Rationale: Diagnosis of sarcopenia in older adults is essential for early treatment in clinical practice. Bio-electrical impedanceanalysis (BIA) may be a valid means to assess appendicular lean mass (ALM) in older adults, but limited evidence is available.Therefore, we aim to evaluate the validity of BIA to assess ALM in older adults.Methods: In 215 community dwelling older adults (age ≥ 55 years), ALM was measured by BIA (Tanita MC-780; 8-points) andcompared with dual-energy X-ray absorptiometry (DXA, Hologic Discovery A) as reference. Validity for assessing absolute values ofALM was evaluated by: 1) bias (mean difference), 2) percentage of accurate predictions (within 5% of DXA values), 3) individualerror (root mean squared error (RMSE), mean absolute deviation), 4) limits of agreement (Bland-Altman analysis). For diagnosis oflow ALM, the lowest quintile of ALM by DXA was used (below 21.4 kg for males and 15.4 for females). Sensitivity and specificityof detecting low ALM by BIA were assessed.Results: Mean age of the subjects was 71.9 ± 6.4, with a BMI of 25.8 ± 4.2 kg/m2, and 70% were females. BIA slightlyunderestimated ALM compared to DXA with a mean bias of -0.6 ± 0.2 kg. The percentage accurate predictions was 54% withRMSE 1.6 kg and limits of agreements -3.0 – +1.8 kg. Sensitivity was 79%, indicating that 79% of subjects with low ALMaccording to DXA also had low ALM with the BIA. Specificity was 90%, indicating that 90% of subjects with ‘no low’ ALMaccording to DXA also had ‘no low’ ALM with the BIA.Conclusions: This comparison showed a poor validity of BIA to assess absolute values of ALM, but a reasonable sensitivity andspecificity to diagnose a low level of ALM in community-dwelling older adults in clinical practice.
STUDY DESIGN: Cross-sectional study.OBJECTIVES: This study: (1) investigated the accuracy of bioelectrical impedance analysis (BIA) and skinfold thickness relative to dual-energy X-ray absorptiometry (DXA) in the assessment of body composition in people with spinal cord injury (SCI), and whether sex and lesion characteristics affect the accuracy, (2) developed new prediction equations to estimate fat free mass (FFM) and percentage fat mass (FM%) in a general SCI population using BIA and skinfolds outcomes.SETTING: University, the Netherlands.METHODS: Fifty participants with SCI (19 females; median time since injury: 15 years) were tested by DXA, single-frequency BIA (SF-BIA), segmental multi-frequency BIA (segmental MF-BIA), and anthropometry (height, body mass, calf circumference, and skinfold thickness) during a visit. Personal and lesion characteristics were registered.RESULTS: Compared to DXA, SF-BIA showed the smallest mean difference in estimating FM%, but with large limits of agreement (mean difference = -2.2%; limits of agreement: -12.8 to 8.3%). BIA and skinfold thickness tended to show a better estimation of FM% in females, participants with tetraplegia, or with motor incomplete injury. New equations for predicting FFM and FM% were developed with good explained variances (FFM: R2 = 0.94; FM%: R2 = 0.66).CONCLUSIONS: None of the measurement techniques accurately estimated FM% because of the wide individual variation and, therefore, should be used with caution. The accuracy of the techniques differed in different subgroups. The newly developed equations for predicting FFM and FM% should be cross-validated in future studies.
Background & aims: 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. Methods: 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. Results: 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. Conclusions: 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. Trial registration: ClinicalTrials.gov (NCT02555670).
