The use of commercial food purchase data for public health nutrition research: A systematic review

Long-term impact of unhealthy food tax on consumption and the drivers behind: A longitudinal study in Hungary

Several countries have introduced public health product taxes with the objective of reducing the absolute amount of consumption of unhealthy food and tackling obesity. This study aims to estimate the long-term impact of the Hungarian public health product tax introduced in 2011. To achieve this, a unique consumer purchase dataset was analysed to examine daily fast-moving consumer goods purchases from a representative sample of 2,000 households from 2010 to 2018. The results indicate that the tax has been fully reflected in consumer prices. A decline in consumption was observed initially, consistent with previous experiences in Hungary and other countries. However, over time, the data suggests a recovery and even an increase in line with the growth of disposable income. The proportion of taxed products in total fast-moving consumer goods purchases increased from 5.9 % (95 % CI: 5.7 % to 6.0 %) in 2010 to 7.4 % (95 % CI: 7.3 % to 7.6 %) in 2018. Furthermore, the tax has contributed to increased inequality as low-income households spend a higher proportion of their total expenditure on it. Although taxes on unhealthy foods have proven effective in the short-term, they may not be adequate for reducing overall consumption in the long-term, particularly as disposable income increases. In conclusion, implementing complex interventions is necessary to achieve sustainable positive changes in dietary habits.

Citizens' digital footprints to support health promotion at the local level-PUHTI study, Finland

BACKGROUND

We aimed to explore to the possibilities of utilizing automatically accumulating data on health-owned for example by local companies and non-governmental organizations-to complement traditional health data sources in health promotion work at the local level.

METHODS

Data for the PUHTI study consisted of postal code level information on sport license holders, drug purchase and sales advertisements in a TOR online underground marketplace, and grocery sales in Tampere. Additionally, open population register data were utilized. An interactive reporting tool was prepared to show the well-being profile for each postal code area. Feedback from the tool's end-users was collected in interviews.

RESULTS

The study showed that buying unhealthy food and alcohol, selling or buying drugs, and participating in organized sport activities differed by postal code areas according to its socioeconomic profile in the city of Tampere. The health and well-being planners and managers of Tampere found that the new type of data brought added value for the health promotion work at the local level. They perceived the interactive reporting tool as a good tool for planning, managing, allocating resources and preparing forecasts.

CONCLUSIONS

Traditional health data collection methods-administrative registers and health surveys-are the cornerstone of local health promotion work. Digital footprints, including data accumulated about people's everyday lives outside the health service system, can provide additional information on health behaviour for various population groups. Combining new sources with traditional health data opens a new perspective for health promotion work at local and regional levels.

Trends in Sugar From Packaged Foods and Beverages Purchased by US Households Between 2002 and 2020

BACKGROUND

Excess sugar consumption is a public health concern in the United States. How sugar purchases have changed over time, whether there are disparities across subpopulations, and the contribution of various food groups are unclear.

OBJECTIVE

To assess trends in sugar from packaged foods and beverages purchased by US households between 2002 and 2020.

DESIGN

This is an open cohort study.

PARTICIPANTS/SETTING

We obtained data from the NielsenIQ U.S. Homescan Consumer Panel, which collects data on household purchases of all consumer packaged goods in 52 metropolitan and 24 non-metropolitan markets across the United States. We assessed data on food and beverage purchases for 1,163,447 household-years.

MAIN OUTCOME MEASURES

The primary outcomes are the total sugar in grams purchased per capita per day and percentage of calories from sugar, by sociodemographic group.

STATISTICAL ANALYSES PERFORMED

We used linear regression to estimate trends in total grams of sugar per capita per day, percentage of calories from sugar, and percentage of total sugar purchases by food or beverage group. We estimated means for select years and tested for significance compared with 2002 and with the previous timepoint and calculated the overall P-value for the linear trend using time series regression.

RESULTS

Total sugar purchases decreased over the study period, both in absolute terms (-37.2 g/capita/day; 95% confidence interval [CI], -38.7, -35.6) and as a percentage of total calories purchased (-5.3 percentage points; 95% CI, -5.5, -5.2). Sugar purchases declined for all sociodemographic groups, but disparities have persisted or widened, particularly among individuals who are non-Hispanic Black, low-income, and with lower educational attainment. Beverages' contributions to sugar purchases decreased 8.1 percentage points (95% CI, -8.4, -7.8).

CONCLUSION

In the United States, purchases of sugar declined, but disparities by socioeconomic status and race or ethnicity persisted or widened. Policies to further reduce sugar consumption and the burden of diet-related disparities are needed.

Monitoring health and nutrition claims on food labels in Brazil

Introduction

The monitoring of nutrition and health claims on food and beverage labels has been proposed by international and national organizations because it can collaborate with the development of public policies to regulate food labeling and marketing strategies. One way of carrying out this monitoring is by using data collected by private companies.

