OBJECTIVE: The prevalence of osteoarthritis (OA) increases, but the impact of the disorder on peoples' functional capacity is not known. Therefore, the objective of this study was to compare self-reported health status and functional capacity of subjects with early OA of hip and/or knee to reference data of healthy working subjects and to assess whether this capacity is sufficient to meet physical job demands.METHODS: Self-reported health status and functional capacity of 93 subjects from the Cohort Hip and Cohort Knee (CHECK) were measured using the Short-Form 36 Health Survey and 6 tests of the Work Well Systems Functional Capacity Evaluation. Results were compared with reference data from 275 healthy workers, using t-tests. To compare the functional capacity with job demands, the proportions of subjects with OA performing lower than the p(5) of reference data were calculated.RESULTS: Compared to healthy workers, the subjects (mean age 56) from CHECK at baseline reported a significantly worse physical health status, whereas the women (n = 78) also reported a worse mental health status. On the FCE female OA subjects performed significantly lower than their healthy working counterparts on all 6 tests. Male OA subjects performed lower than male workers on 3 tests. A substantial proportion of women demonstrated functional capacities that could be considered insufficient to perform jobs with low physical demands.CONCLUSIONS: Functional capacity and self-reported health of subjects with early OA of the hips and knees were worse compared to healthy ageing workers. A substantial proportion of female subjects did not meet physical job demands.
OBJECTIVE: To reach consensus on the most important biopsychosocial factors that influence functional capacity results in patients with chronic nonspecific musculoskeletal pain, arranged in the framework of the International Classification of Functioning, Disability and Health.DESIGN: Three-round, internet-based Delphi survey.SETTING: Not applicable.PARTICIPANTS: Participants were scientists, clinicians, and patients familiar with functional capacity testing. Scientists were invited through purposive sampling based on the number of relevant publications in peer-reviewed journals. The scientists recruited clinicians and patients through snowball sampling.INTERVENTIONS: Not applicable.MAIN OUTCOME MEASURES: Consensus was reached if at least moderate influence (25%) was achieved and an interquartile range of no more than 1 point was reached.RESULTS: Thirty-three scientists, 21 clinicians, and 21 patients from 9 countries participated. Participants reached consensus on 6 factors that can influence the outcome of the lifting test, having a median of severe influence (50%-95%): catastrophic thoughts and fear, patient adherence to "doctor's orders," internal and external motivation, muscle power, chronic pain behavior, and avoidance behavior. Motivation, chronic pain behavior, and sensation of pain were the top 3 factors affecting postural tolerance and repetitive movement functional capacity tests. Furthermore, participants reported 28 factors having a median of moderate influence (25%-49%) that could influence the outcome of lifting, postural tolerance, and repetitive movement tests.CONCLUSIONS: Overall, chronic pain behavior, motivation, and sensation of pain are the main factors that can influence functional capacity results. We recommend that scientists and clinicians, respectively, consider the most important factors when planning future studies and when interpreting functional capacity test results.
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Background: Functional Capacity (FC) is a multidimensional construct within the activity domain of the International Classification of Functioning, Disability and Health framework (ICF). Functional capacity evaluations (FCEs) are assessments of work-related FC. The extent to which these work-related FC tests are associated to bio-, psycho-, or social factors is unknown. The aims of this study were to test relationships between FC tests and other ICF factors in a sample of healthy workers, and to determine the amount of statistical variance in FC tests that can be explained by these factors. Methods: A cross sectional study. The sample was comprised of 403 healthy workers who completed material handling FC tests (lifting low, overhead lifting, and carrying) and static work FC tests (overhead working and standing forward bend). The explainable variables were; six muscle strength tests; aerobic capacity test; and questionnaires regarding personal factors (age, gender, body height, body weight, and education), psychological factors (mental health, vitality, and general health perceptions), and social factors (perception of work, physical workloads, sport-, leisure time-, and work-index). A priori construct validity hypotheses were formulated and analyzed by means of correlation coefficients and regression analyses. Results: Moderate correlations were detected between material handling FC tests and muscle strength, gender, body weight, and body height. As for static work FC tests; overhead working correlated fair with aerobic capacity and handgrip strength, and low with the sport-index and perception of work. For standing forward bend FC test, all hypotheses were rejected. The regression model revealed that 61% to 62% of material handling FC tests were explained by physical factors. Five to 15% of static work FC tests were explained by physical and social factors. Conclusions: The current study revealed that, in a sample of healthy workers, material handling FC tests were related to physical factors but not to the psychosocial factors measured in this study. The construct of static work FC tests remained largely unexplained.