In veel Afrikaanse landen zien we een inperking van de maatschappelijke ruimte (‘civic space’). Deze ruimte is cruciaal om in democratische staten transparantie, vrijheid van meningsuiting en verantwoording van bestuur te realiseren. In een steeds sterke digitaliserende maatschappij wordt toegang tot digitale middelen een mensenrecht. Daar waar regeringen proberen hun burgers en organisaties dat recht tot digitale informatievoorziening en –uitwisselingen te ontnemen komen de Sustainable Development Goals in het gedrang. Doel African Digital Rights Network (ADRN) wil inzicht verkrijgen in de stakeholders ne technologieën die betrokken zijn net het openen of onderdrukken van de online maatschappelijke ruimte (‘civic space’). Het netwerk beoogt bij te dragen aam empowerment van burgers om hun digitale mensenrechten uit te oefenen. Resultaten ADRN heeft een vergelijkende studie van 10 Afrikaanse landen uitgevoerd naar het gebruik van digitale technologieën voor het openen of onderdrukken van de online maatschappelijke ruimte (‘civic space’). Het project heeft onder andere geleidt tot de volgende publicatie: Mapping the Supply of Surveillance Technologies to Africa: Case Studies from Nigeria, Ghana, Morocco, Malawi, and Zambia Looptijd 01 mei 2020 - 20 april 2021 Aanpak ADRN organiseert een netwerk van onderzoekers, analisten, digitale rechtenorganisaties en activisten om de dynamiek van het openen en onderdrukken van de digitale maatschappelijke ruimte in kaart te brengen. Het netwerk bouwt op een interdisciplinaire onderzoeksaanpak o.l.v. het Institute for Development Studies, een vooraanstaand onderzoeksinstituut. Relevantie van het project Het onderzoek leidt tot aanbevelingen voor o.a. beleidsmakers en maatschappelijke organisaties ter bevordering van de digitale maatschappelijke ruimte. Daarnaast worden digitale tools en trainingsmateriaal gefaciliteerd voor het monitoren van ontwikkelingen en dreigingen van de digitale maatschappelijke ruimte. CofinancieringDit onderzoek wordt gefinancierd door UKRI - GCRF Digital Innovation for Development in Africa (DIDA)Meer weten? UKRI GCRF: African Digital Rights Network Website ADRN
Micro and macro algae are a rich source of lipids, proteins and carbohydrates, but also of secondary metabolites like phytosterols. Phytosterols have important health effects such as prevention of cardiovascular diseases. Global phytosterol market size was estimated at USD 709.7 million in 2019 and is expected to grow with a CAGR of 8.7% until 2027. Growing adoption of healthy lifestyle has bolstered demand for nutraceutical products. This is expected to be a major factor driving demand for phytosterols.Residues from algae are found in algae farming and processing, are found as beachings and are pruning residues from underwater Giant Kelp forests. Large amounts of brown seaweed beaches in the province of Zeeland and are discarded as waste. Pruning residues from Giant Kelp Forests harvests for the Namibian coast provide large amounts of biomass. ALGOL project considers all these biomass residues as raw material for added value creation.The ALGOL feasibility project will develop and evaluate green technologies for phytosterol extraction from algae biomass in a biocascading approach. Fucosterol is chosen because of its high added value, whereas lipids, protein and carbohydrates are lower in value and will hence be evaluated in follow-up projects. ALGOL will develop subcritical water, supercritical CO2 with modifiers and ethanol extraction technologies and compare these with conventional petroleum-based extractions and asses its technical, economic and environmental feasibility. Prototype nutraceutical/cosmeceutical products will be developed to demonstrate possible applications with fucosterol.A network of Dutch and African partners will supply micro and macro algae biomass, evaluate developed technologies and will prototype products with it, which are relevant to their own business interests. ALGOL project will create added value by taking a biocascading approach where first high-interest components are processed into high added value products as nutraceutical or cosmeceutical.
Micro and macro algae are a rich source of lipids, proteins and carbohydrates, but also of secondary metabolites like phytosterols. Phytosterols have important health effects such as prevention of cardiovascular diseases. Global phytosterol market size was estimated at USD 709.7 million in 2019 and is expected to grow with a CAGR of 8.7% until 2027. Growing adoption of healthy lifestyle has bolstered demand for nutraceutical products. This is expected to be a major factor driving demand for phytosterols. Residues from algae are found in algae farming and processing, are found as beachings and are pruning residues from underwater Giant Kelp forests. Large amounts of brown seaweed beaches in the province of Zeeland and are discarded as waste. Pruning residues from Giant Kelp Forests harvests for the Namibian coast provide large amounts of biomass. ALGOL project considers all these biomass residues as raw material for added value creation. The ALGOL feasibility project will develop and evaluate green technologies for phytosterol extraction from algae biomass in a biocascading approach. Fucosterol is chosen because of its high added value, whereas lipids, protein and carbohydrates are lower in value and will hence be evaluated in follow-up projects. ALGOL will develop subcritical water, supercritical CO2 with modifiers and ethanol extraction technologies and compare these with conventional petroleum-based extractions and asses its technical, economic and environmental feasibility. Prototype nutraceutical/cosmeceutical products will be developed to demonstrate possible applications with fucosterol. A network of Dutch and African partners will supply micro and macro algae biomass, evaluate developed technologies and will prototype products with it, which are relevant to their own business interests. ALGOL project will create added value by taking a biocascading approach where first high-interest components are processed into high added value products as nutraceutical or cosmeceutical.
