The tempo and timing of puberty: associations with early adolescent weight gain and body composition over three years

Introduction: Adequate nutrition plays an important role in linear growth throughout childhood, including puberty. However, not all children are willing or able to consume an adequate and balanced diet daily. We aimed to evaluate the 1-year effectiveness and safety of nutritional supplementation on linear growth, weight gain, and changes in body composition in short and lean peripubertal boys. Methods: A 1-year, 2-phase multicenter interventional study comprising 1–6 months of a double-blinded intervention with nutritional formula or placebo, followed by 6–12 months of an open-label extension with the nutritional formula for all participants. Results: The outcomes of the double-blinded intervention were reported previously. A total of 79/98 (81%) boys, aged ≥10 years, Tanner stages 1–3, completed the open-labeled extension phase. For this phase, a significant dose-response correlation (p < 0.05) was found of the consumption of the formula with Δ height-SDS, Δ weight-SDS, and Δ muscle mass (crude correlations and after adjustment for baseline age and end-of-study Tanner stage). In the extension phase and in the 12-month analysis, participants who were good formula consumers (intake ≥50% of the recommended dose) maintained their height-SDS, while poor consumers had a significant decline in their height-SDS (p = 0.028 and p = 0.009, between group difference in the extension phase and 12-month analysis, respectively). Between-group differences were not observed in the Tanner stage at any point of the study. No serious adverse events were reported. Conclusions: An intervention in healthy peripubertal boys suggests that 1-year consumption of a multi-nutrient, protein-rich nutritional supplement is efficacious and safe. The induced changes in growth and body composition, although modest, may be clinically significant. The effect of the formula on growth parameters was not mediated by enhancement of the pubertal tempo.

Physical activity interventions alone often do not elicit favorable changes in body composition. However, most studies have reported only mean changes in body composition across treatment groups. PURPOSE: To examine the extent to which individual-level energy expended (EE) during an exercise program is associated with changes in body mass and composition. METHODS: The sample included 666 adult participants (43% men, 32% black) from the HERITAGE Family Study. The training involved a progressive (55-75% VO2max) 20-week cycling program. The power output and duration of each training session was recorded, and the EE (kcal) was calculated for each individual. Body weight, BMI, waist and hip circumference, fat mass (FM), fat free mass (FFM), percent body fat (%BF), CT-derived visceral adipose tissue (VAT) and subcutaneous tissue (SAT) were measured pre- and post-training. Stepwise regression models were used to determine associations between absolute changes (post-pre) in body composition from EE, age, race and baseline values. RESULTS: For the total sample, EE (mean ± SD) was 18,509 ± 6,966 kcal with -0.3 ± 2.5 kg weight loss. On average, men expended more than women (23,664 ± 6,652 vs. 14,607 ± 4,056 kcal; p<0.001) and whites expended more than blacks (20,200 ± 7,126 vs. 14,938 ± 5,008 kcal; p<0.001). For the total sample, changes in FM (p<0.01) and %BF (p<0.01) were negatively associated with EE. In women, EE was positively associated with changes in FFM (p<0.02). For men, EE was negatively associated with changes in weight (p<0.01), BMI (p<0.01), FM (p<0.03), and FFM (p<0.01). Overall, the variance in changes in body composition explained by EE was low (partial r2 = 0.5-2.3%). CONCLUSIONS: The average weight loss in this study was nominal and individual level energy expended was weakly associated with changes in body composition, particularly in men.

