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This study explored associations between child eating behaviors and maternal feeding practices, specifically testing the hypotheses that maternal "restriction" is associated with having a child with stronger food approach tendencies (eg, overresponsiveness to food), and maternal pressure to eat is associated with having a child with food avoidant tendencies (eg, satiety responsiveness). Five-hundred thirty-one families with 7- to 9-year-old children from schools in London, UK, were invited to take part in the Physical Exercise and Appetite in Children Study (PEACHES). Results are from baseline data of this longitudinal study. Of those invited, 405 gave consent for their child to participate (51.6% male; 48% female). Just over half of the mothers (n=213, 53%) completed the Child Eating Behavior Questionnaire and the Child Feeding Questionnaire for the index child (mean age: 8.3±0.62 years) during the 2006-2007 school year. Children were weighed and measured at school by trained researchers. As predicted, maternal restriction was associated with child food responsiveness (P0.001), and maternal pressure to eat was associated with child satiety responsiveness (P0.001), slowness (P=0.03), and fussiness (P=0.01). Child enjoyment of food was associated with lower maternal pressure to eat (P=0.01). All effects were independent of the child's body mass index standard deviation score and sociodemographic factors. Practitioners may find it useful to take an interactional perspective, acknowledging that children both influence and are influenced by their parents' feeding practices. This will allow the development of targeted interventions and better parental guidance on managing obesogenic eating behaviors in young children.

BACKGROUND: The relative reinforcing value (RRV) of food, defined as how hard an individual is prepared to work to gain access to food rather than a nonfood alternative, has been shown to be higher in obese adults and children than in their normal-weight counterparts. However, these cross-sectional studies are unable to determine whether a high RRV of food is predictive of adiposity change or whether it is a consequence of being obese. OBJECTIVE: The objective was to examine the association between the RRV of food and 1-y weight gain in children aged 7-10 y. DESIGN: An observational longitudinal study design was used. The RRV of food was determined by using a questionnaire method at baseline when the children (n = 316) were aged 7-9 y. Adiposity [body mass index (BMI), BMI SD score, fat mass index, waist circumference, and waist circumference SD score] was assessed at baseline and after 1 y. RESULTS: Regression analyses indicated that the RRV of food was not associated with any measure of adiposity at baseline or at the 1-y follow-up (all P > 0.58). Changes in BMI (B = 0.06, P < 0.001), BMI SD score (B = 0.03, P = 0.001), and fat mass index (B = 0.09, P = 0.001) after 1 y were significantly predicted by the RRV of food at baseline. CONCLUSIONS: The RRV of food predicted the change in adiposity over a relatively short-term period of 1 y and thus may be associated with the development of obesity. The lack of association in cross-sectional analyses indicates that this behavior is a risk factor for weight gain, although weight differences may not emerge until later childhood.

Background Information on the efficacy and costs associated with targeting obesity can inform implementation of cost-effective policies. Within the Economics of Chronic Diseases (EConDA) project, we aimed to quantify the health and economic impact of two approaches to reduce chronic disease in eight European countries through to 2050: a multicomponent lifestyle intervention (MCLI) and a sugar-sweetened beverage tax. Methods Body-mass index (BMI), disease epidemiology, and cost data for the diseases modelled (type 2 diabetes, coronary heart disease, stroke, and hypertension) were obtained from the literature for Bulgaria, Finland, Greece, Lithuania, the Netherlands, Poland, Portugal, and the UK. When country-specific data were not available, other countries were used as a proxy after adjustment for between-country differences. Mean change in BMI after annual MCLI to reduce energy intake and improve physical activity through behaviour change was obtained from the literature and was estimated after a 20% excise tax on sugar-sweetened beverages. A microsimulation model created country-representative synthetic populations. We determined simulated health outcomes in a baseline scenario using projections of BMI trends for each country up to 2050 and in two scenarios applying the interventions' respective BMI reduction to the BMI trends in the population. Simulated individuals developed diseases on the basis of their BMI and outputs provided the incidence and costs associated with the different scenarios. Findings The prevalence of obesity and incidence of BMI-related disease was forecast to increase in all countries to 2050. MCLI had the largest effect on type 2 diabetes, ranging from 147 cases per 100 000 avoided (SD 17) in Bulgaria to 1003 (21) in Portugal by 2050. The highest costs avoided were for stroke (up to €1·15 million, SD €0·008 million) in Portugal. Although tax on sugar-sweetened beverages also had the largest effect on diabetes (from 5 per 100 000 cases avoided [SD 8] in the Netherlands to 87 [13] in the UK), the costs avoided were lower than for MCLI. Interpretation These results highlight the variation in impact depending on the type of intervention aimed at the prevention of chronic diseases. An integrated approach to reducing obesity is required, so that a battery of approaches, varying in uptake and targeted population group, could be useful to obtain a greater effect on BMI reduction. Funding European Commission Health Programme and the Executive Agency for Health and Consumers (project number 2012 12 13).

