โก Quick Summary
This scoping review highlights the potential of big data analytics to enhance decision-making in large-scale food fortification (LSFF) and biofortification. Despite its promise, the application of big data in these areas remains limited, with significant opportunities for improvement in public health monitoring and production efficiency.
๐ Key Details
- ๐ Dataset: 1,678 records analyzed from 2012 to 2022
- ๐งฉ Focus areas: 60% on production, 19.5% on inputs, 16.7% on public health monitoring
- โ๏ธ Technologies explored: Blockchain, IoT, machine learning, artificial intelligence
- ๐ Key findings: 7 records specifically addressed public health monitoring related to LSFF
๐ Key Takeaways
- ๐ Big data analytics can significantly improve decision-making in food fortification.
- ๐ก Public health monitoring is underrepresented in current literature, with only 16.7% addressing it.
- ๐ค Technologies like blockchain and IoT can enhance traceability of fortified products.
- ๐ Machine learning can predict fortification gaps effectively.
- ๐ The study emphasizes the need for broader applications of big data in distribution and regulation.
- ๐ Limited literature indicates a gap in research and application in LSFF and biofortification.
- ๐ Most relevant studies were published between 2018 and 2022.
๐ Background
The integration of big data analytics into health decision-making has shown remarkable potential, particularly in areas like disease surveillance and healthcare delivery. This review focuses on how these analytics can be applied to large-scale food fortification and biofortification, which are critical for improving nutritional outcomes globally.
๐๏ธ Study
Following the PRISMA guidelines, the authors conducted a comprehensive analysis of open-access peer-reviewed literature and gray literature from 2012 to 2022. Out of 1,678 records, only 28 specifically mentioned LSFF or biofortification, indicating a need for further exploration in this field.
๐ Results
The findings revealed that a majority of the literature focused on production (60%) and inputs (19.5%), while only a small fraction (16.7%) addressed public health monitoring. This suggests a significant opportunity for leveraging big data to enhance public health outcomes related to food fortification.
๐ Impact and Implications
The implications of this study are profound. By expanding the use of big data analytics in LSFF and biofortification, stakeholders can improve decision-making, efficiency, and sustainability across the food value chain. Technologies such as machine learning and artificial intelligence can play a pivotal role in addressing nutritional deficiencies and enhancing public health monitoring.
๐ฎ Conclusion
This scoping review underscores the untapped potential of big data analytics in food fortification and biofortification. By focusing on underexplored areas such as distribution and regulation, we can enhance the effectiveness of these initiatives, ultimately leading to better health outcomes. Continued research and application in this field are essential for realizing the full benefits of big data in nutrition.
๐ฌ Your comments
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How big data analytics can strengthen large-scale food fortification and biofortification decision-making: A scoping review.
Abstract
Big data analytics have shown great potential to improve decision-making in health, including disease surveillance and healthcare delivery. This scoping review explores how big data supports decision-making in large-scale food fortification (LSFF) and biofortification across the food value chain. Following PRISMA guidelines, we analyzed open-access peer-reviewed literature and gray literature from 2012 to 2022. Given the limited literature, we broadened our search to include big data applications in agriculture and nutrition, aiming to draw relevant insights for LSFF and biofortification. Of 1678 records, 28 mentioned LSFF or biofortification, all published between 2018 and 2022. Overall, most records focused on production (60%) and inputs (19.5%). Notably, 16.7% (n = 7) of records mentioning LSFF or biofortification addressed public health monitoring, compared to 2.3% (n = 45) of those without a mention. Use case examples include blockchain and Internet of Things (IoT) for fortified product traceability, machine learning to predict fortification gaps, and artificial intelligence to analyze anemia prevalence, highlighting opportunities to enhance both production and public health monitoring. Despite this potential, big data use in LSFF and biofortification remains limited. Expanding its use in underexplored areas, such as distribution and regulation, could enhance decision-making, efficiency, and sustainability in LSFF and biofortification.
Author: [‘Walsh F’, ‘Zhenchuk A’, ‘Luthringer C’, ‘Kratz C’, ‘Schweigert F’]
Journal: Ann N Y Acad Sci
Citation: Walsh F, et al. How big data analytics can strengthen large-scale food fortification and biofortification decision-making: A scoping review. How big data analytics can strengthen large-scale food fortification and biofortification decision-making: A scoping review. 2025; (unknown volume):(unknown pages). doi: 10.1111/nyas.70028