The number of chronically ill patients increases every year. This is partly due to an unhealthy lifestyle. However, the frequency and quality of (evidence-based) health promotion activities conducted by Dutch general practitioners (GPs) and practice nurses (PNs) are limited. The aim of this pilot study was to explore which lifestyle interventions Dutch GPs and PNs carry out in primary care, which barriers and facilitators can be identified and what main topics are with respect to attitudes towards health promoting activities. These topic areas will be identified for a future, larger scale study.

To date, many epidemiologic studies examining associations between obesity and dietary and sedentary/physical activity behaviors have focused on assessing Body Mass Index (BMI) at one point in time. Recent developments in statistical techniques make it possible to study the potential heterogeneity in the development of BMI during childhood by identifying distinct subpopulations characterized by distinct developmental trajectories. Using Latent Class Growth (Mixture) Modelling (LCGMM) techniques we aimed to identify BMI trajectories in childhood and to examine associations between these distinct trajectories and dietary, sedentary and physical activity behaviors. This longitudinal study explored BMI standard deviation score (SDS) trajectories in a sample of 613 children from 4 to 12 years of age. In 2006, 2009 and 2012 information on children’s health related behaviors was obtained by parental questionnaires, and children’s height and weight were measured. Associations with behaviors were investigated with logistic regression models. We identified two BMI SDS trajectories; a decreasing BMI SDS trajectory (n = 416; 68 %) and an increasing BMI SDS trajectory (n = 197; 32 %). The increasing BMI SDS trajectory consisted of more participants of lower socio-economic status (SES) and of non-western ethnicity. Maternal overweight status was associated with being in the increasing BMI SDS trajectory at both baseline and follow-up six years later (2006: Odds Ratio (OR), 2.9; 95 % confidence interval (CI) 1.9 to 4.3; 2012 OR, 1.8; 95 % CI 1.2 to 2.6). The increasing BMI SDS trajectory was associated with the following behaviors; drinking sugared drinks > 3 glasses per day, participation in organized sports < 1 h per week, and TV viewing > 2 h per day, though participation in organized sports at follow-up was the only significant result. Our results indicate the importance of healthy lifestyle behaviors at a young age, and indicate that maternal BMI is a very important risk factor for the development of childhood overweight. Comprehension of heterogeneity in the development of BMI and associations with modifiable health related behaviors is interesting for prevention by targeting high risk behaviors in early childhood, especially in low SES children, children of non-western ethnicity and children whose mother is overweight.

Background: Little is known regarding the patterning and socio-demographic distribution of multiple sedentary behaviours in children. The aims of this study were to: 1) describe the leisure-time sedentary behaviour of 9–10 year old British children, and 2) establish associations with objectively-measured sedentary time. Methods: Cross-sectional analysis in the SPEEDY study (Sport, Physical activity and Eating behaviour: Environmental Determinants in Young people) (N=1513, 44.3% boys). Twelve leisure-time sedentary behaviours were assessed by questionnaire. Objectively-measured leisure-time sedentary time (Actigraph GT1M, <100 counts/minute) was assessed over 7 days. Differences by sex and socioeconomic status (SES) in self-reported sedentary behaviours were tested using Kruskal-Wallis tests. The association between objectively-measured sedentary time and the separate sedentary behaviours (continuous (minutes) and categorised into 'none’ 'low’ or 'high’ participation) was assessed using multi-level linear regression. Results: Sex differences were observed for time spent in most sedentary behaviours (all p ≤ 0.02), except computer use. Girls spent more time in combined non-screen sedentary behaviour (median, interquartile range: girls: 770.0 minutes, 390.0-1230.0; boys: 725.0, 365.0 - 1182.5; p = 0.003), whereas boys spent more time in screen-based behaviours (girls: 540.0, 273.0 - 1050.0; boys: 885.0, 502.5 - 1665.0; p < 0.001). Time spent in five non-screen behaviours differed by SES, with higher values in those of higher SES (all p ≤ 0.001). Regression analyses with continuous exposures indicated that reading (β = 0.1, p < 0.001) and watching television (β = 0.04, p < 0.01) were positively associated with objectively-measured sedentary time, whilst playing board games (β = -0.12, p < 0.05) was negatively associated. Analysed in categorical form, sitting and talking (vs. none: 'low’ β = 26.1,ns; 'high’ 30.9, p < 0.05), playing video games (vs. none: 'low’ β = 49.1, p < 0.01; 'high’ 60.2, p < 0.01) and watching television (vs. lowest tertile: middle β = 22.2,ns; highest β = 31.9, p < 0.05) were positively associated with objectively-measured sedentary time whereas talking on the phone (vs. none: 'low’ β = -38.5, p < 0.01; 'high’ -60.2, p < 0.01) and using a computer/internet (vs. none: 'low’ β = -30.7, p < 0.05; 'high’ -4.2,ns) were negatively associated. Conclusions: Boys and girls and children of different socioeconomic backgrounds engage in different leisure-time sedentary behaviours. Whilst a number of behaviours may be predictive of total sedentary time, collectively they explain little overall variance. Future studies should consider a wide range of sedentary behaviours and incorporate objective measures to quantify sedentary time where possible.

