Height, adiposity and hormonal cardiovascular risk markers in childhood: how to partition the associations?

Objective:Obesity is associated with rapid growth during childhood. There is uncertainty over how to adjust for body size, when using adiposity as a proxy for cardiovascular risk. We studied associations of height, body composition (by dual-energy X-ray absorptiometry) and cardiovascular risk markers (insulin resistance (IR), leptin) in children.Methods:Using partial correlations in 172 children aged 7-12 years, we investigated associations of (a) fat mass with IR or leptin, adjusting for height, or lean mass, and (b) height or lean mass with IR or leptin, adjusting for fat mass. Analyses were conducted both cross-sectionally at each age, and for changes between 7 and 12 years.Results:Height, fat mass, lean mass, IR and leptin were all inter-correlated at all ages. Whilst fat mass was strongly associated with IR and leptin, height was independently negatively associated with leptin (whole sample, adjusting for age: boys r=-0.12, girls r=-0.13; P<0.001). Independent of adiposity, height was also associated with insulin IR (whole sample, adjusting for age: boys r=0.11, girls r=0.20; P<0.001). When analyzed by year of age, these associations tended to remain significant at older ages. Change in height from 7-12 years was also associated with change in IR (boys: r=0.18, P<0.05; girls: r=0.34, P<0.01), independently of change in adiposity, with similar findings for lean mass.Conclusions:During childhood, markers of cardiovascular risk have a complex profile, responding to growth as well as fat accumulation. Taller and faster-growing children have elevated risk markers, independently of their adiposity. These findings have implications for the interpretation of pediatric indices of adiposity that aim to adjust for body size. Adiposity indices that perform best at summarizing metabolic risk may not be those that perform best at understanding the developmental aetiology of risk.International Journal of Obesity accepted article preview online, 10 February 2014; doi:10.1038/ijo.2014.24

A FAMILY OF CATION ATPASE-LIKE MOLECULES FROM PLASMODIUM-FALCIPARUM

Abstract. We report the nucleotide and derived amino acid sequence of the ATPase 1 gene from Plasmodium falciparum. The amino acid sequence shares homology with the family of &quot;P-type cation transloeating ATPases in conserved regions important for nucleotide binding, conformational change, or phosphorylation. The gene, which is present on chromosome 5, has a product longer than any other reported for a P-type ATPase. Interstrain analysis from 12 parasite isolates by the polymerase chain reaction reveals that a 330-bp nucleotide sequence encoding three cytoplasmic regions conserved in cation ATPases (regions a-c) is of constant length. By contrast, another 360-bp sequence which is one of four regions we refer to as

Commentary: Paternal and maternal influences on offspring phenotype: the same, only different.

In mammals, the female provides substantially more repro-ductive investment than the male. Biologists have long wondered why exactly this should be so. According to Dawkins and Carlyle, the answer is simply that, with in-ternal fertilization, males get the first opportunity to de-fault on parental care, and females are left, quite literally, holding the baby.1 Whether or not males actually provide parental care can then be negotiated: marmoset males pro-vide a lot, even undergoing pregnancy weight gain to fund their postnatal care,2 whereas hedgehogs offer nothing. In teleost fish, for whom fertilization is external, it is the fe-males who vanish after laying the eggs and the males who provide doting parental care.1 In energetic terms, female mammals have a much greater ‘reproductive energy bur-den ’ than males, but it has also been proposed that thi

The evolution of human adiposity and obesity: where did it all go wrong?

Because obesity is associated with diverse chronic diseases, little attention has been directed to the multiple beneficial functions of adipose tissue. Adipose tissue not only provides energy for growth, reproduction and immune function, but also secretes and receives diverse signaling molecules that coordinate energy allocation between these functions in response to ecological conditions. Importantly, many relevant ecological cues act on growth and physique, with adiposity responding as a counterbalancing risk management strategy. The large number of individual alleles associated with adipose tissue illustrates its integration with diverse metabolic pathways. However, phenotypic variation in age, sex, ethnicity and social status is further associated with different strategies for storing and using energy. Adiposity therefore represents a key means of phenotypic flexibility within and across generations, enabling a coherent life-history strategy in the face of ecological stochasticity. The sensitivity of numerous metabolic pathways to ecological cues makes our species vulnerable to manipulative globalized economic forces. The aim of this article is to understand how human adipose tissue biology interacts with modern environmental pressures to generate excess weight gain and obesity. The disease component of obesity might lie not in adipose tissue itself, but in its perturbation by our modern industrialized niche. Efforts to combat obesity could be more effective if they prioritized 'external' environmental change rather than attempting to manipulate 'internal' biology through pharmaceutical or behavioral means

