The present data suggest that active commuting to school per se does not affect FM or BMI until considering distance to school. Increasing walking or cycling distance results in decreasing FM. However, the everyday need to get to and from school may enhance adolescents' overall PA.

Objective: To identify lifestyle clusters in adolescents and to characterize their association with overweight and obesity. Design: Cross-sectional and longitudinal data of the Kiel Obesity Prevention Study. Setting: Schools in Kiel, Germany. Subjects and methods: Cross-sectional data of 1894 adolescents aged 14 years and 4-year longitudinal data of a subsample of 389 children aged 10 and 14 years. Selfreported data of physical activity, modes of commuting to school, media time, nutrition, alcohol consumption and smoking were used to identify lifestyle clusters with two-step cluster analysis. Obesity indices (height, weight, waist circumference and fat mass (FM)) were measured. Results: Three lifestyle clusters were identified: a 'low activity and low-risk behaviour' cluster (cluster 1: n 740, 39?1 %); a 'high media time and high-risk behaviour' cluster (cluster 2: n 498, 26?3 %); and a 'high activity and medium-risk behaviour' cluster (cluster 3: n 656, 34?6 %). Strictly speaking, none of these clusters was considered to be markedly healthy. The prevalence of overweight and obesity tended to be lower in cluster 3 (15?9 %) than in clusters 1 (20?4 %) and 2 (20?5 %; P 5 0?053). Longitudinally, 4-year changes in FM were found to be lowest in cluster 2, but the 4-year incidence rate of obesity was lowest in cluster 3. Conclusions: Explicit healthy lifestyles do not exist, but an active lifestyle reduces the incidence of obesity. In adolescents, health promotion should take into account the diversity of lifestyles and address specific lifestyle clusters.

Objective: The aim of this study was to evaluate the 8-year outcome of school-based intervention on weight status, lifestyle and blood pressure (BP) as part of the Kiel Obesity Prevention Study (KOPS). Methods: Within a quasi-randomized controlled trial, 240 intervention (I) and 952 non-intervention (NI) students at age 6 and 14 years were assessed in schools. Six nutrition units followed by 20-min running games were performed within the first year at school. Primary outcome was the 8-year change in body mass index standard deviation score (BMI-SDS) according to German references. Effective intervention was tested using multilevel linear regression analysis. Results: Eight-year changes in BMISDS were +0.18 and +0.22 with increases in prevalence of overweight from 8.3 to 10.4% and 7.0 to 11.2% in I and NI students, respectively. Cumulative 8-year incidence of overweight was 5.9% and 7.1% in I and NI students, respectively. There was no overall effect of intervention, but a significant interaction was shown between the intervention and the socio-economic status (SES), which demonstrated that in high SES, the 8-year change in BMI-SDS was in favour of I (–0.17 in I and +0.17 in NI; p < 0.01). Intervention had no measurable effects on lifestyle and BP. Conclusions: School-based health promotion has some favourable and sustained effects on 8-year changes in BMI-SDS, which are most pronounced in students of high SES families. The data argue in favour of further preventive measures.

AIMS:Prevention of obesity is a public health agenda. There are only few longitudinal studies on prevention of overweight in children. The Kiel Obesity Prevention Study (KOPS) intends to characterise the determinants of childhood overweight and the effect of preventive measures within schools as well as within families. METHODS: Between 1996 and 2005, KOPS investigated 4997 German 5-7 and 4487 9-11-y-old children or 41 and 37% of the total population of all first and fourth graders in 32 primary schools in Kiel (248 000 inhabitants), northwest Germany. Main outcome measures were nutritional status, health habits and risk factors of disease. In addition, health promotion was performed each year in three schools for all first graders and their teachers (nutrition education and active school breaks) together with a family-oriented approach in families with obese and preobese children. Up to now, the children were followed for 4 y and were reinvestigated at age 10 y. RESULTS: The KOPS population was representative for all 5-7 and 9-11-y-old children in Kiel. The prevalence of overweight/ obesity (Z90th/97th BMI reference percentile) was 7.0/5.8 and 11.3/6.3% in 5-7 and 9-11-y-old children, respectively. Parental overweight, a low socio-economic status and a high birth weight were identified as main risk factors for overweight in prepubertal children. The first results of the interventions show that obesity prevention was possible, but there were limited success rates in boys and children from low social class. CONCLUSION: Faced with the environmental contributors to the obesity problem societal rather than individual responsibilities are evident. This idea suggests that dissecting and tackling the obesogenic environment is necessary to complement school-and family-based interventions.