Objective

To compare information on nutrition and health claims available in a commercial database of a private company that monitors the launch of new foods and beverages in Brazilian food retailers with information on those same claims manually coded by trained research assistants.

Methods

This is a cross-sectional observational study using a data sample of newly launched food and beverages available at a commercial database from 2018 to 2021. We compared the information on health and nutrition claims available on the commercial dataset with reliable information on the same nutrition and health claims manually coded by trained research assistants using a tested taxonomy to classify such claims. We used Gwet's Kappa AC1 with 95% CI and percentage agreement to compare both data sources and calculated sensitivity and specificity of the compared data.

Results

A total of 6,722 foods and beverages were analyzed. Mintel-GNPD presented 36.28% (n = 2,439) of nutrition claims, while in the trained researchers' coding, it was 33.73% (n = 2,267). We found a prevalence of 5.4% (n = 362) for health claims in Mintel-GNPD and 10.8% (n = 723) in the researchers' coding. All subcategories of nutrition and health claims showed high agreement (Kappa >0.81). Health claims presented kappa = 0.89 with 33.7% sensitivity and 98.0% specificity while nutrition claims showed kappa = 0.86 with 92.9% sensitivity and 92.5% specificity.

Conclusion

Nutrition and health claims showed high agreement, with great results in nutrition claims, indicating that Mintel-GPND is suitable for monitoring such claims on food and beverage packaging in Brazil. Additionally, our findings show a high prevalence of nutrition and health claims on food packages launched in the Brazilian food retail, highlighting the need to monitor these to develop public policies to regulate food marketing on packaging in Brazil.

Effective policies to promote sugar reduction in soft drinks: lessons from a comparison of six European countries

BACKGROUND

Many countries have sought to incentivise soft drinks manufacturers to reduce sugar in their products as part of efforts to address a growing prevalence of obesity. Are their policies effective?

METHODS

Using a difference-in-differences design, we compared trends in the sugar content of 10 695 new sugar-sweetened beverages (SSB) launched between 2010 and 2019 in six European markets, including the UK and France (taxes designed to incentivise reformulation), the Netherlands (policy based on voluntary agreements to reduce sugar), Germany, Italy and Spain (no national policies).

RESULTS

The announcement in 2016 and adoption in 2018 of the UK tax led to yearly reductions in average sugar content of 17% (95% CI: 15-19%) to 31% (13-48%) between 2016 and 2019, compared to 2015, while the 2018 French tax produced a 6% (95% CI: 5-7%) sugar reduction only in 2018, compared to 2017, shortly after it was redesigned to provide a stronger incentive for reformulation. Voluntary agreements implemented in the Netherlands in 2014 led to an 8% (95% CI: 4-13%) sugar reduction only in 2015, compared to 2013.

CONCLUSION

The analysis supports the conclusions that sugar reductions in new SSBs have been greater in countries that have adopted specific policies to encourage them; a sugar-based tax design encourages more sugar reductions than a volume-based tax design; the tax rate and the amount of the tax reduction from switching to the next lower tier in a sugar-based tax design may be critical to incentivize reformulation.

The development of a method for the global health community to assess the proportion of food and beverage companies' sales that are derived from unhealthy foods

CONTEXT

Corporate engagement with food and beverage companies who produce food associated with health harms is a divisive topic in the global nutrition community, with high-profile cases of conflict of interest increasingly coming under scrutiny. There is a need for an agreed method to support health organizations in deciding whether and how to engage with large food and beverage manufacturers.

AIM

The aim of this study was to develop a method to quantify the proportion of sales from food and beverage companies that are derived from unhealthy foods to support organizations in determining which companies might be considered high-risk for engagement.

METHODS

The 2015 WHO Euro nutrient profile model was applied to 35,550 products from 1294 brands manufactured by the top 20 global food and beverage companies from seven countries (Australia, Brazil, China, India, South Africa, UK and USA). For the purpose of this study, products that met the WHO Euro criteria were classified as "healthier" and those that failed were classified as "unhealthy". Products were grouped by brand and weighted by the brand's value sales for 2020. The primary outcome was the proportion of each company's sales that were classified as unhealthy and healthier by company and category.

RESULTS

Overall, 89% of the top 20 companies' brand sales were classified as unhealthy. For every USD$10 spent on the top 20 companies' brands, only $1.10 was spent on products considered healthier. All companies saw the majority of their sales come from unhealthy foods, including soft drinks, confectionery and snacks. None of Red Bull or Ferrero's sales were classified as healthier and less than 5% of total sales were healthier for Mondelēz, Mars, and PepsiCo. Some companies had higher proportions of sales deriving from healthier products, including Grupo Bimbo (48%), Danone (34%) and Conagra (32%), although the majority of their sales were still derived from unhealthy foods.

