Potential determinants of obesity among children and adolescents in Germany: results from the cross-sectional KiGGS study

<p>Abstract</p> <p>Background</p> <p>Obesity among children and adolescents is a growing public health problem. The aim of the present paper is to identify potential determinants of obesity and risk groups among 3- to 17-year old children and adolescents to provide a basis for effective prevention strategies.</p> <p>Methods</p> <p>Data were collected in the German Health Interview and Examination Survey for Children and Adolescents (KiGGS), a nationally representative and comprehensive data set on health behaviour and health status of German children and adolescents. Body height and weight were measured and body mass index (BMI) was classified according to IOTF cut-off points. Statistical analyses were conducted on 13,450 non-underweight children and adolescents aged 3 to 17 years. The association between overweight, obesity and several potential determinants was analysed for this group as well as for three socio-economic status (SES) groups. A multiple logistic regression model with obesity as the dependent variable was also calculated.</p> <p>Results</p> <p>The strongest association with obesity was observed for parental overweight and for low SES. Furthermore, a positive association with both overweight (including obesity) and obesity was seen for maternal smoking during pregnancy, high weight gain during pregnancy (only for mothers of normal weight), high birth weight, and high media consumption. In addition, high intakes of meat and sausages, total beverages, water and tea, total food and beverages, as well as energy-providing food and beverages were significantly associated with overweight as well as with obesity. Long sleep time was negatively associated with obesity among 3- to 10-year olds. Determinants of obesity occurred more often among children and adolescents with low SES.</p> <p>Conclusion</p> <p>Parental overweight and a low SES are major potential determinants of obesity. Families with these characteristics should be focused on in obesity prevention.</p

Do the effects of interventions aimed at the prevention of childhood obesity reduce inequities? A re-analysis of randomized trial data from two Cochrane reviews

Background Public health attempts to prevent obesity in children and young people should aim to minimize health inequalities. Two Cochrane reviews examining interventions aiming to prevent childhood obesity found that interventions promoting (only) physical activity have a small beneficial effect on BMI for people aged 5–18 years, as do interventions promoting physical activity alongside healthy eating for 5–11 year olds. We examined whether the effectiveness of the interventions included in these reviews differed according to eight factors associated with inequity: place, race/ethnicity, occupation, gender/sex, religion, education, socio-economic status, and social capital (the PROGRESS framework). Methods We collected data on change in BMI (standardized or unstandardized), subgrouped by baseline measures of PROGRESS factors, for intervention and control groups, from trial authors. We calculated the intervention effect per subgroup (mean difference), then contrasted these to estimate interactions between intervention and the baseline factors. We combined interaction estimates for each factor across trials using meta-analyses. Findings We collected subgrouped data from 81 trials that took place between 2001 and 2020, involving 84,713 participants. We found no substantial differences in effectiveness of interventions for PROGRESS subgroups in most scenarios. However, in the younger age group (5–11 years), the effect of interventions on standardized BMI appeared to be higher in boys (average difference in mean differences 0.03; 95% CI 0.01 to 0.06; 45 studies, n = 44,740), which was consistent in direction with the BMI effect (average difference in mean differences 0.06 kg/m2; 95% CI −0.02 to 0.13; 31 studies, n = 27,083). Interpretation Our findings suggest that those responsible for public health can promote these beneficial interventions without major concerns about increasing inequalities but should be mindful that these interventions may work better in boys aged 5–11 years than girls. More data are needed, so we encourage future trialists to perform subgroup analyses on PROGRESS factors

Combined effects of weight loss and physical activity on all-cause mortality of overweight men and women

To estimate the excess deaths associated with weight loss in combination with leisure time physical activity among overweight or obese people

Abdominal and gynoid adiposity and the risk of stroke

Background: Previous studies have indicated that fat distribution is important in the development of cardiovascular disease (CVD). We investigated the association between fat distribution, as measured by dual energy X-ray absorptiometry (DXA), and the incidence of stroke. Methods: A cohort of 2751 men and women aged >= 40 years was recruited. Baseline levels of abdominal, gynoid and total body fat were measured by DXA. Body mass index (BMI, kg m(-2)) was calculated. Stroke incidence was recorded using the regional stroke registry until subjects reached 75 years of age. Results: During a mean follow-up time of 8 years and 9 months, 91 strokes occurred. Of the adiposity indices accessed abdominal fat mass was the best predictor of stroke in women (hazard ratio (HR) = 1.66, 95% confidence interval (CI) = 1.23-2.24 per standard deviation increase), whereas the ratio of gynoid fat to total fat mass was associated with a decreased risk of stroke (HR = 0.72, 95% CI = 0.54-0.96). Abdominal fat mass was the only of the adiposity indices assessed that was found to be a significant predictor of stroke in men (HR = 1.49, 95% CI = 1.06-2.09). The associations between abdominal fat mass and stroke remained significant in both women and men after adjustment for BMI (HR = 1.80, 95% CI = 1.06-3.07; HR = 1.71, 95% CI = 1.13-2.59, respectively). However, in a subgroup analyses abdominal fat was not a significant predictor after further adjustment for diabetes, smoking and hypertension. Conclusion: Abdominal fat mass is a risk factor for stroke independent of BMI, but not independent of diabetes, smoking and hypertension. This indicates that the excess in stroke risk associated with abdominal fat mass is at least partially mediated through traditional stroke risk factors. International Journal of Obesity (2011) 35, 1427-1432; doi: 10.1038/ijo.2011.9; published online 22 February 201

Ability of biolectric impedance to predict fat-free mass in prepubertal children

Measurements of body composition are being made increasingly widely in pediatrics. Tetrapolar whole body impedance (BI) is particularly suitable as a method of estimating boyd composition in children and is therefore the subject of great interest at present. However, the ability of BI to accurately estimate fat-free mass (FFM) in children is unclear, and users of BI are faced with a growing choice of prediction equations for estimation of FFM. Studies in adults have suggested that choice of prediction equation can have a profound effect on the estimate obtained. The aim of the present study was to measure the ability of four published pediatric BI equations to predict FFM in 98 Caucasian prepubertal children (mean age 9.0 y). For three of the published equations, limits of agreement between predicted and reference FFM were wide and distinct biases were apparent. With mean FFM of 25 kg, the equation of L. Cordain et al. overestimated reference FFM (95% CI +2.1 to +3.1 kg), whereas those of P. Deurenberg et al. (95% CI -1.9 to -2.9 kg) and F. Schaefer et al. (95% CI -1.4 to -2.5 kg) systematically underestimated reference FFM. The equation of Houtkooper et al. (95% CI -0.2 to +0.8 kg) predicted FFM with negligible bias and had narrower limits of agreement relative to the reference method than the other three equations tested. We conclude that the ability of BI to predict body composition in children depends on the equation chosen and that the general applicability of BI equations cannot be safely assumed. Cross-validation of BI equations is recommended before they are used routinely for estimation of body composition in children

Lean body mass: the development and validation of prediction equations in healthy adults

Background: There is a loss of lean body mass (LBM) with increasing age. A low LBM has been associated with increased adverse effects from prescribed medications such as chemotherapy. Accurate assessment of LBM may allow for more accurate drug prescribing. The aims of this study were to develop new prediction equations (PEs) for LBM with anthropometric and biochemical variables from a development cohort and then validate the best performing PEs in validation cohorts