Instead, it involves a lifestyle with healthy eating patterns, regular physical activity, and stress management. People with gradual, steady weight loss about 1 to 2 pounds per week are more likely to keep the weight off than people who lose weight quickly.

Sleep, age, genetics, diseases, medications, and environments may also contribute to weight management. If you are concerned about your weight or have questions about your medications, talk with your health care provider.

Whether you have a family history of heart disease, want to see your kids get married, or want to feel better in your clothes, write down why you want to lose weight. Writing it down can confirm your commitment. Post these reasons where they serve as a daily reminder of why you want to make this change.

Write down everything you eat and drink for a few days in a food and beverage diary. Tracking physical activity [PDFKB] , sleep, and emotions can also help you understand current habits and stressors. This can also help identify areas where you can start making changes.

Next, examine your lifestyle. Identify things that might pose challenges to your weight loss efforts. For example, does your work or travel schedule make it hard to get enough physical activity? Do your coworkers often bring high-calorie items, such as doughnuts, to the workplace?

Think through things you can do to help overcome these challenges. If you have a chronic condition or a disability, ask your health care provider for resources to support healthy weight. This may include referral to a registered dietitian and other clinical or community programs, federally approved medications or devices, or surgery.

Ask for a follow-up appointment to monitor changes in your weight or any related health conditions. Set short-term goals and reward your efforts along the way. Maybe your long-term goal is to lose 40 pounds and to control your high blood pressure. Short-term goals might be to drink water instead of sugary beverages, take a minute evening walk, or have a vegetable with supper.

Setting unrealistic goals, such as losing 20 pounds in 2 weeks, can leave you feeling defeated and frustrated. Being realistic also means expecting occasional setbacks. When setbacks happen, get back on track as quickly as possible.

Also think about how to prevent setbacks in similar future situations. Keep in mind everyone is different—what works for someone else might not be right for you. Try a variety of activities such as walking, swimming, tennis, or group exercise classes.

The project has developed a framework and digital architecture for interventions in the context of EB tracking and will generate results that will help inform the next generation of personalised interventions for effective self-management of weight and health. The overall cost of obesity could be as high as EUR — billion, because obesity is linked to a range of physical and psychological illnesses [ 3 ].

These costs are set to rise in parallel with obesity prevalence [ 4 ]. Obesity affects psychological wellbeing, self-esteem, education and employment prospects especially in younger people and women [ 5, 6 ]. It is associated with decreases in health-related quality of life and overall life expectancy and greater health care expenditures [ 7 ].

Complex conditions such as obesity that have a large behavioural component to their development and maintenance do not have simple solutions but require concerted action through multicomponent interventions aimed at both prevention and treatment.

Evidence-based interventions and commercial programmes for weight loss WL are widely available [ 9, 10 ]. Eighty percent of those who achieve clinically significant WL fail to sustain that WL over a period of 12 months [ 12 ].

Factors responsible for weight regain include physiological resistance to WL [ 13 ], the obesogenic environment [ 8 ], individual experiences of stress and life events [ 14 ], and a general lack of knowledge on the part of consumers on how to effectively manage energy balance EB behaviours dietary intake and physical activity [ 15 ].

There is now considerable evidence documenting the effects of both non-commercial and commercial behavioural, pharmacological, or surgical interventions on initial WL [ 9, 10, ]. All of these approaches are subject to some degree of longer-term weight regain [ 17, 30 ].

Behavioural programmes have central elements of dietary energy restriction, some form of behavioural counselling and support, and some advice regarding physical activity see below [ 31, 32 ]. For completers of nonsurgical WL clinical trials i.

Behaviour change interventions, some available commercially, deliver an initial WL [ ]. However, long-term WL maintenance WLM is more challenging; weight relapse is common [ 17 ] and obesity is a chronic relapsing condition [ 38, 39 ].

National weight control registries have shown that WLM is possible for thousands of individuals previously diagnosed with obesity, but not probable for most [ 12, 40, 41 ]. Several systematic reviews and analyses have identified the critical elements that future interventions must effectively address and described modest effect sizes that need to be amplified to improve longer-term weight outcomes.

These include behavioural interventions to change diet, physical activity, and other weight control behaviours through components targeting self-regulation of behaviours, increased autonomous motivation, and self-efficacy [ ].

