Decreasing severity of obesity from early to late adolescence and young adulthood associates with longitudinal metabolomic changes implicated in lower cardiometabolic disease risk.

BACKGROUND: Obesity in childhood is associated with metabolic dysfunction, adverse subclinical cardiovascular phenotypes and adult cardiovascular disease. Longitudinal studies of youth with obesity investigating changes in severity of obesity with metabolomic profiles are sparse. We investigated associations between (i) baseline body mass index (BMI) and follow-up metabolomic profiles; (ii) change in BMI with follow-up metabolomic profiles; and (iii) change in BMI with change in metabolomic profiles (mean interval 5.5 years). METHODS: Participants (n = 98, 52% males) were recruited from the Childhood Overweight Biorepository of Australia study. At baseline and follow-up, BMI and the % >95th BMI-centile (percentage above the age-, and sex-specific 95th BMI-centile) indicate severity of obesity, and nuclear magnetic resonance spectroscopy profiling of 72 metabolites/ratios, log-transformed and scaled to standard deviations (SD), was performed in fasting serum. Fully adjusted linear regression analyses were performed. RESULTS: Mean (SD) age and % >95th BMI-centile were 10.3 (SD 3.5) years and 134.6% (19.0) at baseline, 15.8 (3.7) years and 130.7% (26.2) at follow-up. Change in BMI over time, but not baseline BMI, was associated with metabolites at follow-up. Each unit (kg/m2) decrease in sex- and age-adjusted BMI was associated with change (SD; 95% CI; p value) in metabolites of: alanine (-0.07; -0.11 to -0.04; p < 0.001), phenylalanine (-0.07; -0.10 to -0.04; p < 0.001), tyrosine (-0.07; -0.10 to -0.04; p < 0.001), glycoprotein acetyls (-0.06; -0.09 to -0.04; p < 0.001), degree of fatty acid unsaturation (0.06; 0.02 to 0.10; p = 0.003), monounsaturated fatty acids (-0.04; -0.07 to -0.01; p = 0.004), ratio of ApoB/ApoA1 (-0.05; -0.07 to -0.02; p = 0.001), VLDL-cholesterol (-0.04; -0.06 to -0.01; p = 0.01), HDL cholesterol (0.05; 0.08 to 0.1; p = 0.01), pyruvate (-0.08; -0.11 to -0.04; p < 0.001), acetoacetate (0.07; 0.02 to 0.11; p = 0.005) and 3-hydroxybuturate (0.07; 0.02 to 0.11; p = 0.01). Results using the % >95th BMI-centile were largely consistent with age- and sex-adjusted BMI measures. CONCLUSIONS: In children and young adults with obesity, decreasing the severity of obesity was associated with changes in metabolomic profiles consistent with lower cardiovascular and metabolic disease risk in adults.

Obesity during childhood is associated with higher cancer mortality rate during adulthood: the i3C Consortium.

BACKGROUND: In high-income countries, cancer is the leading cause of death among middle-aged adults. Prospective data on the effects of childhood risk exposures on subsequent cancer mortality are scarce. METHODS: We examined whether childhood body mass index (BMI), blood pressure, glucose and lipid levels were associated with adult cancer mortality, using data from 21,012 children enrolled aged 3-19 years in seven prospective cohort studies from the U.S., Australia, and Finland that have followed participants from childhood into adulthood. Cancer mortality (cancer as a primary or secondary cause of death) was captured using registries. RESULTS: 354 cancer deaths occurred over the follow-up. In age-, sex, and cohort-adjusted analyses, childhood BMI (Hazard ratio [HR], 1.13; 95% confidence interval [CI] 1.03-1.24 per 1-SD increase) and childhood glucose (HR 1.22; 95%CI 1.01-1.47 per 1-SD increase), were associated with subsequent cancer mortality. In a multivariable analysis adjusted for age, sex, cohort, and childhood measures of fasting glucose, total cholesterol, triglycerides, and systolic blood pressure, childhood BMI remained as an independent predictor of subsequent cancer mortality (HR, 1.24; 95%CI, 1.03-1.49). The association of childhood BMI and subsequent cancer mortality persisted after adjustment for adulthood BMI (HR for childhood BMI, 1.35; 95%CI 1.12-1.63). CONCLUSIONS: Higher childhood BMI was independently associated with increased overall cancer mortality.