Both baseline cardiorespiratory fitness and adiposity predict the risk of cancer mortality. However, the effects of changes in these two factors over time have not been evaluated thoroughly. The aim of this study was to examine the independent and joint associations of changes in cardiorespiratory fitness and body composition on cancer mortality. The cohort consisted of 13,930 men (initially cancer-free) with two or more medical examinations from 1974 to 2002. Cardiorespiratory fitness was assessed by a maximal treadmill exercise test, and body composition was expressed by body mass index (BMI) and percent body fat. Changes in cardiorespiratory fitness and body composition between the baseline and the last examination were classified into loss, stable, and gain groups. There were 386 deaths from cancer during an average of 12.5 yr of follow-up. After adjusting for possible confounders and BMI, change hazard ratios (95% confidence intervals) of cancer mortality were 0.74 (0.57-0.96) for stable fitness and 0.74 (0.56-0.98) for fitness gain. Inverse dose-response relationships were observed between changes in maximal METs and cancer mortality (P for linear trend = 0.05). Neither BMI change nor percent body fat change was associated with cancer mortality after adjusting for possible confounders and maximal METs change. In the joint analyses, men who became less fit had a higher risk of cancer mortality (P for linear trend = 0.03) compared with those who became more fit, regardless of BMI change levels. Being unfit or losing cardiorespiratory fitness over time was found to predict cancer mortality in men. Improving or maintaining adequate levels of cardiorespiratory fitness appears to be important for decreasing cancer mortality in men.

To examine the utility of changes in cardiorespiratory fitness (CRF) and body composition in response to exercise training in adolescents with obesity beyond simple measures of body weight change. This is a secondary analysis of our previously published randomized trials of aerobic, resistance, and combined training. We included 104 adolescents (body mass index (BMI) ≥85th percentile) who had complete baseline and post-intervention data for CRF, regional body fat, insulin sensitivity, and oral glucose tolerance. Associations between changes in body composition and CRF with cardiometabolic variables were examined adjusted for age, sex, Tanner stage, race, exercise group, and weight loss. At baseline, CRF, visceral fat and liver fat were correlated with insulin sensitivity with and without adjustment for BMI percentile. Training-associated changes in CRF, visceral fat, and liver fat were also correlated with insulin sensitivity changes, but not independent of body weight change. After accounting for body weight change, none of the body composition or CRF were associated with changes in insulin sensitivity, glucose tolerance, systolic blood pressure, or high-density lipoprotein cholesterol. Although CRF and body composition were strong independent correlates of insulin sensitivity at baseline, changes in CRF and visceral fat were not associated with changes in insulin sensitivity after accounting for body weight change. Clinicaltrials.gov registration nos.: NCT00739180, NCT01323088, NCT01938950. Novelty With exercise training, changes in body weight, CRF, visceral fat, and liver fat were correlated with changes in insulin sensitivity. Changes in body composition or CRF generally did not remain significant correlates of changes in insulin sensitivity after adjusting for body weight changes.

Introduction: A previous epigenome-wide association study has causally linked DNA methylation (DNAm) at the SREBF1 gene (cg11024682) with obesity and lipids. However, little is known about whether DNAm at SREBF1 is associated with long-term changes in body adiposity and composition. Hypothesis: We hypothesized that participants with different DNAm at SRBF1 might respond differently to dietary weight-loss interventions on changes in body adiposity and composition. Methods: The current study included 314 individuals with overweight or obese, who participated in POUNDS Lost: a 2-year randomized dietary weight-loss trial. The blood DNAm level was profiled by methylC-capture sequencing at baseline. Regional DNAm at SREBF1 was calculated as the average methylation level over CpGs within ±250 bp of cg11024682. Body composition, including total fat mass (FM), percentage of FM (FM%), total fat-free mass (FFM), percentage of FFM (FFM%), and percentage of trunk fat (TF%) were measured by dual-energy X-ray absorptiometry (DEXA) at baseline, 6 months, and 2 years. Results: Lower regional DNAm at SREBF1 was significantly associated with changes in body composition across 2 years ( Table ). At 6 months, per SD lower regional DNAm at SREBF1 was significantly associated with greater reductions in FM (β [SE] -0.23 [0.07], p=0.002), FM% (-0.30 [0.09], p&lt;0.001), and TF% (-0.44 [0.13], p&lt;0.001), and greater increases in FFM (0.18 [0.08], p=0.028) and FFM% (0.30 [0.09], p&lt;0.001), regardless of dietary intervention groups and independent of concurrent weight loss. Such association remained at 2 years: FM (β [SE] -0.21 [0.10], p=0.045), FM% (-0.32 [0.11], p=0.004), TF% (-0.36 [0.16], p=0.026), FFM (0.22 [0.12], p=0.07) and FFM% (0.32 [0.11], p=0.004). Conclusions: Overweight and obese individuals with a lower regional DNAm at SREBF1 achieved greater improvement in body composition across the 2-year intervention, independent of concurrent weight loss, suggesting DNAm at SREBF1 is predictive of individuals’ response to treatment.