There is evidence that some of the behaviours that lead to WL are continued during WLM and that some additional behaviours are recruited during the period of WLM [ 46 ].

The transition from WL to WLM is a dynamic interaction between behavioural strategies to lose weight and the physiological and environmental resistance to WL [ 8, 19, 47 ], which creates a tonic pull that can undermine the behaviours that led to the initial WL.

Thus, those who lose weight are at a high risk for weight regain. Many people who have engaged in an initial WL attempt actually aim to achieve further WL rather than WLM.

Many people attempting to maintain their WL therefore experience periods where they revisit strategies they originally used to lose weight, to cope with weight relapse, or to lose further weight.

Longer-term weight management typically involves attempts at achieving sustainable change in habitual eating, activity, and self-regulation behaviours. These changes interact with changes in physiological and emotional systems, which together with aspects of the environment food marketing, psychosocial stress, work routines, time urgency, and sedentary routines produce strong influences that promote weight relapse.

Thus, there is a need to develop sustainable solutions that prevent weight relapse [ 38, 48 ]. WL trajectories slow as time progresses. The exact physiological mechanisms that oppose further WL and often promote weight regain are multiple, complex, individually subtle, and difficult to quantify specifically, although they include changes in energy expenditure, appetite, and energy intake [ ].

In addition, many people experience behavioural lapses and relapses as more pronounced situational or momentary events. Avoiding both gradual and more pronounced weight regain requires behavioural strategies in which relapse coping and WLM become learned skills of self-regulation, autonomy and motivation [ ] as part of a longer-term process [ 38, ].

Evidence suggests that core features of more effective WLM interventions include behaviour change techniques such as self-monitoring of weight and behaviour , relapse prevention, goal setting, and action plans for diet and physical activity, which improve self-efficacy [ 44, 58, 63 ]. Thus, self-regulation of EB behaviours appears to be a key intervention target for longer-term weight management.

Physical activity and dietary interventions based on current behaviour change theories characteristically achieve relatively modest effects of over 12 months [ 64, 65 ].

Research identifying and linking specific behaviour change approaches or techniques to mechanisms of action of behaviour change interventions is still a developing field [ 66, 67 ]. Historically, behaviour change models have focused on social cognition e.

It is also believed that automatic processes emotions, desires, habits resulting from associative learning and physiological states may also have a large impact on behaviour and behaviour change. These processes tend to be relatively rapid, automatic, impulsive less conscious , and habitual in comparison to the slow, deliberative processes of motivation and self-regulation [ 70, 71 ].

Furthermore, in the context of EB behaviours, the development of self-regulatory behaviour change is sometimes effortful, particularly in the face of a physiological resistance to WL, while unconscious or automatic components of EB behaviours are rapid and effortless [ 72 ].

Such processes may have a considerable capacity to undermine the initial self-regulation of EB behaviours particularly eating behaviours in the face of a physiological system that resists longer-term WL.

Automatic components of self-regulation may also promote longer-term behaviour changes if they are engaged and developed [ ]. At the outset of the project, we hypothesised that another aspect of automaticity potentially affecting EB behaviours is distress tolerance and emotional responses.

Food is a powerful source of pleasure and reward [ ]. This has consequences for our ability to form planned, reasoned behavioural pathways to manage our weight. People with overweight and obesity commonly experience stigma, which enhances psychosocial stress and negatively impacts physical and mental wellbeing [ ].

Stigma impacts shame, self-criticism, and unfavourable social comparisons, creating feelings of inferiority and inadequacy in relation to others [ 82 ]. Weight management therefore has a large emotional dimension.

The relationship between stress, emotion, and food intake can derail strategies of planned behaviour and promote relapse [ 83, 84 ]. This is probably why shame and self-criticism are associated with binge eating [ 85 ], obesity [ 79, 80 ], and problems linked to body image [ 82, 86, 87 ].

Acceptance, self-compassion, and mindfulness-based approaches may help to address these issues [ 88 ] and may help to reduce obesity-related eating behaviours [ 89, 90 ]. At the outset of the project we hypothesised that self-monitoring, self-regulation, and autonomous motivation in WLM could favourably be supported by strategies that promote stress management and emotion regulation [ 88, ].