Use of antibiotics and risk of type 2 diabetes, overweight and obesity: the Cardiovascular Risk in Young Finns Study and the national FINRISK study.

PURPOSE: To investigate whether exposure to systemic antibiotics influences the risk of developing type 2 diabetes and overweight/obesity. METHODS: The study sample comprised 2209 (110 with incident diabetes) participants from the population-based Cardiovascular Risk in Young Finns Study (YFS) aged 24-39 years in 2001. The exposure was national linked register data on purchased antibiotic courses between 1993 and 2001. Clinical examinations including BMI were conducted in 2001, 2007 and 2011. Participants with prevalent diabetes in 2001 were excluded. Data on type 2 diabetes was also obtained from two national registers until 2017. Data from four population-based National FINRISK studies were used for replication (N = 24,674, 1866 with incident diabetes). RESULTS: Prior antibiotic exposure (> 5 versus 0-1 antibiotic courses) was associated with subsequent type 2 diabetes in both YFS (OR 2.29; 95%CI 1.33-3.96) and FINRISK (HR 1.73; 95%CI 1.51-1.99). An increased risk for type 2 diabetes was observed in YFS (OR 1.043; 95%CI 1.013-1.074) and FINRISK (HR 1.022; 95%CI 1.016-1.029) per course. Exposure to antibiotics increased the risk of overweight/obesity (BMI > 25 kg/m2) after a 10-year follow-up in YFS (OR 1.043; 95%CI 1.019-1.068) and in FINRISK (OR 1.023; 95%CI 1.018-1.029) at baseline per antibiotic course. Adjustments for confounders from early life in YFS and at baseline in FINRISK, including BMI, socioeconomic status, smoking, insulin, blood pressure, and physical activity, did not appreciably alter the findings. CONCLUSION: Our results show that exposure to antibiotics was associated with increased risk for future type 2 diabetes and overweight/obesity and support judicious antibiotic prescribing.

Childhood and Adulthood Passive Smoking and Nonalcoholic Fatty Liver in Midlife: A 31-year Cohort Study.

INTRODUCTION: Identifying early life risk factors remains key to the prevention of nonalcoholic fatty liver (hereinafter "fatty liver") in adulthood. However, the longitudinal association of childhood passive smoking with adult fatty liver is not studied. We examined the association of childhood and adulthood passive smoking with fatty liver in midlife. METHODS: This was a 31-year prospective cohort study of 1,315 participants. Information on childhood passive smoking (parental smoking) was collected in 1980 (aged 3-18 years) and 1983 and adulthood passive smoking in 2001, 2007, and 2011. Fatty liver was determined by ultrasound in 2011 (aged 34-49 years). RESULTS: The prevalence of fatty liver was 16.3%. Both childhood and adulthood passive smoking were associated with higher risk of fatty liver, adjusting for potential confounders such as age, sex, childhood socioeconomic status, and adulthood physical activity and alcohol consumption (relative risk = 1.41, 95% confidence interval: 1.01-1.97 for childhood; 1.35, 1.01-1.82 for adulthood). Individuals with persistent exposure to passive smoking between childhood and adulthood had the highest risk (relative risk = 1.99, 95% confidence interval: 1.14-3.45) compared with those without passive smoking in either childhood or adulthood. DISCUSSION: Passive smoking in both child and adult lives are associated with increased risk of adult fatty liver, suggesting that the prevention of passive smoking should start as early as possible and maintain throughout lifetime.

Early clinical markers of overweight/obesity onset and resolution by adolescence.

