A Progressive Nutrient Profiling System to Guide Improvements in Nutrient Density of Foods and Beverages

Improving the nutrient density of processed foods is one way to bring the global food supply closer to the WHO Sustainable Development Goals. Nutrient profiling (NP) has emerged as the preferred method of monitoring the progress toward product innovation and reformulation. This paper presents PepsiCo Nutrition Criteria (PNC), a new internal NP model that was designed to guide and monitor improvements in nutrient density and overall nutritional quality of foods and beverages. The new PNC NP model assigns food products into four classes of increasing nutritional value, based on the content of nutrients to limit, along with nutrients and ingredients to encourage. The nutrient standards used for category assignment followed those developed by global dietary authorities. Standards are proposed for calories, sodium, added sugars, saturated, and industrially produced trans fats. Also included are minimum values for food groups to encourage, low-fat dairy, and for country-specific gap nutrients. Internal use of the NP model has spurred product changes that are consistent with WHO goals for industry transparency. An audited review of company products showed that 48% met added sugar, 65% met sodium, and 71% met saturated fat goals. By the end of 2020, in the top 26 regions in which products are sold, 48% of the total sales volume of global beverages had 100 kcal or less from added sugars per 355 ml serving representing 80% of beverage volume and over 90% of food volume sold globally. The PNC NP model is not consumer-facing but is specifically intended for internal use to motivate stepwise and incremental product innovation and reformulation. Transparent and published NP models further WHO goals of engaging industry stakeholders in the (re)formulation of processed foods and beverages consistent with public health goals.

Download Full-text

Process and Method for Implementation of Automated Nutrient Profiling Reporting for a Global Food and Beverage Portfolio

Current Developments in Nutrition ◽

10.1093/cdn/nzaa060_008 ◽

2020 ◽

Vol 4 (Supplement_2) ◽

pp. 1370-1370

Author(s):

Danielle Martin ◽

Michael Zarro ◽

Maike Rahn ◽

Jenny Gusba ◽

Christina Sherry

Keyword(s):

Multidisciplinary Team ◽

Saturated Fat ◽

Fold Increase ◽

Data Availability ◽

Product Portfolio ◽

Food Groups ◽

Volume Data ◽

Added Sugars ◽

Nutrient Profiling

Abstract Objectives With the increasing need for dynamic and flexible nutrient profiling of foods and beverages, PepsiCo has expanded capabilities to report on global nutrition data for business guidance and reporting to regulatory and health agencies. Additional processes were established to integrate nutrition and finance information and influence the long-term data strategy needs of the organization. Methods A multidisciplinary team of nutrition science, finance and IT professionals was assembled to systematically collect and link nutritional and financial data. A controlled, centralized database was created with data from 2015 to present from multiple data sources. Data quality is reviewed quarterly. Dashboards, scorecards and other reporting outputs were created (Tableau software, 2019.02) with end-user input, to measure performance against country-specific regulations, Front-of-Pack (FOP) labeling requirements and internal nutritional guidelines. Results Nutrition data from > 40,000 products are captured annually and linked with sales volume data. There was a 2.5-fold increase in countries contributing data since 2015 (10 vs 26 markets), representing >80% of the company's annual food/beverage sales volumes. Current reports focus on analyzing nutrients-to-encourage (protein, fiber, specific vitamins and/or minerals), food-groups-to-encourage (fruits, vegetables, whole grains, fat-free/low-fat dairy and nuts/seeds/legume) and nutrients-to-limit (saturated fat, sodium, added sugars, trans-fat). Dashboards are currently utilized by 9 company functions, supporting several requests, including national nutrition regulations (n = 2 dashboards), FOP labeling systems (n = 2), retail store requirements (n = 1), internal sustainability goals (n = 3) and customized reports (n = 40). Across all iterations, dashboards have received >1000 views. Conclusions Automated nutrient profiling has been successfully implemented by a multidisciplinary team. Dashboards provide end-users with a timely and efficient tool to dynamically analyze PepsiCo's product portfolio guiding short- and long-term business decisions. Future work includes informing opportunities to improve the nutrient profile of PepsiCo's portfolio and increasing data availability and analysis. Funding Sources PepsiCo Inc.