Use of fat mass and fat free mass standard deviation scores obtained using simple measurement methods in healthy children and patients: comparison with the reference 4-component model

Background Clinical application of body composition (BC) measurements for individual children has been limited by lack of appropriate reference data. Objectives (1) To compare fat mass (FM) and fat free mass (FFM) standard deviation scores (SDS) generated using new body composition reference data and obtained using simple measurement methods in healthy children and patients with those obtained using the reference 4-component (4-C) model; (2) To determine the extent to which scores from simple methods agree with those from the 4-C model in identification of abnormal body composition. Design FM SDS were calculated for 4-C model, dual-energy X-ray absorptiometry (DXA; GE Lunar Prodigy), BMI and skinfold thicknesses (SFT); and FFM SDS for 4CM, DXA and bioelectrical impedance analysis (BIA; height2/Z)) in 927 subjects aged 3.8–22.0 y (211 healthy, 716 patients). Results DXA was the most accurate method for both FM and FFM SDS in healthy subjects and patients (mean bias (limits of agreement) FM SDS 0.03 (±0.62); FFM SDS −0.04 (±0.72)), and provided best agreement with the 4-C model in identifying abnormal BC (SDS ≤−2 or ≥2). BMI and SFTs were reasonable predictors of abnormal FM SDS, but poor in providing an absolute value. BIA was comparable to DXA for FFM SDS and in identifying abnormal subjects

Worldwide variability in growth: incorporating developmental plasticity, body composition and maternal effects

In their seminal book “Worldwide variation in human growth,” published in 1976, Eveleth and Tanner highlighted substantial variability within and between populations in the magnitude and schedule of human growth. In the four decades since then, research has clarified why growth variability is so closely associated with human health. First, growth patterns are strongly associated with body composition, both in the short- and long-term. Poor growth in early life constrains the acquisition of lean tissue, while compensatory “catch-up” growth may elevate body fatness. Second, these data are examples of the fundamental link between growth and developmental plasticity. Growth is highly sensitive to ecological stresses and stimuli during early “critical windows,” but loses much of this sensitivity as it undergoes canalization during early childhood. Crucially, the primary source of stimuli during early “critical windows” is not the external environment itself, but rather maternal phenotype, which transduces the impact of ecological conditions. Maternal phenotype, representing many dimensions of “capital,” thus generates a powerful impact on the developmental trajectory of the offspring. There is increasing evidence that low levels of maternal capital impact the offspring's size at birth, schedule of maturation, and body composition and physiological function in adulthood. While evidence has accrued of substantial heritability in adult height, it is clear that the pathway through which it is attained has major implications for metabolic phenotype. Integrating these perspectives is important for understanding how developmental plasticity may on the one hand contribute to adaptation, while on the other shape susceptibility to non-communicable disease

Prenatal, birth and early life predictors of sedentary behavior in young people: a systematic review

