Dalia Haroun

Pediatric reference data for lean tissue properties: density and hydration from age 5 to 20 y

BACKGROUND Hydrometry and densitometry are widely used to assess pediatric body composition due to their ease of application. The accuracy of these techniques depends on the validity of age- and sex-specific constant values for lean tissue hydration or density. Empirical data on these constants, and their variability between individuals, are lacking. OBJECTIVES The objectives were to measure lean tissue hydration and density in a large sample of children and adolescents and to derive prediction equations. DESIGN Body composition was measured in 533 healthy individuals (91% white) aged 4-23 y by using the 4-component model. Age- and sex-specific median values for hydration and density were obtained by using the LMS (lambda, mu, sigma) method. Regression analysis was used to generate prediction equations on the basis of age, sex, and body mass index SD score (BMI SDS). Values were compared with those in previously published predictions. RESULTS Age-associated changes in density and hydration differed between the sexes. Compared with our empirical values, use of published values resulted in a mean bias of 2.1% fat (P < 0.0001). Age, sex, and BMI SDS were all significant predictors of lean tissue hydration and density. With adjustment for age and sex, hydration was higher, and density lower, in higher-BMI SDS individuals. CONCLUSIONS The chemical maturation of lean tissue is not a linear process and proceeds differently in males and females. Previously published reference values are inaccurate and induce clinically significant bias in percentage fat. New empirical reference values are provided for use in pediatric hydrometry and densitometry. Further research that extends to cover nonwhite ethnic groups is needed.

Body-composition reference data for simple and reference techniques and a 4-component model: a new UK reference child

BACKGROUND A routine pediatric clinical assessment of body composition is increasingly recommended but has long been hampered by the following 2 factors: a lack of appropriate techniques and a lack of reference data with which to interpret individual measurements. Several techniques have become available, but reference data are needed. OBJECTIVE We aimed to provide body-composition reference data for use in clinical practice and research. DESIGN Body composition was measured by using a gold standard 4-component model, along with various widely used reference and bedside methods, in a large, representative sample of British children aged from 4 to ≥20 y. Measurements were made of anthropometric variables (weight, height, 4 skinfold thicknesses, and waist girth), dual-energy X-ray absorptiometry, body density, bioelectrical impedance, and total body water, and 4-component fat and fat-free masses were calculated. Reference charts and SD scores (SDSs) were constructed for each outcome by using the lambda-mu-sigma method. The same outcomes were generated for the fat-free mass index and fat mass index. RESULTS Body-composition growth charts and SDSs for 5-20 y were based on a final sample of 533 individuals. Correlations between SDSs by using different techniques were ≥0.68 for adiposity outcomes and ≥0.80 for fat-free mass outcomes. CONCLUSIONS These comprehensive reference data for pediatric body composition can be used across a variety of techniques. Together with advances in measurement technologies, the data should greatly enhance the ability of clinicians to assess and monitor body composition in routine clinical practice and should facilitate the use of body-composition measurements in research studies.

Validation of BIA in Obese Children and Adolescents and Re-evaluation in a Longitudinal Study

Decrease in fat mass (FM) is a one of the aims of pediatric obesity treatment; however, measurement techniques suitable for routine clinical assessment are lacking. The objective of this study was to validate whole‐body bioelectrical impedance analysis (BIA; TANITA BC‐418MA) against the three‐component (3C) model of body composition in obese children and adolescents, and to test the accuracy of our new equations in an independent sample studied longitudinally. A total of 77 white obese subjects (30 males) aged 5–22 years, BMI‐standard deviation score (SDS) 1.6–3.9, had measurements of weight, height (HT), body volume, total body water (TBW), and impedance (Z). FM and fat‐free mass (FFM) were calculated using the 3C model or predicted from TANITA. FFM was predicted from HT2/Z. This equation was then evaluated in 17 other obese children (5 males) aged 9–13 years. Compared to the 3C model, TANITA manufacturers equations overestimated FFM by 2.7 kg (P < 0.001). We derived a new equation: FFM = −2.211 + 1.115 (HT2/Z), with r2 of 0.96, standard error of the estimate 2.3 kg. Use of this equation in the independent sample showed no significant bias in FM or FFM (mean bias 0.5 ± 2.4 kg; P = 0.4), and no significant bias in change in FM or FFM (mean bias 0.2 ± 1.8 kg; P = 0.7), accounting for 58% (P < 0.001) and 55% (P = 0.001) of the change in FM and FFM, respectively. Our derived BIA equation, shown to be reliable for longitudinal assessment in white obese children, will aid routine clinical monitoring of body composition in this population.

Evaluation of DXA against the four-component model of body composition in obese children and adolescents aged 5-21 years.

