Relationship between submaximal oxygen uptake, detailed body composition, and resting energy expenditure in overweight subjects.

OBJECTIVE: We investigated the impact of detailed body composition on aerobic fitness to determine whether regional components of fat mass have independent effects on VO2submax , and whether VO2submax and detailed body composition independently explain variation in REE. METHODS: 71 healthy adults (80% female, 20% male, BMI 28.2-43.8 kg/m(2) ) were investigated. Body composition was measured by the four-compartment model together with whole body magnetic resonance imaging (MRI) to assess high and low metabolic rate organs and regional fat depots. VO2submax was estimated at 75% of predicted maximum heart rate. RESULTS: There was a strong association between VO2submax and FFM and all organ masses except for heart. Skeletal muscle mass accounted for 34.8% of the variance in VO2submax . In addition, subcutaneous adipose tissue (SAT) of extremities explained additional 14.4%. FFM and FM explained 71.3% of the variance in REE. Including the components of FFM and FM, the explained variance in REE increased by about 5.8%; skeletal muscle mass explained 70.0% of the variance in REE and kidney and liver masses explained additional 7.1%. VO2submax correlated with REE. Taking into account body composition, VO2submax did not add to the variance in REE. CONCLUSION: FFM is a determinant of both VO2submax and REE. Modeling either REE or VO2submax from individual components of FFM, about 77.1% of variance in REE (by muscle, liver and kidneys mass) and 34.8% of variance in VO2submax (by skeletal muscle mass) could be explained. FM explained additional variance in REE, whereas SAT of extremities added to the variance in VO2submax only.

"läuft."--a school-based multi-component program to establish a physically active lifestyle in adolescence: study protocol for a cluster-randomized controlled trial.

BACKGROUND: Physical activity during childhood and adolescence is associated with substantial health benefits and tracks into adulthood. Nevertheless, only 22.7% of German adolescents are sufficiently physically active. Thus, the promotion of an active lifestyle in youth is an essential issue of public health.This study will evaluate the implementation and efficacy of the "läuft." program to enhance physical activity in adolescence. "läuft." is a multicomponent school-based program developed on the basis of effective strategies for health interventions and behavioral change. METHODS/DESIGN: The "läuft." physical activity program targets four different levels. (a) Each student receives a pedometer and documents his/her steps over 12 weeks using an interactive user account on the "läuft." homepage. (b) For classes there will be different competitions, with achieving the most steps in selected weeks, the highest increases of steps and developing the most inventive ideas to promote physical activity in school. Besides, the intervention includes four educational lessons. (c) The headmasters and teaching staff of the participating schools will get information material with suggestions and encouragement to enhance physical activity in school. Participating teachers will be invited to an introductory seminar. (d) Parents will be provided with informational material about the program and will be invited to a parent-teacher conference about the benefits of being physically active and how they can support their children in engaging in a physically active lifestyle.To evaluate the efficacy of the "läuft." physical activity program, a two-arm cluster randomized controlled trial will be conducted in three waves: (1) baseline assessment, January/February 2014, (2) post assessment, June/July 2014 and (3) 12-month follow-up assessment, June/July 2015. Data collection will include physical and medical testing, self-administered questionnaires, group discussions and document analyses. DISCUSSION: "läuft." aims at fostering a physically active lifestyle in adolescence while a considerable decline of physical activity is present. Physical activity programs based in the school setting and following a multicomponent approach have been proven to be most successful. Furthermore, the use of pedometers is promising to enhance physical activity during the entire day and targets a wide range of adolescents regarding fitness and weight. TRIAL REGISTRATION: Current Controlled Trials ISRCTN49482118.

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/buses 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.

Carbohydrate quality and quantity affect glucose and lipid metabolism during weight regain in healthy men.

In this controlled, parallel-group feeding trial, we examined the impact of carbohydrate (CHO) intake and glycemic index (GI) on glucose and lipid metabolism during refeeding after weight loss. Healthy men (n = 32 total, age: 25.5 ± 3.9 y, BMI: 23.5 ± 2.0 kg/m2) overconsumed diets containing either 50% or 65% CHO for 1 wk (+50% of energy requirements) and then underwent 3 wk of calorie restriction (CR; -50%) followed by 2 wk of overconsuming (refeeding, +50%) the same diet but with either a low or high GI (40 vs.70 during CR, 41 vs.74 during refeeding) so that glycemic load (GL; dietary CHO content x GI) differed between groups during all phases. Glucose profiles were assessed by continuous interstitial glucose monitoring, insulin sensitivity (IS) by fasting blood sampling, oral glucose tolerance test (OGTT) and hyperinsulinemic-euglycemic clamp, and liver fat by MRI. Daytime area under the curve-glucose during refeeding was higher with high compared with low GI (P = 0.01) and 65% compared with 50% CHO intake (P = 0.05) and correlated with dietary GL (r = 0.71; P < 0.001). IS increased with CR and decreased again with refeeding in all groups. The decrease in OGTT-derived IS was greater with high- than with low-GI diets (-41 vs. -15%; P-interaction = 0.01) and correlated with dietary GL during refeeding (r = -0.51; P < 0.01). Serum triglycerides (TGs) and liver fat also improved with CR (-17 ± 38 mg/dL and -1.1 ± 1.3%; P < 0.05 and <0.001) and increased again with refeeding (+48 ± 48 mg/dL and +2.2 ± 1.6%; P < 0.001). After refeeding, serum TGs and liver fat were elevated above baseline values with 65% CHO intake only (+59.9 ± 37.5 mg/dL and +1.1 ± 1.7%, P-interaction <0.001 and <0.05). In conclusion, a diet low in GI and moderate in CHO content (i.e., low GL) may have health benefits by positively affecting daylong glycemia, IS, and liver fat.

Clustering of lifestyle factors and association with overweight in adolescents of the Kiel Obesity Prevention Study.

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. Self-reported 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 = 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.

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.

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/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.

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.