Ocean warming will continue to affect the growth, body condition and geographic distributions of marine fishes and understanding these effects is an urgent challenge for fisheries research and ...management. Determining how temperature is recorded in fish otolith carbonate, provides an additional chronological tool to investigate thermal histories, preferences and patterns of movement throughout an individual's life history. The influence of three water temperature treatments (22°C, 25°C, and 28°C) on hatchery-reared juvenile stout whiting, Sillago robusta, was tested using a controlled outdoor mesocosm system. Fish were measured for change in length and weight, and body condition was determined using bioelectrical impedance analysis. Sagittal otoliths were analysed for stable oxygen (δ18Ootolith) and carbon (δ13Cotolith) isotopes via isotope ratio mass spectrometry. Whiting kept at 22°C were significantly smaller and had diminished body condition compared to fish in 25°C and 28°C, which did not significantly differ from each other. The δ18O otolith values of stout whiting demonstrated a negative temperature-dependent fractionation relationship which was similar in slope but had a different intercept to the relationships reported for inorganic aragonite and other marine fish species. The δ13C otolith values also showed a negative relationship with water temperature, and the calculated proportion of metabolic carbon M in otoliths differed between fish reared in the coolest (22°C) and warmest (28°C) temperature treatments. Overall, the results suggest that stout whiting may have reached an upper growth threshold between 25°C and 28°C, and that growth and body condition may be optimised during warmer seasons and toward the northerly regions of their distribution. Otolith oxygen thermometry shows promise as a natural tracer of thermal life history, and species-specific fractionation equations should be utilised when possible to prevent errors in temperature reconstructions of wild-caught fish.
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•The impact of ocean warming on juvenile stout whiting (Sillago robusta) was tested using an outdoor mesocosm experiment•Fish in warmer water temperatures grew larger and developed improved body condition•Otolith oxygen isotope ratios demonstrated a negative relationship with water temperature•Species-specific otolith oxygen isotope relationships should be applied to temperature reconstructions when possible•Stout whiting may be a climate ‘winner’ along the east coast of Australia
BIA is easy, non-invasive, relatively inexpensive and can be performed in almost any subject because it is portable. Part II of these ESPEN guidelines reports results for fat-free mass (FFM), body ...fat (BF), body cell mass (BCM), total body water (TBW), extracellular water (ECW) and intracellular water (ICW) from various studies in healthy and ill subjects. The data suggests that BIA works well in healthy subjects and in patients with stable water and electrolytes balance with a validated BIA equation that is appropriate with regard to age, sex and race. Clinical use of BIA in subjects at extremes of BMI ranges or with abnormal hydration cannot be recommended for routine assessment of patients until further validation has proven for BIA algorithm to be accurate in such conditions. Multi-frequency- and segmental-BIA may have advantages over single-frequency BIA in these conditions, but further validation is necessary. Longitudinal follow-up of body composition by BIA is possible in subjects with BMI 16–34kg/m2 without abnormal hydration, but must be interpreted with caution. Further validation of BIA is necessary to understand the mechanisms for the changes observed in acute illness, altered fat/lean mass ratios, extreme heights and body shape abnormalities.
The use of bioelectrical impedance analysis (BIA) is widespread both in healthy subjects and patients, but suffers from a lack of standardized method and quality control procedures. BIA allows the ...determination of the fat-free mass (FFM) and total body water (TBW) in subjects without significant fluid and electrolyte abnormalities, when using appropriate population, age or pathology-specific BIA equations and established procedures. Published BIA equations validated against a reference method in a sufficiently large number of subjects are presented and ranked according to the standard error of the estimate.
The determination of changes in body cell mass (BCM), extra cellular (ECW) and intra cellular water (ICW) requires further research using a valid model that guarantees that ECW changes do not corrupt the ICW. The use of segmental-BIA, multifrequency BIA, or bioelectrical spectroscopy in altered hydration states also requires further research.