OBJECTIVES: We examined how combinations of clinical indicators at various ages predict overweight/obesity development, as well as resolution, by 10-11 and 14-15 years of age. METHODS: Data were derived from Birth (N = 3469) and Kinder (N = 3276) cohorts of the Longitudinal Study of Australian Children, followed from ages 2-3 and 4-5 years, respectively. Every two years, 25 potential obesity-relevant clinical indicators were quantified. Overweight/obesity was defined using International Obesity Taskforce cutpoints at 10-11 years and 14-15 years. RESULTS: In both cohorts, three factors predicted both development and resolution of overweight/obesity in multivariable models. Among normal weight children, increased odds of developing overweight/obesity were associated with higher child (odd ratio (OR) 1.67-3.35 across different study waves) and maternal (OR 1.05-1.09) BMI, and inversely with higher maternal education (OR 0.60-0.62, when assessed at age 2-7 years). Lower odds of resolving existing overweight/obesity were related with higher child (OR 0.51-0.79) and maternal (OR 0.89-0.95) BMI, and inversely with higher maternal education (OR 1.62-1.92, when assessed at age 2-5 years). The prevalence of overweight/obesity at the age of 14-15 years was 13% among children with none of these risk factors at age 6-7 years, compared with 71% among those with all 3 risk factors (P < 0.001). CONCLUSIONS: From early childhood onwards, child and maternal BMI and maternal education predict overweight/obesity onset and resolution by adolescence. A simple risk score, easily available to child health clinicians, could help target treatment or prevention.

Longitudinal association of a body mass index (BMI) genetic risk score with growth and BMI changes across the life course: The Cardiovascular Risk in Young Finns Study.

BACKGROUND: The role of genetic risk scores associated with adult body mass index (BMI) on BMI levels across the life course is unclear. We examined if a 97 single nucleotide polymorphism weighted genetic risk score (wGRS97) associated with age-related progression in BMI at different life stages and distinct developmental trajectories of BMI across the early life course. METHODS: 2188 Cardiovascular Risk in Young Finns Study participants born pre-1980 who had genotype data and objective measurements of height and weight collected up to 8 times from age 6 to 49 years. Associations were examined using Individual Growth Curve analysis, Latent Class Growth Mixture Modelling, and Poisson modified regression. RESULTS: The wGRS97 associated with BMI from age 6 years with peak effect sizes observed at age 30 years (females: 1.14 kg/m2; males: 1.09 kg/m2 higher BMI per standard deviation increase in wGRS97). The association between wGRS97 and BMI became stronger with age in childhood but slowed in adolescence, especially in females, and weakened at age 35-40 years. A higher wGRS97 associated with an increased BMI velocity in childhood and adulthood, but not with BMI change in adulthood. Compared with belonging to a 'normal stable' life-course trajectory group (normal BMI from childhood to adulthood), a one standard deviation higher wGRS97 associated with a 13-127% increased risk of belonging to a less favourable life-course BMI trajectory group. CONCLUSIONS: Individuals with genetic susceptibility to higher adult BMI have higher levels and accelerated rates of increase in BMI in childhood/adolescence, and are at increased risk of having a less favourable life-course BMI trajectory.

Age-Specific Estimates and Comparisons of Youth Tri-Ponderal Mass Index and Body Mass Index in Predicting Adult Obesity-Related Outcomes.

OBJECTIVES: To estimate and compare tri-ponderal mass index (TMI) and body mass index (BMI) at each age from childhood to young adulthood in the prediction of adulthood obesity-related outcomes. STUDY DESIGN: Participants of this observational study (n = 432) were from a 20-year infancy-onset randomized atherosclerosis prevention trial. BMI and TMI were calculated using weight and height measured annually from participants between ages 2 and 20 years. Outcomes were aortic intima-media thickness (at the age of 15, 17, or 19 years), impaired fasting glucose and elevated insulin levels, homeostasis model assessment of insulin resistance index, serum lipids, and hypertension at the age of 20 years. Poisson regressions, Pearson correlation, logistic regression, and area under the curve (AUC) were used to estimate and/or compare associations and predictive utilities between BMI and TMI with all outcomes. RESULTS: The associations and predictive utilities of BMI and TMI with all outcomes were stronger at older ages. BMI had significantly stronger correlations than TMI with insulin (at age 16 years), systolic blood pressure (age 5-20 years), and triglycerides (age 18 years). BMI had significantly greater predictive utilities than TMI for insulin resistance (at age 14-16 years; difference in AUC = 0.018-0.024), elevated insulin levels (age 14-16 years; difference in AUC = 0.018 and 0.025), and hypertension (age 16 to 20 years; difference in AUC = 0.017-0.022) but they were similar for other outcomes. CONCLUSIONS: TMI is not superior to BMI at any ages from childhood to young adulthood in the prediction of obesity-related outcomes in young adulthood.

Youth to adult body mass index trajectories as a predictor of metabolically healthy obesity in adulthood.

