Temporal trends in pregnancy weight gain and birth weight in Bavaria 2000-2007: slightly decreasing birth weight with increasing weight gain in pregnancy

Aims: To assess temporal trends in birth weight and pregnancy weight gain in Bavaria from 2000 to 2007. Methods: Data on 695,707 mother and infant pairs (singleton term births) were available from a compulsory reporting system for quality assurance, including information on birth weight, maternal weight at delivery and at booking, maternal smoking, age, and further anthropometric and lifestyle factors. Pregnancy weight gain was defined as: weight prior to delivery minus weight at first booking minus weight of the newborn. Results: Although mean weight gain during pregnancy increased considerably from 10.10 to 10.73 kg in seven years, the mean birth weight in mature singletons decreased slightly from 3433 to 3414 g. These trends could not be explained by concurrent changes in the rates of primiparity, smoking and gestational diabetes. Conclusions: These German data confirm an increased weight gain during pregnancy with adjustment for potential confounders

The effect of cardiovascular risk factors on the longitudinal evolution of the carotid intima medial thickness in children with type 1 diabetes mellitus

<p>Abstract</p> <p>Background</p> <p>Type 1 diabetes mellitus is a generally accepted atherogenic risk factor. The aim of this prospective longitudinal study was to evaluate changes in carotid intima media thickness (cIMT) in children and adolescents with type 1 diabetes mellitus (T1DM) using standardized methods.</p> <p>Methods</p> <p>We re-evaluated cIMT in 70 (38 f) of initial 150 (80 f) patients with T1DM after 4 years. At re-evaluation, mean (± SD) age was 16.45 ± 2.59 y, mean diabetes duration was 9.2 ± 3.24 y and patients had a mean HbA1c of 8.14 ± 1.06%.</p> <p>Results</p> <p>Mean cIMT z-scores increased significantly during 4 years (0.58 ± 0.75, p < 0.001) as well as BMI-z-score (0.41 ± 0.81, p < 0.01), systolic blood pressure (0.77 ± 1.15, p < 0.01) and HbA1c (0.90 ± 1.07, < 0.001). In a linear regression model systolic blood pressure z-score at first measurement (0.02, CI: 0.01, 0.04) was a significant predictor for the mean effect on cIMT z-score. In a logistic regression model significant risk factors for an increase in IMT of ≥1.5 z-scores were BMI z-scores (OR: 3.02, CI:1.11, 10.14), diabetes duration (OR:1.32, CI:1.04, 1.77) and systolic blood pressure (OR: 1.14, CI: 1.04, 1.27) at first measurement each.</p> <p>Conclusions</p> <p>Longitudinal cIMT measurements revealed progression in subclinical atherosclerosis during a four year period in diabetic children and adolescents. Systolic blood pressure and BMI were related to cIMT increment. Control of these risk factors by lifestyle and medical intervention may prevent progression of cIMT in diabetic children.</p

Sexual difference in bone geometry of adult patients with classical congenital adrenal hyperplasia: Data using peripheral quantitative computed tomography

BACKGROUND/AIMS Glucocorticoid treatment may influence bone and muscle development in patients with congenital adrenal hyperplasia (CAH). This study evaluated bone mineral density (BMD), bone geometry and muscle mass. METHODS 73 adult patients with classical CAH were followed. BMD, bone geometry and muscle mass were measured using peripheral quantitative computed tomography (pQCT). Glucocorticoid-equivalent doses throughout life were calculated and at the time pQCT androgen levels were measured. RESULTS In males the mean standard deviation (SD) score for trabecular BMD (-0.33 ± 0.71) was reduced, whereas mean cortical BMD (1.05 ± 1.11) was elevated. Mean total (0.86 ± 1.12) and medullary cross-sectional area (CSA; 1.12 ± 1.17) were significantly increased (p < 0.001). In all patients SD scores for cortical thickness (-0.65 ± 0.91) and muscle CSA (-0.83 ± 0.91) were reduced. Treatment duration was associated with lower trabecular BMD in males (r = -0.63, p < 0.001). Suppressed androgens and simple virilizing CAH had an adverse effect on the muscle CSA SD score (OR 0.58 and 0.46, respectively, p < 0.05). CONCLUSION There was a sexual difference with enlarged total and medullary CSA in females, whereas in males trabecular BMD was reduced and cortical BMD elevated. Cortical thickness and muscle CSA were reduced in all CAH patients with a possible long-term impact on bone development and stability. Monitoring of bone and muscle development might be warranted

Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children

Genetic factors are important determinants of overweight. We examined whether there are differential effect sizes depending on children's body composition. We analysed data of n = 4,837 children recorded in the Avon Longitudinal Study of Parents and Children (ALSPAC), applying quantile regression with sex- and age-specific standard deviation scores (SDS) of body mass index (BMI) or with body fat mass index and fat-free mass index at 9 years as outcome variables and an "obesity-risk-allele score" based on eight genetic variants known to be associated with childhood BMI as the explanatory variable. The quantile regression coefficients increased with increasing child's BMI-SDS and fat mass index percentiles, indicating larger effects of the genetic factors at higher percentiles. While the associations with BMI-SDS were of similar size in medium and high BMI quantiles (40th percentile and above), effect sizes with fat mass index increased over the whole fat mass index distribution. For example, the fat mass index of a normal-weight (50th percentile) child was increased by 0.13 kg/m(2) (95% confidence interval (CI): 0.09, 0.16) per additional allele, compared to 0.24 kg/m(2) per allele (95% CI: 0.15, 0.32) in children at the 90th percentile. The genetic associations with fat-free mass index were weaker and the quantile regression effects less pronounced than those on fat mass index. Genetic risk factors for childhood overweight appear to have greater effects on fatter children. Interaction of known genetic factors with environmental or unknown genetic factors might provide a potential explanation of these findings

Gestational Weight Gain and Body Mass Index in Children: Results from Three German Cohort Studies

Previous studies suggested potential priming effects of gestational weight gain (GWG) on offspring's body composition in later life. However, consistency of these effects in normal weight, overweight and obese mothers is less clear. We combined the individual data of three German cohorts and assessed associations of total and excessive GWG (as defined by criteria of the Institute of Medicine) with offspring's mean body mass index (BMI) standard deviation scores (SDS) and overweight at the age of 5-6 years (total: n = 6,254). Quantile regression was used to examine potentially different effects on different parts of the BMI SDS distribution. All models were adjusted for birth weight, maternal age and maternal smoking during pregnancy and stratified by maternal pre-pregnancy weight status. In adjusted models, positive associations of total and excessive GWG with mean BMI SDS and overweight were observed only in children of non- overweight mothers. For example, excessive GWG was associated with a mean increase of 0.08 (95% CI: 0.01, 0.15) units of BMI SDS (0.13 (0.02, 0.24) kg/m(2) of 'real' BMI) in children of normal-weight mothers. The effects of total and excessive GWG on BMI SDS increased for higher- BMI children of normal-weight mothers. Increased GWG is likely to be associated with overweight in offspring of non-overweight mothers

Risk Factors for Obesity: Further Evidence for Stronger Effects on Overweight Children and Adolescents Compared to Normal-Weight Subjects