A cross-sectional analysis examining the impact of gender and early pubertal stage on insulin sensitivity (Si) and body composition was carried out as part of a longitudinal study to determine how Si relates to body composition changes during puberty. The study population consisted of 97 healthy children (age range, 9.7-14.5 yr; 28 Tanner stage 2 boys, 25 stage 3 boys, 22 Tanner stage 2 girls, and 22 stage 3 girls). Si was determined by the modified minimal model of Bergman. Body fatness was assessed by body mass index (BMI), skinfold thickness, hydrodensitometry, and bioelectrical impedance. Results showed that stage 3 girls and stage 2 boys had significantly more body fat than stage 2 girls and stage 3 boys. Si was significantly lower (P < 0.02) and insulin-like growth factor-I levels higher (P < 0.006) in stage 3 girls compared to those in the other 3 groups. The best predictor of Si in all subjects was BMI (r2 = -0.63; P < 0.0001). In a stepwise multiple regression analysis, Si was best predicted from BMI, gender, and Tanner stage. According to this model, Si decreased as BMI increased and was lower in girls and Tanner stage 3 children. In boys, Si was best predicted from total fat mass and Tanner stage. In girls, Si correlated inversely with BMI, parental obesity, and insulin-like growth factor-I levels. Neither testosterone nor estradiol levels were associated with Si. These results demonstrate that Si, like body composition, has gender-dependent changes during puberty. It is, thus, possible that these pubertal changes in Si relate to changes in body composition.

Changes in body composition in women using long-acting reversible contraception

Most of the mothers are very attentitve to changes in body composition, especially postpartum weight loss. One of the factors believed to facilitate the weight loss and body fat loss in postpartum mothers is breastfeeding. Factor that affect the relationship between breastfeeding with maternal postpartum body composition are food intake and physical activity. The aim of this study is to analyze the change in body composition between the mother who give exclusive breastfeeding for 6 months and the mother who don’t and also attempts to analyze the effect of breastfeeding duration to the change in body composition and the factor affecting it.This study used the panel study with longitudinal approach. 32 respondents observed for 6 months. Fat mass measurement data are collected using skinfold caliper and breastfeeding status, food intake and physical actiuvity data are collected using interview. The relationship between breastfeeding with the change in body composition is analyzed using t-test analysis. T-test analysis are also used to test the effect of food intake and physical activity to breastfeeding. Regression analysis are used to analyze the effect of food intake and physical activity to body composition.According to the result of statistical analysis, there is no significance effect of breastfeeding for 6 months to the change in maternal postpartum body composition (fat mass and free fat mass) (p = 0.743; p = 0.771) and also no significance effect of food intake and physical activity to the relation between breastfeeding with the change in body composition. There is a significance effect of breastfeeding for 4 months to the change in the body composition (p = 0.046). The average fat mass change in mother who give exclusive breastfeed is higher than the one who don’t.From 32 respondents in this study, only 4 mothers can successfully give exclusive breastfeed for 6 months. The average fat mass change in mother who give exclusive breastfeed is higher than the one who don’t. There is no significance effect of breastfeeding for 6 months to the change in maternal postpartum body composition (fat mass and free fat mass). There is a significance effect of breastfeeding for 4 months to the change in maternal postpartum body composition.Keywords: Breastfeeding, body composition, maternal postpartum

