MODELLING OF HEALTHY AND SUSTAINABLE SEAFOOD CHOICES

海鲜是我们最全球化的食品之一，代表了数千种捕捞或养殖物种的多样化生产系统。它在我们的整个食物系统中发挥着不可或缺的作用，是蛋白质、ω-3脂肪酸、维生素和微量营养素的重要膳食来源。英国海鲜摄入量目前是基于“五大”的消费，即鳕鱼，黑线鳕，金枪鱼，鲑鱼和对虾。然而，在不同年龄组中，只有大约一半的成年人每周食用推荐的一份油性鱼类。此外，人们还担心在积极的健康影响和环境影响之间可能存在的权衡问题，例如渔业或水产养殖对生态系统的影响，可持续性和鱼类消费之间的联系并不总是很好地定义。这个跨学科的博士项目将整合营养资产和生命周期评估（LCA）将海产食品的所有成分合并为一个功能单位，以便能够确定哪些鱼种以最低的气候代价提供最大的营养价值，哪些鱼种来自陆地蛋白质来源。为此，英国商业相关鱼类的营养密度分数将与其环境影响数据相结合。此外，将根据影响海鲜消费的已知驱动因素和障碍，如价格，生态标签和健康信息，开发一种食品交换工具，可以模拟更健康，“绿色”和负担得起的“交换”，以促进购买海鲜，以重新链接其他动物源性蛋白质来源。食物交换将使用内部（Rowett）营养，温室气体排放（GHGE）和6000种食物的价格数据库以及线性规划工具来计算，以优化现有的NDNS食物摄入量数据。模拟批量模型运行计算的食物交换将提供最重要的健康，绿色和负担得起的海鲜交换的见解，可用于健康信息的发展和海鲜行业销售其产品。将为包括消费者和网上食品零售商在内的最终用户设计食品交换工具的测试版。这种决策支持工具已被发现是有效的驱动行为改变，因为它们允许科学知识被报告的格式，这是非专家访问。这个博士项目提供了一个独特的机会，与营养，渔业和水产养殖，健康和可持续饮食和工具开发的建模领域的关键专家合作。该项目将提供广泛的培训，以解释NDNS等大型饮食调查的数据和结果，进行高级统计分析，如在统计软件包R中使用线性混合建模方法，并使用大型数据集（由BioSS支持）。

Seafood is one of our most global food commodities, representing a diverse range of production systems for thousands of fished or farmed species. It plays an integral role in our overall food system, being an important dietary source of protein, omega-3 fatty acids, vitamins and micronutrients. UK seafood intake is currently based on the consumption of the 'big five' which are cod, haddock, tuna, salmon and prawns. However, across age groups, only around half of adults consume the recommended one portion of oily fish per week. Furthermore, there are concerns about potential trade-offs between positive health effects and environmental impacts such as ecosystem impacts of fisheries or aquaculture, and links between sustainability and fish consumption are not always well defined.This interdisciplinary PhD project will integrate nutritional assets and life cycle assessment (LCA) of seafood into one functional unit to allow the identification of fish species that provide the greatest nutritional value at the lowest climate costs, against those from terrestrial protein sources. For this, nutrient density scores for commercially relevant fish species in the UK will be combined with its environmental impact data. In addition, a Food Swap tool that can model healthier, 'greener' and affordable 'swaps' to promote the purchase of seafood to replalinked ce other animal-derived protein sources will be developed based on known drivers and barriers affecting seafood consumption like price, ecolabels and health messages. Food swaps will be calculated using an in-house (Rowett) nutrient, greenhouse gas emission (GHGE) and price database of 6000 foods, and a linear programming tool to optimise existing NDNS food intake data against UK dietary targets. Simulated batch model runs of calculated food swaps will provide insights into the most important healthier, greener and affordable seafood swaps which could be applied for the development of health messages and for the seafood industries to market their produce. A beta-version of the Food Swap tool will be designed with end-users, including consumers and on-line food retailers. Such decision support tools have been found to be effective in driving behaviour change as they allow scientific knowledge to be reported in a format which is accessible to non-experts.This PhD project offers a unique opportunity to work with key experts in the fields of nutrition, fisheries & aquaculture, modelling of healthy and sustainable diets and tool development. The project will provide extensive training in the interpretation of data and results from large dietary surveys such as the NDNS, performing advanced statistical analysis, such as linear mixed modelling approaches, in statistical package R and working with large datasets (supported by BioSS).