BACKGROUND: Adiposity in childhood and adolescence (youth) has been shown to associate with adult metabolic health. What is not known, is whether youth body mass index (BMI) associates with metabolically healthy obesity (MHO) in adulthood, and if so, the age when the BMI to MHO association emerges. This study aimed to determine if BMI trajectories from youth to adulthood differed between adults with MHO and metabolically unhealthy obesity (MUHO). METHODS: The Cardiovascular Risk in Young Finns Study had measured weight and height up to eight times in individuals from youth (3-18 years in 1980) to adulthood (24-49 years). Adult MHO was defined as BMI ≥ 30 kg m-2, normal fasting glucose (<5.6 mmol l-1), triglycerides (<1.695 mmol l-1), high density lipoprotein cholesterol (≥1.295 mmol l-1 females, ≥1.036 mmol l-1 males), blood pressure (<130/85 mmHg) and no medications for these conditions. BMI trajectories were compared for adults with MHO and MUHO using multilevel mixed models adjusted for age, sex and follow-up time. RESULTS: Mean (SD) follow-up time was 29 (3) years. Five hundred and twenty-four participants were obese in adulthood, 66 (12.6%) had MHO. BMI was similar through childhood, adolescence and young adulthood. BMI trajectories diverged at age 33, when individuals with MHO had at least 1.0 kg m-2 lower BMI than those with MUHO, significantly lower at 36 (-2.1 kg m-2, P = 0.001) and 42 years (-1.7 kg m-2; P = 0.005). CONCLUSION: Adult MHO was characterized by lower adult BMI, not youth BMI. Preventing additional weight gain among adults who are obese may be beneficial for metabolic health.

Time spent watching television impacts on body mass index in youth with obesity, but only in those with shortest sleep duration.

AIM: To determine the interplay between sleep and sedentary behaviours on body mass index (BMI) in children with obesity. METHODS: Cross-sectional study of 343 children with obesity aged 4-17 years, from a tertiary care weight management clinic in Melbourne, Victoria, Australia. Multifaceted data relating to activity and sleep from child and parent questionnaires analysed with anthropometric data collected during routine clinical care. Associations between sleep duration and activity measures were examined via regression models with adjustment for potential confounders. RESULTS: Higher BMI was associated with more hours spent watching television (P = 0.04), as well as less reported enjoyment of physical activity (P = 0.005) and less time spent in organised sport activity (P = 0.005). Higher BMI was also associated with higher levels of obstructive sleep apnoea (P = 0.002). Less time in bed was associated with higher levels of BMI (P = 0.03) but analysis by sex revealed this association to only hold for males. In the whole group, a significant television and sleep interaction was seen, such that increasing television watching was associated with higher BMI, but only in those with shortest sleep duration. CONCLUSIONS: Both poor sleep and increasing screen time (including television viewing, smart-phone use, internet use or video-gaming) appear to impact BMI in children with obesity, with a particular detrimental effect of television viewing in those who sleep less. Efforts to improve sleep time and quality in children may minimise negative effects of screen time on increasing BMI and should be included in public health strategies to combat obesity in childhood.

Impact of Lipid Measurements in Youth in Addition to Conventional Clinic-Based Risk Factors on Predicting Preclinical Atherosclerosis in Adulthood: International Childhood Cardiovascular Cohort Consortium.