Because of the improved survival rate, both short term and long term adverse effects of breast cancer treatment have become increasingly important. Body weight and body composition before, during, and after chemotherapy may influence side effects during treatment and survival. The aims of this thesis were to assess among stage I-IIIB breast cancer patients: 1) the association between pre-treatment body composition and dose-limiting toxicities during chemotherapy, 2) potential changes in body weight and body composition during and after chemotherapy compared to changes in age-matched women without cancer in the same time period, and 3) dietary intake during chemotherapy compared to age-matched women without cancer in the same time period. Chapter 2 describes the association between pre-treatment body composition and dose-limiting toxicities during chemotherapy. Data from 172 breast cancer patients who participated in the COBRA-study were analysed. Body composition was measured using a total body Dual Energy X-ray Absorption (DEXA) scan. Information regarding dose-limiting toxicities was abstracted from medical records. A higher BMI (kg/m2) and a higher fat mass (kg and percentage) were associated with an increased risk of dose-limiting toxicity, while lean body mass (kg) was not associated with risk of toxicities. Chapter 3 presents the findings of a meta-analysis on changes in body weight during chemotherapy in breast cancer patients. The meta-analysis showed an overall gain in body weight of 2.7 kg (95% CI: 2.0-3.3) during chemotherapy, with a high degree of heterogeneity (I2= 94.2%). Weight gain in breast cancer patients was more pronounced in papers published before 2000 and studies including cyclophosphamide, methotrexate and 5-fluorouracil as chemotherapy regime. Chapter 4 describes changes in body weight and body composition during and after chemotherapy. Data from 145 patients and 121 women of an age-matched comparison group, participating in the COBRA-study were analysed. Body composition was measured using DEXA-scan at three time points during the study period. For the patient group, these tie points were: before start of chemotherapy, shortly after chemotherapy, and 6 months after chemotherapy. For the comparison group these measurements were conducted over a similar time frame: baseline, 6 months after baseline, and 12 months after baseline. In addition, we identified determinants of changes in body weight and body composition. Shortly after chemotherapy, patients had a significantly higher body weight, BMI, and lean body mass than women in the comparison group, while fat mass was similar. Six months after chemotherapy no differences in body weight or body composition were observed between the patient and comparison group. A younger age, better appetite during chemotherapy, and an ER-receptor negative tumour were associated with greater changes in body weight over time. A younger age and better appetite during chemotherapy were associated with greater changes in fat mass over time, while the only determinant associated with greater changes in lean body mass over time was a better appetite during chemotherapy. Chapter 5 describes the dietary intake and food groups before and during chemotherapy of breast cancer patients compared with women without cancer. In addition we assessed the association between symptoms and energy intake. Data from 117 breast cancer patients and 88 women without breast cancer who participated in the COBRA-study were used. Habitual dietary intake before chemotherapy was assessed using a food frequency questionnaire. Two 24-hr dietary recalls were used to assess actual dietary intake during chemotherapy for patients and within 6 months for the comparison group. Shortly after the 24-hr dietary recall, participants filled out questionnaires about symptoms. Before chemotherapy, dietary intake was similar for both groups. During chemotherapy, breast cancer patients reported significantly lower total energy, total fat, total protein, and alcohol intake than women without cancer, which could be explained by a lower intake of specific food groups. Overall results from this thesis suggest that pre-treatment fat mass is associated with dose-limiting toxicities during chemotherapy. Weight gain during chemotherapy appeared to be more modest than we expected based on literature and changes in body composition during chemotherapy consist mainly of an increase in lean body mass, which is only temporary and returned to baseline within 6 months after chemotherapy. A higher appetite during chemotherapy was associated with changes in body weight and body composition. A younger age at diagnosis was associated with greater changes in body weight and fat mass, but not with changes in lean body mass. In addition, an ER-receptor negative tumour was associated with greater changes in body weight, but not with changes in fat mass or lean body mass. During chemotherapy women with breast cancer have a lower intake of energy, fat, protein and alcohol compared to age-matched women without cancer, which was expressed in a lower intake of specific food groups. The results of this thesis do not suggest that dietary intake is associated with weight gain during chemotherapy.

Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan

Correlation of Body Mass Index to Dual-Energy X-Ray Absorptiometry in Assessment of Body Composition during Therapy for Childhood Acute Lymphoblastic Leukemia

Bone mineral accretion during childhood and adolescence is subject to a number of influences, including body composition changes, sexual maturation and growth. Bone mass and density increase with age and vary by sex, so bone health must be evaluated like other growth outcomes, i.e. in relation to age- and sex-specific reference ranges. Peak bone mass, the amount of bone acquired at the end of skeletal development is an important determinant of lifelong skeletal health. The timing of puberty is inversely related to peak bone mass, such that individuals who experience puberty at older ages have lower bone mass in young adulthood. Height, an indicator of skeletal size, is correlated with bone mineral content and density. Even more importantly, children who are tall for their age have greater bone mass and density than children of average or short stature. Body composition, particularly lean body mass, has a positive effect on bone accretion because of the mechanical strains of muscle mass on bone accretion. The effect of height growth is positively associated with bone accretion, but the magnitude of the effect is not the same at all pubertal stages; in Tanner stage 5, height growth has a more pronounced effect on bone accretion than at the beginning of puberty. Understanding these complex relationships is essential to understanding bone metabolism during this part of the life cycle and the challenges of assessing bone health in children with medical conditions that threaten bone health.