BACKGROUND: Our aim was to systematically summarize the evidence on whether prenatal, birth and early life factors up to 6 years of age predict sedentary behavior in young people (≤18 years). METHODS: PRISMA guidelines were followed, and searches were conducted in PubMed, SPORTDiscus, EMBASE and Web of Science up to December 1, 2015. We included observational (non-intervention) and longitudinal studies, that reported data on the association between one or more of the potential predictors and objectively or subjectively measured sedentary behavior. Study quality was assessed using a formal checklist and data extraction was performed using standardized forms independently by two researchers. RESULTS: More than 18,000 articles were screened, and 16 studies, examining 10 different predictors, were included. Study quality was variable (0.36-0.95). Two studies suggest that heritability and BMI in children aged 2-6 years were significant predictors of sedentary behavior later in life, while four and seven studies suggest no evidence for an association between gestational age, birth weight and sedentary behavior respectively. There was insufficient evidence whether other prenatal, birth and early life factors act as predictors of later sedentary behavior in young people. CONCLUSION: The results suggest that heritability and early childhood BMI may predict sedentary behavior in young people. However, small number of studies included and methodological limitations, including subjective and poorly validated sedentary behavior assessment, limits the conclusions. TRIAL REGISTRATION: The systematic review is registered in the International Prospective Register of Systematic Reviews, PROSPERO, 17.10.2014 ( CRD42014014156)

The "drive to eat" hypothesis: energy expenditure and fat-free mass but not adiposity are associated with milk intake and energy intake in 12 week infants

BACKGROUND: Recent work has challenged the long-held assumption that appetite functions to maintain stable body mass and fat mass (FM), suggesting instead that appetite matches food intake to energy expenditure and its correlate, fat-free mass (FFM). Whether this scenario applies to young infants, in chronic positive energy balance, remains unknown. OBJECTIVES: To test associations of components of energy expenditure and body composition with milk intake (MI) and energy intake (EI) in 12-week infants, by reanalyzing published cross-sectional data. METHODS: Data were available for 48 infants. In addition to anthropometric measurements, we assessed MI and EI by test-weighing, sleeping metabolic rate (SMR) by indirect calorimetry, and FFM, FM, and total energy expenditure (TEE) by doubly labeled water. Mean parental height was calculated as a marker of infant growth drive. Correlation and multiple regression analyses were applied. RESULTS: MI and EI correlated with FFM (r = 0.47 and 0.57, respectively; P  0.6). MI and EI correlated with SMR (r = 0.42 and 0.53, respectively; P  0.2). In a multiple regression analysis, MI was independently associated with TEE (partial r = 0.39) and FFM (partial r = 0.35). EI showed similar associations. Mean parental height was correlated with weight gain, MI, and EI. CONCLUSIONS: As in adults, MI and EI in young infants were strongly associated with FFM and with total and sleeping components of energy expenditure, but not with fatness. The infant's growth drive contributed to these associations. This suggests that appetite is regulated by the rate of energy expenditure, the size of energy-using tissues, and tissue deposition rate, and that the high levels of body fat characteristic of infants may not constrain weight gain

Resting Energy Expenditure of Children With End-stage Chronic Liver Disease Before and After Liver Transplantation

Objectives: Our objective was to test the hypothesis that children with end-stage chronic liver disease (ESCLD) are hypermetabolic when compared to healthy children, and that this hypermetabolism persists for at least 6 months after liver transplant. Methods: Seventeen patients with end-stage chronic liver disease and 14 healthy controls had their resting energy expenditure measured (mREE) by indirect calorimetry. Weight, height, and body mass index were converted to standard deviation (SD) scores. Children older than 5 years had air displacement plethysmography and patients older than 5 years also had whole body dual-energy X-ray absorptiometry with characterization of fat mass (FM), fat-free mass (FFM), and bone-free fat free (lean) mass. Results: When compared to the prediction equation 44% of the patients and 50% of the healthy controls were hypermetabolic. The younger patients (0–5 years) had a lower mREE than the healthy controls but were significantly lighter and shorter than their healthy counterparts. mREE correlated strongly for all children with age, weight, height, and FFM. There was a strong negative correlation between age and mREE/kg in both patients (rs = −0.94, P < 0.01) and controls (rs = −0.91, P < 0.01). Almost 84% of the variance in mREE was explained by age (P < 0.001). There were no significant differences between resting energy expenditure (REE)/FFM between the 2 groups. mREE/kg before liver transplant correlated with mREE/kg after transplant (Pearson r = 0.83, P < 0.01). Conclusions: REE mostly reflected the size of the child. The patients were not hypermetabolic when compared to the healthy children. The main determinant of REE/kg after transplant was REE/kg before transplant