Download Full-text

Food processing: criteria for dietary guidance and public health?

Proceedings of The Nutrition Society ◽

10.1017/s0029665118002513 ◽

2018 ◽

Vol 78 (1) ◽

pp. 4-18 ◽

Cited By ~ 14

Author(s):

Julie Miller Jones

Keyword(s):

Public Health ◽

Food Processing ◽

Food Selection ◽

Processed Foods ◽

Food Groups ◽

Nutrition And Health ◽

Added Sugars ◽

Nutrient Density ◽

Meal Planning ◽

Scarcity Of Resources

The NOVA food categorisation recommends ‘avoiding processed foods (PF), especially ultra-processed foods (UPF)’ and selecting minimally PF to address obesity and chronic disease. However, NOVA categories are drawn using non-traditional views of food processing with additional criteria including a number of ingredients, added sugars, and additives. Comparison of NOVA's definition and categorisation of PF with codified and published ones shows limited congruence with respect to either definition or food placement into categories. While NOVA studies associate PF with decreased nutrient density, other classifications find nutrient-dense foods at all levels of processing. Analyses of food intake data using NOVA show UPF provide much added sugars. Since added sugars are one criterion for designation as UPF, such a proof demonstrates a tautology. Avoidance of foods deemed as UPF, such as wholegrain/enriched bread and cereals or flavoured milk, may not address obesity but could decrease intakes of folate, calcium and dietary fibre. Consumer understanding and implementation of NOVA have not been tested. Neither have outcomes been compared with vetted patterns, such as Dietary Approaches to Stop Hypertension, which base food selection on food groups and nutrient contribution. NOVA fails to demonstrate the criteria required for dietary guidance: understandability, affordability, workability and practicality. Consumers’ confusion about definitions and food categorisations, inadequate cooking and meal planning skills and scarcity of resources (time, money), may impede adoption and success of NOVA. Research documenting that NOVA can be implemented by consumers and has nutrition and health outcomes equal to vetted patterns is needed.

Download Full-text

Sources of excessive saturated fat, trans fat and sugar consumption in Brazil: an analysis of the first Brazilian nationwide individual dietary survey

Public Health Nutrition ◽

10.1017/s1368980012004892 ◽

2012 ◽

Vol 17 (1) ◽

pp. 113-121 ◽

Cited By ~ 50

Author(s):

Rosangela A Pereira ◽

Kiyah J Duffey ◽

Rosely Sichieri ◽

Barry M Popkin

Keyword(s):

Total Energy ◽

Energy Intake ◽

Rural Areas ◽

Family Income ◽

Saturated Fat ◽

Total Sugar ◽

Total Energy Intake ◽

Food Groups ◽

Cross Sectional ◽

Added Sugars

AbstractObjectiveTo examine the patterns of consumption of foods high in solid fats and added sugars (SoFAS) in Brazil.DesignCross-sectional study; individual dietary intake survey. Food intake was assessed by means of two non-consecutive food records. Foods providing >9·1 % of energy from saturated fat, or >1·3 % of energy from trans fat, or >13 % of energy from added sugars per 100 g were classified as high in SoFAS.SettingBrazilian nationwide survey, 2008–2009.SubjectsIndividuals aged ≥10 years old.ResultsMean daily energy intake was 8037 kJ (1921 kcal), 52 % of energy came from SoFAS foods. Contribution of SoFAS foods to total energy intake was higher among women (52 %) and adolescents (54 %). Participants in rural areas (43 %) and in the lowest quartile of per capita family income (43 %) reported the smallest contribution of SoFAS foods to total energy intake. SoFAS foods were large contributors to total saturated fat (87 %), trans fat (89 %), added sugar (98 %) and total sugar (96 %) consumption. The SoFAS food groups that contributed most to total energy intake were meats and beverages. Top SoFAS foods contributing to saturated fat and trans fat intakes were meats and fats and oils. Most of the added and total sugar in the diet was supplied by SoFAS beverages and sweets and desserts.ConclusionsSoFAS foods play an important role in the Brazilian diet. The study identifies options for improving the Brazilian diet and reducing nutrition-related non-communicable chronic diseases, but also points out some limitations of the nutrient-based criteria.

