BACKGROUND: An early return to normal intake and early mobilization enhances postoperative recovery. However, one out of six surgical patients is undernourished during hospitalization and approximately half of the patients eat 50% or less of the food provided to them. We assessed the use of newly introduced breakfast buffets in two wards for gastrointestinal and oncological surgery and determined the impact on postoperative protein and energy intake.METHODS: A prospective pilot cohort study was conducted to assess the impact of the introduction of breakfast buffets in two surgical wards. Adult patients had the opportunity to choose between an attractive breakfast buffet and regular bedside breakfast service. Primary outcomes were protein and energy intake during breakfast. We asked patients to report the type of breakfast service and breakfast intake in a diary over a seven-day period. Prognostic factors were used during multivariable regression analysis.RESULTS: A total of 77 patients were included. The median percentage of buffet use per patient during the seven-day study period was 50% (IQR 0-83). Mean protein intake was 14.7 g (SD 8.4) and mean energy intake 332.3 kcal (SD 156.9). Predictors for higher protein intake included the use of the breakfast buffet (β = 0.06, p = 0.01) and patient weight (β = 0.13, p = 0.01). Both use of the breakfast buffet (β = 1.00, p = 0.02) and Delirium Observation Scale scores (β = -246.29, p = 0.02) were related to higher energy intake.CONCLUSION: Introduction of a breakfast buffet on a surgical ward was associated with higher protein and energy intake and it could be a promising approach to optimizing such intake in surgical patients. Large, prospective and preferably randomized studies should confirm these findings.
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Bijen zijn door hun rol in het bestuiven van planten volstrekt onmisbaar voor het behoud van flora en fauna in Nederland én zij hebben een cruciale economische functie in de land- en tuinbouw. Al een aantal jaren is het duidelijk dat actie nodig is om bijen te beschermen. In 2013 heeft het toenmalige kabinet een Actieprogramma Bijengezondheid gepresenteerd. Dat richtte zich vooral op de honingbij. Deze nieuwe Nationale Bijenstrategie richt zich op alle ‘bestuivers’, in het bijzonder de vele wilde bijensoorten. In Nederland horen juist wilde bijen tot de voornaamste bestuivers. Meer dan de helft van de wilde bijensoorten staat echter op de Rode Lijst. Zij worden met uitsterven bedreigd. In 2017 is in Nederland breed onderkend dat meer insecten in de gevarenzone verkeren. Daarom hebben wetenschappers en maatschappelijke organisaties stappen gezet voor een Deltaplan Biodiversiteitsherstel groene ruimte van Nederland. Verbinding tussen de bijenstrategie en dit deltaplan is van groot belang. Met deze nieuwe strategie willen wij tot een alomvattende aanpak komen om alle bijensoorten en andere bestuivers blijvend te behouden. Daarvoor hebben wilde bijen twee dingen nodig: nestelgelegenheid en voldoende voedselaanbod, zeg maar: bed & breakfast for bees. In de vele initiatieven waaraan wordt gewerkt en in deze strategie zijn drie kernthema’s vastgesteld, namelijk 1) het bevorderen van de biodiversiteit, 2) het verbeteren van de wisselwerking tussen landbouw en natuur en 3) het helpen van imkers om de gezondheid van de honingbij te verbeteren.
