28 research outputs found
Health benefits of different sport disciplines for adults:systematic review of observational and intervention studies with meta-analysis
Health benefits of different sports:A systematic review and meta-analysis of longitudinal and intervention studies Including 2.6 million adult participants
Background Several reviews have examined the health benefits of participation in specific sports, such as baseball,cricket, cross-country skiing, cycling, downhill skiing, football, golf, judo, rugby, running and swimming. However, newprimary studies on the topic have recently been published, and the respective meta-analytic evidence needs to beupdated.Objectives To systematically review, summarise and appraise evidence on physical health benefits of participationin different recreational sports.Methods Searches for journal articles were conducted in PubMed/MEDLINE, Scopus, SpoLit, SPORTDiscus, SportsMedicine & Education Index and Web of Science. We included longitudinal and intervention studies investigatingphysical health outcomes associated with participation in a given sport among generally healthy adultswithout disability.Results A total of 136 papers from 76 studies conducted among 2.6 million participants were included in the review.Our meta-analyses of available evidence found that: (1) cycling reduces the risk of coronary heart disease by 16%(pooled hazard ratio [HR] = 0.84; 95% confidence interval [CI]: 0.80, 0.89), all-cause mortality by 21% (HR = 0.79; 95% CI:0.73, 0.84), cancer mortality by 10% (HR = 0.90; 95% CI: 0.85, 0.96) and cardiovascular mortality by 20% (HR = 0.80; 95%CI: 0.74, 0.86); (2) football has favourable effects on body composition, blood lipids, fasting blood glucose, blood pressure,cardiovascular function at rest, cardiorespiratory fitness and bone strength (p < 0.050); (3) handball has favourableeffects on body composition and cardiorespiratory fitness (p < 0.050); (4) running reduces the risk of all-causemortality by 23% (HR = 0.77; 95% CI: 0.70, 0.85), cancer mortality by 20% (HR = 0.80; 95% CI: 0.72, 0.89) and cardiovascularmortality by 27% (HR = 0.73; 95% CI: 0.57, 0.94) and improves body composition, cardiovascular function at restand cardiorespiratory fitness (p < 0.010); and (5) swimming reduces the risk of all-cause mortality by 24% (HR = 0.76;95% CI: 0.63, 0.92) and improves body composition and blood lipids (p < 0.010).ConclusionsA range of physical health benefits are associated with participation in recreational cycling, football, handball, running and swimming. More studies are needed to enable meta-analyses of health benefits of participation in other sports.PROSPERO registration number CRD42021234839
First application of IFCB high-frequency imaging-in-flow cytometry to investigate bloom-forming filamentous cyanobacteria in the Baltic Sea
Cyanobacteria are an important part of phytoplankton communities, however, they are also known for forming massive blooms with potentially deleterious effects on recreational use, human and animal health, and ecosystem functioning. Emerging high-frequency imaging flow cytometry applications, such as Imaging FlowCytobot (IFCB), are crucial in furthering our understanding of the factors driving bloom dynamics, since these applications provide community composition information at frequencies impossible to attain using conventional monitoring methods. However, the proof of applicability of automated imaging applications for studying dynamics of filamentous cyanobacteria is still scarce. In this study we present the first results of IFCB applied to a Baltic Sea cyanobacterial bloom community using a continuous flow-through setup. Our main aim was to demonstrate the pros and cons of the IFCB in identifying filamentous cyanobacterial taxa and in estimating their biomass. Selected environmental parameters (water temperature, wind speed and salinity) were included, in order to demonstrate the dynamics of the system the cyanobacteria occur in and the possibilities for analyzing high-frequency phytoplankton observations against changes in the environment. In order to compare the IFCB results with conventional monitoring methods, filamentous cyanobacteria were enumerated from water samples using light microscopical analysis. Two common bloom forming filamentous cyanobacteria in the Baltic Sea, Aphanizomenon flosaquae and Dolichospermum spp. dominated the bloom, followed by an increase in Oscillatoriales abundance. The IFCB results compared well with the results of the light microscopical analysis, especially in the case of Dolichospermum. Aphanizomenon biomass varied slightly between the methods and the Oscillatoriales results deviated the most. Bloom formation was initiated as water temperature increased to over 15°C and terminated as the wind speed increased, dispersing the bloom. Community shifts were closely related to movements of the water mass. We demonstrate how using a high-frequency imaging flow cytometry application can help understand the development of cyanobacteria summer blooms
Cross-impact analysis of Finnish electricity system with increased renewables: Long-run energy policy challenges in balancing supply and consumption