Download Full-text

Ultra-processed foods and added sugars in the Chilean diet (2010)

Public Health Nutrition ◽

10.1017/s1368980017001161 ◽

2017 ◽

Vol 21 (1) ◽

pp. 125-133 ◽

Cited By ~ 67

Author(s):

Gustavo Cediel ◽

Marcela Reyes ◽

Maria Laura da Costa Louzada ◽

Euridice Martinez Steele ◽

Carlos A Monteiro ◽

...

Keyword(s):

Total Energy ◽

Energy Intake ◽

Total Energy Intake ◽

Processed Foods ◽

Food Groups ◽

Dietary Recommendations ◽

Cross Sectional ◽

Added Sugars ◽

Percentage Point Increase ◽

Point Increase

AbstractObjectiveTo assess the consumption of ultra-processed foods and analyse its association with the content of added sugars in the Chilean diet.DesignCross-sectional study of national dietary data obtained through 24 h recalls and classified into food groups according to the extent and purpose of food processing (NOVA classification).SettingChile.SubjectsA probabilistic sample of 4920 individuals (aged 2 years or above) studied in 2010 by a national dietary survey (Encuesta Nacional de Consumo Alimentario).ResultsUltra-processed foods represented 28·6 (se 0·5) % of total energy intake and 58·6 (se 0·9) % of added sugars intake. The mean percentage of energy from added sugars increased from 7·7 (se 0·3) to 19·7 (se 0·5) % across quintiles of the dietary share of ultra-processed foods. After adjusting for several potential sociodemographic confounders, a 5 percentage point increase in the dietary share of ultra-processed foods determined a 1 percentage point increase in the dietary content of added sugars. Individuals in the highest quintile were three times more likely (OR=2·9; 95 % CI 2·4, 3·4) to exceed the 10 % upper limit for added sugars recommended by the WHO compared with those in the lowest quintile, after adjusting for sociodemographic variables. This association was strongest among individuals aged 2–19 years (OR=3·9; 95 % CI 2·7, 5·9).ConclusionsIn Chile, ultra-processed foods are important contributors to total energy intake and to the consumption of added sugars. Actions aimed at limiting consumption of ultra-processed foods are being implemented as effective ways to achieve WHO dietary recommendations to limit added sugars and processed foods, especially for children and adolescents.

Download Full-text

Diet and Economic Modelling to Improve the Quality and Affordability of the Australian Diet for Low and Medium Socioeconomic Households

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18115771 ◽

2021 ◽

Vol 18 (11) ◽

pp. 5771

Author(s):

Michelle Blumfield ◽

Carlene Starck ◽

Tim Keighley ◽

Peter Petocz ◽

Anna Roesler ◽

...

Keyword(s):

