Background: Our aim was to identify dietary patterns by the level of maternal education that contribute to BMI, fat mass index (FMI), and fat-free mass index (FFMI) in children at age 5 and to assess if these dietary patterns are related to BMI at age 10. Methods: Per group (low/middle/high level), Reduced Rank Regression (RRR) was used to derive dietary patterns for the response variables BMI z-score, FMI, and FFMI in 1728 children at age 5 in the Amsterdam Born Children and their Development (ABCD) cohort. Regression analyses were then used to determine the association with BMI at age 10. Results: In each group, pattern 1 was characterized by its own cluster of food groups. Low: water/tea, savory snacks, sugar, low-fat meat, and fruits; middle: water/tea, low-fat cheese, fish, low-fat dairy, fruit drink, low-fat meat, and eggs; and high: low-fat cheese, fruits, whole-grain breakfast products, and low-fat and processed meat. Additionally, in each group, pattern 1 was positively associated with BMI z-scores at age 10 (low: β ≤ 0.43 [95% CI ≤ 0.21; 0.66], p < 0.001, middle: β ≤ 0.23 [0.09; 0.36], p ≤ 0.001, and high: β ≤ 0.24 [0.18; 0.30], p < 0.001). Conclusions: The dietary patterns stratified by the level of maternal education are characterized by different food groups. But in all the groups, pattern 1 is positively associated with BMI at age 10.
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Hundreds of sensors in our smartphones, cars, houses and other "smart" devices feed the IoT, that monitors both our functioning, and that of the smart devices. In 2050 the Internet of Things - which processes and stores all sensor data - will require a multiple of all the current energy together in air traffic and meat consumption. Living an environmentally friendly life will be just a drop in the ocean. With every step we take, servers all over the world start to analyze and store sensor data from the smartphone in our pocket. Habermas states that the system supplants ("colonizes") the lifeworld. It is of great importance that economic and social disciplines make a serious effort to restore the balance between the system world and the lifeworld.
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INTRODUCTION: Sufficient high quality dietary protein intake is required to prevent or treat sarcopenia in elderly people. Therefore, the intake of specific protein sources as well as their timing of intake are important to improve dietary protein intake in elderly people.OBJECTIVES: to assess the consumption of protein sources as well as the distribution of protein sources over the day in community-dwelling, frail and institutionalized elderly people.METHODS: Habitual dietary intake was evaluated using 2- and 3-day food records collected from various studies involving 739 community-dwelling, 321 frail and 219 institutionalized elderly people.RESULTS: Daily protein intake averaged 71 ± 18 g/day in community-dwelling, 71 ± 20 g/day in frail and 58 ± 16 g/day in institutionalized elderly people and accounted for 16% ± 3%, 16% ± 3% and 17% ± 3% of their energy intake, respectively. Dietary protein intake ranged from 10 to 12 g at breakfast, 15 to 23 g at lunch and 24 to 31 g at dinner contributing together over 80% of daily protein intake. The majority of dietary protein consumed originated from animal sources (≥60%) with meat and dairy as dominant sources. Thus, 40% of the protein intake in community-dwelling, 37% in frail and 29% in institutionalized elderly originated from plant based protein sources with bread as the principle source. Plant based proteins contributed for >50% of protein intake at breakfast and between 34% and 37% at lunch, with bread as the main source. During dinner, >70% of the protein intake originated from animal protein, with meat as the dominant source.CONCLUSION: Daily protein intake in these older populations is mainly (>80%) provided by the three main meals, with most protein consumed during dinner. More than 60% of daily protein intake consumed is of animal origin, with plant based protein sources representing nearly 40% of total protein consumed. During dinner, >70% of the protein intake originated from animal protein, while during breakfast and lunch a large proportion of protein is derived from plant based protein sources.
The growing awareness of consumers of the increasing problem with livestock and meat production due to the high nitrogen emissions and the related impact on climate change drives consumption of plant based vegetarian alternatives. Similarly there is also an increasing demand for animal-free, eco-friendly alternative vegan leather. Consequently there has been significant interest in developing leather-like vegan materials from multiple plant sources, such as mango, pineapple and mushroom based materials. However, the commercialization and the growth of sustainable vegan leather production is hampered significantly by the difficulty of achieving the needed quality for the various consumer products as well as the high prices of the vegan alternatives. In the Growing Leather project two SMEs, BioscienZ and B4Plastics, will combine forces with Avans University of Applied Sciences to develop vegan leather from the mushroom based material called mycelium. BioScienZ is a biotech company with strong expertise and capacity to produce low-cost and consistent quality mycelium. B4Plastics is a material development company, with strengths in designing and distributing eco-plastic products. In this project Avans University will use several mycelium types (produced by BioscienZ), and with the guidance of B4Plastics, it will test various additives under many different conditions, to ultimately develop an environmentally friendly, vegan material that will have comparable material characteristics to animal leather and is competitive in price.
