studies have attempted to predict weight outcomes from information collected from participants before they start the programme. Identifying significant predictors of weight loss outcomes is central to improving treatments for obesity, as it could help professionals focus efforts on those most likely to benefit, suggest supplementary or alternative treatments for those less likely to succeed, and help in matching individuals to different treatments. To date, however, research efforts have resulted in weak predictive models with limited practical usefulness. The two primary goals of this article are to review the best individual-level psychosocial pre-treatment predictors of short- and long-term (1 year or more) weight loss and to identify research needs and propose directions for further work in this area. Results from original studies published since 1995 show that few previous weight loss attempts and an autonomous, self-motivated cognitive style are the best prospective predictors of successful weight management. In the more obese samples, higher initial body mass index (BMI) may also be correlated with larger absolute weight losses. Several variables, including binge eating, eating disinhibition and restraint, and depression/mood clearly do not predict treatment outcomes, when assessed before treatment. Importantly, for a considerable number of psychosocial constructs (e.g. eating self-efficacy, body image, self-esteem, outcome expectancies, weight-specific quality of life and several variables related to exercise), evidence is suggestive but inconsistent or too scant for an informed conclusion to be drawn. Results are discussed in the context of past and present conceptual and methodological limitations, and several future research directions are described.

PMID: 7674884;Abstract:

The purpose of this study was to compare the relationships of anthropometric, bioelectrical impedance analysis (BIA), and near infrared interactance (NIR) measurements with a multiple-component (MC) criterion estimate of body composition de rived from body density (D), body water (W), and bone mineral (B) in 48 white adults aged 49-80 yr. Relative errors of predicting the MC criterion from the practical measurements were determined by simple regressions within gender and calculated as the SEE divided by the criterion mean and expressed as a percentage. Relative errors were lowest for the BIA variable, height²/resistance (4.8-5.0%), higher for body mass index and the sum of 10 skinfold thicknesses (7.0-14.5%), and highest for NIR derived optical density readings at the biceps and the sum of 10 sites (10.8- 15.8%). Due to the low relative prediction error for height²/resistance, sex-specific BIA formulas for estimating fat-free mass from D, W, and B (FFM- DWB) were developed. The SEEs for predicting FFM DWB from BIA, weight, and age were both 1.5 kg in women and men. Because BIA is not limited to ambulatory subjects, it is concluded that BIA may be a particularly useful, practical technique for estimating body composition in older adults.