Weight management is a dynamic process, with a pre-treatment phase, a treatment (including process) phase and post-treatment maintenance, and where relapse is possible during both the treatment and maintenance.Variability in the statistical power of the studies concerned, heterogeneity in the definitions, the complexity of obesity and treatment success, the constructs and measures used to predict weight loss maintenance, and an appreciation of who, and how many people achieve it, make prediction difficult.In models of weight loss or maintenance: (i) predictors explain up to 20-30% of the variance; (ii) many predictors are the sum of several small constituent variables, each accounting for a smaller proportion of the variance; (iii) correlational or predictive relationships differ across study populations; (iv) interindividual variability in predictors and correlates of outcomes is high; (v) most of the variance remains unexplained.Greater standardisation of predictive constructs and outcome measures, in more clearly defined study populations, tracked longitudinally, is needed better to predict who sustains weight loss.Treatments need to develop a more individualised approach that is sensitive to patients' needs and individual differences, which requires measuring and predicting patterns of intra-individual behaviour variations associated weight loss and its maintenance. This information will help people shape behaviour change solutions to their own lifestyle needs.3

Abbreviations: EB, energy balance; EE, energy expenditure; EI, energy intake; Hex, high exercise level; Mex, medium exercise level; Nex, no exercise. Physical activity has the potential to modulate appetite control by improving the sensitivity of the physiological satiety signalling system, by adjusting macronutrient preferences or food choices and by altering the hedonic response to food. There is evidence for all these actions. Concerning the impact of physical activity on energy balance, there exists a belief that physical activity drives up hunger and increases food intake, thereby rendering it futile as a method of weight control. There is, however, no evidence for such an immediate or automatic effect. Short (1-2 d)-term and medium (7-16 d)-term studies demonstrate that men and women can tolerate substantial negative energy balances of ≤ 4 MJ energy cost/d when performing physical activity programmes. Consequently, the immediate effect of taking up exercise is weight loss (although this outcome is sometimes difficult to assess due to changes in body composition or fluid compartmentalization). However, subsequently food intake begins to increase in order to provide compensation for about 30 % of the energy expended in activity. This compensation (up to 16 d) is partial and incomplete. Moreover, subjects separate into compensators and non-compensators. The exact nature of these differences in compensation and whether it is actually reflective of non-compliance with protocols is yet to be determined. Some subjects (men and women) performing activity with a cost of ≤ 4 MJ/d for 14 d, show no change in daily energy intake. Conversely, it can be demonstrated that when active individuals are forced into a sedentary routine food intake does not decrease to a lower level to match the reduced energy expenditure. Consequently, this situation creates a substantial positive energy balance accompanied by weight gain. The next stage is to further characterize the compensators and non-compensators, and to identify the mechanisms (physiological or behavioural) that are responsible for the rate of compensation and its limits.Energy balance: Physical activity: Appetite EB, energy balance; EE, energy expenditure; EI, energy intake; Hex, high exercise level; Mex, medium exercise level; Nex, no exercise.

The effects of incremental exercise on appetite, energy intake (EI), expenditure (EE) and balance (EB) in lean men and women were examined. Six men (age 29·7 (SD 5·9) years, weight 75·2 (SD 15·3) kg, height 1·75 (SD 0·11) m) and six women (age 24·7 (SD 5·9) years, weight 66·7 (SD 9·10) kg, height 1·70 (SD 0·09) m) were each studied three times during a 16 d protocol, corresponding to no additional exercise (Nex), moderate-intensity exercise (Mex; 1·5 -2·0 MJ/d) and high-intensity exercise (Hex; 3·0 -4·0 MJ/d) regimens. Subjects were fed to EB during days 1 -2, and during days 3-16 they fed ad libitum from a medium-fat diet of constant composition. Daily EE, assessed using the doubly labelled water method, was 9·2, 11·6 and 13·7 MJ/d (P, 0·001; SED 0·45) for the women and 12·2, 14·0 and 16·7 MJ/d (P¼ 0·007; SED 1·11) for the men on the Nex, Mex and Hex treatments, respectively. EI was 8·3, 8·6 and 9·9 MJ/d (P¼ 0·118; SED 0·72) for the women and 10·6, 11·6 and 12·0 MJ/d (P¼ 0·031; SED 0·47) for the men, respectively. On average, subjects compensated for about 30 % of the exercise-induced energy deficit. However, the degree of compensation varied considerably among individuals. The present study captured the initial compensation in EI for exercise-induced energy deficits. Total compensation would take a matter of weeks.Exercise: Appetite: Energy balance: Feeding behaviour: Human studies A low level of physical activity, typical of Western society, is deemed conducive to weight gain (1,2) . In addition, it is believed by some that increases in physical activity will promote weight loss (3) . However, individuals are unlikely to continue to lose weight over prolonged periods if they elevate daily energy expenditure (EE) by increasing physical activity (for example, Sum et al. ). It is intuitively obvious that energy intake (EI) will eventually begin to track EE, and body weight will stabilise. However, the exact manner in which changes in levels of physical activity influence feeding behaviour over periods long enough to affect energy balance (EB) is not clearly understood. There is a large body of literature on the effect of training programmes on body weight and composition in athletes (5 -10) . Likewise, a number of important studies have examined the effects of training programmes on weight loss in obese subjects (for example, Schoeller et al. (11) and Saris (12) ). Fewer studies have examined the relationship between changes in EE and feeding behaviour in normally sedentary, non-obese subjects who do not have a pre-conceived goal of weight reduction or a training programme. The reviews of King et al. of the effects of exercise regimens on appetite and EI show that in short-to mediumterm intervention studies (often no longer than 2-5 d), 19 % report an increase in EI after exercise; 65 % show no change and 16 % show a decrease (13 -15) . Longer-term studies that measure body composition suggest some fat mass is lost but lean body mass tends to be preserved in response to exercise regimens, depending on the ...