Background Obesity in the European region has more than tripled since 1980, making it one of the 21st century's main public health challenges. To monitor the prevention and control of major non-communicable diseases (NCDs) WHO and its member states designed an NCD global monitoring framework in which countries agreed to halt obesity levels by 2025. To monitor the feasibility of achieving this goal, we aimed to project the future trends of obesity (body-mass index [BMI] ≥30 kg/m 2 ) to 2025 for each of the 53 WHO European Region Member States. Methods We extrapolated past BMI trends using a non-linear, multivariate, categorical regression model to estimate country-specific projected prevalence of obesity in adults by 2025. We fitted the model to both measured and self-reported data from cross-sectional country-specific BMI data from nationally representative surveys collected between 1990 and 2015. BMI data were obtained from the WHO BMI database, country statistical databases, health reports, and information collected via personal communication. Findings By 2025, obesity is predicted to increase in 44 countries. If present trends continue, 33 of the 53 countries will have an obesity prevalence of 20% or more. The highest projected obesity prevalence is predicted for Ireland (43%, 95% CI 28–58). The smallest absolute increase in the projected obesity prevalence from 2015 to 2025 was in Finland (20% by 2025, 95% CI 11–29), Lithuania (24%, 10–38), and the Netherlands (14%, 10–18), each of them with an estimated absolute increase in obesity prevalence of 2% by 2025. Interpretation Despite efforts from governments, the prevalence of obesity in the European region continues to increase, and with it the health and economic burden of its associated diseases. This paints a concerning picture of the future burden of obesity-related NCDs across the region. Greater and continued effort for the implementation of effective preventive policies and interventions is required from governments if they are to halt obesity prevalence in 10 years'. The data presented by this study could be used to assess or set country-specific obesity reduction targets, as well as provide leverage for investment in obesity prevention and monitoring programmes. Funding WHO Regional Office for Europe.

Background The prevalence of morbid obesity is increasing worldwide, with numbers doubling in the past 20 years. Morbid obesity (body-mass index [BMI] ≥40 kg/m 2 ) is associated with a high risk of chronic disease, such as type 2 diabetes, coronary heart disease, stroke, mental illness, and some cancers, and increased all-cause mortality rates. In addition, individuals with morbid obesity have more complex health issues and challenges in the health-care system than do those with a lower BMI. A recent global study reported a prevalence range from less than 0·1% in Chinese women to 23·1% in American women. Morbid obesity accounts for 24–35% of all obesity-related costs, presenting a substantial burden on the economy and health service. We aimed to project trends in morbid obesity to 2035 in adults in England, Scotland, and Wales. Methods Morbid obesity rates for the three countries were obtained from the Health Survey for England (1993–2015) and Welsh Health Survey (2004–14) through the UK data service online resource and from the Scottish Health Survey team directly (2003, 2008–14). Rates were determined for men and women aged 16 and older separately (in 5 year age-groups). A multivariate non-linear regression was fitted to the data to project BMI trends. Building on previous models used by the UK Health Forum, we used BMI prevalence data, with age and sex as covariates. Validation was not done for this study, but has been done in earlier work with the Foresight study. Findings Morbid obesity prevalence is projected to vary from 4% (in Scottish men aged 16–24 years old) to 54% (in English men aged 75 and older) by 2035. England and Wales are projected to have higher rates of morbid obesity in men than in women whereas the opposite is true of Scotland. Of the three countries, Wales is projected to have the highest levels of morbid obesity. Additional work is looking at population data. Interpretation The prevalence of morbid obesity is set to increase to 2035 across England, Scotland, and Wales. This increase will have serious health and financial implications for the health service and population. The next stage will be to run a microsimulation to test the impact of morbid obesity on future disease burden. Funding None.

Background Many chronic diseases are interrelated and their effects under changing exposures need to be better understood. Policy makers and planners need to understand what the current distributions of avoidable chronic disease are, among whom, and how they are likely to develop in the future, particularly their effect on different populations, what will be the health consequences of the extrapolated trends, and how much these consequences can be attenuated with what we currently know and might come to know. Modelling the effects by evidence-based extrapolation, incorporating and attributing the epidemiology of related diseases, can give rise to straightforward estimates of incidence and death rates for the most common related conditions for the next 50 years. This modelling can be done by making basic assumptions about plausible change of risk in disease rates tracking into adulthood using established likelihoods from current trends. These rates in turn are used to compare predicted illness and mortality rates with those that arise from demographic extrapolation from existing current mortality rates. These figures can be used to revise estimates of the healthy working population, by removing death rates and accounting for sickness in a manner that incorporates known and current changes in disease incidence. The model builds on work originally developed for Foresight Tackling Obesities (UK) and subsequent work modelling obesity and related diseases in a further 36 countries. Methods A microsimulation model was used to project future health of each of possibly millions of individuals with a given demography (of any region) through to a given year, and various scenarios were simulated. Competing risks were examined in real simulated time. Related diseases and associated health-care costs were calculated on the basis of trends in risk factors distributed among these individuals. In the case of obesity, 13 diseases were considered. We simulated three hypothetical future scenarios: no reduction and 1% and 5% reductions in body-mass index (BMI). Ultimately, health and other costs incurred or saved can be compared with the costs of intervention. The simulation model was developed in discrete modules to enable radical change and updating of assumptions and parameters. We did not apply any future discounting for this project. Findings Small reductions in risk factors can have substantial effects on future burdens of disease and avoidable health-care costs. In the UK, 1% reduction in BMI rates will save £15·5 billion, whereas in the USA the medical costs will be reduced by US$686 billion. With a 5% reduction in BMI, medical cost savings in the UK will be £61·8 billion and in the USA $1·93 trillion. The figures are substantial for other countries too, reaching $45 million for Russia, $1·8 billion for Mexico, and $4·8 billion for Brazil. All savings will be achieved by 2050. Interpretation This predictive modelling has significant resonance with policy makers. Using sensitivity analysis we can test the outcome of interventions at a national or subnational level over a timescale that is difficult to measure by conventional evaluative methods. Funding GlaxoSmithKline (grant number 27875780), Robert Wood Johnson Foundation (numbers 260639 and 61468 and 66284), Centers for Disease Control and Prevention (U48/DP00064-00S1 and 1U48DP001946).