The objective was to examine longitudinal 4-year-relationships between neighbourhood social environment and children’s body mass index-standard deviation score (BMI-SDS) taking into account the built environment. Furthermore, we have analysed the influence of potential interactions between the social environment and family/social data on children’s BMI-SDS. Between 2006–2008 and 2010–2012, anthropometric measurements were conducted among 485 children (age at baseline: 6.1 (5.8–6.4)). Socio-demographic characteristics and perception of residential environment were reported by parents. Geographic Information Systems were used to examine street length, number of food outlets and distance to the nearest playground and park/green space within an 800 m Euclidian buffer of each participant address point. Additional data on neighbourhood characteristics (e.g., traffic density, walkability, crime rates) were obtained from the State Capital of Kiel, Germany. In a multivariate model, walkability, street type, socioeconomic status of the district and perceived frequency of passing trucks/busses were associated with BMI-SDS over 4 years, but only neighbourhood SES had an effect on change in BMI-SDS. However, familial/social factors rather than neighbourhood environment (especially social environment) had an impact on children’s BMI-SDS over 4 years. Thus, social inequalities in childhood overweight are only partially explained by social neighbourhood environment.

Objective: To systematically analyse determinants of overweight prevalence and incidence in children and adolescents, as a basis of treatment and prevention. Design: Cross-sectional and longitudinal data of the Kiel Obesity Prevention Study (KOPS). Setting: Schools in Kiel, Germany. Subjects: Cross-sectional data from 6249 students aged 5-16 years and 4-year longitudinal data from 1087 children aged 5-11 years. Weight status of students was assessed and familial factors (weight status of parents and siblings, smoking habits), social factors (socio-economic status, nationality, single parenting), birth weight as well as lifestyle variables (physical activity, media time, nutrition) were considered as independent variables in multivariate logistic regression analyses to predict the likelihood of the student being overweight. Results: The cross-sectional data revealed the prevalence of overweight as 18?3 % in boys and 19?2 % in girls. In both sexes determinants of overweight prevalence were overweight and obese parents, overweight siblings, parental smoking, single parenthood and non-German nationality. High birth weight and low physical activity additionally increased the risk in boys. High media time and low parental education were significant determinants in girls. Effect of media time was mediated by maternal weight status in boys as well as by socio-economic status and age in girls. From the longitudinal data, the 4-year cumulative incidence of overweight was 10?0 % in boys and 8?2 % in girls. Parental obesity, parental smoking and low physical activity were determinants of overweight incidence in boys, whereas paternal obesity increased the risk in girls.Conclusions: Treatment and prevention should address family and social determinants with a focus on physical activity and media use.Childhood obesity is a major public health challenge. At present there is a lack of convincing evidence about suitable and effective strategies for the prevention of childhood overweight. Recently, an obesity prevention evidence framework has been proposed (1) . Key policies include: (i) building a case for action on obesity; (ii) identifying contributing factors and points of intervention; (iii) defining opportunities for action; (iv) evaluating potential interventions; and (v) selecting a portfolio of specific policies, programmes and actions. Therefore, a systematic analysis of determinants of overweight in the micro-as well as the macro-environment is necessary to provide a sound basis for developing strategies against overweight. The systematic analysis should include an analysis of the determinants of overweight prevalence as well as overweight incidence, separately. Childhood overweight (and not only obesity) is predictive for adult morbidity and mortality (2) . In addition, the life-long persistence and health consequences of overweight and obesity in many children suggest a strong need for the prevention of overweight (2) . Primary prevention strategies address the whole population, in particular normalweight sub...