ESPEN guidelines for the clinical use of BIA measurements are described in a paper to appear soon in Clinical Nutrition.
Body mass, body mass index (BMI), and body composition components are essential for health and longevity. Considering the influence of demographic factors on body composition, there is a need for ...tailored reference values based on age-, sex-, and geography. We aimed to construct a comprehensive reference material on body composition in healthy Norwegian adults.
In this cross-sectional study, we estimated age- and sex-specific reference values for body-, fat-, and muscle mass variables using multi-frequency bioelectrial impedance analysis (such as body fat percentage, skeletal muscle mass and visceral fat area) in 22,191 healthy adults aged 20–99 years participating in the Trøndelag Health Study 4 (HUNT4). We calculated the fat mass and skeletal muscle mass index as the total fat and muscle mass relative to height squared and used general linear models to explore the associations between physical activity (PA), BMI, and age.
With a BMI (kg/m2) of 25.4 (SD 5.1) and 26.0 (4.5) for women and men, respectively, the youngest age group (20–39 yrs) had a lower BMI compared to their counterparts aged 40–59 years (26.3 4.5 and 27.5 3.8) and ≥ 60 years (25.7 4.1 and 26.5 3.4), respectively. Those aged 20–39 years also had the lowest values for the different body fat variables measured. Fat mass index (kg/m2) was 8.41 (4.00) and 5.81 (3.29) for women and men aged 20–39 years, respectively, compared to 9.25 (3.21) and 6.86 (2.46) for those aged ≥60 years. The oldest age group had the lowest values for the various muscle mass variables; women and men aged 60+ years had a skeletal muscle mass index (kg/m2) of 8.91 (0.85) and 10.96 (1.00), respectively. Corresponding values for those aged 20–39 years were 9.33 (0.97) and 11.49 (1.15). For all age groups and both sexes, regular physical activity was associated with lower levels of fat mass, whereas the association between muscle mass and PAwas less conclusive. When using body fat percentage as an obesity measure, we observed a much higher obesity prevalence (41.2%) in the study population compared to BMI (17.3%).
Our study offers a comprehensive reference for body composition among healthy adults in Norway, aiding the identification of abnormal fat and muscle mass values across age groups. We also highlight that BMI often misclassifies individuals with adiposity levels in the overweight or obese category as lean. Therefore, incorporating body composition when defining obesity could enable early intervention to prevent cardiometabolic diseases.
Evidence supports that growth trajectory during infancy has a major impact on body composition. We aimed to examine body composition in children born small for gestational age (SGA) or appropriate ...for gestational age (AGA) adjusted for postnatal growth velocity. We enrolled 365 children, 75 SGA and 290 AGA, aged 7 to 10 years, examining anthropometrics, skinfold thickness, and body composition using bioelectrical impedance analysis. Growth velocity was defined as rapid or slow (weight gain > or <0.67 z-scores, respectively). Gestational age, sex, delivery mode, gestational diabetes, hypertension, nutrition, exercise, parental body mass index (BMI), and socioeconomic status were considered. At a mean of 9 years of age, SGA compared with AGA-born children, had significantly lower lean mass. BMI was negatively associated with SGA status (beta = 0.80, P = .046), after adjusting for birth weight, delivery mode, and breastfeeding. The lean mass index was negatively associated with SGA status (beta = 0.39, P = .018), after adjusting for the same factors. SGA-born participants with slow growth velocity had significantly lower lean mass in comparison to AGA-born counterparts. SGA-born children with rapid compared with those with slow growth velocity had significantly higher absolute fat mass. BMI was negatively associated with a slow postnatal growth pattern (beta = 0.59, P = .023), and the lean mass index was negatively associated with a slow postnatal growth pattern (beta = 0.78, P = .006), after adjusting for the same factors. In conclusion, SGA-born children presented a lower lean mass in comparison to AGA-born counterparts, whereas BMI and lean mass index were negatively associated with slow postnatal growth velocity.