BACKGROUND: Data suggest that the prediction of adult cardiovascular disease using a model comprised entirely of adult nonlaboratory-based risk factors is equivalent to an approach that additionally incorporates adult lipid measures. We assessed and compared the utility of a risk model based solely on nonlaboratory risk factors in adolescence versus a lipid model based on nonlaboratory risk factors plus lipids for predicting high-risk carotid intima-media thickness (cIMT) in adulthood. METHODS: The study comprised 2893 participants 12 to 18 years of age from 4 longitudinal cohort studies from the United States (Bogalusa Heart Study and the Insulin Study), Australia (Childhood Determinants of Adult Health Study), and Finland (The Cardiovascular Risk in Young Finns Study) and followed into adulthood when cIMT was measured (mean follow-up, 23.4 years). Overweight status was defined according to the Cole classification. Hypertension was defined according to the Fourth Report on High Blood Pressure in Children and Adolescents from the National High Blood Pressure Education Program. High-risk plasma lipid levels were defined according to the National Cholesterol Education Program Expert Panel on Cholesterol Levels in Children. High cIMT was defined as a study-specific value ≥90th percentile. Age and sex were included in each model. RESULTS: In univariate models, all risk factors except for borderline high and high triglycerides in adolescence were associated with high cIMT in adulthood. In multivariable models (relative risk [95% confidence interval]), male sex (2.7 [2.0-2.6]), prehypertension (1.4 [1.0-1.9]), hypertension (1.9 [1.3-2.9]), overweight (2.0 [1.4-2.9]), obesity (3.7 [2.0-7.0]), borderline high low-density lipoprotein cholesterol (1.6 [1.2-2.2]), high low-density lipoprotein cholesterol (1.6 [1.1-2.1]), and borderline low high-density lipoprotein cholesterol (1.4 [1.0-1.8]) remained significant predictors of high cIMT (P<0.05). The addition of lipids into the nonlaboratory risk model slightly but significantly improved discrimination in predicting high cIMT compared with nonlaboratory-based risk factors only (C statistics for laboratory-based model 0.717 [95% confidence interval, 0.685-0.748] and for nonlaboratory 0.698 [95% confidence interval, 0.667-0.731]; P=0.02). CONCLUSIONS: Nonlaboratory-based risk factors and lipids measured in adolescence independently predicted preclinical atherosclerosis in young adulthood. The addition of lipid measurements to traditional clinic-based risk factor assessment provided a statistically significant but clinically modest improvement on adolescent prediction of high cIMT in adulthood.

Sex and puberty-related differences in metabolomic profiles associated with adiposity measures in youth with obesity.

BACKGROUND: Specific patterns of metabolomic profiles relating to cardiometabolic disease are associated with increased weight in adults. In youth with obesity, metabolomic data are sparse and associations with adiposity measures unknown. OBJECTIVES: Primary, to determine associations between adiposity measures and metabolomic profiles with increased cardiometabolic risks in youth with obesity. Secondary, to stratify associations by sex and puberty. METHODS: Participants were from COBRA (Childhood Overweight BioRepository of Australia; a paediatric cohort with obesity). Adiposity measures (BMI, BMI z-score, %truncal and %whole body fat, waist circumference and waist/height ratio), puberty staging and NMR metabolomic profiles from serum were assessed. Statistics included multivariate analysis (principal component analysis, PCA) and multiple linear regression models with false discovery rate adjustment. RESULTS: 214 participants had metabolomic profiles analyzed, mean age 11.9 years (SD ± 3.1), mean BMI z-score 2.49 (SD ± 0.24), 53% females. Unsupervised PCA identified no separable clusters of individuals. Positive associations included BMI z-score and phenylalanine, total body fat % and lipids in medium HDL, and waist circumference and tyrosine; negative associations included total body fat % and the ratio of docosahexaenoic acid/total fatty acids and histidine. Stratifying by sex and puberty, patterns of associations with BMI z-score in post-pubertal males included positive associations with lipid-, cholesterol- and triglyceride-content in VLDL lipoproteins; total fatty acids; total triglycerides; isoleucine, leucine and glycoprotein acetyls. CONCLUSION: In a paediatric cohort with obesity, increased adiposity measures, especially in post-pubertal males, were associated with distinct patterns in metabolomic profiles.

Psychosocial measures and weight change in a clinical paediatric population with obesity.

PURPOSE: Poor quality of life has been shown to occur in youth with obesity. This study aimed to assess associations between health-related quality of life, general mental health and general psychological distress measures, collectively termed psychosocial health questionnaires (PSH), with weight outcomes in a busy paediatric weight management service. METHODS: A cross-sectional longitudinal clinical cohort, 'Childhood Overweight BioRepository of Australia (COBRA)', was used (n = 250, median age 11, range 2-18 year, mean BMI z-score 2.5 ± 0.2). Clinical data were collected and HRQOL questionnaires; Pediatric Quality of Life 4.0 (PedsQL), 'Sizing Me/Them Up' (SMU/STU), and psychological well-being questionnaires; strengths and difficulties questionnaire (SDQ) and Kessler 10 (K10) were completed by the child and primary caregiver. PSH results were compared to age- and sex-adjusted BMI z-score at baseline and follow-up. Direct logistic regression modelling was performed to assess the impact of PSH factors on the likelihood of successful weight reduction over a period of ≥ 12 months. RESULTS: Mean self-report PSH scores were: 68.0 ± 15.28 (PedsQL, range 0-100), 64.8 ± 15.8, (SMU, range 0-100), 17.3 ± 4.4 (SDQ, range 0-40) and 20.0 ± 7.7 (K10, range 0-50). A significant negative correlation was observed between PSH scores and childhood obesity (baseline BMI z-scores (p < 0.01)). No correlations were observed between psychological well-being measures and BMI z-scores. Higher subscale scores of the PedsQL and SDQ, which measure impaired psychosocial health and more difficulties with hyperactivity and inattention, significantly predict weight loss in children with obesity after 12 months. CONCLUSION: PSH questionnaires may be useful in identifying individuals who require additional support to achieve weight loss goals in a tertiary weight management service.

