{"title":"数学优化在撒哈拉以南非洲以食物为基础的饮食建议发展中作为饮食建模工具的相关性:范围审查。","authors":"Sakiko Shiratori , MG Dilini Abeysekara","doi":"10.1016/j.advnut.2025.100480","DOIUrl":null,"url":null,"abstract":"<div><div>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 (<em>n</em> = 24), developing nutritionally and regionally optimized and cost-minimized food baskets (<em>n</em> = 4), and describing the use of LP as a method for designing population-specific food-based dietary guidelines (<em>n</em> = 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.</div></div>","PeriodicalId":7349,"journal":{"name":"Advances in Nutrition","volume":"16 8","pages":"Article 100480"},"PeriodicalIF":9.2000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Relevance of Mathematical Optimization as a Tool for Diet Modeling in the Development of Food-Based Dietary Recommendations in Sub-Saharan Africa: A Scoping Review\",\"authors\":\"Sakiko Shiratori , MG Dilini Abeysekara\",\"doi\":\"10.1016/j.advnut.2025.100480\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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 (<em>n</em> = 24), developing nutritionally and regionally optimized and cost-minimized food baskets (<em>n</em> = 4), and describing the use of LP as a method for designing population-specific food-based dietary guidelines (<em>n</em> = 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.</div></div>\",\"PeriodicalId\":7349,\"journal\":{\"name\":\"Advances in Nutrition\",\"volume\":\"16 8\",\"pages\":\"Article 100480\"},\"PeriodicalIF\":9.2000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Nutrition\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2161831325001164\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NUTRITION & DIETETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Nutrition","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2161831325001164","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
Relevance of Mathematical Optimization as a Tool for Diet Modeling in the Development of Food-Based Dietary Recommendations in Sub-Saharan Africa: A Scoping Review
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.
期刊介绍:
Advances in Nutrition (AN/Adv Nutr) publishes focused reviews on pivotal findings and recent research across all domains relevant to nutritional scientists and biomedical researchers. This encompasses nutrition-related research spanning biochemical, molecular, and genetic studies using experimental animal models, domestic animals, and human subjects. The journal also emphasizes clinical nutrition, epidemiology and public health, and nutrition education. Review articles concentrate on recent progress rather than broad historical developments.
In addition to review articles, AN includes Perspectives, Letters to the Editor, and supplements. Supplement proposals require pre-approval by the editor before submission. The journal features reports and position papers from the American Society for Nutrition, summaries of major government and foundation reports, and Nutrient Information briefs providing crucial details about dietary requirements, food sources, deficiencies, and other essential nutrient information. All submissions with scientific content undergo peer review by the Editors or their designees prior to acceptance for publication.