Beate Landsberg

Associations between active commuting to school, fat mass and lifestyle factors in adolescents: the Kiel Obesity Prevention Study (KOPS)

Objective:To examine possible associations between active commuting (walking or cycling) to school, parameters of adiposity and lifestyle factors in 14-year-old adolescents of the Kiel Obesity Prevention Study.Subjects:A total of 626 14-year-old adolescents.Methods:Measured body mass index (BMI), fat mass (FM), distance to school as well as self-reported modes and duration of commuting to school, time spent in structured and unstructured physical activities (PAs), media use, nutrition, alcohol consumption and smoking.Results:Parameters of adiposity did not differ between different commuting modes after stratifying by gender. Active commuters reported higher overall PA, which was caused by commuting activity and time spent in unstructured PA in girls and just by commuting activity in boys. In active commuters, 28.4% of overall PA was explained by commuting activity. Additionally, TV viewing was lower in active commuters. Compared to their inactively commuting counterparts, actively commuting boys were less likely to smoke. After controlling for potential confounders the interaction term ‘active commuting by distance to school’ and ‘time spent in structured PA’ were independent predictors of FM, whereas active commuting by itself showed no effect.Conclusion: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.

Association of different obesity indices with blood pressure and blood lipids in children and adolescents.

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 > or = 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.

Energy gain and energy gap in normal-weight children: longitudinal data of the KOPS.

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/m2)/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.

Eight-year follow-up of school-based intervention on childhood overweight--the Kiel Obesity Prevention Study.

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.

Determinants of the prevalence and incidence of overweight in children and adolescents

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.

Longitudinal Influences of Neighbourhood Built and Social Environment on Children’s Weight Status

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.

Associations between neighbourhood characteristics, body mass index and health-related behaviours of adolescents in the Kiel Obesity Prevention Study: a multilevel analysis

Background/Objectives:To understand determinants of overweight, several studies addressed the association between neighbourhood characteristics and adult obesity. However, little is known about the association of such characteristics with adolescents’ overweight. This study aims at the influence of neighbourhood characteristics on adolescent body mass index (BMI) and lifestyle and to what extent BMI and lifestyle variation between neighbourhoods can be explained by neighbourhood characteristics.Subjects/Methods:We used cross-sectional data from the Kiel Obesity Prevention Study collected between 2004 and 2008 in 28 different residential districts of the city of Kiel (North Germany). Anthropometric data were available for 1675 boys and 1765 girls (n=3440) aged 13–15 years, and individual lifestyle factors and sociodemographic data were included in the analysis. At the macro level, six different neighbourhood characteristics were used: unemployment rate, population density, traffic density, prevalence of energy-dense food supply, number of sports fields and parks, and crime rate. To test our main hypothesis, linear and logistic multilevel regression analyses were performed to predict BMI and lifestyle factors in individuals nested in neighbourhoods.Results:Findings of multilevel analysis show little between-neighbourhood variations in BMI and health-related behaviours. In all, 2% of BMI variation, 4% of media time variation and 3% of variation in snacking behaviour could be attributed to differences in neighbourhoods.Conclusions:Environmental factors are significantly associated with adolescent BMI and health-related behaviour; however, their total effect is small. Owing to these results, recommendations for structural policy measures as part of prevention of overweight in adolescents must be made cautiously.

Attributable risks for childhood overweight: evidence for limited effectiveness of prevention

OBJECTIVE: Calculation of attributable risks (ARs) of childhood overweight to estimate effectiveness of prevention strategies. METHODS: We used pooled data of 4 population-based German studies including 34 240 children and adolescents aged 3 to 18 years to calculate the impact of familial, social, “early life”, and lifestyle factors on overweight. ARs (joint for all determinants as well as partial risks) were calculated. RESULTS: The prevalence of childhood overweight was 13.4%. Successfully tackling all determinants can reduce overweight by 77.7% (ie, from 13.4% to 3.0%; = joint AR) with partial effects of treating parental overweight (42.5%); improving social status (14.3%); reducing media time to <1 hour per day (11.4%); and not smoking during pregnancy, low weight gain during pregnancy, and breastfeeding (together 9.5%), respectively. Improving all preventable risk factors (ie, early life factors and lifestyle) the effect is 9.2%. Media time has the strongest effect. CONCLUSIONS: The determinants identified explained 78% of the prevalence of overweight. Taking into account the partial ARs, the effectiveness of lifestyle interventions to prevent overweight in children is limited. Our data argue in favor of interventions aimed at families and social environments, with a major focus on promoting a lower screen time and computer use in children.

