Background: Many weight loss programmes show short-term success, but long-term data in larger studies are scarce, especially in community settings. Attrition is common and complicates the interpretation of long-term outcomes.
Objective: To investigate 2-year outcomes and explore issues of attrition and missing data.
Subjects: A total of 772 overweight and obese adults recruited by primary care practices in Australia, Germany and the UK and randomised to a 12-month weight loss intervention delivered in a commercial programme (CP) or in standard care (SC).
Measurement: Weight change from 0-24 and 12-24 months including measured weights only and measured and self-reported weights, using last observation carried forward (LOCF), baseline observation carried forward (BOCF), completers-only and missing-at-random (MAR) analyses.
Results: A total of 203 participants completed the 24-month visit. Using measured weights only, there was a trend for greater 24-month weight loss in CP than in SC, but the difference was only statistically significant in the LOCF and BOCF analyses: LOCF: -4.14 vs -1.99 kg, difference adjusted for centre -2.08 kg, P<0.001; BOCF: -1.33 vs -0.74 kg, adjusted difference -0.60 kg, P=0.032; completers: -4.76 vs -2.99 kg, adjusted difference -1.53 kg, P=0.113; missing at random: -3.00 vs -1.94 kg, adjusted difference -1.04 kg, P=0.150. Both groups gained weight from 12-24 months and weight regain was significantly (P<0.001) greater for CP than for SC in all analysis approaches. Inclusion of self-reported weights from a further 138 participants did not change the interpretation of the findings.
Conclusion: Initial weight loss was poorly maintained during the no-intervention follow-up, but both groups did have lower weight over the 24 months. Attrition was high in both groups, and assumptions about missing data had considerable impact on the magnitude and statistical significance of treatment effects. It is vital that trials on weight loss interventions consider the plausibility of these differences in an analytical approach when interpreting research findings and comparing data between studies.