Background:Body composition is increasingly measured in pediatric obese patients. Although dual-energy X-ray absorptiometry (DXA) is widely available, and is precise, its accuracy for body composition assessment in obese children remains untested.Objective:We aimed to evaluate DXA against the four-component (4C) model in obese children and adolescents in both cross-sectional and longitudinal contexts.Design:Body composition was measured by DXA (Lunar Prodigy) and the 4C model in 174 obese individuals aged 5–21 years, of whom 66 had a second measurement within 1.4 years. The Bland–Altman method was used to assess agreement between techniques for baseline body composition and change therein.Results:A significant minority of individuals (n=21) could not be scanned successfully due to their large size. At baseline, in 153 individuals with complete data, DXA significantly overestimated fat mass (FM; Δ=0.9, s.d. 2.1 kg, P<0.0001) and underestimated lean mass (LM; Δ=−1.0, s.d. 2.1 kg, P<0.0001). Multiple regression analysis showed that gender, puberty status, LM and FM were associated with the magnitude of the bias. In the longitudinal study of 51 individuals, the mean bias in change in fat or LM did not differ significantly from zero (FM: Δ=−0.02, P=0.9; LM: Δ=0.04, P=0.8), however limits of agreement were wide (FM: ±3.2 kg; LM: ±3.0 kg). The proportion of variance in the reference values explained by DXA was 76% for change in FM and 43% for change in LM.Conclusions:There are limitations to the accuracy of DXA using Lunar Prodigy for assessing body composition or changes therein in obese children. The causes of differential bias include variability in the magnitude of tissue masses, and stage of pubertal development. Further work is required to evaluate this scenario for other DXA models and manufacturers.

Family-based behavioural treatment of childhood obesity in a UK national health service setting: randomized controlled trial

Background:The best outcomes for treating childhood obesity have come from comprehensive family-based programmes. However there are questions over their generalizability.Objective:To examine the acceptability and effectiveness of ‘family-based behavioural treatment’ (FBBT) for childhood obesity in an ethnically and socially diverse sample of families in a UK National Health Service (NHS) setting.Methods:In this parallel group, randomized controlled trial, 72 obese children were randomized to FBBT or a waiting-list control. Primary outcomes were body mass index (BMI) and BMI s.d. scores (SDSs). Secondary outcomes were weight, weight SDSs, height, height SDSs, waist, waist SDSs, FM index, FFM index, blood pressure (BP) and psychosocial measures. The outcomes were assessed at baseline and after treatment, with analyses of 6-month data performed on an intent-to-treat (ITT) basis. Follow-up anthropometric data were collected at 12 months for the treatment group.Results:ITT analyses included all children with baseline data (n=60). There were significant BMI SDS changes (P<0.01) for the treatment and control groups of −0.11 (0.16) and −0.10 (1.6). The treatment group showed a significant reduction in systolic BP (−0.24 (0.7), P<0.05) and improvements in quality of life and eating attitudes (P<0.05), with no significant changes for the control group. However the between-group treatment effects for BMI, body composition, BP and psychosocial outcomes were not significant. There was no overall change in BMI or BMI SDSs from 0–12 months for the treatment group. No adverse effects were reported.Conclusions:Both treatment and control groups experienced significant reductions in the level of overweight, but with no significant difference between them. There were no significant group differences for any of the secondary outcomes. This trial was registered at http://www.controlled-trials.com/ under ISRCTN 51382628.

Prenatal and postnatal programming of body composition in obese children and adolescents: evidence from anthropometry, DXA and the 4-component model

Background:Low-birth weight has been proposed to programme central adiposity in childhood. However, there is little information on associations between fetal weight gain and fat distribution within obese individuals.Objectives:To investigate associations between birth weight and postnatal weight gain with body composition in a sample of obese children and adolescents.Subjects and methods:Body composition was measured using anthropometry, dual-emission X-ray absorptiometry and the 4-component model in 45 male and 76 female obese individuals aged 5–22 years. General linear models were used to investigate associations between birth weight standard deviation score (SDS), or change in weight SDS between birth and follow-up, and body composition, adjusting for age, pubertal status, height and gender.Results:Birth weight SDS ranged from −1.86 to 3.46, and was inversely associated with current weight SDS after adjustment for height SDS. Birth weight SDS was weakly associated with waist and hip girths, but not waist–hip ratio or trunk fat, after adjusting for age, height, pubertal status and gender. Change in weight SDS was strongly associated with total and central adiposity.Conclusions:Despite incorporating substantial variability, birth weight SDS was only a weak predictor of tissue masses and their distribution in obese children. Variability in central adiposity was more strongly associated with the magnitude of postnatal growth, which in turn was weakly inversely associated with birth weight SDS. In a population uniformly characterised by excess body weight, postnatal weight gain exerted the dominant impact on adiposity and fat distribution.

Aggregate predictions improve accuracy when calculating metabolic variables used to guide treatment

BACKGROUND Many components of clinical management are tailored to metabolic variables, such as fat-free mass, fat mass, resting metabolic rate (RMR), and body surface area. However, these traits are difficult to measure in routine care and are typically predicted from simple anthropometric or bedside body-composition measurements. Many prediction equations have been published, but validation studies have shown that these equations tend to have limited accuracy in individuals and many have significant average bias. OBJECTIVE We tested a mathematical approach that assumes that the aggregate of many independent predictions is more accurate than the best single prediction. DESIGN Body composition was measured in 196 children aged 4-16 y by using the 4-component model. RMR was measured in 142 adult women. Data on weight, height, age, skinfold thickness, and body impedance were used in published equations to predict body composition (12 equations) or RMR (13 equations). The accuracy of individual compared with aggregate predictions, relative to the reference measurements, was compared by using the Bland and Altman method. RESULTS For childrens body composition and adult RMR, the aggregate predictions had lower mean biases and lower limits of agreement than did the individual predictions, and the aggregate predictions performed better than did any individual prediction. CONCLUSIONS Aggregate predictions perform better than single predictions at predicting fat-free mass, fat mass, total body water, and RMR. Our findings indicate that the accuracy of calculating variables such as energy requirements and drug and dialysis dosages can be improved significantly with the use of our mathematical approach.