Diet Quality ◽

Low Cost ◽

Food Group ◽

Cost Ratio ◽

Economic Modelling ◽

Processed Foods ◽

Added Sugars ◽

Processing Level ◽

Nutrient Density ◽

The Impact

Food costs are a barrier to healthier diet selections, particularly for low socioeconomic households who regularly choose processed foods containing refined grains, added sugars, and added fats. In this study, the objectives were to: (i) identify the nutrient density-to-cost ratio of Australian foods; (ii) model the impact of substituting foods with lower nutrient density-to-cost ratio with those with the highest nutrient density-to-cost ratio for diet quality and affordability in low and medium socioeconomic households; and (iii) evaluate food processing levels. Foods were categorized, coded for processing level, analysed for nutrient density and cost, and ranked by nutrient density-to-cost ratio. The top quartile of nutrient dense, low-cost foods included 54% unprocessed (vegetables and reduced fat dairy), 33% ultra-processed (fortified wholegrain bread and breakfast cereals <20 g sugars/100 g), and 13% processed (fruit juice and canned legumes). Using substitution modelling, diet quality improved by 52% for adults and 71% for children across all households, while diet affordability improved by 25% and 27% for low and medium socioeconomic households, respectively. The results indicate that the quality and affordability of the Australian diet can be improved when nutritious, low-cost foods are selected. Processing levels in the healthier modelled diets suggest that some ultra-processed foods may provide a beneficial source of nutrition when consumed within national food group recommendations.

Download Full-text

Consumption of ‘extra’ foods (energy-dense, nutrient-poor) among children aged 16–24 months from western Sydney, Australia

Public Health Nutrition ◽

10.1017/phn2006970 ◽

2006 ◽

Vol 9 (8) ◽

pp. 1035-1044 ◽

Cited By ~ 65

Author(s):

Karen L Webb ◽

Marjaana Lahti-Koski ◽

Ingrid Rutishauser ◽

Debra J Hector ◽

Natalia Knezevic ◽

...

Keyword(s):

Dietary Assessment ◽

Randomised Trial ◽

Saturated Fat ◽

Food Groups ◽

Cross Sectional ◽

Food Records ◽

Dietary Assessment Methods ◽

Nutrient Density ◽

Portion Sizes ◽

Sydney Australia

AbstractObjectiveThis study evaluates the contribution of energy-dense, nutrient-poor ‘extra’ foods to the diets of 16–24-month-old children from western Sydney, Australia.DesignAn analysis of cross-sectional data collected on participants in the Childhood Asthma Prevention Study (CAPS), a randomised trial investigating the primary prevention of asthma from birth to 5 years. We collected 3-day weighed food records, calculated nutrient intakes, classified recorded foods into major food groups, and further classified foods as either ‘core’ or ‘extras’ according to theAustralian Guide to Healthy Eating.SettingPregnant women, whose unborn child was at risk of developing asthma because of a family history, were recruited from all six hospitals in western Sydney, Australia. Data for this study were collected in clinic visits and at participants’ homes at the 18-month assessment.ParticipantsFour hundred and twenty-nine children participating in the CAPS study; 80% of the total cohort.ResultsThe mean consumption of ‘extra’ foods was ∼150 g day− 1and contributed 25–30% of the total energy, fat, carbohydrate and sodium to the diets of the study children. ‘Extra’ foods also contributed around 20% of fibre, 10% of protein and zinc, and about 5% of calcium. Children in the highest quintile of ‘extra’ foods intake had a slightly higher but not significantly different intake of energy from those in the lowest quintile. However, significant differences were evident for the percentage of energy provided by carbohydrate and sugars (higher) and protein and saturated fat (lower). The intake of most micronutrients was also significantly lower among children in the highest quintile of consumption. The intake of ‘extra’ foods was inversely associated with the intake of core foods.ConclusionsThe high percentage of energy contributed by ‘extra’ foods and their negative association with nutrient density emphasise the need for dietary guidance for parents of children aged 1–2 years. These preliminary data on commonly consumed ‘extra’ foods and portion sizes may inform age-specific dietary assessment methods.