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Direct Air Capture (DAC) technology is necessary to help achieve the EU's 2050 climate goals, since it allows for net-negative emissions. This will be needed to offset historic emissions while working alongside with other CCU technologies. To make DAC technology truly effective, the carbon footprint of the process itself should be as low as possible. This project describes research plans to minimize the DAC carbon footprint (as well as cost per ton of CO2) by developing technology to maximize DAC filter lifetimes. The project outlines a strategic partnership between Skytree, a Dutch DAC start-up, and Dr. Baumgarter’s research group at the University of Amsterdam. Based on Life Cycle Analyses (LCA) performed by Skytree, they have identified that extending the lifetime of DAC filters can lower the overall carbon footprint by 35%. Similarly, Techno-Economic Assessment indicated that this increased lifetime could lower the cost per ton of CO2 by 10%. To achieve this, both parties will develop an indicator technique to accurately describe filter lifetime to allow for data-driven optimized filter maintenance. The indicator development will expand on a patented technology developed by Skytree. The current technology uses a colorimetric dye to qualitatively assess filter capacity. By gaining access to advanced analytical methods built at UvA, this technology can be enhanced to allow for quantitative sorbent capacity and thus lifetime predictions. Since Dr. Baumgartner’s group specializes in building innovative spectroscopic technique that can monitor functional materials during gas sorption processes, the proposed studies will be able to directly and accurately link sorbent capture performance (using IR spectroscopy) with indicator dye intensity (using UV-Vis spectroscopy). This will allow for the fast development of a calibrated filter lifetime indicator. This makes the foreseen research highly practical and impactful, as the results will directly be implemented in commercial DAC/CCU technology.
Regular physical activity is considered to be an important component of a healthy lifestyle that decreases the risk of coronary heart disease, diabetes mellitus type 2, hypertension, colon and breast cancer, obesity and other debilitating conditions. Physical activity can also improve functional capacity and therefore also the quality of life in older adults. Despite all these favorable aspects, a substantial part of the Dutch older adult population is still underactive or even sedentary. To change this for the better, the Groningen Active Living Model (GALM) was developed.Aim of GALM is to stimulate recreational sports activities in sedentary and underactive older adults in the 55-65 age band. After a door-to-door visit as part of an intensive recruitment phase, a fitness test was conducted followed by the GALM recreational sports program. This program was based on principles from evolutionary-biological play theory and insights fromsocial cognitive theory. The program was versatile in nature (e.g. softball, dance, self-defense, swimming, athletics, etc.) in two main ways: a) to improve compliance with the program different sports were offered, which was reported to be more appealing for older adults; b) by aiming at more components of motor fitness (e.g. strength, flexibility, speed, endurance and coordination). Between 1997 and 2005 more than 552,000 persons were visited door-to-door, over 55,700 were tested, and 41,310 participated in the GALM recreational sports program. The aim of the present thesis is to determine the effects of participation in the GALM recreational sports program on physical activity, health and fitness outcomes.Chapter 2 describes the effectiveness of the GALM recruitment in selecting and recruiting sedentary and underactive older adults. Three municipalities in the Netherlands were selected, and in every municipality four neighborhoods were included. Two of each of the four neighborhoods were randomly assigned as intervention and the others as control neighborhoods. In total, 8,504 persons were mailed and received a home visit. During this home visit the GALM recruitment questionnaire was collected on which the selection between sedentary/underactive and physically active older adults was based. Ultimately we succeeded inincluding 12.3% (315 of the 2,551 qualifying) of the older adults, 79.4% of whom could be indeed considered sedentary or underactive. The cost of successfully