Traditionally, puberty has been the peak time for diagnosis of type 1 diabetes in childhood,1 thought to reflect a transient pubertal increase in insulin resistance (IR). The increase was first described by Amiel et al.2 in 1986, and subsequently reported in cross-sectional studies.3-6 Despite comparable insulin secretion, IR was reportedly around 30% higher in both healthy and diabetic adolescents at Tanner stages 2 to 4 compared with prepubertal children or adults. More recently, however, the pubertal peak in type 1 diabetes incidence has been lost, with a shift towards presentation in early to mid-childhood, before the onset of puberty.7-11 This has occurred alongside a rising incidence of childhood type 1 diabetes,12 and the advent of type 2 diabetes diagnoses in adolescents and children.13 Indeed, in some racial groups (Asian Pacific Islanders14 and American Indians15), the rate of new cases of type 2 diabetes exceeds that of type 1. In Japanese school children, type 2 diabetes is seven times more common than type 1, and its incidence has increased more than 30-fold over the past 20 years,16 while in African American and Hispanic young people aged 10–19 years, the rate of new cases of both types of diabetes is similar.17 How much of the shift towards younger presentation of diabetes can be attributed to increasing obesity? Longitudinal study is needed to understand the contribution of changing body composition to the changes in IR. A number of longitudinal studies have replicated Amiel's observation of higher IR during pubertal development;18-22 however, until very recently, only two groups had been able to measure IR more than twice in the same children. Moran et al.23 measured adolescents on three occasions, and found a rise in IR that was independent of the normal maturational changes in adiposity. In contrast, Hoffman et al.,24 measuring children three times over an 18-month period from 10 years found no changes in insulin sensitivity between Tanner stages which were independent of changes in BMI. Interpretation has been all the more difficult because existing longitudinal studies of IR during puberty have used different methods to determine onset of puberty, and have reported on children of widely varying age at baseline.18-24 The youngest reported mean age was 9.2 years in a repeated measures study by Goran and Gower,19 while others began with children aged between 9.8 and 13 years18, 20, 21, 23, 24 or even at Tanner stage 2.22 Entering puberty early has been shown to increase the risk for later diabetes and cardiovascular disease25, 26 although the wide variation in the timing and duration of normal puberty, and the mechanisms controlling physiological regulation of puberty are still relatively poorly understood. A cohort of uniform age, with repeated measures from early childhood together with an objective measure of pubertal onset was needed to establish the association between IR and puberty. In the most detailed study to date of IR trends in healthy prepubertal and early pubertal children, the EarlyBird Diabetes Study recently reported on 235 healthy children measured annually from 5–14 years.27 Pubertal onset was ascertained in two ways – the hormonal onset pinpointed by the first detection of luteinising hormone (LH) ≥0.2U/L, sustained over two consecutive measures, while phenotypic onset was self-assessed Tanner stage 2 (mean genital/breast and pubic hair development). IR, measured by HOMA, fell initially from 5–7 years, and then rose significantly year-on-year up to 12 years in girls and 14 years in boys. Importantly, the rise in IR began four years before the first detectable rise in LH, and four years before the first reported phenotypic change in both genders. Linear mixed-effects modelling revealed that increases in % fat (measured by dual energy x-ray absorptiometry) accounted for 25% of the increase in IR in boys (30% in girls) over the four-year period leading up to pubertal onset. However, even when adjusting for % fat, height, age, physical activity, socio-economic status and IGF-1, 55% of the prepubertal rise in IR in boys (61% in girls) remained unexplained. The reason for this mid-childhood rise in IR remains unclear, although increased secretion of steroidal adrenal hormones (adrenarche), which typically occurs at 6–8 years, is a possible contributor. Measures of dehydroepiandrosterone sulphate in the EarlyBird cohort should clarify this. This is the first report of ‘prepubertal insulin resistance’ in healthy children, revealed only by repeated measurements in the same children from an early age. The rise in IR occurred in all children, whatever their adiposity, although it was more pronounced in fatter children, particularly girls. The majority of children and adolescents with type 2 diabetes are female, consistent with their greater adiposity and IR. The implications of the EarlyBird findings are that the period of increased risk for new diabetes now extends back to mid-childhood, rather than being restricted to the ‘pubertal’ teenage years. In addition, clinicians treating children with type 1 diabetes should be aware of increased IR, and thus increased insulin requirement, from the age of 7–8 years. Further EarlyBird publications will examine IR trends over the late pubertal period and determine whether the period of increased risk now extends from mid-childhood up to full maturation, or whether IR returns to normal ‘prepubertal’ levels earlier than previously thought, and how IR trends differ between the genders. The finding that adiposity is the greatest determinant of childhood IR is not new, but gives increasing cause for concern given current obesity levels in children. The UK National Child Measurement Programme recently published its findings on data collected during the 2010/11 school year (www.ic.nhs.uk/ncmp). Among Reception Year children (age 4–5) almost one in 10 (9.4% of those measured) was obese, while in Year 6 (age 10–11) the proportion had risen to almost one in five (19%). Nationally, 93% of all eligible children were measured. Since the beginning of the Child Measurement Programme, the proportion of overweight and obese children in Reception Year has remained virtually unchanged (22.9% in 2006/7, 22.6% in 2010/11). In Year 6, however, the proportion has increased from 31.6% in 2006/7 to 33.4% in 2010/11. The underlying trend is therefore for an increasing number of children to become overweight or obese during their primary school years, exactly at the time when the physiological increase in IR puts them at risk of developing diabetes. It would seem that the public health message to tackle childhood obesity is still not getting through, particularly in deprived urban areas of the UK (www.ic.nhs.uk/ncmp). The individual, societal and financial burdens of the obesity epidemic, along with the associated morbidity from type 2 diabetes and heart disease, are likely to weigh heavily on the next generation of young adults. The EarlyBird findings suggest that the insulin resistance of puberty, thought to coincide with phenotypic changes, may instead be an age-related phenomenon, starting in mid-childhood, and increasing in intensity in response to changes in sex hormones and body composition. The period of increased risk in susceptible children may extend for longer than previously thought and applies to all children from the age of 7 years, irrespective of fat levels, although fatter children will be most at risk. I am grateful to Professor Terry Wilkin and to Dr Linda Voss, to the other EarlyBird team members, and to the EarlyBird children and their parents. I acknowledge the support of the Novo Nordisk UK Research Foundation, and our current sponsors: the Bright Futures Trust, the EarlyBird Diabetes Trust, the Kirby Laing Foundation and the Peninsula Foundation, Plymouth, UK.