AbstractClimate change and global economic pressures are strong drivers for energy economies to transition towards climate-neutrality, low-carbon economy and better energy and resource efficiencies. The response to these pressures, namely the increased use of renewable energy, creates a set of new challenges related to supply-demand balance for energy policy and electricity system planning. This study analyses the emergent problems resulting from the renewable energy response. These complex aspects of change in the electricity system are analysed with a cross-impact model based on an expert-driven modeling process, consisting of workshops, panel evaluations and individual expert work. The model is then analysed using a novel computational cross-impact technique, EXIT. The objective of the study is to map the important direct drivers of change in the period 2017â2030 in electricity consumption and production in Finland, construct a cross-impact model from this basis, and discover the emergent and systemic dynamics of the modeled system by analysis of this model.</div
Drop-out and mood improvement: a randomised controlled trial with light exposure and physical exercise [ISRCTN36478292]
BACKGROUND: Combining bright light exposure and physical exercise may be an effective way of relieving depressive symptoms. However, relatively little is known about individual factors predicting either a good response or treatment failure. We explored background variables possibly explaining the individual variation in treatment response or failure in a randomised trial. METHODS: Participants were volunteers of working-age, free from prior mental disorders and recruited via occupational health centres. The intervention was a randomised 8-week trial with three groups: aerobics in bright light, aerobics in normal room lighting, and relaxation/stretching in bright light. Good response was defined as a 50% decrease in the symptom score on either the Hamilton Depression Rating Scale (HDRS) or 8-item scale of atypical symptoms. Background variables for the analysis included sex, age, body-mass index, general health habits, seasonal pattern, and sleep disturbances. RESULTS: Complete data were received from 98 subjects (11 men, 87 women). Of them, 42 (5 men, 37 women) were classified as responders on the HDRS. Overall, light had a significant effect on the number of responders, as assessed with the HDRS (X(2 )= .02). The number needed to treat (NNT) for light was 3.8. CONCLUSIONS: We investigated the effect of bright light and exercise on depressive symptoms. Problems with sleep, especially initial insomnia, may predict a good response to treatment using combined light and exercise. Bright light exposure and physical exercise, even in combination, seem to be well tolerated and effective on depressive symptoms
InDEx â Industrial Data Excellence
InDEx, the Industrial Data Excellence program, was created to investigate what industrial data can be collected, shared, and utilized for new intelligent services in high-performing, reliable and secure ways, and how to accomplish that in practice in the Finnish manufacturing industry.InDEx produced several insights into data in an industrial environment, collecting data, sharing data in the value chain and in the factory environment, and utilizing and manipulating data with artificial intelligence. Data has an important role in the future in an industrial context, but data sources and utilization mechanisms are more diverse than in cases related to consumer data. Experiences in the InDEx cases showed that there is great potential in data utili zation.Currently, successful business cases built on data sharing are either company-internal or utilize an existing value chain. The data market has not yet matured, and third-party offerings based on public and private data sources are rare. In this program, we tried out a framework that aimed to securely and in a controlled manner share data between organizations. We also worked to improve the contractual framework needed to support new business based on shared data, and we conducted a study of applicable business models. Based on this, we searched for new data-based opportunities within the project consortium. The vision of data as a tradeable good or of sharing with external partners is still to come true, but we believe that we have taken steps in the right direction.The program started in fall 2019 and ended in April 2022. The program faced restrictions caused by COVID-19, which had an effect on the intensity of the work during 2020 and 2021, and the program was extended by one year. Because of meeting restrictions, InDEx collaboration was realized through online meetings. We learned to work and collaborate using digital tools and environments. Despite the mentioned hindrances, and thanks to Business Finlandâs flexibility, the extension time made it possible for most of the planned goals to be achieved.This report gives insights in the outcomes of the companiesâ work within the InDEx program. DIMECC InDEx is the first finalized program by the members of the Finnish Advanced Manufacturing Network (FAMN, www.famn.fi).</p