Congenital Anorectal Malformation Severity Does Not Predict Severity of Congenital Heart Defects.

OBJECTIVE: To determine the prevalence of congenital heart defects (CHDs) in patients with mild or severe congenital anorectal malformations (CARMs), and whether all patients with CARM need pediatric cardiology screening. STUDY DESIGN: We included 129 patients with CARM born between 2004 and 2013, and referred to University Medical Center Groningen. Recto-perineal and recto-vestibular fistulas were classified as mild CARMs, all others as severe. Significant patent foramen ovale, secundum atrial septal defect, and small ventricular septum defect were classified as minor CHDs, all others as major. RESULTS: Of 129 patients with CARM, 67% had mild CARM, 33% severe CARM, and 17% were additionally diagnosed with CHD. CHDs were distributed equally in patients with mild or severe CARMs. Patients with multiple congenital abnormalities were more frequently diagnosed with CHD (n = 16, 36%) than patients without multiple congenital malformations (n = 5, 9%, P = .001). Patients with CARM diagnosed with CHD using pediatric cardiac echo screening were younger than 3 months of age at diagnosis. Earlier general pediatric examinations missed 7 (50%) children with mild and 4 (50%) with severe CHDs. CONCLUSIONS: The severity of CARM could predict neither prevalence nor severity of CHD. More than one-half of CHDs were missed during the first physical examination. No new CHDs were found in patients older than 3 months of age at the time CARMs were diagnosed. We recommend screening all patients with CARM younger than 3 months of age for CHD at the time CARM is diagnosed. Preoperative echocardiography should be the rule in children younger than 3 months of age and with multiple congenital anomalies.

Waist-to-height ratio, waist circumference and BMI as indicators of percentage fat mass and cardiometabolic risk factors in children aged 3-7 years.

OBJECTIVE: To assess whether waist-to-height-ratio (WHtR) is a better estimate of body fat percentage (BF%) and a better indicator of cardiometabolic risk factors than BMI or waist circumference (WC) in young children. METHODS: WHtR, WC and BMI were measured by trained staff according to standardized procedures. (2)H2O and (2)H2(18)O isotope dilution were used to assess BF% in 61 children (3-7 years) from the general population, and bioelectrical impedance (Horlick equation) was used to assess BF% in 75 overweight/obese children (3-5 years). Cardiometabolic risk factors, including diastolic and systolic blood pressure, HOMA2-IR, leptin, adiponectin, triglycerides, total cholesterol, HDL- and LDL-cholesterol, TNFα and IL-6 were determined in the overweight/obese children. RESULTS: In the children from the general population, after adjustments for age and gender, BMI had the highest explained variance for BF% compared to WC and WHtR (R(2) = 0.32, 0.31 and 0.23, respectively). In the overweight/obese children, BMI and WC had a higher explained variance for BF% compared to WHtR (R(2) = 0.68, 0.70 and 0.50, respectively). In the overweight/obese children, WHtR, WC and BMI were all significantly positively correlated with systolic blood pressure (r = 0.23, 0.30, 0.36, respectively), HOMA2-IR (r = 0.53, 0.62, 0.63, respectively), leptin (r = 0.70, 0.77, 0.78, respectively) and triglycerides (r = 0.33, 0.36, 0.24, respectively), but not consistently with other parameters. CONCLUSION: In young children, WHtR is not superior to WC or BMI in estimating BF%, nor is WHtR better correlated with cardiometabolic risk factors than WC or BMI in overweight/obese children. These data do not support the use of WHtR in young children.

Growth during infancy and childhood, and adiposity at age 16 years: ages 2 to 7 years are pivotal.

OBJECTIVE: To assess the period during infancy and childhood in which growth is most associated with adolescent adiposity and the metabolic syndrome (MS) and whether this differs depending on maternal smoking during pregnancy. STUDY DESIGN: A longitudinal population-based cohort study among 772 girls and 708 boys. RESULTS: Weight gains between ages 2-4 years and ages 4-7 years were most strongly associated with higher body mass index (BMI), sum of skinfold measurements, body fat percentage, and waist circumference at age 16. A one SD increase in weight between ages 2-4 and 4-7 years was associated with increases in outcome measures of +0.82 to +1.47 SDs (all P < .001), and with a less favorable MS score. In children whose mothers smoked during pregnancy, the association of relative weight gain during ages 2-4 years with adolescent BMI was stronger than in children whose mothers did not smoke. For adolescent BMI, the increase was 0.42 SD higher (P = .01). This was similar for the other adiposity measures. CONCLUSIONS: Large relative increases in weight from ages 2 to 7 years are associated with adolescent adiposity and MS. This is more pronounced in adolescents whose mothers smoked during pregnancy.

The role of fitness in the association between fatness and cardiometabolic risk from childhood to adolescence.

