Shiratori Sakiko, Abeysekara Mg Dilini
Information and Public Relations Office, Japan International Research Center for Agricultural Sciences (JIRCAS), Tsukuba, Ibaraki, Japan.
Information and Public Relations Office, Japan International Research Center for Agricultural Sciences (JIRCAS), Tsukuba, Ibaraki, Japan; Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi, Tokyo, Japan.
Adv Nutr. 2025 Jul 11;16(8):100480. doi: 10.1016/j.advnut.2025.100480.
This study aimed to understand the role of mathematical programming in the development of food-based dietary recommendations (FBRs) in sub-Saharan Africa (SSA), identify current limitations, and highlight opportunities for advancing evidence-based dietary interventions. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews, a systematic search from January 2000 to May 2024 identified 97 relevant studies. Among these, 30 studies spanning 12 SSA countries (of 48 countries and territories in SSA) met the inclusion criteria. The reviewed studies leveraged linear programming (LP) or extensions of LP (i.e., linear goal programming) to formulate FBRs by optimizing current dietary patterns to meet nutritional needs and gaps (n = 24), developing nutritionally and regionally optimized and cost-minimized food baskets (n = 4), and describing the use of LP as a method for designing population-specific food-based dietary guidelines (n = 2). The primary goal of the reviewed studies is to develop nutritionally adequate and economically affordable food patterns, rather than to address multiple chronic nutrition-related conditions simultaneously, reflecting the distinct priorities of diet modeling in low-resource settings compared with those of resource-rich contexts. The formulated FBRs and optimized diets are often defined for specific demographic groups, with a limited geographic scope reflecting regional priorities. Diets can be optimized both nutritionally and economically by prioritizing locally available food groups and items; however, in some cases, additional supplementation and or inclusion of rarely consumed nutrient-dense foods may be necessary. Mathematical optimization, particularly LP, is a valuable tool for addressing dietary challenges and developing evidence-based, context-specific FBRs. Its use is facilitated by the availability of user-friendly software. However, its successful application requires high-quality input data, consideration of behavioral and practical aspects, and interdisciplinary collaboration. High-quality input data and incorporating sociocultural contexts are critical for leveraging mathematical optimization to inform inclusive and effective dietary recommendations in SSA.
本研究旨在了解数学规划在撒哈拉以南非洲（SSA）基于食物的膳食建议（FBRs）制定中的作用，识别当前的局限性，并突出推进循证膳食干预的机会。按照系统评价和Meta分析扩展版的系统评价优先报告项目（PRISMA-ScR），对2000年1月至2024年5月进行的系统检索，共识别出97项相关研究。其中，来自SSA的48个国家和地区中的12个国家的30项研究符合纳入标准。综述的研究利用线性规划（LP）或LP的扩展方法（即线性目标规划）来制定FBRs，方法包括通过优化当前饮食模式以满足营养需求和差距（n = 24）、开发营养和区域优化且成本最小化的食物篮（n = 4），以及描述将LP用作设计针对特定人群的基于食物的膳食指南的方法（n = 2）。综述研究的主要目标是制定营养充足且经济实惠的食物模式，而非同时解决多种与营养相关的慢性疾病，这反映了与资源丰富环境相比，低资源环境中饮食建模的不同优先事项。制定的FBRs和优化饮食通常针对特定人群定义，地理范围有限，反映了区域优先事项。通过优先考虑当地可得的食物类别和品种，饮食在营养和经济方面均可得到优化；然而，在某些情况下，可能需要额外补充和/或纳入很少食用的营养密集型食物。数学优化，尤其是LP，是应对膳食挑战和制定循证、因地制宜的FBRs的宝贵工具。用户友好型软件的可用性促进了其使用。然而，其成功应用需要高质量的输入数据、对行为和实际方面的考虑以及跨学科合作。高质量的输入数据和纳入社会文化背景对于利用数学优化为SSA提供包容性和有效的膳食建议至关重要。