Is a single bioelectrical impedance equation valid for children of wide ranges of age, pubertal status and nutritional status? Evidence from the 4-component model

Background/Objectives:Bioelectrical impedance analysis (BIA) is widely used to predict body composition in paediatric research and clinical practice. Many equations have been published, but provide inconsistent predictions.Aims:To test whether a single equation for lean mass (LM) estimation from BIA is appropriate across wide ranges of age, pubertal status and nutritional status, by testing whether specific groups differ in the slope or intercept of the equation.Subjects/Methods:In 547 healthy individuals aged 4–24 years (240 males), we collected data on body mass (BM) and height (HT), and lean mass (LM) using the 4-component model. Impedance (Z) was measured using TANITA BC418MA instrumentation. LM was regressed on HT2/Z. Multiple regression analysis was conducted to investigate whether groups based on gender, age, pubertal status or nutritional status differed in the association of LM with HT2/Z.Results:BM ranged from 5 to 128 kg. HT2/Z was a strong predictor of LM (r 2=0.953, s.e.e.=2.9 kg). There was little evidence of a sex difference in this relationship, however, children aged 4–7 years and 16–19 years differed significantly from other age groups in regression slopes and intercepts. Similar variability was encountered for pubertal stage, but not for nutritional status.Conclusions:No single BIA equation applies across the age range 4–24 years. At certain ages or pubertal stages, the slope and intercept of the equation relating LM to HT2/Z alters. Failure to address such age effects is likely to result in poor accuracy of BIA (errors of several kg) for longitudinal studies of change in body composition.

Assessing Knowledge of, and Attitudes to, HIV/AIDS among University Students in the United Arab Emirates

Background The Middle East and North Africa (MENA) region is among the top two regions in the world with the fastest growing HIV epidemic. In this context, risks and vulnerability are high as the epidemic is on the rise with evidence indicating significantly increasing HIV prevalence, new HIV infections and AIDS-related deaths. Objective The aim of the survey was to assess HIV/AIDS knowledge and attitudes related to HIV/AIDS among a wide group of university students in the United Arab Emirates (UAE). Methods In a cross-sectional survey, a total sample of 2,294 students (406 male; 1,888 female) from four universities in three different Emirates in the UAE were approached to take part in the study. Students self-completed a questionnaire that was designed to measure their knowledge and attitudes to HIV/AIDS. Results The overall average knowledge score of HIV.AIDS was 61%. Non-Emirati and postgraduates demonstrated higher levels of knowledge compared to Emirati and undergraduate students respectively. No significant differences between males and females; and marital status were found. Eighty-five percent of students expressed negative attitudes towards people living with HIV, with Emirati and single students significantly holding more negative attitudes compared to non-Emiratis and those that are married respectively. Conclusions The findings provide strong evidence that there is a need to advocate for appropriate National HIV/AIDS awareness raising campaigns in universities to reduce the gaps in knowledge and decrease stigmatizing attitudes towards people living with HIV/AIDS.

Evaluation of lean tissue density for use in air displacement plethysmography in obese children and adolescents

Background/Objectives:Body composition techniques are required for monitoring response to treatment in individual obese children, and assessing the efficacy of weight loss programmes. Densitometry is readily undertaken, using air displacement plethysmography (ADP), but requires appropriate information on the density of lean tissue (DLT). The aims of this study were to develop predictive equations for DLT in obese children and adolescents, and to test the accuracy of ADP when using such predicted DLT values in an independent longitudinal sample using the four-component model as the reference method.Subjects/Methods:Equations for the prediction of DLT from age, gender and body mass index standard deviation score were developed in 105 children (39 boys). Accuracy of ADP, when incorporating predicted DLT values, was tested for baseline body composition and its change over time in a separate sample of 51 children (20 boys).Results:The predictive equation explained 33% of the variance in DLT. Fat mass obtained from ADP using such predicted values had a mean (s.d.) bias of 0.32 (1.39) kg, nonsignificant, whereas change in fat mass had an error of −0.25 (1.38) kg, nonsignificant. Hydration was strongly correlated with DLT.Conclusions:Use of ADP with predicted DLT values was associated with nonsignificant bias when estimating fat mass and its change over time. This study aids the application of ADP in childhood obesity research and clinical practise. The limits of agreement (±2.8 kg) relative to four-component values are moderately better than those for X-ray absorptiometry (±3.2 kg). Further improvement to accuracy would require assessment of lean tissue hydration by bioelectrical impedance.