MODELLING OF HEALTHY AND SUSTAINABLE SEAFOOD CHOICES

海鲜是我们最具全球性的食品之一，代表着数以千计的捕捞或养殖物种的各种生产系统。它在我们的整个食物系统中扮演着不可或缺的角色，是蛋白质、omega-3脂肪酸、维生素和微量营养素的重要膳食来源。英国目前的海鲜摄入量是以鳕鱼、黑线鳕、金枪鱼、三文鱼和对虾这五大类的消费量为基础的。然而，在各个年龄段中，只有大约一半的成年人每周摄入推荐的一份油性鱼类。此外，人们担心积极的健康影响和环境影响之间的潜在权衡，例如渔业或水产养殖对生态系统的影响，而且可持续性和鱼类消费之间的联系并不总是被很好地定义。这个跨学科的博士项目将把海鲜的营养资产和生命周期评估整合到一个功能单元中，以便能够确定以最低的气候成本提供最大营养价值的鱼种，而不是来自陆地蛋白质来源的鱼种。为此，英国具有商业意义的鱼类的营养密度得分将与其环境影响数据结合起来。此外，将根据已知的驱动因素和影响海产品消费的障碍，如价格、生态标签和健康信息，开发一个食品交换工具，该工具可以模拟更健康、更环保和负担得起的“交换”，以促进购买海鲜以补充CE其他动物来源的蛋白质来源。食品互换将使用6000种食品的内部营养素(Rowett)、温室气体排放(GHGE)和价格数据库，以及一个线性编程工具来优化现有的NDNS食品摄入量数据，以符合英国的饮食目标。计算食品互换的模拟批次模型运行将提供对最重要的更健康、更绿色和负担得起的海鲜互换的见解，这些互换可用于制定健康信息，并供海鲜行业营销其产品。将为包括消费者和在线食品零售商在内的最终用户设计食品交换工具的测试版。这种决策支持工具被发现在推动行为变化方面是有效的，因为它们允许以非专家可以访问的格式报告科学知识。这一博士项目提供了与营养、渔业和水产养殖、健康和可持续饮食建模和工具开发领域的关键专家合作的独特机会。该项目将在解释大型膳食调查的数据和结果方面提供广泛的培训，例如，在统计包R中执行高级统计分析，例如线性混合建模方法，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).