Renal sinus fat (RSF) crucially influences metabolic regulation, inflammation, and vascular function. We investigated the association between RSF accumulation, metabolic disorders, and nutritional status in obese individuals with hypertension. A cross-sectional study involved 51 obese hypertensive patients from Salamat Specialized Community Clinic (February–September 2022). Basic and clinical information were collected through interviews. Data included anthropometrics, blood pressure, number of antihypertensive medications, body composition (bioelectrical impedance analysis), dietary intake (semi-quantitative 147-item food frequency questionnaire), and blood samples. Renal sinus fat was measured via ultrasonography. Statistical analyses included Pearson correlation, binary logistic regression, and linear regression. RSF positively correlated with abdominal visceral adipose tissue (VAT) area (P = 0.016), systolic blood pressure (SBP) (P = 0.004), and diastolic blood pressure (DBP) (P = 0.005). A strong trend toward a positive association was observed between antihypertensive medications and RSF (P = 0.062). In linear regression, RSF was independently associated with abdominal VAT area, SBP, and DBP after adjusting for confounders. After considering other risk factors, RSF volume relates to prescribed antihypertensive medications, hypertension, and central fat accumulation in obese hypertensive subjects. These findings suggest the need for further investigations into whether RSF promotes metabolic disorders.

Several novel anthropometric indices, including paediatric body adiposity index (BAIp) and triponderal mass index (TMI), have emerged as potential tools for estimating body fat in preschool children. However, their comparative validity and accuracy, particularly when compared with established indicators such as BMI, have not been thoroughly investigated. This cross-sectional study enrolled 2869 preschoolers aged 3–6 years in Wuhan, China. The non-parametric Bland–Altman analysis was employed to evaluate the agreement between BMI, BAIp and TMI with percentage of body fat (PBF), determined by bioelectrical impedance analysis (BIA), serving as the reference measure of adiposity. Additionally, receiver operating characteristic curve analysis was conducted to assess the effectiveness of BMI, BAIp and TMI in screening for obesity. BAIp demonstrated the least bias in estimating PBF, showing discrepancies of 3·64 % (95 % CI 3·40 %, 4·12 %) in boys and 3·95 % (95 % CI 3·79 %, 4·23 %) in girls. Conversely, BMI underestimated PBF by 3·89 % (95 % CI 3·70 %, 4·37 %) in boys and 4·81 % (95 % CI 4·59 %, 5·09 %) in girls, while TMI also underestimated PBF by 5·15 % (95 % CI 4·90 %, 5·52 %) in boys and 5·68 % (95 % CI 5·30 %, 5·91 %) in girls. BAIp exhibited the highest AUC values (AUC = 0·867–0·996) in boys, whereas in girls, there was no statistically significant difference between BMI (AUC = 0·936, 95 % CI 0·921, 0·948) and BAIp (AUC = 0·901, 95 % CI 0·883, 0·916) in girls (P = 0·054). In summary, when considering the identification of obesity, BAIp shows promise as a screening tool for both boys and girls.

We aim to understand the effects of hydration changes on athletes’ neuromuscular performance, on body water compartments, fat-free mass hydration and hydration biomarkers and to test the effects of the intervention on the response of acute dehydration in the hydration indexes. The H2OAthletes study (clinicaltrials.gov ID: NCT05380089) is a randomised controlled trial in thirty-eight national/international athletes of both sexes with low total water intake (WI) (i.e. < 35·0 ml/kg/d). In the intervention, participants will be randomly assigned to the control (CG, n 19) or experimental group (EG, n 19). During the 4-day intervention, WI will be maintained in the CG and increased in the EG (i.e. > 45·0 ml/kg/d). Exercise-induced dehydration protocols with thermal stress will be performed before and after the intervention. Neuromuscular performance (knee extension/flexion with electromyography and handgrip), hydration indexes (serum, urine and saliva osmolality), body water compartments and water flux (dilution techniques, body composition (four-compartment model) and biochemical parameters (vasopressin and Na) will be evaluated. This trial will provide novel evidence about the effects of hydration changes on neuromuscular function and hydration status in athletes with low WI, providing useful information for athletes and sports-related professionals aiming to improve athletic performance.