It is important to note that the majority of studies examining psychological and social predictors of longer-term weight outcomes as mechanisms of action of behaviour change interventions have either used pre-treatment predictors [ 98, 99 ] or correlates of WL and maintenance rather than sequential measures of outcomes throughout intervention and follow-up periods Fig.

To our knowledge, no studies have directly linked longitudinal changes in compensatory EB physiology and behaviour to mechanisms of action of behaviour change interventions. The current scientific debate focuses on the process of WLM given that pre-treatment predictors of WL tend to explain relatively little of subsequent weight outcomes [ 44, 98, 99 ].

For instance, Varkevisser et al. It therefore appears albeit from limited evidence that it is important to understand processes of change in the self-management of EB behaviours during the course of weight management interventions. This requires longitudinal studies where processes of psychosocial change and EB behaviours are both tracked over time.

The majority of studies examining psychosocial predictors of longer-term weight outcomes, as mechanisms of action of behaviour change interventions, have used either pre-treatment predictors [ 98, 99 ] or correlates of WL and maintenance rather than sequential measures of outcomes throughout intervention and follow-up periods.

Recent evidence suggests that factors influencing changes in behaviours during the course of weight management interventions are important determinants of success of failure at longer-term weight management [ 44 ].

There are currently numerous WL mobile applications apps available to citizens. Initial opportunistic reviews of the effectiveness of commonly available WL mobile apps available on Apple and Android websites in showed that they typically included only a minority of the behavioural strategies shown to be effective in evidence-based interventions [ , ].

In particular, behavioural strategies that help to improve motivation, reduce stress, and improve problem solving were generally missing in such apps [ ]. A systematic review of weight management apps suggested that alone they produce modest effects on weight and health outcomes and they may be more effective as part of multicomponent interventions [ ].

This suggests that most weight management apps previously missed key evidence-based approaches for longer-term behaviour changes. A systematic review and meta-analysis of e-health interventions for the prevention and treatment of obesity found evidence of significant but modest effects of eHealth interventions as a treatment option for obesity, but there was insufficient evidence to suggest that such interventions may be valuable for WLM [ ].

A more recent extensive systematic review and meta-analysis assessing the effectiveness of app-based mobile interventions for improving nutritional behaviours and health outcomes found some beneficial effects of goals and planning, feedback and monitoring, shaping knowledge, and social support on both of these outcomes [ ].

Other systematic reviews indicate that weight management apps may have positive effects on weight-related outcomes, although the methodological quality of many studies is low [ , ].

While there is an urgent need for sustainable and cost-effective solutions that are easy and convenient to use for the consumer and manageable for the health care provider, it is important to conduct randomised trials of digital technologies for WLM and to try to understand the mechanisms by which they may influence weight and health outcomes.

The NoHoW project was a 5-year European Commission Horizon funded Research and Innovation Action in the Personalising Health and Care-Self Management of Health and Disease: citizen engagement and mHealth call, focused on developing evidence-based digital technologies and tools for WLM grant agreement No.

The project was developed around the most promising evidence-based behaviour change techniques for WLM self-monitoring, goal setting, action control, autonomous motivation, and also assessment of building self-efficacy combined with contextual behavioural science approaches to emotion regulation and stress management to facilitate weight-regain prevention.

Evidence of effective weight management practices is still limited. To design a digital offering that addresses the needs of European citizens, the project initially examined why a representative sample of European citizens make WL efforts, how often these efforts are made over a year, and the specific methods people use for WL.

Information was gained from international surveys of 2, consumers in 3 countries, from longitudinal analysis of weight management experience in an existing cohort of 2, successful WL maintainers, and from qualitative studies of those engaged in WLM attempts [ ].

Because information technology offers cost-effective, scalable, and attractive tools for teaching and supporting these techniques, some of which are currently delivered through resource-intensive face-to-face therapies, the project has developed a digital toolkit TK using theoretically informed, evidence-based behaviour change approaches.

The project has surveyed digital interventions for WLM in the context of the most up-to-date behavioural science research, using this knowledge to develop a digital TK for WLM based on 2 key conditions, i. It formally tested the efficacy of this digital TK through a large-scale randomised controlled trial, conducted over a 6-month active intervention and subsequent month follow-up, by using a mobile enabled website, activity trackers, and Wi-Fi weight scales.

