High consumption of animal-source foods, specifically meat, adversely affects human health and the environment. Dietary habits are shaped at younger ages and a reduction in meat consumption may be facilitated by the life course transitions in early adulthood, but studies are limited. This study among young Dutch adults aimed to describe their perceptions on the influence of life course transitions on meat consumption, barriers and enablers to reduce meat consumption, and strategies for reducing meat consumption. Barriers and enablers were grouped applying the COM-B model that includes capability, opportunity, and motivation. This quantitative cross-sectional study included a representative sample of 1806 young adults from two Dutch consumer panels who completed an online survey. Young adults frequently reported life course transitions, especially those related to moving house, to have decreased their meat consumption. Barriers and enablers to reduce meat consumption were identified for all three factors of the COM-B model. Important barriers included taste, perceived high prices of meat alternatives, and habits. In contrast, important enablers included care for the environment and animal welfare, enjoyment of smaller portions of meat and saving money. However, barriers and enablers largely differed by groups of meat consumption frequency. Self-perceived effective strategies for reducing meat consumption were price reduction of meat alternatives, recipes for vegetarian meals, and more attractive meat alternatives. The findings of this study are relevant for the development of targeted behaviour-change programmes including interventions in the physical and the social environment (like lowering prices and improving the offer of meat alternatives).
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Due to a growing challenge to feed the world’s population and an increased awareness to minimize the impact of our food choices on climate change, a more plant-based diet has gained popularity with a growing number of plant-based products on the market. To stimulate a plant-based diet that also improves long-term health, data are needed to monitor whether these products are healthy alternatives to animal-based foods. Therefore, this study inventoried 916 plant-based meat, fish, and dairy alternatives from eight Dutch supermarkets. The nutritional quality of each product was assessed by (1) the Dutch food-based dietary guidelines and (2) the Nutri-Score. The results show that over 70% of meat, fish, and dairy alternatives have an A/B Nutri-Score (indicating high nutritional quality), but do not comply with the Dutch dietary guidelines. This is mainly due to high salt and low vitamin B12 and iron content (meat and fish alternatives) or low protein and calcium levels (dairy alternatives). In conclusion, the majority of plant-based products are nutritionally not full alternatives of the animal-based equivalents; however, there are still opportunities for reformulation. To aid the consumer in making healthy plant-based food choices, a better alignment between the Nutri-Score and the recommended dietary guidelines is needed.
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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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