To date, population based surveys aimed at gaining insight in health related behaviour of children have often used either child self-reports or parent proxy reports. It remains unclear however, if surveys using different sources of information from either parents or children are comparable. In addition, (over)weight status of children can lead to under- and over reporting by parents and children as a result of social desirability bias. We aimed at gaining insight in the level of agreement between parents and child reports regarding aspects of certain dietary, physical activity and sedentary behaviours, and whether there are differences in agreement between parents and child reports in healthy-weight and overweight children. Weighted kappa was used to determine the level of agreement between child and parent reports on health-related behaviour in 1998 parent-child dyads. We also stratified for weight status of the children. Information on children’s health related behaviours was obtained by parental and children’s questionnaires, and children’s height and weight were measured. Associations between children’s weight status and children reporting less, reporting more and reporting the same amount of health behaviour as their parents were investigated with multinomial logistic regression analysis. The Cohen’s kappa coefficients ranged from almost perfect agreement for the variable means of transportation, fair for the variables breakfast consumption and frequency of outside play to slight for the variables duration of outside play, frequency and duration of TV/DVD viewing and family dinner. Overweight children were significantly more likely to report less breakfast consumption (OR = 2.6 (95% CI: 1.3 – 5.1)) and lower frequency of outside play than their parents (OR = 1.8 (95% CI: 1.1 – 2.9)). There can be considerable disagreement between the health related behaviours of children as reported by parents or the children themselves. Based on the present study, it cannot be concluded whether parents’ or children’s reports are more accurate. For future studies, social desirability and recall bias would be best demonstrated in a validation study comparing child and parent self-reports with more objective measures of physical activity and food intake.

One might expect that a perception of obesity being a risk factor and disease, contributes to effective obesity prevention and management strategies. However, obesity rates continue to increase worldwide. The question arises whether obesity is truly perceived as a risk factor and a disease. This paper aims at describing perception of obesity as risk factor and disease among individuals seeking care, individuals not seeking care, the society, and different professionals having a role in the field of obesity. The paper is a reflection of the lecture on the topic that was given at the EASO's New Investigators United's Summer School 2016 in Portugal and the discussion with the new investigators and other senior speakers. Individual obese patients seeking help are very much aware of obesity being a risk factor and disease, but perceptions regarding obesity seem to be flawed among those who do not seek help for obesity. Also, misperceptions regarding obesity play a role at different levels, including society, different political levels, the fields of health care and social work, prevention organizations, and the food and marketing industry. The food and marketing industry has an enormous role in changing perceptions by the society and policy makers. Obesity rates will continue to increase as long as individuals, the society, and professionals at different levels have false interpretations of the severity of obesity. Severe action is needed against those who are playing a role in maintaining false perceptions of obesity as a risk factor and disease.

Objective: This study aims at assessing the status of obesity management in the European region and identifying future goals and objectives of professionals working in the field of obesity. Methods: Presidents of all 31 EASO-affiliated (EASO = European Association for the Study of Obesity) national associations for the study of obesity were asked to invite 5 obesity experts from their country to participate in a survey. A total of 74 obesity professionals out of 23 countries participated. Questions addressed the development of guidelines, the status of obesity management, and goals and objectives for the future in obesity management. Further, EASO's three vice-presidents participated in in-depth, semi-structured interviews, in which they were asked to provide their reflection on the survey data. Results: Most countries define obesity as a clinical and chronic disease, but various differences in obesity management standards exist across Europe. Existing guidelines mainly focus on the acute treatment of obesity rather than on long-term approaches. Conclusion: Multidisciplinary approaches for obesity management and the collaboration between general practitioners and hospitals as well as between professionals at the local level and networks of obesity management centers need to be improved across Europe. Good practices and evidence are available.