BackgroundDropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods.Methodology/Principal FindingsWe searched PubMed and Cochrane databases (2000–2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e−λt) where λ was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive.Conclusion/SignificanceOur analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis.

In this study, high fitness was a stronger predictor of cancer mortality in men, whereas high BMI was a stronger predictor of cancer mortality in women.

Results:The relationship between BMI and WC as characterized by the slope of the linear regression of WC on BMI does not seem to be changing significantly over time. A small (range, 0.08 to 0.27 cm/yr) increase in WC over time was observed. Discussion: The implications of these findings for public health and for understanding any extant changes in the BMI-mortality rate relationship remain to be elucidated.

OBEJECTIVE:To examine the relative size of the effects of fitness and fatness on mortality in Russian men, and to make comparison to US men. DESIGN: Prospective closed cohort. SUBJECTS: 1359 Russian men and 1716 US men aged 40-59 y at baseline (1972)(1973)(1974)(1975)(1976)(1977) who were enrolled in the Lipids Research Clinics Study. MEASUREMENTS: Fitness was assessed using a treadmill test and fatness was assessed as body mass index (BMI) calculated from measured height and weight. Hazard ratios were calculated using proportional hazard models that included covariates for age, education, smoking, alcohol intake and dietary keys score. All-cause and cardiovascular disease (CVD) mortality were assessed through 1995. RESULTS: In Russian men, fitness was associated with all-cause and CVD mortality, but fatness was not. For mortality from all causes, compared to the fit-not fat, the adjusted hazard ratios were 0.87 (95% CI: 0.55, 1.37) among the fit-fat, 1.86 (95% CI: 1.31, 2.62) among the unfit-not fat and 1.68 (95% CI: 1.06, 2.68) among the unfit-fat. Among US men, the same hazard ratios were 1.40 (95% CI: 1.07, 1.83), 1.41 (95% CI: 1.12, 1.77) and 1.54 (95% CI: 1.24, 2.06), respectively. There were no statistically significant interactions between fitness and fatness in either group of men for all-cause or CVD mortality. CONCLUSION: The effects of fitness on mortality may be more robust across populations than are the effects of fatness.