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Background: A protein intake of 30‐40 g per meal is suggested to maximally stimulate muscle protein synthesis in older adults and could therefore contribute to the prevention of sarcopenia. Protein intake at breakfast and lunch is often low and offers a great opportunity to improve daily protein intake. Protein, however, is known for its satiating effects. Therefore, we explored the association between the amount of protein intake at breakfast and lunch and total daily protein intake in older adults.Methods: Protein intake was assessed by a 3‐day food record in 498 community dwelling older adults (≥55 years) participating different lifestyle interventions. Linear mixed model analysis was used to examine the association between protein intake at breakfast or lunch and total daily protein intake, adjusted for sex, age, body mass index, smoking status, study and total energy intake.Results: After adjustment for potential confounders, a 10 g higher protein intake at breakfast was associated with a 3.2 g higher total daily protein intake (P = 0.008) for males and a 4.9 g (P < 0.001) higher total daily protein intake for females. A 10 g higher protein intake at lunch was associated with a 3.7 g higher total daily protein intake (P < 0.001) for males, and a 5.8 g higher total daily protein intake (P < 0.001) for females.Conclusions: A higher protein intake at breakfast and lunch is associated with a higher total daily protein intake in community dwelling older adults. Stimulating a higher protein intake at breakfast and lunch might represent a promising nutritional strategy to optimise the amount of protein per meal without compromising total daily protein intake.
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Introduction: A protein intake of 25–30 g per meal is suggested to maximally stimulate muscle protein synthesis in older adults in order to prevent sarcopenia. Protein intake at breakfast is often low and therefore breakfast offers the potential for protein suppletion. Since protein is known for its satiating effects, we explored the association between the amount of protein intake at breakfast and total daily protein intake in older adults. Methods: Baseline protein intake was assessed by a 3-day dietary record in 507 community dwelling older adults of 55 years and older participating in lifestyle interventions at the Amsterdam Nutritional Assessment Center. Multiple linear regression analysis was used to examine the association between protein intake at breakfast (in g) and total daily protein intake (in g, and g/kg body weight), adjusted for energy intake (kcal/d), sex, age and BMI. Interactions were tested for sex, age and BMI but were not significant (p>0.80). Results: Mean age was 67.6 ± (SD) 7.3 years, 42% was female, and mean BMI was 30.0 ± 5.6 kg/m2. Total daily protein intake was 81 ± 24 g which equals 0.96 ± 0.3 g/kg and 17.6 ± 3.7 percent of total energy intake. Protein intake at breakfast was 14 ± 7 g. A 10 g higher protein intake at breakfast was associated with a 6.7 g (SE = 1.0; P<0.001) and a 0.06 g/kg (SE = 0.01; P<0.001) higher total daily protein intake after adjustment for confounders. Key conclusions: A higher protein intake at breakfast does not compromise total daily protein intake in community dwelling older adults.
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Introduction: A protein intake of 25–30 g per meal is suggested to maximally stimulate muscle protein synthesis in older adults in order to prevent sarcopenia. Protein intake at breakfast is often low and therefore breakfast offers the potential for protein suppletion. Since protein is known for its satiating effects, we explored the association between the amount of protein intake at breakfast and total daily protein intake in older adults. Methods: Baseline protein intake was assessed by a 3-day dietary record in 507 community dwelling older adults of 55 years and older participating in lifestyle interventions at the Amsterdam Nutritional Assessment Center. Multiple linear regression analysis was used to examine the association between protein intake at breakfast (in g) and total daily protein intake (in g, and g/kg body weight), adjusted for energy intake (kcal/d), sex, age and BMI. Interactions were tested for sex, age and BMI but were not significant (p>0.80). Results: Mean age was 67.6 ± (SD) 7.3 years, 42% was female, and mean BMI was 30.0 ± 5.6 kg/m2. Total daily protein intake was 81 ± 24 g which equals 0.96 ± 0.3 g/kg and 17.6 ± 3.7 percent of total energy intake. Protein intake at breakfast was 14 ± 7 g. A 10 g higher protein intake at breakfast was associated with a 6.7 g (SE = 1.0; P<0.001) and a 0.06 g/kg (SE = 0.01; P<0.001) higher total daily protein intake after adjustment for confounders. Key conclusions: A higher protein intake at breakfast does not compromise total daily protein intake in community dwelling older adults.