Download Full-text

Diet Quality and Water Scarcity: Evidence from a Large Australian Population Health Survey

Nutrients ◽

10.3390/nu11081846 ◽

2019 ◽

Vol 11 (8) ◽

pp. 1846 ◽

Cited By ~ 6

Author(s):

Bradley G. Ridoutt ◽

Danielle Baird ◽

Kimberley Anastasiou ◽

Gilly A. Hendrie

Keyword(s):

Diet Quality ◽

Water Scarcity ◽

Saturated Fat ◽

Dietary Guidelines ◽

Food Groups ◽

Added Sugars ◽

Impact Reduction ◽

Excessive Consumption ◽

Procurement Strategies ◽

Dietary Strategies

There is widespread interest in dietary strategies that lower environmental impacts. However, various forms of malnutrition are also widely prevalent. In a first study of its kind, we quantify the water-scarcity footprint and diet quality score of a large (>9000) population of self-selected adult daily diets. Here, we show that excessive consumption of discretionary foods—i.e., energy-dense and nutrient-poor foods high in saturated fat, added sugars and salt, and alcohol—contributes up to 36% of the water-scarcity impacts and is the primary factor differentiating healthier diets with lower water-scarcity footprint from poorer quality diets with higher water-scarcity footprint. For core food groups (fruits, vegetables, etc.), large differences in water-scarcity footprint existed between individual foods, making difficult the amendment of dietary guidelines for water-scarcity impact reduction. Very large reductions in dietary water-scarcity footprint are possible, but likely best achieved though technological change, product reformulation and procurement strategies in the agricultural and food industries.

Download Full-text

Effects of reducing processed culinary ingredients and ultra-processed foods in the Brazilian diet: a cardiovascular modelling study

Public Health Nutrition ◽

10.1017/s1368980017002063 ◽

2017 ◽

Vol 21 (1) ◽

pp. 181-188 ◽

Cited By ~ 8

Author(s):

Patrícia VL Moreira ◽

Lirije Hyseni ◽

Jean-Claude Moubarac ◽

Ana Paula B Martins ◽

Larissa G Baraldi ◽

...

Keyword(s):

Food Policy ◽

Saturated Fat ◽

Processed Foods ◽

Food Groups ◽

Added Sugar ◽

Policy Model ◽

Regulatory Policies ◽

The Impact ◽

Cvd Mortality ◽

Modelling Study

AbstractObjectiveTo estimate the impact of reducing saturated fat, trans-fat, salt and added sugar from processed culinary ingredients and ultra-processed foods in the Brazilian diet on preventing cardiovascular deaths by 2030.DesignA modelling study.SettingData were obtained from the Brazilian Household Budget Survey 2008/2009. All food items purchased were categorized into food groups according to the NOVA classification. We estimated the energy and nutrient profile of foods then used the IMPACT Food Policy model to estimate the reduction in deaths from CVD up to 2030 in three scenarios. In Scenario A, we assumed that the intakes of saturated fat, trans-fat, salt and added sugar from ultra-processed foods and processed culinary ingredients were reduced by a quarter. In Scenario B, we assumed a reduction of 50 % of the same nutrients in ultra-processed foods and processed culinary ingredients. In Scenario C, we reduced the same nutrients in ultra-processed foods by 75 % and in processed culinary ingredients by 50 %.ResultsApproximately 390 400 CVD deaths might be expected in 2030 if current mortality patterns persist. Under Scenarios A, B and C, CVD mortality can be reduced by 5·5, 11·0 and 29·0 %, respectively. The main impact is on stroke with a reduction of approximately 6·0, 12·6 and 32·0 %, respectively.ConclusionsSubstantial potential exists for reducing the CVD burden through overall improvements of the Brazilian diet. This might require reducing the penetration of ultra-processed foods by means of regulatory policies, as well as improving the access to and promotion of fresh and minimally processed foods.