An obesigenic environment is a potent force for promoting weight gain. However, not all people exposed to such an environment become obese; some remain lean. This means that some people are susceptible to weight gain (in a weight-promoting environment) and others are resistant. Identifying the characteristics of appetite control and food motivation in these two groups could throw light on the causes of weight gain and how this can be either treated or prevented. We have investigated the issue experimentally by identifying people who habitually consume a high-fat diet (greater than 43% fat energy). These individuals have been termed high-fat phenotypes. We have compared individuals, of the same age (mean=37 years old) and gender (male), who have gained weight (BMI=34) or who have remained lean (BMI=22). The susceptible individuals are characterised by a cluster of characteristics including a weak satiety response to fatty meals, a maintained preference for high-fat over low-energy foods in the post-ingestive satiety period, a strong hedonic attraction to palatable foods and to eating, and high scores on the TFEQ factors of Disinhibition and Hunger. The analysis of large databases suggests that this profile of factors contributes to an average daily positive energy balance from food of approximately 0.5 MJ. This profile of characteristics helps to define the symptomatology of a thrifty phenotype.

Objective: This project audited rate and extent of weight loss in a primary care/commercial weight management organisation partnership scheme. Methods: 34,271 patients were referred to Slimming World for 12 weekly sessions. Data were analysed using individual weekly weight records. Results: Average (SD) BMI change was –1.5 kg/m² (1.3), weight change –4.0 kg (3.7), percent weight change –4.0% (3.6), rate of weight change –0.3 kg/week, and number of sessions attended 8.9 (3.6) of 12. For patients attending at least 10 of 12 sessions (n = 19,907 or 58.1%), average (SD) BMI change was –2.0 kg/m² (1.3), weight change –5.5 kg (3.8), percent weight change –5.5% (3.5), rate of weight change –0.4 kg/week, and average number of sessions attended was 11.5 (0.7) (p < 0.001, compared to all patients). Weight loss was greater in men (n = 3,651) than in women (n = 30,620) (p < 0.001). 35.8% of all patients enrolled and 54.7% in patients attending 10 or more sessions achieved at least 5% weight loss. Weight gain was prevented in 92.1% of all patients referred. Attendance explained 29.6% and percent weight lost in week 1 explained 18.4% of the variance in weight loss. Conclusions: Referral to a commercial organisation is a practical option for National Health Service (NHS) weight management strategies, which achieves clinically safe and effective weight loss.

1 2 Background:The relationship between body composition, energy expenditure and ad libitum 3

We assessed the effect of no exercise (Nex; control) and high exercise level (Hex; approximately 4 MJ/day) and two dietary manipulations [a high-fat diet (HF; 50% of energy, 700 kJ/100 g) and low-fat diet (LF; 20% of energy, 300 kJ/100 g)] on compensatory changes in energy intake (EI) and energy expenditure (EE) over 7-day periods. Eight lean men were each studied four times in a 2 x 2 randomized design. EI was directly quantified by weight of food consumed. EE was assessed by heart rate (HR) monitoring. Body weight was measured daily. Mean daily EE was 17.6 and 11.5 MJ/day (P < 0.001) on the pooled Hex and Nex treatments, respectively. EI was higher on HF diets (13.4 MJ/day pooled) compared with the LF diets (9.0 MJ/day). Regression analysis showed that these energy imbalances induced significant compensatory changes in EB over time of approximately 0.3-0.4 MJ/day (P < 0.05). These were due to changes in both EI and EE in the opposite direction to the perturbation in energy balance. These changes were significant, small but persistent, amounting to approximately 0.2 and approximately 0.35 MJ/day for EI and EE, respectively.

BackgroundAverage population dietary intakes do not reflect the wide diversity of dietary patterns across the population. It is recognised that most people in the UK do not meet dietary recommendations and have diets with a high environmental impact, but changing dietary habits has proved very difficult. The purpose of this study was to investigate the diversity in dietary changes needed to achieve a healthy diet and a healthy diet with lower greenhouse gas emissions (GHGE) (referred to as a sustainable diet) by taking into account each individual’s current diet and then minimising the changes they need to make.MethodsLinear programming was used to construct two new diets for each adult in the UK National Diet and Nutrition Survey (n = 1491) by minimising the changes to their current intake. Stepwise changes were applied until (i) dietary recommendations were achieved and (ii) dietary recommendations and a GHGE target were met. First, gradual changes (≤50 %) were made to the amount of any foods currently eaten. Second, new foods were added to the diet. Third, greater reductions (≤75 %) were made to the amount of any food currently eaten and finally, foods were removed from the diet.ResultsOne person out of 1491 in the sample met all the dietary requirements based on their reported dietary intake. Only 7.5 and 4.6 % of people achieved a healthy diet and a sustainable diet, respectively, by changing the amount of any food they currently ate by up to 50 %. The majority required changes to the amount of each food eaten plus the addition of new foods. Fewer than 5 % had to remove foods they ate to meet recommendations. Sodium proved the most difficult nutrient recommendation to meet. The healthy diets and sustainable diets produced a 15 and 27 % reduction in greenhouse gas emissions respectively.ConclusionsSince healthy diets alone do not produce substantial reductions in greenhouse gas emissions, dietary guidelines need to include recommendations for environmental sustainability. Minimising the shift from current dietary intakes is likely to make dietary change more realistic and achievable.