Body composition and phase angle (PhA) have been used to predict mortality in multiple diseases. However, little has been studied regarding segmental measurements, which could potentially help assess subtle changes in specific tissue segments. This study aimed to identify the total PhA cut-off point associated with mortality risk and changes in body composition within a week of hospitalisation in non-critical hospitalised patients with COVID-19. A cohort study was conducted where patients underwent to a complete nutritional assessment upon admission and after seven days, and followed up until hospital discharge or death. A receiver operating characteristic curve was constructed to determine the PhA cut-off point, and the Kaplan–Meier estimator was used to determine survival analysis. Segmental and complete body compositions on admission and after 7 d were compared. We included 110 patients (60 men) with a mean age of 50·5 ± 15·0 years and a median BMI of 28·5 (IQR, 25·6–33·5) kg/m2. The median length of hospital stay was 6 (IQR, 4–9) d, and the mortality rate was 13·6 %. The PhA cut-off point obtained was 4°, with significant differences in the survival rate (P < 0·001) and mortality (HR = 5·81, 95 % CI: 1·80, 18·67, P = 0·003). Segmental and whole-body compositions were negatively affected within one week of hospitalisation, with changes in the approach by the graphical method in both sexes. Nutritional status deteriorates within a week of hospitalisation. PhA < 4° is strongly associated with increased mortality in non-critical hospitalised patients with COVID-19.

Optimal nutrition during pregnancy is vital for both maternal and child health. Our objective was to explore if prenatal diet is associated with children’s height and body fat. Nutrient intake was assessed through a FFQ from 808 pregnant women and summarised to a nutrition index, ‘My Nutrition Index’ (MNI). The association with children’s height and body fat (bioimpedance) was assessed with linear regression models. Secondary analysis was performed with BMI, trunk fat and skinfolds. Overall, higher MNI score was associated with greater height (β = 0·47; (95 % CI 0·00, 0·94), among both sexes. Among boys, higher MNI was associated with 0·15 higher BMI z-scores, 0·12 body fat z-scores, 0·11 trunk fat z-scores, and larger triceps, and triceps + subscapular skinfolds (β = 0·05 and β = 0·06; on the log2 scale) (P-value < 0·05). Among girls, the opposite associations were found with 0·12 lower trunk fat z-scores, and smaller subscapular and suprailiac skinfolds (β = −0·07 and β = −0·10; on the log2 scale) (P-value < 0·05). For skinfold measures, this would represent a ± 1·0 millimetres difference. Unexpectedly, a prenatal diet in line with recommended nutrient intake was associated with higher measures of body fat for boys and opposite to girls at a pre-pubertal stage of development.

The study aimed to explore the relationships of skeletal muscle mass with disease severity in metabolic-associated fatty liver disease (MAFLD) patients with different methods. Consecutive subjects undergoing bioelectrical impedance analysis were included. The steatosis grade and liver fibrosis were evaluated by MRI-derived proton density fat fraction and two-dimensional shear wave elastography. The appendicular skeletal muscle mass (ASM) was adjusted by height2 (ASM/H2), weight (ASM/W) and BMI (ASM/BMI). Overall, 2223 subjects (50·5 %, MAFLD; 46·9 %, male) were included, with the mean age 37·4 ± 10·6 years. In multivariate logistic regression analysis, the subjects with the lowest quartile (Q1) of ASM/W or ASM/BMI had higher risk ratios for MAFLD (OR (95 % CI) in male: 2·57 (1·35, 4·89), 2·11(1·22, 3·64); in female: 4·85 (2·33, 10·01), 4·81 (2·52, 9·16), all P < 0·05, all for Q1 v. Q4). The MAFLD patients with lower quartiles of ASM/W had the higher risk OR for insulin resistance (IR), both in male and female (2·14 (1·16, 3·97), 4·26 (1·29, 14·02) for Q4 v. Q1, both P < 0·05). While the significant OR were not observed when ASM/H2 and ASM/BMI were used. There were significant dose-dependent associations between decreased ASM/W as well as ASM/BMI and moderate–severe steatosis (2·85(1·54, 5·29), 1·90(1·09, 3·31), both P < 0·05) in male MAFLD patients. In conclusion, ASM/W is superior to ASM/H2 and ASM/BMI in predicting the degree of MAFLD. A lower ASM/W is associated with IR and moderate–severe steatosis in non-elderly male MAFLD.

