Purpose: In Amsterdam – the Netherlands – we know that children living in low income households have a lower health status and report lower physical activity levels than their peers in middle- or high-income households. Seven primary schools located in neighborhoods with a low social-economic status are currently developing their own active school using the ‘Creating Active Schools Framework’. This study was conducted to assess the current physical activity and sedentary behavior patterns during and after school of the pupils in these seven primary schools.Methods: In this cross-sectional study, we collect data in seven schools located within an Amsterdam neighborhood with a low social economic status score. Within each school, 4 classes are eligible for participation. Children wear an accelerometer from Monday morning until Friday afternoon to assess physical activity levels. Parents of participating children are asked to complete a questionnaire on baseline characteristics, wellbeing and out of school physical activity behaviors. The mean sedentary time (ST), low physical activity (LPA) time and Moderate to Vigorous physical activity (MVPA) time will be calculated. The association between the outcomes of the accelerometer data and gender and health related outcomes reported by parents will be assessed.Results: The data will be collected between March and May 2023. We will present the average LPA and MVPA during and after school time. The duration of the ST bouts during and after schooltime. And associations between ST, LPA and MVPA and gender and health related outcomes.Conclusions: The results of this study will be used to support local school teams in the development and implementation of local action plans towards a school day that involves less sitting and more physical activity.
This applied research is an attempt to analyse the effectiveness of milk marketing and facilitate developing a sustainable milk value chain for dairy farmer’s groups in Punakha district. Both quantitative and qualitative methods of survey, key informant interviews and focus group discussion were used as research strategies to obtain relevant information. The survey was conducted using both open and closed-ended structured questionnaire in seven subdistricts of Barp, Dzomi, Guma, Kabisa, Shelnga-Bjemi, Talog and Toedwang. A total of 60 respondents; 30 existing milk suppliers and 30 non-milk suppliers were drawn using a simple random sampling technique. One-to-one interviews were conducted following semi-structured questions with eight key informants in the chain. One focus group interview was conducted with the existing dairy farmer groups representatives to triangulate and discover in-depth information about the situation of the milk value chain in the district. The survey data was analysed using the Statistical Package for Social Sciences software version 20. A method of grounded theory design was used to analyse the qualitative data of interviews and focus group discussion. Value chain mapping was employed for assessing the operational situation of the current milk chain. The mean cost of milk production was estimated at Nu.27.53 per litre and the maximum expenses were incurred in animal feeds which were estimated to be 46.34% of the total cost of milk production. In this study, milk producers had the highest share of added value and profit which were estimated at 45.45% and 44.85% respectively. Limited information and coordination amongst stakeholders have contributed to slow progression in the formal milk market. The finding reveals that 90% of nondairy farmer groups respondents were interested in joining formal milk marketing. The average morning milk available for supply from this group would be 4.41 ± 3.07 litres daily by each household. The study also found that 50% of the respondents were interested in supplying evening milk with an average of 4.43 ± 2.25 litres per day per household. Based on the result of this study, it was concluded that there are possibilities of expanding the milk value chain in the district. However, there is a need to enhance consistent milk supply through a quality-based milk payment system, access to reasonable input supplies, and facilitate strong multi-stakeholder processes along the milk value chain.
MULTIFILE
Background: Multiple sclerosis often leads to fatigue and changes in physical behavior (PB). Changes in PB are often assumed as a consequence of fatigue, but effects of interventions that aim to reduce fatigue by improving PB are not sufficient. Since the heterogeneous nature of MS related symptoms, levels of PB of fatigued patients at the start of interventions might vary substantially. Better understanding of the variability by identification of PB subtypes in fatigued patients may help to develop more effective personalized rehabilitation programs in the future. This study aimed to identify PB subtypes in fatigued patients with multiple sclerosis based on multidimensional PB outcome measures. Methods: Baseline accelerometer (Actigraph) data, demographics and clinical characteristics of the TREFAMS-ACE participants (n = 212) were used for secondary analysis. All patients were ambulatory and diagnosed with severe fatigue based on a score of ≥35 on the fatigue subscale of the Checklist Individual Strength (CIS20r). Fifteen PB measures were used derived from 7 day measurements with an accelerometer. Principal component analysis was performed to define key outcome measures for PB and two-step cluster analysis was used to identify PB types. Results: Analysis revealed five key outcome measures: percentage sedentary behavior, total time in prolonged moderate-to-vigorous physical activity, number of sedentary bouts, and two types of change scores between day parts (morning, afternoon and evening). Based on these outcomes three valid PB clusters were derived. Conclusions: Patients with severe MS-related fatigue show three distinct and homogeneous PB subtypes. These PB subtypes, based on a unique set of PB outcome measures, may offer an opportunity to design more individually-tailored interventions in rehabilitation.
MULTIFILE
Based on the model outcomes, Houtlaan’s energy transition will likely result in congestion and curtailmentproblems on the local electricity grid within the next 5-7 years, possibly sooner if load imbalance between phasesis not properly addressed.During simulations, the issue of curtailment was observed in significant quantities on one cable, resulting in aloss of 8.292 kWh of PV production per year in 2030. This issue could be addressed by moving some of thehouses on the affects cable to a neighboring under-utilized cable, or by installing a battery system near the end ofthe affected cable. Due to the layout of the grid, moving the last 7 houses on the affected cable to the neighboringcable should be relatively simple and cost-effective, and help to alleviate issues of curtailment.During simulations, the issue of grid overloading occurred largely as a result of EV charging. This issue can bestbe addressed by regulating EV charging. Based on current statistics, the bulk of EV charging is expected to occurin the early evening. By prolonging these charge cycles into the night and early morning, grid overloading canlikely be prevented for the coming decade. However, such a control system will require some sort of infrastructureto coordinate the different EV charge cycles or will require smart EV chargers which will charge preferentiallywhen the grid voltage is above a certain threshold (i.e., has more capacity available).A community battery system can be used to increase the local consumption of produced electricity within theneighborhood. Such a system can also be complemented by charging EV during surplus production hours.However, due to the relatively high cost of batteries at present, and losses due to inefficiencies, such a systemwill not be financially feasible without some form of subsidy and/or unless it can provide an energy service whichthe grid operator is willing to pay for (e.g. regulating power quality or line voltage, prolonging the lifetime of gridinfrastructure, etc.).A community battery may be most useful as a temporary solution when problems on the grid begin to occur, untila more cost-effective solution can be implemented (e.g. reinforcing the grid, implementing an EV charge controlsystem). Once a more permanent solution is implemented, the battery could then be re-used elsewhere.The neighborhood of Houtlaan in Assen, the Netherlands, has ambitious targets for reducing the neighborhood’scarbon emissions and increasing their production of their own, sustainable energy. Specifically, they wish toincrease the percentage of houses with a heat pump, electric vehicle (EV) and solar panels (PV) to 60%, 70%and 80%, respectively, by the year 2030. However, it was unclear what the impacts of this transition would be onthe electricity grid, and what limitations or problems might be encountered along the way.Therefore, a study was carried out to model the future energy load and production patterns in Houtlaan. Thepurpose of the model was to identify and quantify the problems which could be encountered if no steps are takento prevent these problems. In addition, the model was used to simulate the effectiveness of various proposedsolutions to reduce or eliminate the problems which were identified
