There is substantial evidence documenting the effects of behavioural interventions on weight loss (WL). However, behavioural approaches to initial WL are followed by some degree of longer-term weight regain, and large trials focusing on evidence-based approaches to weight loss maintenance (WLM) have generally only demonstrated small beneficial effects. The current state-of-the-art in behavioural interventions for WL and WLM raises questions of (i) how we define the relationship between WL and WLM, (ii) how energy balance (EB) systems respond to WL and influence behaviours that primarily drive weight regain, (iii) how intervention content, mode of delivery and intensity should be targeted to keep weight off, (iv) which mechanisms of action in complex interventions may prevent weight regain and (v) how to de- The work should be attributed to the School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK. The NoHoW project is a 5 million Euro project that received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 643309. The project brings together a multidisciplinary team of academic experts in behaviour change, consumer science, weight management interventions (and intervention evaluation), weight management delivery, disease prevention, biomathematics, computer science, personal data tracking and human-computer interactions. The primary focus of the project was to develop and evaluate evidence-based behavioural approaches to weight loss maintenance. This article is licensed under the Creative Commons Attribution- NonCommercial-NoDerivatives 4.0 International License (CC BYNC- ND) (http://www.karger.com/Services/OpenAccessLicense). Usage and distribution for commercial purposes as well as any distribution of modified material requires written permission. 2 Obes Facts Stubbs et al. DOI: 10.1159/000513042 sign studies and interventions to maximise effective longerterm weight management. In considering these issues a writing team within the NoHoW Consortium was convened to elaborate a position statement, and behaviour change and obesity experts were invited to discuss these positions and to refine them. At present the evidence suggests that developing the skills to self-manage EB behaviours leads to more effective WLM. However, the effects of behaviour change interventions for WL and WLM are still relatively modest and our understanding of the factors that disrupt and undermine self-management of eating and physical activity is limited. These factors include physiological resistance to weight loss, gradual compensatory changes in eating and physical activity and reactive processes related to stress, emotions, rewards and desires that meet psychological needs. Better matching of evidence-based intervention content to quantitatively tracked EB behaviours and the specific needs of individuals may improve outcomes. Improving objective longitudinal tracking of energy intake and energy expenditure over time would provide a quantitative framework in which to understand the dynamics of behaviour change, mechanisms of action of behaviour change interventions and user engagement with intervention components to potentially improve weight management intervention design and evaluation. Design: The study consisted of 1202 participants from the UK, Denmark and Portugal, participants of the NoHoW study (should we mention it?) who had achieved a verified weight loss of ≥5 % and had a BMI of ≥25 kg/m2 prior to losing weight. Information was available on sleep duration (collected during a 14-day period using the Fitbit Charge 2TM), adiposity measures, weight loss history and several potential confounding factors. Analysis of covariance was conducted to assess the associations between sleep duration and body mass index (BMI), fat mass index (FMI), fat free mass index (FFMI) and waist hip ratio (WHR). Linear regression or analysis of covariance was applied to assess whether weight loss history (twelve-month weight loss, frequency of prior weight loss attempts and average duration of weight loss maintenance after prior weight loss attempts) was associated with attained sleep duration. Results: We found an association between sleep duration and BMI (P<0.001, controlling for ??? If you have space I think you should include them), with the highest BMI observed in the group of participants sleeping < 6 hours a day [34.0 kg/m2 (95% CI: 31.8-36.1)]. Less difference in BMI was detected between the remaining groups, with the lowest BMI observed among participants sleeping 8-9 hours a day [29.4 kg/m2 (95% CI: 28.8-29.9)]. Similar results were found for FMI (P=0.008) and FFMI (P<0.001). We found no association between sleep duration and WHR. Likewise, we found no evidence of associations between weight loss history and attained sleep duration. I have read the results now... It is surprising to see that the FFMI associations present the same pattern as the BMI and FMI. Wouldn't be possible to use a percentage of Fat Mass and Fat Free Mass, instead of the FMI and FFMI. It seems counter-intuitive to observe a similar pattern between a measure of fat and a measure of muscle (I'm oversimplifying here, I know). I suspect that this is showing that the bigger participants - who have more BMI, FM and FFM in kg/m2- are the ones who sleep less. But we may be missing the participants who have more FM relative to their weight - whom I suspect are the ones with worst sleep patterns - and the ones who have more FFM relative to their weight - whom I suspect will have the best sleep pattern. Sorry if I'm making a mess out of this... Conclusion: These results build on the current evidence suggesting that a short sleep duration is associated with a higher BMI with at least 5% WL in the last 12 months. Most previous research has suggested that this association is primarily due to an association between sleep and adiposity, but our results suggests that the association also involves lean mass. We found no evidence of association between weight loss history and attained sleep duration.