Smartphone applications (SPA) now offer the ability to provide accessible in-home monitoring of relevant individual health biomarkers. Previous cross-sectional validations of similar technologies have reported acceptable accuracy with high-grade body composition assessments; this research assessed longitudinal agreement of a novel SPA across a self-managed weight loss intervention of thirty-eight participants (twenty-one males, seventeen females). Estimations of body mass (BM), body fat percentage (BF%), fat-free mass (FFM) and waist circumference (WC) from the SPA were compared with ground truth (GT) measures from a dual-energy X-ray absorptiometry scanner and expert technician measurement. Small mean differences (MD) and standard error of estimate (SEE) were observed between method deltas (ΔBM: MD = 0·12 kg, SEE = 2·82 kg; ΔBF%: MD = 0·06 %, SEE = 1·65 %; ΔFFM: MD = 0·17 kg, SEE = 1·65 kg; ΔWC: MD = 1·16 cm, SEE = 2·52 cm). Concordance correlation coefficient (CCC) assessed longitudinal agreement between the SPA and GT methods, with moderate concordance (CCC: 0·55–0·73) observed for all measures. The novel SPA may not be interchangeable with high-accuracy medical scanning methods yet offers significant benefits in cost, accessibility and user comfort, in conjunction with the ability to monitor body shape and composition estimates over time.

HIV and severe wasting are associated with post-discharge mortality and hospital readmission among children with complicated severe acute malnutrition (SAM); however, the reasons remain unclear. We assessed body composition at hospital discharge, stratified by HIV and oedema status, in a cohort of children with complicated SAM in three hospitals in Zambia and Zimbabwe. We measured skinfold thicknesses and bioelectrical impedance analysis (BIA) to investigate whether fat and lean mass were independent predictors of time to death or readmission. Cox proportional hazards models were used to estimate the association between death/readmission and discharge body composition. Mixed effects models were fitted to compare longitudinal changes in body composition over 1 year. At discharge, 284 and 546 children had complete BIA and skinfold measurements, respectively. Low discharge lean and peripheral fat mass were independently associated with death/hospital readmission. Each unit Z-score increase in impedance index and triceps skinfolds was associated with 48 % (adjusted hazard ratio 0·52, 95 % CI (0·30, 0·90)) and 17 % (adjusted hazard ratio 0·83, 95 % CI (0·71, 0·96)) lower hazard of death/readmission, respectively. HIV-positive v. HIV-negative children had lower gains in sum of skinfolds (mean difference −1·49, 95 % CI (−2·01, −0·97)) and impedance index Z-scores (–0·13, 95 % CI (−0·24, −0·01)) over 52 weeks. Children with non-oedematous v. oedematous SAM had lower mean changes in the sum of skinfolds (–1·47, 95 % CI (−1·97, −0·97)) and impedance index Z-scores (–0·23, 95 % CI (−0·36, −0·09)). Risk stratification to identify children at risk for mortality or readmission, and interventions to increase lean and peripheral fat mass, should be considered in the post-discharge care of these children.

Air displacement plethysmography (ADP) has been considered as the ‘standard’ method to determine body fat in children due to superior validity and reliability compared with bioelectrical impedance analysis (BIA). However, ADP and BIA are often used interchangeably despite few studies comparing measures of percentage body fat by ADP (%FMADP) with BIA (%FMBIA) in children with and without obesity. The objective of this study was to measure concurrent validity and reliability of %FMADP and %FMBIA in 6-to-12-year-old boys with and without obesity. Seventy-one boys (twenty-five with obesity) underwent body composition assessment. Ten boys participated in intra-day reliability analysis. %FMADP was estimated by Bodpod using sex- and age-specific equations of body density. %FMBIA was estimated by a multi-frequency, hand-to-foot device using child-specific equations based on impedance. Validity was assessed by t tests, correlation coefficients and limits of agreement (LoA); and reliability by technical error of measurement (TEM) and intraclass correlation coefficients (ICC). Compared with %FMADP, %FMBIA was significantly underestimated in the cohort (–3·4 ± 5·6 %; effect size = 0·42) and in both boys with obesity (–5·2 ± 5·5 %; ES = 0·90) and without obesity (–2·4 ± 5·5 %; ES = 0·52). A strong, significant positive correlation was found between %FMADP and %FMBIA (r = 0·80). Across the cohort, LoA were 22·3 %, and no proportional bias was detected. For reliability, TEM were 0·65 % and 0·55 %, and ICC were 0·93 and 0·95 for %FMBIA and %FMADP, respectively. Whilst both %FMADP and %FMBIA are highly reliable methods, considerable differences indicated that the devices cannot be used interchangeably in boys age 6-to-12 years.

