Perspective: How to Develop Nutrient Profiling Models Intended for Global Use: A Manual

Drewnowski, Adam; Amanquah, Daniel; Gavin-Smith, Breda

doi:10.1093/advances/nmab018

Cited by 40 publications

(54 citation statements)

References 47 publications

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“…The study showed that current nutrient profiling methods adopted in HIC fail to capture benefit of nutrient dense food such as fortified foods that meet the nutritional needs of people in the Global South. Guidelines for developing a Nutrient Profiling system in LMICs were [64].…”

Section: Ghana-voluntary Fortification Examplementioning

confidence: 99%

Food Fortification: The Advantages, Disadvantages and Lessons from Sight and Life Programs

et al. 2021

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Deficiencies in one or more micronutrients such as iron, zinc, and vitamin A are widespread in low- and middle-income countries and compromise the physical and cognitive capacity of millions of people. Food fortification is a cost-effective strategy with demonstrated health, economic and social benefits. Despite ongoing debates globally and in some countries regarding the performance and safety of food fortification, the practice offers significant benefits across each of the main vehicles for food fortification (large-scale food fortification, biofortification and point-of-use or home fortification) ranging from reducing the prevalence of nutritional deficiencies and economic benefits to societies and economies. Using Sight and Life’s global and national experiences in implementing food fortification efforts, we demonstrate how different programs in LMICs have successfully addressed challenges with food fortification and in doing so, find that these efforts are most successful when partnerships are formed that include the public and private sector as well as other parties that can provide support in key areas such as advocacy, management, capacity building, implementation and regulatory monitoring.

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Section: Ghana-voluntary Fortification Examplementioning

confidence: 99%

Food Fortification: The Advantages, Disadvantages and Lessons from Sight and Life Programs

et al. 2021

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“…More detailed Nutrient Rich Diet (NRD) scores are e.g. NRD9.3 ( Drewnowski, 2009 ; Fulgoni et al, 2009 ) or other scores based on a higher number of nutrients ( Drewnowski et al, 2021 ; Grigoriadis et al, 2021 ; Mertens et al, 2018 ). Such scores can be calculated if detailed food consumption data are available from food balance sheets or food surveys, in combination with food nutrition databases.…”

Section: The Food System Sustainability Compassmentioning

confidence: 99%

A Sustainability Compass for policy navigation to sustainable food systems

Hebinck

Zurek

Achterbosch

et al. 2021

Global Food Security

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Growing acknowledgement that food systems require transformation, demands comprehensive sustainability assessments that can support decision-making and sustainability governance. To do so, assessment frameworks must be able to make trade-offs and synergies visible and allow for inclusive negotiation on food system outcomes relevant to diverse food system actors. This paper reviews literature and frameworks and builds on stakeholder input to present a Sustainability Compass made up of a comprehensive set of metrics for food system assessments. The Compass defines sustainability scores for four societal goals, underpinned by areas of concern. We demonstrate proof of concept of the operationalization of the approach and its metrics. The Sustainability Compass is able to generate comprehensive food system insights that enables reflexive evaluation and multi-actor negotiation for policy making.

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“…The new hybrid NRFh models need to be compared to the established ones [9,10] and also tested in relation to the foods' energy density, defined as kcal/100 g. In past studies [11,12], the preference was for those profiling algorithms that showed low correlations between nutrient density scores and energy density of foods. Those NP models that score calories, total sugar, and saturated fat tend to capture the foods' energy density as opposed to their nutrient content [13][14][15]. Second, it is important to ensure that nutrient density scores generated by NP models are not correlated too highly with food prices, also expressed per 100 kcal of food [11,16].…”

Section: Introductionmentioning

confidence: 99%

“…Second, it is important to ensure that nutrient density scores generated by NP models are not correlated too highly with food prices, also expressed per 100 kcal of food [11,16]. The principal objective is not to point to higher-cost foods but to identify those foods that are both nutrient-rich and affordable [4,14].…”

Section: Introductionmentioning

confidence: 99%

The New Hybrid Nutrient Density Score NRFh 4:3:3 Tested in Relation to Affordable Nutrient Density and Healthy Eating Index 2015: Analyses of NHANES Data 2013–16

Drewnowski

Smith

Fulgoni³

2021

Nutrients

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Background: Hybrid nutrient density scores are based on both nutrients and selected food groups. Objective: To compare the new hybrid nutrient-rich food NRFh 4:3:3 score to other nutrient-rich food (NRF) scores, energy density, and energy cost and to model the impact on the Healthy Eating Index (HEI-2015) of partially replacing less nutrient-rich with more nutrient-rich foods. Methods: Analyses were based on 5870 foods and beverages in the Food and Nutrient Database for Dietary Studies and on 24 h dietary recalls from the National Health and Nutrition Examination Survey (NHANES 2013–16). The NRFh 4:3:3 model was based on four nutrients to encourage (protein fiber, potassium, MUFA + PUFA); three food groups to encourage (dairy, fruit, whole grains); and three nutrients to limit (saturated fat, added sugar, sodium). Ratings generated by NRFh 4:3:3 and by other NRF models were correlated with score components, energy density (kcal/100 g), and energy cost (USD/100 kcal). The impact on HEI-2015 of replacing foods in the lowest nutrient density tertile (T1) with top tertile (T3) foods at 10%, 20%, 30%, and 100% equicaloric replacement was modeled using NHANES 2013–16 dietary data by population subgroups. Results: The NRFh 4:3:3 model awarded higher scores to foods containing dairy, fruit, and whole grains and proportionately lower scores to vegetables when compared to the NRF 9.3 model. Higher NRF and NRFh nutrient density scores were linked to lower energy density and higher energy cost; however, both correlations were lower for the NRFh 4:3:3. Isocaloric replacement of bottom tertile with top tertile foods as rated by both models led to significantly higher HEI-2105 values, based on complete (100%) and on partial (10–30%) replacement. Conclusion: The new NRFh 4:3:3 model provides the basis for developing new metrics of affordable nutrient density. The model identified “best value” food categories that were both affordable and nutrient-rich. Total and partial replacement of low nutrient density with high nutrient density foods was associated with higher HEI-2015 scores, suggesting that even partial inclusion of more nutrient dense foods in the diet may have an important impact on total diet quality.

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Perspective: How to Develop Nutrient Profiling Models Intended for Global Use: A Manual

Cited by 40 publications

References 47 publications

Food Fortification: The Advantages, Disadvantages and Lessons from Sight and Life Programs

Food Fortification: The Advantages, Disadvantages and Lessons from Sight and Life Programs

A Sustainability Compass for policy navigation to sustainable food systems

The New Hybrid Nutrient Density Score NRFh 4:3:3 Tested in Relation to Affordable Nutrient Density and Healthy Eating Index 2015: Analyses of NHANES Data 2013–16

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