Trajectories of Systolic Blood Pressure in Children: Risk Factors and Cardiometabolic Correlates.

OBJECTIVE: To identify systolic blood pressure (SBP) percentile trajectories in children and to describe the early-life risk factors and cardiometabolic correlates of those trajectories. STUDY DESIGN: Using age-, sex-, and height-specific SBP percentiles based on the American Academy of Pediatrics reference, we examined SBP trajectories using latent class mixed models from ages 3 to 8 years (n = 844) from the Growing Up in Singapore Towards healthy Outcomes-study, a Singaporean mother-offspring cohort study. We analyzed associations between SBP trajectories and early-life risk factors using multinomial logistic regression and differences across trajectories in cardiometabolic outcomes using multiple linear regression. RESULTS: Children were classified into 1 of 4 SBP percentile trajectories: "low increasing" (15%), "high stable" (47%), "high decreasing" (20%), and "low stable" (18%). Maternal hypertension during early pregnancy was a predictor of the "high stable" and "low increasing" SBP trajectories. Rapid child weight gain in the first 2 years of life was only associated with the "high stable" trajectory. Compared with children in the "low stable" trajectory, children in the "high stable" SBP trajectory had greater body mass index z scores, sum of skinfold thicknesses, waist circumference from ages 3 to 8 years, and abdominal adipose tissue (milliliters) at 4.5 years (adjusted mean difference [95% CI]: superficial and deep subcutaneous abdominal adipose tissue: 115.2 [48.1-182.3] and 85.5 [35.2-135.8]). Their fat mass (kilograms) (1.3 [0.6-2.0]), triglyceride levels (mmol/L) (0.10 [0.02-0.18]), and homeostasis model assessment of insulin resistance (0.28 [0.11 0.46]) at age 6 years were also greater but not their arterial thickness and stiffness. CONCLUSIONS: Reducing maternal blood pressure during pregnancy and infant weight gain in the first 2 years of life might help to prevent the development of high SBP.

Maternal glycemia during pregnancy and offspring abdominal adiposity measured by MRI in the neonatal period and preschool years: The Growing Up in Singapore Towards healthy Outcomes (GUSTO) prospective mother-offspring birth cohort study.

BACKGROUND: Gestational diabetes is associated with unfavorable body fat distribution in offspring. However, less is known about the effects across the range of maternal gestational glycemia on offspring abdominal adiposity (AA) in infancy and early childhood. OBJECTIVES: This study determined the association between gestational glycemia and offspring AA measured by MRI in the neonatal period and during the preschool years. METHODS: Participants were mother-offspring pairs from the GUSTO (Growing Up in Singapore Towards healthy Outcomes) prospective cohort study. Children who underwent MRI within 2 wk postdelivery (n = 305) and/or at preschool age, 4.5 y (n = 273), and whose mothers had a 2-h 75-g oral-glucose-tolerance test (OGTT) at 26-28 weeks of gestation were included. AA measured by adipose tissue compartment volumes-abdominal superficial (sSAT), deep subcutaneous (dSAT), and internal (IAT) adipose tissue-was quantified from MRI images. RESULTS: Adjusting for potential confounders including maternal prepregnancy BMI, each 1-mmol/L increase in maternal fasting glucose was associated with higher SD scores for sSAT (0.66; 95% CI: 0.45, 0.86), dSAT (0.65; 95% CI: 0.44, 0.87), and IAT (0.64; 95% CI: 0.42, 0.86) in neonates. Similarly, each 1-mmol/L increase in 2-h OGTT glucose was associated with higher neonatal sSAT (0.11; 95% CI: 0.03, 0.19) and dSAT (0.09; 95% CI: 0.00, 0.17). These associations were stronger in female neonates but only persisted in girls between fasting glucose, and sSAT and dSAT at 4.5 y. CONCLUSIONS: A positive association between maternal glycemia and neonatal AA was observed across the whole range of maternal mid-gestation glucose concentrations. These findings may lend further support to efforts toward optimizing maternal hyperglycemia during pregnancy. The study also provides suggestive evidence on sex differences in the impact of maternal glycemia, which merits further confirmation in other studies.This trial was registered at clinicaltrials.gov as NCT01174875.

Faster eating rates are associated with higher energy intakes during an ad libitum meal, higher BMI and greater adiposity among 4·5-year-old children: results from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) cohort.