The purpose of this investigation was to expand upon the limited existing research examining the test–retest reliability, cross-sectional validity and longitudinal validity of a sample of bioelectrical impedance analysis (BIA) devices as compared with a laboratory four-compartment (4C) model. Seventy-three healthy participants aged 19–50 years were assessed by each of fifteen BIA devices, with resulting body fat percentage estimates compared with a 4C model utilising air displacement plethysmography, dual-energy X-ray absorptiometry and bioimpedance spectroscopy. A subset of thirty-seven participants returned for a second visit 12–16 weeks later and were included in an analysis of longitudinal validity. The sample of devices included fourteen consumer-grade and one research-grade model in a variety of configurations: hand-to-hand, foot-to-foot and bilateral hand-to-foot (octapolar). BIA devices demonstrated high reliability, with precision error ranging from 0·0 to 0·49 %. Cross-sectional validity varied, with constant error relative to the 4C model ranging from −3·5 (sd 4·1) % to 11·7 (sd 4·7) %, standard error of the estimate values of 3·1–7·5 % and Lin’s concordance correlation coefficients (CCC) of 0·48–0·94. For longitudinal validity, constant error ranged from −0·4 (sd 2·1) % to 1·3 (sd 2·7) %, with standard error of the estimate values of 1·7–2·6 % and Lin’s CCC of 0·37–0·78. While performance varied widely across the sample investigated, select models of BIA devices (particularly octapolar and select foot-to-foot devices) may hold potential utility for the tracking of body composition over time, particularly in contexts in which the purchase or use of a research-grade device is infeasible.

Various body indicators are used to predict health risks. However, controversies still exist regarding the best indicators to predict CVD. Using a large number of measurements, our aim was to assess their associations with blood pressure (BP) and to identify the most relevant parameters to be used in health surveillance studies. The population included 589 students (67·2 % women) aged 20–25 years from Constantine (Algeria). Sixteen parameters were considered, including crude body measurements, ratios and body fat indicators based on bioelectrical impedance analysis (BIA). We used multi-adjusted linear regression models to assess the associations between body measurements and BP. According to WHO definitions, underweight, overweight-without obesity, obesity and hypertension (HT) were identified in 6·1, 18·0, 2·4 and 5·1 % of the subjects, respectively. Prevalence of HT was higher in men than in women (11·9 % v. 1·8 %; P < 0·001). In the whole sample, almost all indicators were positively associated with systolic and diastolic BP. The suprailiac skinfold had the strongest associations with systolic (β = 3·498; P < 0·001) and diastolic (β = 2·436; P < 0·001) BP, and as a whole, arm circumferences and weight were also good candidates. The currently used BMI, waist-to-hip, waist-to-height ratio and BIA indictors also predicted BP, but they did not seem to be better determinants of BP than crude anthropometric measurements. This study showed that overweight and HT were already found in the present population of young Algerian adults. Most body indicators were highly associated with BP, but simple anthropometric measurements appeared to be particularly useful to predict BP.