The onset of puberty is a period of rapid anatomical and physiological alterations expected to induce changes in metabolic rate and energy requirements of children. To evaluate the changes in anthropometrical features, body composition, physical capacities, and energy expenditure (EE) of boys and girls during the period of onset of puberty. Sixteen children (8 boys and 8 girls were recruited in the same school-class and studied both at 10.4 and 12.8 years of age. Body composition was assessed by bioimpedance analysis. Peak oxygen uptake (peak VO2) was measured using an automated on-line system during exercising on a cycle ergometer. Energy expenditure (EE) was determined by whole-body indirect calorimetry over a 24-h period after a 12-h period of adaptation to the calorimeters. Volunteers followed the same activity programme that included four 15-min periods of exercise. During the onset of puberty, boys and girls gained 4.7 +/- 2.1 kg x y(-1) (P < 0.0003) fat-free mass (FFM), whereas fat mass gain was 1.0 +/- 1.2 kg x y(-1) (P < 0.05) in girls and 0.20 +/- 0.66 kg x y(-1) in boys (NS). Peak VO2 adjusted for differences in FFM was not significantly affected by gender or pubertal stage. However, adjusted external mechanical power performed at peak VO2 was higher in pubertal than in prepubertal children, by 40% (P < 0.0001) and 22% (P < 0.003) in boys and girls, respectively. It was also 17% (P < 0.0002) higher in pubertal boys than in pubertal girls. Daily and sleeping EE increased by 38% and 32% in boys and girls, respectively, during the 2.4-y period (P< 0.0001). Adjusted EEs were also significantly higher in pubertal than in prepubertal boys (P< 0.05 and P< 0.003), but not in girls. The main significant determinants of daily EE were FFM (r2 = 0.866, P < 0.0001), peak VO2 (r2 = 0.017, P < 0.04), and age (r2 = 0.014, P < 0.05). Tanner's stage was an additional determinant of sleeping EE (r2 = 0.025, P < 0.006). The increases in physical capacities and EE during the onset of puberty indicated clear gender differences, which could be explained mainly by alterations of body composition in boys and girls, and by changes in hormonal status in boys. They also stressed the significant increase in energy requirements of children, especially boys, at an early stage of puberty.

During recovery, stroke patients are at risk of developing long-term complications that impact quality of life, including changes in body weight and composition, depression and anxiety, as well as an increased risk of subsequent vascular events. The aetiologies and time-course of these post-stroke complications have not been extensively studied and are poorly understood. Therefore, we assessed long-term changes in body composition, metabolic markers and behaviour after middle cerebral artery occlusion in mice. These outcomes were also studied in the context of obesity, a common stroke co-morbidity proposed to protect against post-stroke weight loss in patients. We found that stroke induced long-term changes in body composition, characterised by a sustained loss of fat mass with a recovery of lean weight loss. These global changes in response to stroke were accompanied by an altered lipid profile (increased plasma free fatty acids and triglycerides) and increased adipokine release at 60 days. After stroke, the liver also showed histological changes indicative of liver damage and a decrease in plasma alanine aminotransferase (ALT) was observed. Stroke induced depression and anxiety-like behaviours in mice, illustrated by deficits in exploration, nest building and burrowing behaviours. When initial infarct volumes were matched between mice with and without comorbid obesity, these outcomes were not drastically altered. Overall, we found that stroke induced long-term changes in depressive/anxiety-like behaviours, and changes in plasma lipids, adipokines and the liver that may impact negatively on future vascular health.