BACKGROUND: Fatness and fitness both influence cardiometabolic risk. OBJECTIVE: The purpose of this study was to investigate whether childhood fatness and increasing fatness from childhood to adolescence are associated with cardiometabolic risk during adolescence and how fitness affects this association. SUBJECTS AND METHODS: Of 565 adolescents (283 boys and 282 girls) from the TRacking Adolescents Individual Life Survey (TRAILS) data on anthropometric parameters (age 11 and 16), metabolic parameters, and fitness (age 16) were available. Body mass index and skinfolds were used as measures for fatness. Increasing fatness was calculated by subtracting Z-scores for fatness at age 11 from Z-score fatness at age 16. Cardiometabolic risk was calculated as the average of the standardized means of mean arterial pressure, fasting serum triglycerides, high-density lipoprotein-cholesterol, glucose, and waist circumference. Insulin resistance was calculated by homeostasis model assessment-insulin resistance (HOMA-IR). Fitness was estimated as maximal oxygen consumption (VO(2) max) during a shuttle run test. RESULTS: Boys showed a higher clustered cardiometabolic risk when compared to girls (p < 0.01). Childhood fatness (age 11) and increasing fatness were independently associated with cardiometabolic risk during adolescence. In boys, high fitness was related to a reduced effect of increasing fatness on clustered cardiometabolic risk. Childhood fatness, increasing fatness, and fitness were independently associated with HOMA-IR. Moreover, in boys this association was dependent of fatness. CONCLUSIONS: Childhood fatness and increasing fatness are associated with increased cardiometabolic risk and HOMA-IR during adolescence, but a good fitness attenuates this association especially in fat boys.

Comparison of methods to assess body fat in non-obese six to seven-year-old children.

BACKGROUND & AIM: Different non-invasive methods exist to evaluate total body fat in children. Most methods have shown to be able to confirm a high fat percentage in children with overweight and obesity. No data are available on the estimation of total body fat in non-obese children. The aim of this study is to compare total body fat, assessed by different methods in non-obese children. METHODS: We compared total body fat, assessed by isotope dilution, dual energy X-ray, skinfold thickness, bioelectrical impedance analysis, combination of these methods as well as BMI in 30 six to seven-year-old children. RESULTS: The children had a mean BMI of 16.01kg/m(2) (range 13.51-20.32) and five children were overweight according to international criteria. Different methods showed rather different absolute values for total body fat. Bland-Altman analysis showed that the difference between the DEXA method and isotope dilution was dependent on the fat percentage. Children with the same BMI show a marked variation in total body fat ranging from 8% to 22% as estimated from the isotope dilution method. CONCLUSION: Non-invasive methods are presently not suited to assess the absolute amount of total body fat in 6-7 years old children.

Influence of common variants near INSIG2, in FTO, and near MC4R genes on overweight and the metabolic profile in adolescence: the TRAILS (TRacking Adolescents' Individual Lives Survey) Study.

BACKGROUND: Overweight is a complex trait in which both environmental and genetic factors play a role. OBJECTIVE: We aimed to evaluate the influence of common genetic variants identified by genome-wide association studies on overweight and the metabolic profile in adolescence. DESIGN: In a population-based cohort of 663 girls and 612 boys aged 16 y, weight, height, skinfold thicknesses, percentage body fat, waist circumference, blood pressure, glucose, insulin, lipid profile, and DNA were obtained. We defined overweight according to international criteria. We performed multiple linear and logistic regression analyses to assess the influence of candidate single nucleotide polymorphisms near the INSIG2, in the FTO, and near the MC4R genes and repeated-measures analyses of available body mass index (BMI) and skinfold thickness data across 3 visits at ages 11, 13.5, and 16 y. RESULTS: A total of 15.1% of participants were overweight or obese at age 16 y. No associations with INSIG2 were found. Common variation in the FTO gene was associated with sex-specific z scores of BMI (B: 0.11; 95% CI: 0.03, 0.19), sum of skinfold thicknesses (B: 0.12; 95% CI: 0.04, 0.20), percentage body fat (B: 0.11; 95% CI: 0.03, 0.19), waist circumference (B: 0.11; 95% CI: 0.03, 0.19), fasting glucose (B: 0.10; 95% CI: 0.00, 0.20), and overweight (odds ratio: 1.34; 95% CI: 1.06, 1.69) at age 16 y. Repeated-measures analyses confirmed the associations for BMI and sum of skinfold thicknesses, and physical activity did not modify these associations. Common variation near the MC4R gene was associated with BMI in cross-sectional (B: 0.11; 95% CI: 0.02, 0.20) and repeated-measures (B: 0.12; 95% CI: 0.03, 0.20) analyses. CONCLUSIONS: Common variation in the FTO gene is associated with overall and abdominal adiposity. Variation near the MC4R gene is associated with BMI. These findings in adolescents strengthen and extend the results from previous research.

Association between depressive symptoms in childhood and adolescence and overweight in later life: review of the recent literature.

OBJECTIVE: To present an overview of the association between depressive symptoms in childhood and adolescence and subsequent overweight in later life. DATA SOURCES: MEDLINE, EMBASE, and Web of Science for all indexed journals from January 1, 1997, to May 30, 2007. STUDY SELECTION: Abstracts of 513 articles were reviewed manually. Studies were excluded if unrelated to depressive symptoms and overweight (n = 460), if they were conducted in an adult population (n = 10) or in a population of all age groups (n = 2), or if they were performed in clinic-based populations of overweight participants. In total, 32 articles were reviewed including 21 cross-sectional and 11 longitudinal reports. Main Exposure Depressive symptoms in childhood and adolescence. Main Outcome Measure Overweight. RESULTS: Four cross-sectional studies that satisfied our quality criteria revealed an association between depressive symptoms and overweight in girls aged 8 to 15 years, reporting different effect sizes including a correlation coefficient of 0.14 and a regression coefficient of 0.27. Four longitudinal studies in accord with our quality criteria suggest that depressive symptoms in childhood or adolescence are associated with a 1.90- to 3.50-fold increased risk of subsequent overweight (95% confidence intervals varying from 1.02 to 5.80, respectively). CONCLUSION: These results support a positive association between depressive symptoms at age 6 to 19 years and overweight in later life, assessed after a period of 1 to 15 years.