Few investigations have evaluated the validity of current body composition technology among racially and ethnically diverse populations. This study assessed the validity of common body composition methods in a multi-ethnic sample stratified by race and ethnicity. One hundred and ten individuals (55 % female, age: 26·5 (sd 6·9) years) identifying as Asian, African American/Black, Caucasian/White, Hispanic, Multi-racial and Native American were enrolled. Seven body composition models (dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), two bioelectrical impedance devices (BIS, IB) and three multi-compartment models) were evaluated against a four-compartment criterion model by assessing total error (TE) and standard error of the estimate. For the total sample, measures of % fat and fat-free mass (FFM) from multi-compartment models were all excellent to ideal (% fat: TE = 0·94–2·37 %; FFM: TE = 0·72–1·78 kg) compared with the criterion. % fat measures were very good to excellent for DXA, ADP and IB (TE = 2·52–2·89 %) and fairly good for BIS (TE = 4·12 %). For FFM, single device estimates were good (BIS; TE = 3·12 kg) to ideal (DXA, ADP, IB; TE = 1·21–2·15 kg). Results did not vary meaningfully between each race and ethnicity, except BIS was not valid for African American/Black, Caucasian/White and Multi-racial participants for % fat (TE = 4·3–4·9 %). The multi-compartment models evaluated can be utilised in a multi-ethnic sample and in each individual race and ethnicity to obtain highly valid results for % fat and FFM. Estimates from DXA, ADP and IB were also valid. The BIS may demonstrate greater TE for all racial and ethnic cohorts and results should be interpreted cautiously.

Assessing children’s growth adequately is important due to the necessary prevention of adequate body composition, especially at pre-pubertal age. Simpler measurements such as anthropometry or bioimpedance, using equations validated in Caucasian children, have been demonstrated to overestimate or underestimate fat mass percentage (FM%) or fat-free mass (FFM) in Chilean children. In a sample of 424 children (198 boys and 226 girls) of 7–9 years old, the three component (3C) model was assessed, where total body water was determined by 2H dilution and body volume by air displacement plethysmography, in order to design and validate anthropometry and bioimpedance equations. The FM (%) equation specific for Chilean children was validated as (1·743 × BMI z-score) + (0·727 × triceps skinfold) + (0·385 × biceps skinfold) + 15·985, against the 3C model (R2 0·79). The new FFM equation (kg) generated was (log FFM = (0·018 × age) + (0·047 × sex) + (0·006 × weight) + (0·027 × resistance) + 2·071), with an R2 0·93 (female = 1 and male = 2). The Bland–Altman analysis shows a mean difference of 0·27 (sd 3·5) for the FM% in the whole group as well as 0·004 (sd 0·9) kg is the mean difference for the bioelectrical impedance analysis (BIA) FFM (kg) equation. The new equations for FM (%) and FFM (kg) in Chilean children will provide a simple and valid tool for the assessment of body composition in cohort studies or to assess the impact of nutritional programmes or public policies.

Anthocyanins and bromelain have gained significant attention due to their antioxidative and anti-inflammatory properties. Both have been shown to improve endothelial function, blood pressure (BP) and oxygen utility capacity in humans; however, the combination of these two and the impacts on endothelial function, BP, total antioxidant capacity (TAC) and oxygen utility capacity have not been previously investigated. The purpose of this study was to investigate the impacts of a combined anthocyanins and bromelain supplement (BE) on endothelial function, BP, TAC, oxygen utility capacity and fatigability in healthy adults. Healthy adults (n 18, age 24 (sd 4) years) received BE or placebo in a randomised crossover design. Brachial artery flow-mediated dilation (FMD), BP, TAC, resting heart rate, oxygen utility capacity and fatigability were measured pre- and post-BE and placebo intake. The BE group showed significantly increased FMD, reduced systolic BP and improved oxygen utility capacity compared with the placebo group (P < 0·05). Tissue saturation and oxygenated Hb significantly increased following BE intake, while deoxygenated Hb significantly decreased (P < 0·05) during exercise. Additionally, TAC was significantly increased following BE intake (P < 0·05). There were no significant differences for resting heart rate, diastolic BP or fatigability index. These results suggest that BE intake is an effective nutritional therapy for improving endothelial function, BP, TAC and oxygen utility capacity, which may be beneficial to support vascular health in humans.