The aim of the present study was to compare individual associations of BMI, triceps skinfold (TSF), waist circumference (WC) and percentage fat mass (%FM) with blood pressure (BP) and blood lipids in children and adolescents. Cross-sectional data on BMI, TSF, WC, %FM as well as on BP, TAG and HDL were analysed in 4220 (BP) and 729 (lipids) 9 -11-year-old children and 3174 (BP) and 536 (lipids) 13 -16-year-old adolescents as part of the Kiel Obesity Prevention Study. All obesity indices were similarly associated with BP and blood lipids. In girls, WC had closer correlations to BP than BMI (systolic BP: 0·27 and 0·24 for BMI, 0·34 and 0·28 for WC in 9 -11-and 13 -16-year-olds). Subjects with an obesity index $ 90th percentile had higher prevalences of elevated BP and blood lipids than subjects with a normal index. In children with normal BMI or WC, an additionally elevated second obesity index was associated with a 2·5 -7·4-fold higher prevalence of high BP when compared with children with normal indices. In adolescents, an elevated WC plus an elevated second obesity index was associated with a 2·6 -8·2-fold higher prevalence of high BP when compared with adolescents with an elevated WC plus a normal second index. We conclude that (i) both BMI and WC are appropriate to estimate CVD risk, (ii) the use of a second obesity index is recommended in children with normal BMI or normal WC as well as in adolescents with elevated WC and (iii) all obesity indices seemed to be appropriate for risk assessment. Overweight: Children: Blood lipids: Cardiovascular disease risk factorsChildhood overweight is a public health problem. Defining overweight in children and adolescents is not uniform with respect to obesity indices and cut-offs used. BMI is widely used as a measure of fat mass (FM) and international BMI reference values for children and adolescents have been published (1) . However, BMI is only an indirect parameter of total body fat and does not reflect body fat distribution (2,3) . In addition, the association between BMI and disease risk is unproven in children and adolescents. In adults, BMI cutoffs for overweight and obesity were defined according to overweight-and obesity-associated co-morbidity (4) . However, in children prospective data on the association between obesity indices and disease risk are rare; for example, longitudinal data of the Bogalusa Heart Study showed a relationship between childhood obesity and incidence of metabolic disorders in young adulthood (5) . The International Obesity Taskforce Working Group recommended that BMI cut-offs for defining overweight and obesity in children should be linked to the adult disease-related cut-off points of 25 and 30 kg/m 2(1) . In addition to BMI, triceps skinfold thickness (TSF), waist circumference (WC) and percentage FM (%FM) as derived from bioelectrical impedance analysis have been recommended to identify individuals with increased overweight-associated disease risks (3) . However, the use of these obesity indices is limited because of methodological aspe...

Population-based prevention of overweight needs evidence-based goals consistent with our present knowledge about energy gap (i.e., daily imbalance between energy intake and energy expenditure resulting in overweight). Longitudinal data of normal-weight children (1,029 girls and 1,028 boys; Kiel Obesity Prevention Study, KOPS) were used to calculate energy gain (i.e., increase in fat mass (FM) and fat-free mass (FFM)) in normal-weight children staying normal weight (persistent children) or becoming overweight (incident children). Taking into account weight gain in proportion to height gain (normal development) energy gap was calculated from increases in FM and FFM exceeding normal development. Children were divided into two groups and were followed from age 6 to 10 (group A) and 10 to 14 years (group B). FM and FFM were measured. Medians of 4-year BMI-(kg/m 2 )/weight changes (kg) were +1.8/+13.2 (A) and +3.0/+18.7 (B) in girls, and +1.6/+12.8 (A) and +2.6/21.7 (B) in boys. Corresponding data for FM/FFM (kg) were +3.1/+10.2 (A) and +5.1/12.7 (B) in girls, and +2.3/10.8 (A) and +3.0/18.6 (B) in boys. The 4-year-incidence of overweight (%) were 9.4 (A) and 5.4 (B) in girls, and 11.0 (A) and 3.8 (B) in boys, respectively. Mean energy gains (kcal/day) were 26.8 (A) and 46.4 (B) in girls, and 22.1 (A) and 32.5 (B) in boys. The 90th percentile of energy gap (kcal/day) in incident children were 58.1 (A) and 72.0 (B) in girls and 46.0 (A) and 53.2 (B) in boys. To prevent overweight in children energy gap should not exceed 46-72 kcal/day.