Children born small for gestational age (SGA) with a slow postnatal growth velocity had lower lean mass in comparison to children born appropriate for gestational age. Moreover, children born SGA with rapid postnatal growth velocity had a significantly higher absolute fat mass in comparison to those with slow postnatal growth velocity.
The Figures of the graphical abstract were partly generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 unported license. Display omitted
•Multifrequency bioelectrical impedance data was used to develop and cross-validate a fat-free mass predictive equation in adolescent soccer athletes.•The new fat-free mass predictive equation is ...accurate at 50 kHz of a multifrequency bioelectrical impedance device.•This device has the potential to estimate fat-free mass in male adolescent soccer athletes.
This study aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using multifrequency bioelectrical impedance analysis (BIA) data in adolescent soccer athletes.
Male adolescent soccer athletes (n = 149; 13–19 y old) were randomly sorted using Excel and independently selected for development group (n = 100) or cross-validation group (n = 49). The FFM reference values were determined using dual-energy X-ray absorptiometry. Single-frequency BIA was used to plot tolerance ellipses. Multifrequency-BIA raw data were used as independent variables in regression models. Student's independent t-test was used to compare development and cross-validation groups. Stepwise multiple regression was used to develop the FFM predictive equation. Bland-Altman plots, Lin's concordance correlation coefficient, according to McBride criteria, precision, accuracy, and standard error of estimate (SEE) were calculated to evaluate the concordance and reliability of estimates. Bioelectrical impedance vector analysis was plotted to assess hydration status.
No differences (P > 0.05) were observed between development and validation groups in chronological age, anthropometric data, bioelectrical impedance data, and FFM values obtained using dual-energy X-ray absorptiometry. Bioelectrical impedance vector analysis tolerance showed that all participants presented adequate hydration status compared to the reference population. The new FFM predictive equation developed and validated: FFM (kg) = −7.064 + 0.592 × chronological age (y) + 0.554 × weight (kg) + 0.365 × height²/resistance (cm²/Ω), presented R² = 0.95; SEE = 1.76 kg; concordance correlation coefficient = 0.95, accuracy = 0.98, and strength of concordance = 0.99.
The present study developed and cross-validated an FFM predictive equation based on multifrequency bioelectrical data providing substantial FFM accuracy for male adolescent soccer athletes.
The aim of this study was to compare bioelectrical impedance analysis (BIA) with dual-energy X-ray absorptiometry (DXA) and investigate the accuracy of BIA in assessing appendicular skeletal muscle ...mass (ASM) and diagnosing sarcopenia. A total of 90 elderly patients hospitalized in the Affiliated Hospital of Hangzhou Normal University from 2019 to 2020 were collected, including 42 males and 48 females. All patients underwent BIA and DXA examinations. Pearson correlation and Bland-Altman analysis were used to compare the differences between BIA and DXA in assessing ASM and diagnosing sarcopenia. ASM measured by BIA was higher than ASM measured by DXA, and there was statistical significance for all differences (
P
< .001); Pearson correlation analysis showed that ASM measured by BIA and DXA was positively correlated in both male (
R
= 0.94) and female (
R
= 0.97) patients (
P
< .001); Bland-Altman analysis showed that there was a high consistency between ASM detected by BIA and DXA; The detection rate of low muscle mass and sarcopenia by BIA and DXA was not statistically significant (
P
> .05). BIA (InBody720) has high accuracy in assessing ASM and diagnosing sarcopenia in hospitalized Chinese older adults, and has the advantages of convenient use, no radiation, and easy promotion, so it can be used as an early screening tool in primary hospitals lacking DXA.
We compared the evaluation of skeletal muscle mass (SMM) using the computed tomography (CT) and bioelectrical impedance analysis (BIA) methods in critically ill patients. We also evaluated whether ...BIA can be applied for measuring SM with high accuracy to critically ill patients.