Background: We recently showed that in preschoolers risk factors for overweight show stronger associations with BMI in children with high BMI values. However, it is unclear whether these findings might also pertain to adolescents. Methods: We extracted data on 3–10 year-old (n = 7,237) and 11–17 year-old (n = 5,986) children from a representative cross-sectional German health survey (KiGGS) conducted between 2003 and 2006 and calculated quantile regression models for each age group. We used z-scores of children's body mass index (BMI) as outcome variable and maternal BMI, maternal smoking in pregnancy, low parental socioeconomic status, exclusive formula-feeding and high TV viewing time as explanatory variables. Results: In both age groups, the estimated effects of all risk factors except formula-feeding on BMI z-score were greatest for children with the highest BMI z-score. The median BMI z-score of 11–17 year-old children with high TV viewing time, for example, was 0.11 [95% CI: 0.03, 0.19] units higher than the median BMI z-score of teenage children with low TV viewing time. This risk factor was associated with an average difference of 0.18 [0.06, 0.30] units at the 90th percentile of BMI z-score and of 0.20 [0.07, 0.33] units at the 97th percentile. Conclusions: We confirmed that risk factors for childhood overweight are associated with greater shifts in the upper parts of the children's BMI distribution than in the middle and lower parts. These findings pertain also to teenagers and might possibly help to explain the secular shift in the upper BMI percentiles in children and adolescents

Cesarean Section on the Risk of Celiac Disease in the Offspring: The Teddy Study

Objective: Cesarean section (C-section) is associated with various immune-mediated diseases in the offspring. We investigated the relationship between mode of delivery and celiac disease (CD) and CD autoimmunity (CDA) in a multinational birth cohort. Methods: From 2004 to 2010, infants from the general population who tested positive for HLADR3-DQ2 or DR4-DQ8 were enrolled in The Environmental Determinants for Diabetes in the Young (TEDDY) study. Children were annually screened for transglutaminase autoantibodies, if positive, they are retested after 3 to 6 months and those persistently positive defined as CDA. Associations of C-section with maternal (age, education level, parity, pre-pregnancy weight, diabetes, smoking, weight gain during pregnancy) and child characteristics (gestational age, birth weight) were examined by Fisher exact test or Wilcoxon rank-sum test. Hazard ratios (HRs) for CDA or CD were calculated by Cox proportional hazard regression models. Results: Of 6087 analyzed singletons, 1600 (26%) were born by C-section (Germany 38%, United States 37%, Finland 18%, Sweden 16%), and the remaining were born vaginally without instrumental support;979 (16%) had developed CDA and 343 (6%) developed CD. C-section was associated with lower risk for CDA (hazard ratio [HR] = 0.85;95% confidence interval [CI] 0.73, 0.99 P = 0.032) and CD (HR = 0.75;95% CI 0.58, 0.98;P = 0.034). After adjusting for country, sex, HLA-genotype, CD in family, maternal education, and breast-feeding duration, significance was lost for CDA (HR = 0.91;95% CI 0.78, 1.06;P = 0.20) and CD (HR = 0.85;95% CI 0.65, 1.11;P = 0.24). Presurgical ruptured membranes had no influence on CDA or CD development. Conclusion: C-section is not associated with increased risk for CDA or CD in the offspring

Prediction intervals for future BMI values of individual children - a non-parametric approach by quantile boosting

Background: The construction of prediction intervals (PIs) for future body mass index (BMI) values of individual children based on a recent German birth cohort study with n = 2007 children is problematic for standard parametric approaches, as the BMI distribution in childhood is typically skewed depending on age. Methods: We avoid distributional assumptions by directly modelling the borders of PIs by additive quantile regression, estimated by boosting. We point out the concept of conditional coverage to prove the accuracy of PIs. As conditional coverage can hardly be evaluated in practical applications, we conduct a simulation study before fitting child- and covariate-specific PIs for future BMI values and BMI patterns for the present data. Results: The results of our simulation study suggest that PIs fitted by quantile boosting cover future observations with the predefined coverage probability and outperform the benchmark approach. For the prediction of future BMI values, quantile boosting automatically selects informative covariates and adapts to the age-specific skewness of the BMI distribution. The lengths of the estimated PIs are child-specific and increase, as expected, with the age of the child. Conclusions: Quantile boosting is a promising approach to construct PIs with correct conditional coverage in a non-parametric way. It is in particular suitable for the prediction of BMI patterns depending on covariates, since it provides an interpretable predictor structure, inherent variable selection properties and can even account for longitudinal data structures

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