Download Full-text

Abstract P355: Development and Validation of a Nutrient Density Score That Includes Foods Groups

Circulation ◽

10.1161/circ.141.suppl_1.p355 ◽

2020 ◽

Vol 141 (Suppl_1) ◽

Author(s):

Jessica D Smith ◽

Victor Fulgoni ◽

Adam Drewnowski

Keyword(s):

Diet Quality ◽

Saturated Fat ◽

Healthy Eating Index ◽

Dietary Guidelines ◽

Food Groups ◽

Unsaturated Fat ◽

Nutrient Density ◽

Density Score ◽

Considerable Work ◽

Development And Validation

Introduction: There has been considerable work performed on nutrient profiling to assess the nutritional contribution of a food to a healthy dietary pattern. Most profiling approaches have focused on nutrients to limit and nutrients to encourage. A few profiling approaches have also included certain food groups in the profiling algorithm. Objectives: The objective of this study was to develop a nutrient density score, based on the Nutrient Rich Food Index (NRF) 6.3, that includes food groups and validate the score against a gold-standard marker of diet quality, the Healthy Eating Index (HEI) 2015. Methods: Stepwise regression was used to develop a nutrient density score based on the day 1 total dietary intake of the U.S. population 2 years and older (excluding pregnant and lactating women) from the National Health and Nutrition Examination Survey (NHANES) 2011-2016 (n=23,743). Intake of food groups was taken from the Food Patterns Equivalent Database (FPED) 2011-2016. Sixteen nutrients (as a percent of the Daily Value) as well as five food groups (as a percentage of recommended intake in 2015-2020 Dietary Guidelines) were considered in the score. Results: When only the 16 nutrients were included in the score, 66% of the variability in the HEI 2015 could be accounted for (R 2 = 0.66). When only the five food groups were considered, the maximum R 2 with the HEI 2015 was 0.50. However, when both nutrients and foods groups were considered, the model explained 74% of the variability in the HEI 2015 (Table). The increase in the R 2 begins to plateau after the inclusion of 10 elements: 3 nutrients to encourage (fiber, potassium and unsaturated fat), 4 food groups (dairy, fruit, whole grains, and nuts and seeds) and 3 nutrients to limit (added sugar, saturated fat, sodium). Conclusion: A nutrient density score that includes both nutrients and foods groups best predicts diet quality as measured by the HEI 2015.

Download Full-text

The nutrient density approach to healthy eating: challenges and opportunities

Public Health Nutrition ◽

10.1017/s136898001400158x ◽

2014 ◽

Vol 17 (12) ◽

pp. 2626-2636 ◽

Cited By ~ 28

Author(s):

Theresa A Nicklas ◽

Adam Drewnowski ◽

Carol E O’Neil

Keyword(s):

Dietary Guidelines ◽

Positive Health ◽

Added Sugars ◽

Nutrient Density ◽

Nutrient Profiling ◽

Challenges And Opportunities ◽

Other Substances ◽

The Usa ◽

Dietary Guidelines For Americans ◽

Universal Definition

AbstractThe term ‘nutrient density’ for foods/beverages has been used loosely to promote the Dietary Guidelines for Americans. The 2010 Dietary Guidelines for Americans defined ‘all vegetables, fruits, whole grains, fat-free or low-fat milk and milk products, seafood, lean meats and poultry, eggs, beans and peas (legumes), and nuts and seeds that are prepared without added solid fats, added sugars, and sodium’ as nutrient dense. The 2010 Dietary Guidelines for Americans further states that nutrient-dense foods and beverages provide vitamins, minerals and other substances that may have positive health effects with relatively few (kilo)calories or kilojoules. Finally, the definition states nutrients and other beneficial substances have not been ‘diluted’ by the addition of energy from added solid fats, added sugars or by the solid fats naturally present in the food. However, the Dietary Guidelines Advisory Committee and other scientists have failed to clearly define ‘nutrient density’ or to provide criteria or indices that specify cut-offs for foods that are nutrient dense. Today, ‘nutrient density’ is a ubiquitous term used in the scientific literature, policy documents, marketing strategies and consumer messaging. However, the term remains ambiguous without a definitive or universal definition. Classifying or ranking foods according to their nutritional content is known as nutrient profiling. The goal of the present commentary is to address the research gaps that still exist before there can be a consensus on how best to define nutrient density, highlight the situation in the USA and relate this to wider, international efforts in nutrient profiling.

Download Full-text