Risikofaktoren für grobmotorische Defizite bei Vorschulkindern

In der Literatur wird eine Verschlechterung grobmotorischer Fähigkeiten bei Kindern beschrieben, die mit verschiedenen Erkrankungen im Erwachsenenalter assoziiert sind. Daher sollen Risikofaktoren für ein motorisches Defizit im Einschulungsalter identifiziert werden, die einer möglichen Prävention zugänglich gemacht werden können. Daten von 205 Kindern im Alter von 5 und 6 Jahren wurden im Rahmen der Schuleingangsuntersuchung 2004/05 in München erhoben. Bestandteil der Studie war der Motoriktest "Seitliches Hin- und Herspringen". Potentielle Einflussgrößen wurden einem Elternfragebogen sowie Daten über die körperliche Aktivität der Kinder gemessen mit dem Akzelerometer entnommen. Verglichen mit den Normtabellen der Universität Karlsruhe zeigten 75% der Münchener Kinder grobmotorische Auffälligkeiten. Als einer Primärprävention zugänglichen Risikofaktoren wurden Rauchen in der Schwangerschaft, hoher Medienkonsum sowie seltenes Ball und Fangen spielen identifiziert. Diese gehen mit einer Leistungsminderung von 8 bis 15% einher. Die Messung mit dem Akzelerometer zeigte keine Assoziation zwischen der körperlichen Aktivität und der grobmotorischen Leistung der Kinder

No temporal association between influenza outbreaks and invasive pneumococcal infections

Objective: To assess whether the influenza peak in populations precedes the annual peak for invasive pneumococcal infections (IPI) in winter.Design: Ecological study. Active surveillance data on influenza A and IPI in children up to 16 years of age collected from 1997 to 2003 were analysed.Setting: Paediatric hospitals in Germany.Patients: Children under 16 years of age.Results: In all years under study, the influenza A season did not appear to affect the IPI season (p = 0.49). Specifically, the influenza peak never preceded the IPI peak.Conclusion: On a population level there was no indication that the annual influenza epidemic triggered the winter increase in the IPI rate or the peak of the IPI distribution in children

Risk factors for childhood obesity: shift of the entire BMI distribution vs. shift of the upper tail only in a cross sectional study

Background: Previous studies reported an increase of upper body mass index (BMI) quantiles for formula fed infants compared to breastfed infants, while corresponding mean differences were low. The aim of this study was to assess the impact of known risk factors for childhood obesity on the BMI distribution. Methods: Data on 4,884 children were obtained at obligatory school entry health examinations in Bavaria (Germany). Exposure variables were formula feeding, maternal smoking in pregnancy, excessive TV-watching, low meal frequency, poor parental education, maternal overweight and high infant weight gain. Cumulative BMI distributions and Tukey mean-difference plots were used to assess possible shifts of BMI distributions by exposure. Results: Maternal overweight and high infant weight gain shifted the entire BMI-distribution with an accentuation on upper quantiles to higher BMI values. In contrast, parental education, formula feeding, high TV consumption, low meal frequency and maternal smoking in pregnancy resulted in a shift of upper quantiles only. Conclusion: The single shifts among upper parts of the BMI distribution might be due to effect modification of the corresponding exposures by another environmental exposure or genetic predisposition. Affected individuals might represent a susceptible subpopulation of the exposed

Maternal smoking during pregnancy and appetite control in offspring

Aims: Intrauterine exposure to tobacco smoke products has been associated with long-term neurobehavioral effects. Modified appetite control might explain the recently observed association between maternal smoking during pregnancy and obesity in offspring. Methods: Some 10,557 British adults aged 42 years born between 3-9 March 1958 were followed up in a birth cohort study (NCDS). The main outcome measure was self-reported poor appetite at age 42 years and main exposure was maternal smoking during pregnancy. Results: The proportion of offspring with poor appetite increased with maternal smoking during pregnancy: nonsmoking 4.5%; (4.0% - 5.0%), medium smoking 5.6%; (4.5 % - 6.8 %), variable smoking 6.8 %; (4.9 % - 9.1 %) and heavy smoking 7.7 %; (6.3 % - 9.4 %). The unadjusted odds ratios for maternal smoking during pregnancy (ever/never) and poor appetite is 1.49 (1.25 - 1.77) and after adjustment for BMI at 42 years and other potential confounding factors it is 1.22 (1.07 - 1.48). Conclusions: Offspring of mothers who smoked during pregnancy were more likely to report a poor appetite independent of a number of potential confounding factors. Although not in the expected direction, the results suggest maternal smoking during pregnancy may influence appetite perception through a developmental influence or through confounding by social factors