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Unhealthy eating behaviors and low levels of physical activity are major problems in adolescents and young adults in vocational education. To develop effective intervention programs, more research is needed to understand how different types of motivation contribute to health behaviors. In the present study, Self-Determination Theory is used to examine how motivation contributes to dietary and physical activity behaviors in vocational students. This cross-sectional study included 809 students (mean age 17.8 ± 1.9 years) attending vocational education in the Netherlands. Linear multilevel regression analyses were used to investigate the association between types of motivation and dietary and physical activity behaviors. Amotivation was negatively associated with breakfast frequency and positively associated with diet soda consumption and high-calorie between-meal snacks. A positive association was found between autonomous motivation and water intake, breakfast frequency, fruit intake, and moderate-to-vigorous physical activity. Autonomous motivation was negatively associated with the consumption of unhealthy products. Controlled motivation was not associated with physical activity or dietary behaviors. Different types of motivation seem to explain either healthy or unhealthy dietary behaviors in vocational students. Autonomous motivation, in particular, was shown to be associated with healthy behaviors and could therefore be a valuable intervention target.
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Specific approaches are needed to reach and support people with a lower socioeconomic position (SEP) to achieve healthier eating behaviours. There is a growing body of evidence suggesting that digital health tools exhibit potential to address these needs because of its specific features that enable application of various behaviour change techniques (BCTs). The aim of this scoping review is to identify the BCTs that are used in diet-related digital interventions targeted at people with a low SEP, and which of these BCTs coincide with improved eating behaviour. The systematic search was performed in 3 databases, using terms related to e/m-health, diet quality and socioeconomic position. A total of 17 full text papers were included. The average number of BCTs per intervention was 6.9 (ranged 3–15). BCTs from the cluster ‘Goals and planning’ were applied most often (25x), followed by the clusters ‘Shaping knowledge’ (18x) and ‘Natural consequences’ (18x). Other frequently applied BCT clusters were ‘Feedback and monitoring’ (15x) and ‘Comparison of behaviour’ (13x). Whereas some BCTs were frequently applied, such as goal setting, others were rarely used, such as social support. Most studies (n = 13) observed a positive effect of the intervention on eating behaviour (e.g. having breakfast) in the low SEP group, but this was not clearly associated with the number or type of applied BCTs. In conclusion, more intervention studies focused on people with a low SEP are needed to draw firm conclusions as to which BCTs are effective in improving their diet quality. Also, further research should investigate combinations of BCTs, the intervention design and context, and the use of multicomponent approaches. We encourage intervention developers and researchers to describe interventions more thoroughly, following the systematics of a behaviour change taxonomy, and to select BCTs knowingly.
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Protein supplementation has shown to improve muscle mass in older adults. However, its effect may be influenced by supplementation dose, frequency and timing. This systematic review aimed to assess the effect of dose, frequency and timing of protein supplementation on muscle mass in older adults. Five databases were systematically searched from inception to 14 March 2023, for randomised controlled trials investigating the effect of protein supplementation on muscle mass in adults aged ≥65 years. Random effects meta-analyses were performed, stratified by population. Subgroups were created for dose (≥30 g, <30 g/day), frequency (once, twice, three times/day) and timing of supplementation (at breakfast, breakfast and lunch, breakfast and dinner, all meals, between meals). Heterogeneity within and between subgroups was assessed using I 2 and Cochran Q statistics respectively. Thirty-eight articles were included describing community-dwelling (28 articles, n=3204, 74.6±3.4 years, 62.8 % female), hospitalised (8 articles, n=590, 77.0±3.7 years, 50.3 % female) and institutionalised populations (2 articles, n=156, 85.7±1.2 years, 71.2 % female). Protein supplementation showed a positive effect on muscle mass in community-dwelling older adults (standardised mean difference 0.116; 95 % confidence interval 0.032–0.200 kg, p=0.007, I 2=15.3 %) but the effect did not differ between subgroups of dose, frequency and timing (Q=0.056, 0.569 and 3.084 respectively, p>0.05). Data including hospitalised and institutionalised populations were limited. Protein supplementation improves muscle mass in community-dwelling older adults, but its dose, frequency or timing does not significantly influence the effect.
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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.
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