Assessment of Representativity of a Study Population - Experience of the Kiel Obesity Prevention Study (KOPS)

Objective: Exemplified by data of the Kiel Obesity Prevention Study (KOPS), different methods to control for response bias and to assess representativity were compared. Methods: 4,997 cross-sectional data of 5- to 7-year-old German children (main cohort) were investigated between 1996 and 2001 within school entry examination. A subgroup responded to a questionnaire to socio-demographic and lifestyle factors (responders, n = 2,631). Representativity of the main cohort was tested in comparison to the total population. To control for response bias within the responders a non-response analysis as well as an analysis of missing values were performed. Results: The comparison with the total population showed a higher prevalence of obese boys and girls from families of low socio-economic status (SES) within the main cohort. The responders were less frequently obese and overweight and more rarely belonged to low SES families when compared with non-responders. Analysis of missing values did not detect any further biases. According to an epidemiological assessment of differences the main cohort of KOPS is suggested to be representative for all 5- to 7-year-old children in Kiel, whereas the responders can be at best called ‘relatively’ representative. Conclusion: The analysis of non-response is the most sensitive method to detect group differences, but a comparison with the total population can also be used to control for biases. In addition representativity has to be proven not only for the main cohort but also for the subgroup of responders with which data analysis will be done.

Soziale Ungleichheit, Migrationshintergrund, Lebenswelten und Übergewicht bei Kindern und Jugendlichen

ZusammenfassungZiel der vorliegenden Arbeit war es, Beziehungen zwischen dem Sozialstatus, Migrationshintergrund, Lebensstil, den Lebenswelten und Übergewicht von Kindern zu untersuchen. Bei Sechs- bis 14-Jährigen, die im Rahmen der Kieler Adipositas-Präventionsstudie (KOPS) untersucht wurden, gibt es eine inverse Beziehung zwischen sozialem Status und Übergewicht: Je niedriger der soziale Status, desto häufiger liegt Übergewicht vor (zum Beispiel für Schulbildung der Eltern niedrig/mittel/hoch, %: 18,4/13,6/7,9). Nichtdeutsche sind im Vergleich zu deutschen Kindern doppelt so häufig übergewichtig (20,2% versus 11,7%), auch bei Kindern mit Migrationshintergrund besteht ein sozialer Gradient im Übergewicht (%: 26,0/28,2/17,2). Lebensstile unterscheiden sich zwischen den Sozialgruppen sowie auch zwischen deutschen und nicht-deutschen Kindern gleicher Sozialschichten. Der soziale Gradient beim Übergewicht ist aber anteilig unabhängig vom Lebensstil. Ein hohes Lebensmittelangebot und eine hohe Verkehrsdichte als Charakteristika der Lebenswelten begünstigen das Auftreten von Übergewicht. Direkte Präventionsmaßnahmen müssen die sozialen Determinanten von Übergewicht und besonders auch Migranten adressieren, die Schaffung „gesunder“ Lebenswelten verspricht additive Effekte.AbstractThis study aimed at studying the relationships between different social determinants, overweight, migration background, lifestyle factors, and neighborhood characteristics in children and adolescents aged 6–14 years. Data were collected within the Kiel Obesity Prevention Study (KOPS). The lower the social status, the higher the prevalence of overweight (e.g., parental education low/middle/high,%: 18.4/13.6/7.9). Non-German children are twice as often overweight as German children (20.2% versus 11.7%) with a social gradient in overweight (%: 26.0/28.2/17.2). There are social differences in health-related behavior between the social groups and also between German and non-German children of the same social group. The social gradient in overweight is, in part, independent of lifestyle factors. Neighborhood characteristics like high food supply and traffic density add to the development of overweight. To summarize, overweight is a social issue; direct prevention has to address the social determinants of health as well as families with migration background. In addition, the development of “healthy” neighborhoods may support the prevention of overweight.