recruiting an older adult was estimated at $84.To assess the effects of a physical activity intervention on health and fitness and explain the results, it is necessary to know program characteristics regarding frequency, intensity, time and content of the activities. With respect to the GALM recreational sports activity program, the only unknown characteristic was intensity. Chapter 3 describes the intensity of this program systematically. Using heart rate monitors, data of 97 persons (mean age 60.1 yr) were collected in three municipalities. The mean intensity of all 15 GALM sessions was 73.7% of the predicted maximal heart rate. Six percent of the monitored heart rate time could be classified as light, 33% as moderate and 61% as hard. In summary, the GALM recreational sports program meets the 1998 ACSM recommendations for intensity necessary to improve cardiorespiratory fitness.Chapters 4 and 5 describe the effects of 6 and 12 months of participation in the GALM recreational sports program, and 181 persons were followed over time. Results after 6 months revealed only few significant between-group differences favoring the intervention group (i.e. sleep, diastolic blood pressure, perceived fitness score and grip strength). Changes in energyexpenditure for leisure-time physical activities (EELTPA) showed an increase in both study groups. From 6 to 12 months a decrease in EELTPA occurred in the intervention group and an increase in the control group. The significant positive time effects for the health outcomes (diastolic blood pressure, BMI, percentage of body fat) that were found after 6 months were diminishedfrom 6 to 12 months. However, the energy expenditure for recreational sports activities (EERECSPORT) demonstrated a continuous increase over 12 months. Parallel to this, significant main effects for time were found in performance-based fitness outcomes (i.e. simple reaction time, leg strength, flexibility of hamstrings and lower back, and aerobic endurance). After 12 months only a significant between-group difference for flexibility of the hamstrings andlower back was found, favoring the control group. In conclusion, a short-term increase in EELTPA was found with accompanying improvements in health outcomes that more or less disappeared in 6 to 12 months. In the long term, results showed a continuous increase in EERECSPORT and performance-based fitness. This latter increase is probably a reflection of the significantimprovement over time in EERECSPORT and the fact that recreational sports activities are of a higher intensity.Aerobic endurance is regarded as the most important component of motor fitness that is relevant for older adults to function independently. In Chapter 6, the development in aerobic endurance after 18 months of participation in the GALM recreational sports program was assessed by means of changes in heart rate during fixed submaximal exercise. Since both groups were comparable regarding changes in energy expenditure for physical activity after 6 months and testing confirmed this, both groups were combined and considered as one group. Multilevel analyses were conducted and models for change were developed. A significant decrease in heart rate over time was found at all walking speeds (4, 5, 6 and 7 km/h). The average decrease in heart rate was 5.5, 6.0, 10.0 and 9.0 beats/min for the 4, 5, 6 and 7 km/h walking speeds, respectively. The relative decrease varied from 5.1 to 7.4% relative to average heart rates at baseline. These results illustrate that participation in the GALM recreational sports program has a positive significant effect on aerobic endurance, and that the participants are able to perform at submaximal intensity more easily.Based on the overall results it can be concluded that this study contributes to the field in how to effectively recruit sedentary and underactive older adults and stimulate them to become and stay active in recreational sports activities. As far as we know, this recruitment in combination with the recreational sport program is not only unique but also effective toward increasing performance-based fitness in the long term. Short-term effects were found in other leisure-time activities and health outcomes. To further stimulate other leisure-time and probably health outcomes besides the favorable effects that were already seen, additional interventions that pay more attention to behavioral change in terms of how to integrate other activities besides sports activities are recommended.