Distinct child-to-adult body mass index trajectories are associated with different levels of adult cardiometabolic risk.

Aims: The relationship between life-course body mass index (BMI) trajectories and adult risk for cardiovascular disease (CVD) is poorly described. In a longitudinal cohort, we describe BMI trajectories from early childhood to adulthood and investigate their association with CVD risk factors [Type 2 diabetes mellitus (T2DM), high-risk lipid levels, hypertension, and high carotid intima-media thickness (cIMT)] in adulthood (34-49 years). Methods and results: Six discrete long-term BMI trajectories were identified using latent class growth mixture modelling among 2631 Cardiovascular Risk in Young Finns Study participants (6-49 years): stable normal (55.2%), resolving (1.6%), progressively overweight (33.4%), progressively obese (4.2%), rapidly overweight/obese (4.3%), and persistent increasing overweight/obese (1.2%). Trajectories of worsening or persisting obesity were generally associated with increased risk of CVD outcomes in adulthood (24-49 years) [all risk ratios (RRs) >15, P < 0.05 compared with the stable normal group]. Although residual risk for adult T2DM could not be confirmed [RR = 2.6, 95% confidence interval (CI) = 0.14-8.23], participants who resolved their elevated child BMI had similar risk for dyslipidaemia and hypertension as those never obese or overweight (all RRs close to 1). However, they had significantly higher risk for increased cIMT (RR = 3.37, 95% CI = 1.80-6.39). Conclusion: The long-term BMI trajectories that reach or persist at high levels associate with CVD risk factors in adulthood. Stabilizing BMI in obese adults and resolving elevated child BMI by adulthood might limit and reduce adverse cardiometabolic profiles. However, efforts to prevent child obesity might be most effective to reduce the risk for adult atherosclerosis.

Maternal inheritance of BDNF deletion, with phenotype of obesity and developmental delay in mother and child.

Childhood obesity is a significant world health problem. Understanding the genetic and environmental factors contributing to the development of obesity in childhood is important for the rational design of strategies for obesity prevention and treatment. Brain-derived neurotrophic factor (BDNF) plays an important role in the growth and development of the central nervous system, there is also an evidence that BDNF plays a role in regulation of appetite. Disruption of the expression of this gene in a child has been previously reported to result in a phenotype of severe obesity, hyperphagia, impaired cognitive function, and hyperactivity. We report a mother and child, both with micro-deletions encompassing the BDNF gene locus, who both have obesity and developmental delay, although without hyperactivity. This report highlights the maternal inheritance of a rare genetic cause of childhood obesity.

Bayesian hierarchical piecewise regression models: a tool to detect trajectory divergence between groups in long-term observational studies.