We included 135 critically ill surgical patients (83 men and 52 women, mean age: 59.3 years) who got the BIA and abdominal CT scan both within 7 days during the intensive care unit (ICU) stay. With CT scan, skeletal muscle area (SMA) measured from the L3 spine level image was used for calculation of the whole body skeletal muscle volume and mass (kg). Body composition data from BIA were obtained using touch-type electrodes and 50 kHz current. Subgroup analyses for SMM were performed according to the sex, SMA, and edema status of the patients with Pearson correlation or regression analysis et al.
SMM from CT and BIA showed a good correlation (p < 0.0001) to sex, SMA, and edema in the subgroup analysis. A stronger correlation was noted between SMM from CT and BIA in male patients or mild edema group than for the other groups. SMM from BIA showed greater values than that from CT (mean difference, 3.35 kg) in all groups, except the normal SMA (higher than 170 cm2 in men, and 110 cm2 in women) group. Male patients and mild edema group showed more SMM as evaluated by BIA when compared to the other groups.
SMM measure by BIA in critically ill patients showed high correlation with SMM calculation by CT scan and had greater values than SMM from CT scan.
Ajou University Hospital Institutional Review Board DEV-DE4-15-115, Registered Jan 1 2015.
Low muscle mass and -quality on ICU admission, as assessed by muscle area and -density on CT-scanning at lumbar level 3 (L3), are associated with increased mortality. However, CT-scan analysis is not ...feasible for standard care. Bioelectrical impedance analysis (BIA) assesses body composition by incorporating the raw measurements resistance, reactance, and phase angle in equations. Our purpose was to compare BIA- and CT-derived muscle mass, to determine whether BIA identified the patients with low skeletal muscle area on CT-scan, and to determine the relation between raw BIA and raw CT measurements.
This prospective observational study included adult intensive care patients with an abdominal CT-scan. CT-scans were analysed at L3 level for skeletal muscle area (cm2) and skeletal muscle density (Hounsfield Units). Muscle area was converted to muscle mass (kg) using the Shen equation (MMCT). BIA was performed within 72 h of the CT-scan. BIA-derived muscle mass was calculated by three equations: Talluri (MMTalluri), Janssen (MMJanssen), and Kyle (MMKyle). To compare BIA- and CT-derived muscle mass correlations, bias, and limits of agreement were calculated. To test whether BIA identifies low skeletal muscle area on CT-scan, ROC-curves were constructed. Furthermore, raw BIA and CT measurements, were correlated and raw CT-measurements were compared between groups with normal and low phase angle.
110 patients were included. Mean age 59 ± 17 years, mean APACHE II score 17 (11–25); 68% male. MMTalluri and MMJanssen were significantly higher (36.0 ± 9.9 kg and 31.5 ± 7.8 kg, respectively) and MMKyle significantly lower (25.2 ± 5.6 kg) than MMCT (29.2 ± 6.7 kg). For all BIA-derived muscle mass equations, a proportional bias was apparent with increasing disagreement at higher muscle mass. MMTalluri correlated strongest with CT-derived muscle mass (r = 0.834, p < 0.001) and had good discriminative capacity to identify patients with low skeletal muscle area on CT-scan (AUC: 0.919 for males; 0.912 for females). Of the raw measurements, phase angle and skeletal muscle density correlated best (r = 0.701, p < 0.001). CT-derived skeletal muscle area and -density were significantly lower in patients with low compared to normal phase angle.
Although correlated, absolute values of BIA- and CT-derived muscle mass disagree, especially in the high muscle mass range. However, BIA and CT identified the same critically ill population with low skeletal muscle area on CT-scan. Furthermore, low phase angle corresponded to low skeletal muscle area and -density.
ClinicalTrials.gov (NCT02555670).
•Previous studies have shown that low muscle mass is associated with outcome. The absolute values of BIA- and CT-derived muscle mass are not comparable but the two are significantly correlated.•BIA and CT identify the same critically ill population with low muscle mass.•The BIA- and CT-derived markers for muscle quality, phase angle and skeletal muscle density, are correlated.
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