There is a need for accurate, inexpensive and field-friendly methods to assess body composition in children. Bioelectrical impedance analysis (BIA) is a promising approach; however, there have been limited validation and use among young children in resource-poor settings. We aim to develop and validate population-specific prediction equations for estimating total fat mass (FM), fat free-mass (FFM) and percentage body fat (PBF) in Vietnamese children (4–7 years) using reactance and resistance from BIA, anthropometric variables and demographic information. We conducted a cross-sectional survey of 120 children. Body composition was measured using dual-energy X-ray absorptiometry (DXA), BIA and anthropometry. To develop prediction equations, we split all data into development (70 %) and validation datasets (30 %). The model performance was evaluated using predicted residual error sum of squares, root mean squared error (RMSE), mean absolute error (MAE) and R2. We identified a top performing model with the least number of parameters (age, sex, weight and resistance index or resistance and height), low RMSE (FM 0·70, FFM 0·74, PBF 3·10), low MAE (FM 0·55, FFM 0·62, PBF 2·49), high R2 (FM 0·95, FFM 0·92, PBF 0·82) and the least difference between predicted values and actual values from DXA (FM 0·03 kg or 0·01 sd, FFM 0·06 kg or 0·02 sd, PBF 0·27 % or 0·04 sd). In conclusion, we developed the first valid and highly predictive equations to estimate FM, FFM and PBF in Vietnamese children using BIA. These findings have important implications for future research on the double burden of disease and risks associated with overweight and obesity in young children.

Measurement of body composition is increasingly important in research and clinical settings but is difficult in very young children. Bioelectrical impedance analysis (BIA) and air displacement plethysmography (ADP) are well-established but require specialist equipment so are not always feasible. Our aim was to determine if anthropometry and skinfold thickness measurements can be used as a substitute for BIA or ADP for assessing body composition in very young New Zealand children. We used three multi-ethnic cohorts: 217 children at a mean age of 24·2 months with skinfold and BIA measurements; seventy-nine infants at a mean age of 20·9 weeks and seventy-three infants at a mean age of 16·2 weeks, both with skinfold and ADP measurements. We used Bland–Altman plots to compare fat and fat-free mass calculated using all potentially relevant equations with measurements using BIA or ADP. We also calculated the proportion of children in the same tertile for measured fat or fat-free mass and tertiles (i) calculated using each equation, (ii) each absolute skinfold, and (iii) sum of skinfold thicknesses. We found that even for the best equation for each cohort, the 95 % limits of agreement with standard measures were wide (25–200 % of the mean) and the proportion of children whose standard measures fell in the same tertile as the skinfold estimates was ≤69 %. We conclude that none of the available published skinfold thickness equations provides good prediction of body composition in multi-ethnic cohorts of very young New Zealand children with different birth history and growth patterns.

The present study investigated the association between protein intake and lean mass according to obesity status over a 12-year period. Data on 4412 participants aged 40–69 years were obtained from the Korean Genome and Epidemiology Study. The usual dietary protein intake of these participants was assessed at baseline using a semi-quantitative FFQ. Body composition was measured using bioelectrical impedance analysis at baseline and after a 12-year follow-up. Linear mixed-effects models were used to examine the associations between lean mass after a 12-year follow-up and protein intake at baseline. After adjusting for covariates and lean mass at baseline, comparisons between the highest and lowest tertiles revealed that dietary protein intake was positively associated with lean mass in both men (β = 0·79, P = 0·001) and women (β = 0·28, P = 0·082) after the 12-year period; however, those differences were attenuated after additional adjustment for fat mass at baseline and were stronger in the normal-weight group (men, β = 0·85, P = 0·002; women, β = 0·97, P < 0·001) but were not detected in the obese group. In the obese group, age (men, β = 4·08, P < 0·001; women, β = 2·61, P < 0·001) and regular physical activity (men, β = 0·88, P = 0·054; women, β = 0·76, P < 0·001) were significantly associated with lean mass after 12 years of follow-up. The results of the present study showed that protein intake may contribute to the prevention of ageing-related lean mass loss; however, the impact of this intake may vary depending on obesity status. Therefore, the maintenance of a healthy body weight during ageing through enhanced protein intake is likely to confer health benefits.