Alternative regression models to assess increase in childhood BMI

<p>Abstract</p> <p>Background</p> <p>Body mass index (BMI) data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations.</p> <p>Methods</p> <p>Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs), quantile regression and Generalized Additive Models for Location, Scale and Shape (GAMLSS). We analyzed data of 4967 children participating in the school entry health examination in Bavaria, Germany, from 2001 to 2002. TV watching, meal frequency, breastfeeding, smoking in pregnancy, maternal obesity, parental social class and weight gain in the first 2 years of life were considered as risk factors for obesity.</p> <p>Results</p> <p>GAMLSS showed a much better fit regarding the estimation of risk factors effects on transformed and untransformed BMI data than common GLMs with respect to the generalized Akaike information criterion. In comparison with GAMLSS, quantile regression allowed for additional interpretation of prespecified distribution quantiles, such as quantiles referring to overweight or obesity. The variables TV watching, maternal BMI and weight gain in the first 2 years were directly, and meal frequency was inversely significantly associated with body composition in any model type examined. In contrast, smoking in pregnancy was not directly, and breastfeeding and parental social class were not inversely significantly associated with body composition in GLM models, but in GAMLSS and partly in quantile regression models. Risk factor specific BMI percentile curves could be estimated from GAMLSS and quantile regression models.</p> <p>Conclusion</p> <p>GAMLSS and quantile regression seem to be more appropriate than common GLMs for risk factor modeling of BMI data.</p

An illustration of and programs estimating attributable fractions in large scale surveys considering multiple risk factors

Background: Attributable fractions (AF) assess the proportion of cases in a population attributable to certain risk factors but are infrequently reported and mostly calculated without considering potential confounders. While logistic regression for adjusted individual estimates of odds ratios (OR) is widely used, similar approaches for AFs are rarely applied. Methods: Different methods for calculating adjusted AFs to risk factors of cardiovascular disease (CVD) were applied using data from the National Health and Nutrition Examination Survey (NHANES). We compared AFs from the unadjusted approach using Levin's formula, from Levin's formula using adjusted OR estimates, from logistic regression according to Bruzzi's approach, from logistic regression with sequential removal of risk factors ('sequential AF') and from logistic regression with all possible removal sequences and subsequent averaging ('average AF'). Results: AFs following the unadjusted and adjusted (using adjusted ORs) Levin's approach yielded clearly higher estimates with a total sum of more than 100% compared to adjusted approaches with sums < 100%. Since AFs from logistic regression were related to the removal sequence of risk factors, all possible sequences were considered and estimates were averaged. These average AFs yielded plausible estimates of the population impact of considered risk factors on CVD with a total sum of 90%. The average AFs for total and HDL cholesterol levels were 17%, for hypertension 16%, for smoking 11%, and for diabetes 5%. Conclusion: Average AFs provide plausible estimates of population attributable risks and should therefore be reported at least to supplement unadjusted estimates. We provide functions/macros for commonly used statistical programs to encourage other researchers to calculate and report average AFs

Over-indebtedness as a marker of socioeconomic status and its association with obesity: a cross-sectional study

BACKGROUND: The recent credit crunch will have implications for private households. Low socioeconomic status is associated to various diseases. While income, education and occupational status is frequently used in definitions of socioeconomic status, over-indebtedness of private households is usually not considered. Over-indebtedness is currently increasing in high-income countries. However, its association with health – particularly with obesity – remains unknown. Therefore, the aim of this study was to assess an association between over-indebtedness and overweight or obesity. METHODS: A cross-sectional study on over-indebtedness and health including 949 over-indebted subjects from 2006 and 2007 in Rhineland-Palatinate and Mecklenburg-Western Pomerania (Germany) and the telephonic health survey 2003 of the Robert Koch-Institute including 8318 subjects, who are representative for the German population, were analysed with adjusted logistic regression considering overweight (BMI ≥25.0 kg/m(2)) and obesity (BMI ≥30 kg/m(2)) as response variable. RESULTS: After adjusting for socio-economic (age, sex, education, income) and health factors (depression, smoking habits) an independent effect of the over-indebt situation on the probability of overweight (aOR 1.97 95%-CI 1.65–2.35) and obesity (aOR 2.56 95%-CI 2.07–3.16) could be identified. CONCLUSION: Over-indebtedness was associated with an increased prevalence of overweight and obesity that was not explained by traditional definitions of socioeconomic status. Over-indebtedness should be additionally considered when assessing health effects of socioeconomic status