BACKGROUND: Bayesian hierarchical piecewise regression (BHPR) modeling has not been previously formulated to detect and characterise the mechanism of trajectory divergence between groups of participants that have longitudinal responses with distinct developmental phases. These models are useful when participants in a prospective cohort study are grouped according to a distal dichotomous health outcome. Indeed, a refined understanding of how deleterious risk factor profiles develop across the life-course may help inform early-life interventions. Previous techniques to determine between-group differences in risk factors at each age may result in biased estimate of the age at divergence. METHODS: We demonstrate the use of Bayesian hierarchical piecewise regression (BHPR) to generate a point estimate and credible interval for the age at which trajectories diverge between groups for continuous outcome measures that exhibit non-linear within-person response profiles over time. We illustrate our approach by modeling the divergence in childhood-to-adulthood body mass index (BMI) trajectories between two groups of adults with/without type 2 diabetes mellitus (T2DM) in the Cardiovascular Risk in Young Finns Study (YFS). RESULTS: Using the proposed BHPR approach, we estimated the BMI profiles of participants with T2DM diverged from healthy participants at age 16 years for males (95% credible interval (CI):13.5-18 years) and 21 years for females (95% CI: 19.5-23 years). These data suggest that a critical window for weight management intervention in preventing T2DM might exist before the age when BMI growth rate is naturally expected to decrease. Simulation showed that when using pairwise comparison of least-square means from categorical mixed models, smaller sample sizes tended to conclude a later age of divergence. In contrast, the point estimate of the divergence time is not biased by sample size when using the proposed BHPR method. CONCLUSIONS: BHPR is a powerful analytic tool to model long-term non-linear longitudinal outcomes, enabling the identification of the age at which risk factor trajectories diverge between groups of participants. The method is suitable for the analysis of unbalanced longitudinal data, with only a limited number of repeated measures per participants and where the time-related outcome is typically marked by transitional changes or by distinct phases of change over time.

Long term risk of severe retinopathy in childhood-onset type 1 diabetes: a data linkage study.

OBJECTIVES: To determine the relationship between glycaemic control trajectory and the long term risk of severe complications in people with type 1 diabetes mellitus, as well as the effects of paediatric and adult HbA1c levels. DESIGN, SETTING, PARTICIPANTS: Data linkage study of data for adults with childhood-onset type 1 diabetes (diagnosed during 1975-2010) who had transitioned from paediatric diabetes care at the Royal Children's Hospital (Melbourne) to adult diabetes care at the Royal Melbourne Hospital during 1992-2013. MAIN OUTCOME MEASURES: Severe complications were categorised as severe diabetic retinopathy (SDR), chronic kidney disease, ulceration or amputation, and death. Mean HbA1c levels were calculated for the paediatric and adult periods. Four glycaemic control trajectories were defined according to mean paediatric and adult HbA1c levels: stable low (paediatric and adult HbA1c ≤ 66 mmol/mol); improving (paediatric HbA1c > 66 mmol/mol, adult HbA1c ≤ 66 mmol/mol); worsening (paediatric HbA1c ≤ 66 mmol/mol, adult HbA1c > 66 mmol/mol); and stable high (paediatric and adult HbA1c > 66 mmol/mol). RESULTS: 503 eligible participants (253 men) were identified, 26 (5.2%) of whom had at least one severe complication, including 16 with SDR (3.2%). No-one in the stable low group, but 4% of the improving, 1% of the worsening, and 7% of the stable high groups developed SDR. Higher mean paediatric (per 10.9 mmol/mol increase: odds ratio [OR], 2.9; 95% CI, 1.9-4.3; P < 0.01) or adult HbA1c levels (OR, 2.1; 95% CI, 1.4-3.1; P < 0.01) were associated with increased risk of SDR, as was longer duration of type 1 diabetes (per additional year: OR, 1.3; 95% CI, 1.2-1.5; P < 0.01). CONCLUSION: SDR was associated with higher paediatric HbA1c levels, independent of glycaemic control during adulthood; it was not documented in patients with a stable low glycaemic control trajectory.

Continuous and Dichotomous Metabolic Syndrome Definitions in Youth Predict Adult Type 2 Diabetes and Carotid Artery Intima Media Thickness: The Cardiovascular Risk in Young Finns Study.

OBJECTIVES: To examine the utility of continuous metabolic syndrome (cMetS) scores vs a dichotomous metabolic syndrome (MetS) definition in youth to predict adult type 2 diabetes mellitus (T2DM) and carotid intima-media thickness (IMT). STUDY DESIGN: Participants (n = 1453) from the population-based, prospective, observational Cardiovascular Risk in Young Finns Study who were examined in youth (when aged 9-18 years) and re-examined 15-25 years later. Four cMetS scores were constructed according to procedures most often used in the literature that comprised the youth risk factor inputs of body mass index, blood pressure, glucose, insulin, high-density lipoprotein-cholesterol, and triglycerides. Adult outcomes included T2DM and high carotid IMT (≥ 90 th percentile). RESULTS: For a 1 SD increase in cMetS scores in youth, participants had a 30%-78% increased risk of T2DM and 12%-61% increased risk of high carotid IMT. Prediction of adult T2DM and high carotid IMT using cMetS scores in youth was essentially no different to a dichotomous MetS definition with area under the receiver-operating characteristic curve ranging from 0.54-0.60 (continuous definitions) and 0.55-0.59 (dichotomous) with 95% CIs often including 0.5, and integrated discrimination improvement from -0.2% to -0.6%. CONCLUSIONS: cMetS scores in youth are predictive of cardiometabolic outcomes in adulthood. However, they do not have increased predictive utility over a dichotomous definition of MetS.