Lipid-based nutrient supplements (LNS) may be beneficial for malnourished HIV-infected patients starting antiretroviral therapy (ART). We assessed the effect of adding vitamins and minerals to LNS on body composition and handgrip strength during ART initiation. ART-eligible HIV-infected patients with BMI <18·5 kg/m2 were randomised to LNS or LNS with added high-dose vitamins and minerals (LNS-VM) from referral for ART to 6 weeks post-ART and followed up until 12 weeks. Body composition by bioelectrical impedance analysis (BIA), deuterium (2H) diluted water (D2O) and air displacement plethysmography (ADP), and handgrip strength were determined at baseline and at 6 and 12 weeks post-ART, and effects of LNS-VM v. LNS at 6 and 12 weeks investigated. BIA data were available for 1461, D2O data for 479, ADP data for 498 and handgrip strength data for 1752 patients. Fat mass tended to be lower, and fat-free mass correspondingly higher, by BIA than by ADP or D2O. At 6 weeks post-ART, LNS-VM led to a higher regain of BIA-assessed fat mass (0·4 (95 % CI 0·05, 0·8) kg), but not fat-free mass, and a borderline significant increase in handgrip strength (0·72 (95 % CI −0·03, 1·5) kg). These effects were not sustained at 12 weeks. Similar effects as for BIA were seen using ADP or D2O but no differences reached statistical significance. In conclusion, LNS-VM led to a higher regain of fat mass at 6 weeks and to a borderline significant beneficial effect on handgrip strength. Further research is needed to determine appropriate timing and supplement composition to optimise nutritional interventions in malnourished HIV patients.

Age- and sex-based BMI cut-offs are used to define overweight and obesity, but the relationship between BMI and body composition has not been very well studied in children or compared between children of different ethnic groups. Body size and composition in childhood are also influenced by size at birth. Our aim was to compare body size and composition at 2 years in children with different ethnicity and size at birth. We prospectively followed a multi-ethnic cohort of 300 children born with risk factors for neonatal hypoglycaemia (infants of diabetics, large or small at birth or late preterm) to 2 years corrected age. Complete data on weight, height and head circumference and body composition using bioelectrical impedance 24±1 months corrected age were available in 209 children. At birth, compared with European children, Chinese, Indian and other ethnicity children were lighter, and Indian children had smaller head circumferences, but birth lengths were similar in all ethnic groups. At 2 years, Pacific children were heavier and had higher BMI z scores, and Indian children had smaller head circumferences and lower BMI z scores than those from other ethnic groups. However, fat mass and fat-free mass indices were similar in all groups. At median BMI, fat mass:fat-free mass ratio was 23 % lower in Pacific than in Indian children (0·22 v. 0·27, P=0·03). BMI is not a good indicator of adiposity in this multi-ethnic cohort of 2-year-old New Zealand children.

Favourable body composition has been associated with higher dietary protein intake. However, little is known regarding this relationship in a population of Chinese Americans (CHA), who have lower BMI compared with other populations. The aim of the present study was to assess the relationship between dietary protein intake, fat mass (FM) and fat-free mass (FFM) in CHA. Data were from the Chinese American Cardiovascular Health Assessment (CHA CHA) 2010–2011 (n 1707); dietary intake was assessed using an adapted and validated FFQ. Body composition was assessed using bioelectrical impedance analysis. The associations between protein intake (% energy intake) and BMI, percentage FM (FM%), percentage FFM (FFM%), FM index (FMI) and FFM index (FFMI) were examined using multiple linear regression adjusted for age, sex, physical activity, acculturation, total energy intake, sedentary time, smoking status, education, employment and income. There was a significant positive association between dietary protein and BMI (B = 0·056, 95 % CI 0·017, 0·104; P = 0·005), FM (B = 0·106, 95 % CI 0·029, 0·184; P = 0·007), FM% (B = 0·112, 95 % CI 0·031, 0·194; P = 0·007) and FMI (B = 0·045, 95 % CI 0·016, 0·073; P = 0·002). There was a significant negative association between dietary protein and FFM% (B = −0·116, 95 % CI −0·196, −0·036; P = 0·004). In conclusion, higher dietary protein intake was associated with higher adiposity; however, absolute FFM and FFMI were not associated with dietary protein intake. Future work examining the relationship between protein source (i.e. animal) and body composition is warranted in this population of CHA.