Faster eating rates are associated with increased energy intake, but little is known about the relationship between children's eating rate, food intake and adiposity. We examined whether children who eat faster consume more energy and whether this is associated with higher weight status and adiposity. We hypothesised that eating rate mediates the relationship between child weight and ad libitum energy intake. Children (n 386) from the Growing Up in Singapore Towards Healthy Outcomes cohort participated in a video-recorded ad libitum lunch at 4·5 years to measure acute energy intake. Videos were coded for three eating-behaviours (bites, chews and swallows) to derive a measure of eating rate (g/min). BMI and anthropometric indices of adiposity were measured. A subset of children underwent MRI scanning (n 153) to measure abdominal subcutaneous and visceral adiposity. Children above/below the median eating rate were categorised as slower and faster eaters, and compared across body composition measures. There was a strong positive relationship between eating rate and energy intake (r 0·61, P<0·001) and a positive linear relationship between eating rate and children's BMI status. Faster eaters consumed 75 % more energy content than slower eating children (Δ548 kJ (Δ131 kcal); 95 % CI 107·6, 154·4, P<0·001), and had higher whole-body (P<0·05) and subcutaneous abdominal adiposity (Δ118·3 cc; 95 % CI 24·0, 212·7, P=0·014). Mediation analysis showed that eating rate mediates the link between child weight and energy intake during a meal (b 13·59; 95 % CI 7·48, 21·83). Children who ate faster had higher energy intake, and this was associated with increased BMI z-score and adiposity.

New measure of insulin sensitivity predicts cardiovascular disease better than HOMA estimated insulin resistance.

CONTEXT: Accurate assessment of insulin sensitivity may better identify individuals at increased risk of cardio-metabolic diseases. OBJECTIVES: To examine whether a combination of anthropometric, biochemical and imaging measures can better estimate insulin sensitivity index (ISI) and provide improved prediction of cardio-metabolic risk, in comparison to HOMA-IR. DESIGN AND PARTICIPANTS: Healthy male volunteers (96 Chinese, 80 Malay, 77 Indian), 21 to 40 years, body mass index 18-30 kg/m(2). Predicted ISI (ISI-cal) was generated using 45 randomly selected Chinese through stepwise multiple linear regression, and validated in the rest using non-parametric correlation (Kendall's tau τ). In an independent longitudinal cohort, ISI-cal and HOMA-IR were compared for prediction of diabetes and cardiovascular disease (CVD), using ROC curves. SETTING: The study was conducted in a university academic medical centre. OUTCOME MEASURES: ISI measured by hyperinsulinemic euglycemic glucose clamp, along with anthropometric measurements, biochemical assessment and imaging; incident diabetes and CVD. RESULTS: A combination of fasting insulin, serum triglycerides and waist-to-hip ratio (WHR) provided the best estimate of clamp-derived ISI (adjusted R(2) 0.58 versus 0.32 HOMA-IR). In an independent cohort, ROC areas under the curve were 0.77±0.02 ISI-cal versus 0.76±0.02 HOMA-IR (p>0.05) for incident diabetes, and 0.74±0.03 ISI-cal versus 0.61±0.03 HOMA-IR (p<0.001) for incident CVD. ISI-cal also had greater sensitivity than defined metabolic syndrome in predicting CVD, with a four-fold increase in the risk of CVD independent of metabolic syndrome. CONCLUSIONS: Triglycerides and WHR, combined with fasting insulin levels, provide a better estimate of current insulin resistance state and improved identification of individuals with future risk of CVD, compared to HOMA-IR. This may be useful for estimating insulin sensitivity and cardio-metabolic risk in clinical and epidemiological settings.

Skull stripping using graph cuts.

Removal of non-brain tissues, particularly dura, is an important step in enabling accurate measurement of brain structures. Many popular methods rely on iterative surface deformation to fit the brain boundary and tend to leave residual dura. Similar to other approaches, the method proposed here uses intensity thresholding followed by removal of narrow connections to obtain a brain mask. However, instead of using morphological operations to remove narrow connections, a graph theoretic image segmentation technique was used to position cuts that isolate and remove dura. This approach performed well on both the standardized IBSR test data sets and empirically derived data. Compared to the Hybrid Watershed Algorithm (HWA; (Segonne et al., 2004)) the novel approach achieved an additional 10-30% of dura removal without incurring further brain tissue erosion. The proposed method is best used in conjunction with HWA as the errors produced by the two approaches often occur at different locations and cancel out when their masks are combined. Our experiments indicate that this combination can substantially decrease and often fully avoid cortical surface overestimation in subsequent segmentation.