Body mass index in ambulatory children with cerebral palsy: A cohort study.

AIM: Children with cerebral palsy (CP) have reduced levels of physical activity compared with children without physical disability and experience risk factors for becoming overweight or obese. In the Australian CP population, there is little information available about the weight status of children with CP. The aims of this study were to compare the distribution of body mass index (BMI) in a cohort of ambulant children with CP with the BMI distribution of Australian children and explore the relationship between BMI and gross motor function. METHODS: A retrospective cohort study of 587 children with CP Gross Motor Function Classification System (GMFCS) levels I-III who attended a Gait Laboratory between July 1995 and January 2012 was carried out. The BMI and Z-score were calculated at each assessment. Data were grouped into the categories of underweight, healthy, overweight and obese according to age-specific and sex-specific percentiles. RESULTS: There were 348 boys and 240 girls with a mean age 11.2 (standard deviation 3.2) years. Mean BMI Z-score was 0.11 (standard deviation 1.33). Seven percent of children were underweight, 73.6% healthy, 7.3% overweight and 12.1% obese. This was similar to the distribution of children without disability. The largest percentage of children in the healthy group were classified GMFCS I. The largest percentage of children in the obese group were classified GMFCS III. CONCLUSIONS: In this cohort, 19.4% of ambulant children with CP were overweight or obese. This is of concern as BMI may impact on the outcomes of surgical intervention and rehabilitation. Further research is needed to determine the consequences of obesity for children with CP.

Type 2 diabetes mellitus in children and adolescents.

BACKGROUND: The incidence of type 2 diabetes mellitus (T2DM) in children and adolescents is increasing, mirroring the epidemic of paediatric obesity. Early-onset T2DM is associated with poor long-term outcomes. OBJECTIVE: In this article, we describe the growing problem of early-onset T2DM in Australia, explore the difference between early-onset and adult-onset T2DM, and review the management of T2DM in children and adolescents. DISCUSSION: T2DM is difficult to differentiate from the more common type 1 diabetes mellitus (T1DM) in the paediatric population. Risk factors for T2DM include obesity, ethnicity and family history, and adolescence is a predisposing time for the development of T2DM due to physiological insulin resistance. Early-onset T2DM is more associated with shorter duration to insulin requirement, development of diabetic complications and cardiovascular disease than adult-onset T2DM and T1DM. The main goals in management include normalising hyperglycaemia, facilitating lifestyle modifications and managing diabetes-related and obesity-related comorbidities.

Viewpoint article: Childhood obesity--looking back over 50 years to begin to look forward.

The last 50 years have seen the emergence of childhood obesity as a major public health concern and a condition now regularly encountered in routine general paediatric practice. Causes are extremely complex, bringing together multifactorial environmental factors and individual genetics, and we still do not have a clear understanding of why some children appear predisposed to exaggerated and sometimes extreme weight gain. Overweight and obese children of today face an uncertain future. They are likely to experience higher rates of type 2 diabetes and heart disease, as well as many other health problems. However, while the prevalence of childhood obesity has progressively increased over the last few decades, so has research into its underlying causes. This has led to large-scale trials aimed at improving prevention or treatment. As data have emerged from such studies, we have begun to accept that the heterogeneity of obesity means that broad 'common sense' strategies to address diet and activity will not lead to success on their own. Now is the time to begin to build on this information, dispelling myths and beliefs, in order to focus research efforts and take first steps towards more sophisticated strategies that go beyond the surface behaviours that simply potentiate obesity. Through carefully designed studies, aimed at tackling fundamental questions missed in the hasty development of 'common sense' approaches, will come answers that can lead to the development of more effective community- and health-care-orientated prevention and treatment programmes.