The retirement phase is an opportunity to integrate healthy (nutrition/exercise) habits into daily life. We conducted this systematic review to assess which nutrition and exercise interventions most effectively improve body composition (fat/muscle mass), body mass index (BMI), and waist circumference (WC) in persons with obesity/overweight near retirement age (ages 55–70 y). We conducted a systematic review and network meta-analysis (NMA) of randomized controlled trials, searching 4 databases from their inception up to July 12, 2022. The NMA was based on a random effects model, pooled mean differences, standardized mean differences, their 95% confidence intervals, and correlations with multi-arm studies. Subgroup and sensitivity analyses were also conducted. Ninety-two studies were included, 66 of which with 4957 participants could be used for the NMA. Identified interventions were clustered into 12 groups: no intervention, energy restriction (i.e., 500–1000 kcal), energy restriction plus high-protein intake (1.1–1.7 g/kg/body weight), intermittent fasting, mixed exercise (aerobic and resistance), resistance training, aerobic training, high protein plus resistance training, energy restriction plus high protein plus exercise, energy restriction plus resistance training, energy restriction plus aerobic training, and energy restriction plus mixed exercise. Intervention durations ranged from 8 wk to 6 mo. Body fat was reduced with energy restriction plus any exercise or plus high-protein intake. Energy restriction alone was less effective and tended to decrease muscle mass. Muscle mass was only significantly increased with mixed exercise. All other interventions including exercise effectively preserved muscle mass. A BMI and/or WC decrease was achieved with all interventions except aerobic training/resistance training alone or resistance training plus high protein. Overall, the most effective strategy for nearly all outcomes was combining energy restriction with resistance training or mixed exercise and high protein. Health care professionals involved in the management of persons with obesity need to be aware that an energy-restricted diet alone may contribute to sarcopenic obesity in persons near retirement age.This network meta-analysis is registered at https://www.crd.york.ac.uk/prospero/ as CRD42021276465.
MULTIFILE
BACKGROUND: Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.METHODS: Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined.RESULTS: We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small.CONCLUSIONS: We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.
When it comes to hard to solve problems, the significance of situational knowledge construction and network coordination must not be underrated. Professional deliberation is directed toward understanding, acting and analysis. We need smart and flexible ways to direct systems information from practice to network reflection, and to guide results from network consultation to practice. This article presents a case study proposal, as follow-up to a recent dissertation about online simulation gaming for youth care network exchange (Van Haaster, 2014).
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.
This project develops a European network for transdisciplinary innovation in artistic engagement as a catalyst for societal transformation, focusing on immersive art. It responds to the professionals in the field’s call for research into immersive art’s unique capacity to ‘move’ people through its multisensory, technosocial qualities towards collective change. The project brings together experts leading state-of-the-art research and practice in related fields with an aim to develop trajectories for artistic, methodological, and conceptual innovation for societal transformation. The nascent field of immersive art, including its potential impact on society, has been identified as a priority research area on all local-to-EU levels, but often suffers from the common (mis)perception as being technological spectacle prioritising entertainment values. Many practitioners create immersive art to enable novel forms of creative engagement to address societal issues and enact change, but have difficulty gaining recognition and support for this endeavour. A critical challenge is the lack of knowledge about how their predominantly sensuous and aesthetic experience actually lead to collective change, which remains unrecognised in the current systems of impact evaluation predicated on quantitative analysis. Recent psychological insights on awe as a profoundly transformative emotion signals a possibility to address this challenge, offering a new way to make sense of the transformational effect of directly interacting with such affective qualities of immersive art. In parallel, there is a renewed interest in the practice of cultural mediation, which brings together different stakeholders to facilitate negotiation towards collective change in diverse domains of civic life, often through creative engagements. Our project forms strategic grounds for transdisciplinary research at the intersection between these two developments. We bring together experts in immersive art, psychology, cultural mediation, digital humanities, and design across Europe to explore: How can awe-experiences be enacted in immersive art and be extended towards societal transformation?
Industry 4.0 omvat de toenemende digitalisatie binnen bedrijven, resulterend in een inter-connectiviteit tussen mensen, objecten en systemen in real time. Dit resulteert in fundamentele veranderingen in de manier waarop mensen werken, beslissingen nemen en hun activiteiten managen. Deze nieuwe technologieën, zoals robotoplossingen beïnvloeden ook de manier waarop kennis wordt verworven, overgedragen en gebruikt en vragen om nieuwe managementpraktijken om het leren, de kennisdeling en zodoende het continu verbeteren te faciliteren (Lepore, et al., 2022). Dit onderzoek bouwt voort op bevindingen uit eerdere onderzoeken (RAAK Integraal Robotiseren). Waar eerder is gekeken naar succesfactoren voor het implementeren van de robot oplossing, wordt nu gekeken naar het continue verbeteren van de robotoplossing, met de focus op de impact van interne sociale relaties. De Social Network Analysis (SNA) zou kunnen helpen om de ontwikkeling en dynamiek van kennisdelingsrelaties tijdens robotiseringstrajecten in kaart te brengen en interventies te plannen, voor het verbeteren van dergelijke relaties. De uitkomst van dit onderzoek geeft het MKB een meetinstrument, waarmee een nulmeting kan worden gecreëerd. De nulmeting geeft inzicht hoe de inrichting van de interne kennisdelingsrelaties zijn opgebouwd. Met de interpretatie van de resultaten kan bepaald worden hoe effectief deze relaties zijn. Doelstelling van dit onderzoek is het ontwikkelen van een SNA meetinstrument waarmee inzicht gecreëerd wordt in het ontstaan van- en dynamiek binnen kennisdelingsrelaties. Met deze kennis kunnen Mkb’ers interventies uitvoeren om kritische kennis gerelateerd aan de robotoplossing bij de juiste personen te borgen.