Secondary outcomes were month changes in body composition e. State-of-the-art consumer devices were employed to track physical activity and body weight throughout the trial. Finally, we developed a digital architecture that linked the TK to users, collected and streamed data from participants to a central data hub for storage and analysis, and facilitated trial administration and management.

The overall project was based around 5 objectives. The primary objectives of the NoHoW project were to understand how weight is lost and managed in Europe, develop a digital TK to support WL maintenance, evaluate the impact of the TK on WL maintenance through a 2 × 2 factorial randomised controlled trial, identify predictive signatures of weight relapse and maintenance, and inform future digital interventions for longer-term weight management.

To engage citizens in longer-term weight management, and design evidence-based tools to support them, we characterised weight management practices across Europe.

This has established when and how a representative sample of 2, Europeans make WL efforts over a year [ 14, ]. We also followed an existing cohort of 2, successful WL maintainers in a commercial weight management programme longitudinally over 12 months to identify the factors that contribute to successful WLM and collected qualitative insights into self-regulatory behaviours in WLM.

In other fields of prevention science, such as smoking cessation, the answers to these questions are known and have contributed to progress in self-management and improved health [ ]. The project aimed to fill this gap for obesity, WL, and WLM.

We have developed a digital TK of behaviour change tools to support users in maintaining their WL Fig. These tools cover: 1 self-regulation and motivational skills to promote volitional aspects of WLM and 2 emotion regulation and stress management to improve eating control.

Within each condition, participants were reminded to visit the TK to complete sessions and could, to a limited extent, choose the sequence and number of times they accessed TK components. Participants were asked to wear the tracking devices Fitbit Charge 2 continuously except during charging and water-based activities and weigh themselves twice a week Fitbit Aria cloud-connected scales.

The digital TK was linked to a central data hub, which: 1 aggregated data from all the measures made on each user; 2 supported limited tracking, feedback, and behavioural signature profiling; and 3 provided statistical models and analyses of the intervention outcomes. User evaluation of the TK was measured through a user-centred design approach [ ].

Conceptual basis for the development of the NoHoW TK and its intended impact on the cycle of WL and weight regain. The efficacy and cost-effectiveness of the TK and multiple mediation analyses of processes of behaviour change will be reported in separate publications.

Through statistical analysis and modelling of primary and secondary outcome data in the data hub, we will relate psychological and behavioural outcomes to tracked EB behaviours [ ], sleep [ ], and weight change. This will establish a foundation for future predictive decision support systems that match user profiles to TK development strategies for WLM.

The project began with work package 1 WP1 , where we established how weight is lost and managed in European citizens through a pan-European survey of 2, consumers to establish why, when, and how many European citizens make WL efforts over a year, how often these efforts are made, and the specific methods people use.

We also established how WL successes and weight relapses relate to socioeconomic, cultural, and specific lifestyle contexts. These data informed the design of the digital TK for weight management [ 14, ].

We have also conducted month repeat longitudinal measures of weight management experience in an existing cohort of 2, successful WL maintainers attending Slimming World TM. The infrastructure to identify these participants and regularly follow-up their weight was established through the regular data monitoring architecture of Slimming World TM [ ].

Finally, we explored self-regulation of food intake in Danish WL maintainers and the potential of NoHoW to attract user groups through qualitative research methods [ ]. In WP2 we developed and validated the NoHoW TK and its specific components Fig.

WP2 has been informed by: 1 user needs and requirements from WP1, 2 knowledge from behaviour change theory and known applications, 3 research evidence on predictors of WLM, and 4 previous experience from project partners in designing health-related ICT-based tools, for example [ ].

This WP added self-tracking technologies FitBit Charge 2 and Aria scales for continuous tracking of physical activity and body weight. Throughout the trial the University of Leeds has been working on relating these measures to criterion measures of energy expenditure and storage through complex mathematical modelling [ ].

The full description of the TK will be given in a separate publication. In WP3 and WP4 we delivered an RCT to evaluate the efficacy and cost-effectiveness of the TK Fig.

The full protocol for the trial is described in a separate publication [ ]. The factorial structure is a major step forward from conventional 2-armed trials. It allows tests of 3 main hypotheses, i. Secondary moderation analysis will test if baseline features predict who is more likely to benefit from each of the interventions.

The 4 arms of the trial enable us to examine if specific combinations of digitally delivered TK components affect WLM success over and above frequent self-monitoring. WP4 delivered the NoHoW trial at the 3 intervention centres through intervention delivery, monitoring, governance and ethics, health economics, database management, and statistical analysis.

This WP was responsible for conducting the intervention and follow-up with final measures to monitor the effect of the intervention. The main results of the NoHoW intervention will be given in a separate publication.

WP5 managed the overall digital architecture of the project and created a central data storage facility whereby all data collected during the project was delivered, cleaned, and stored securely for the duration of the project and 20 years thereafter Fig. The data hub received and deposited data during the intervention and made available all data generated in the project WP1—4 and 6.

This database has been set up in Edinburgh, Scotland, with links to the TK management centre WP2 for automated data feed in from the TK as used by participants in the intervention. At the end of the intervention, WP5 provided the primary statistical analysis of the RCT outcomes and health economics analysis to feed into WP6, the development of the business model for the NoHoW project.

WP6 was responsible for the future exploitation planning for TK v2. Exploitation planning activities explored how to make results, insights, and technologies from NoHoW available across different channels based on their commercialisation and impact potential. WP8 was responsible for project management, i.

This WP acted as a liaison with the EU, handled administration, deliverables, and reports, and addressed project-wide issues such as quality, intellectual property and intra-team communication.

The NoHoW project has gathered an evidence base of weight management practices across Europe and around the world [ 11 ] and longitudinally tracked psychological predictors of WLM in a large cohort of commercial weight management participants who have achieved a significant amount of WL and are explicitly seeking to maintain that loss [ 14, ].

The NoHoW TK is a research grade technology that, where possible, has used commercially available solutions Fitbit activity and weight trackers and Qualtrics questionnaires to improve the experience of participants engaged in its evaluation.

The TK is based on: 1 evidence-based state-of-art theories of behaviour change, including techniques associated with self-regulation skills self-regulation theory , building autonomous motivation self-determination theory , and emotional regulation and stress management, and 2 web design expertise and 3 user testing.

Informed by the guidelines for the development of complex behaviour change interventions and principles applied in previous theory-based behaviour change interventions, we have used systematic approaches to the translation of theory and evidence from face-to-face interventions to digital intervention components.

This included: 1 theory selection and development of the content logic models, 2 TK guiding principles and selection of the intervention techniques, 3 translating these techniques into the TK components, 4 TK technical development, and 5 user evaluation and TK refinement.

The NoHoW TK was hypothesised to influence mechanisms of action that may impact EB behaviours and longer-term weight outcomes. We have developed personalised feedback equations that, based on individual weight changes and activity behaviour measured by the Fitbit devices , informed participants about what seemed to have worked for their individual weight journey, and we applied machine learning algorithms to predict EE from steps, heart rate, and subject characteristics in a range of activities, compared to indirect calorimetry [ ].

Shortly thereafter, we chuck the whole plan with the intention to start another day. Instead, consider a "No Restart" principle. Pick any diet and or exercise program you want, but superimpose a No Restart rule. It means that when you get off track, you don't quit, you simply come back when you are ready at exactly the point where you left off.

Treat it like you are a collector of coins. You would come back to where you left off when life allowed. The same is true with weight loss plans. Come back in where you left off so you have something at the end of a given time period vs. nothing because you quit. the same starting point every few weeks.

Second, ditch the restriction. Early calorie restriction sets off a variety of survival-based resistances from the body, including hunger hormone spikes, metabolism slows, inflammation, anxiety , food-seeking behaviors, and more.

To change your body, you must provide the right nutrients. Supplement early on and exercise. Don't restrict. Staying full leads to longer times on the program, a change in your exercise capacity, and more tools to succeed in the long run.

Third, focus on recovery. Many of the would-be dieters that "start on Monday" and try to white-knuckle through to the end find themselves quitting. This approach is like planning to climb a mountain and sprinting the whole way.

It won't work. In the mountain analogy, you have to stop and acclimate to the altitude, stop and rest to eat and recharge to make it to the top of the mountain. The same is true for weight loss: if you are going to reach your goal, you have to focus on the "in-between days.