DISCUSSION

The results presented in this study highlight the reliance the leading food and beverage companies have on sales of unhealthy products that are contributing to diet-related disease globally. The method and steps we have laid out here could be used by organizations in the global health community to identify companies that have conflicts of interest when it comes to engaging with governments, international organizations and public health bodies on issues of policy and regulation.

National nutrition surveillance programmes in 18 countries in South-East Asia and Western Pacific Regions: a systematic scoping review

Objective

To identify and analyse ongoing nutrition-related surveillance programmes led and/or funded by national authorities in countries in South-East Asian and Western Pacific Regions.

Methods

We systematically searched for publications in PubMed® and Scopus, manually searched the grey literature and consulted with national health and nutrition officials, with no restrictions on publication type or language. We included low- and middle-income countries in the World Health Organization South-East Asia Region, and the Association of Southeast Asian Nations and China. We analysed the included programmes by adapting the United States Centers for Disease Control and Prevention's public health surveillance evaluation framework.

Findings

We identified 82 surveillance programmes in 18 countries that repeatedly collect, analyse and disseminate data on nutrition and/or related indicators. Seventeen countries implemented a national periodic survey that exclusively collects nutrition-outcome indicators, often alongside internationally linked survey programmes. Coverage of different subpopulations and monitoring frequency vary substantially across countries. We found limited integration of food environment and wider food system indicators in these programmes, and no programmes specifically monitor nutrition-sensitive data across the food system. There is also limited nutrition-related surveillance of people living in urban deprived areas. Most surveillance programmes are digitized, use measures to ensure high data quality and report evidence of flexibility; however, many are inconsistently implemented and rely on external agencies' financial support.

Conclusion

Efforts to improve the time efficiency, scope and stability of national nutrition surveillance, and integration with other sectoral data, should be encouraged and supported to allow systemic monitoring and evaluation of malnutrition interventions in these countries.

Changes in household food grocery shopping patterns in Melbourne, Australia during COVID-19 restrictions in 2020

OBJECTIVE

To investigate the impact of COVID-19 restrictions in Melbourne, 2020, on food grocery purchases.

METHODS

Grocery purchase data for 2019 and 2020 were accessed for 1,413 Melbourne households (NielsenIQ Homescan Consumer Panel) and linked to a nutrition composition database (FoodSwitch).

RESULTS

Per capita expenditure and dietary energy from groceries increased by 21.2% and 17.7%, respectively, during lockdowns, with marginally larger increases in expenditure and energy purchases from unhealthy products than healthy products (21.9% and 18.0% v 20.2% and 17.5%). The most socioeconomically disadvantaged households spent the least on but purchased the most energy from unhealthy products during lockdowns ($108 and 109MJ per capita per month), with the inverse found for the most advantaged households ($121 and 102MJ per capita per month). An increase in the overall proportion of total expenditure from unhealthy products during lockdowns was identified (+0.7%); however, there was no evidence of a difference in the proportion of energy purchased from unhealthy products. For most quintiles of household socioeconomic disadvantage/advantage, there were no statistically significant changes in the contribution of unhealthy products to total expenditure and energy purchases.

CONCLUSIONS

There was no substantial deterioration in the healthiness of grocery purchases during COVID-19 lockdowns in Melbourne. However, any additional purchases of unhealthy products are a concern. Further research on other sources of foods and drinks is also required to ascertain impacts on broader dietary patterns.

IMPLICATIONS FOR PUBLIC HEALTH

The increase in energy purchased may have implications for overweight and obesity as a risk factor for COVID-19 and chronic diseases. Governments and retailers may need to consider measures to encourage improved diet quality during future crises.

Purchase of ultra-processed foods in Norway: a repeated cross-sectional analysis of food sales in 2013 and 2019

OBJECTIVE

A dietary pattern dominated by ultra-processed foods has been associated with non-communicable diseases in several studies. A previous study from 2013 found a high share of ultra-processed foods in Norwegian food sales. This study aimed to investigate the current share of ultra-processed foods in Norway and the development in expenditure on ultra-processed foods from 2013.

DESIGN

A repeated cross-sectional analysis of scanner data from the Consumer Price Index from September 2013 and 2019 and an investigation of the processing degree according to the NOVA classification system.

SETTING

Food sales in Norway.

PARTICIPANTS

Norwegian grocery stores (n 180, for both time periods).

RESULTS

The share of expenditure in 2019 was highest for ultra-processed foods (46·5 %) and minimally or unprocessed foods (36·3 %), followed by processed foods (8·5 %) and processed culinary ingredients (1·3 %). An increasing degree of processing was found for several of the food groups between 2013 and 2019; however, most effect sizes were weak. In 2019, soft drinks became the most frequently purchased food item, surpassing milk and cheese, with the highest expenditure in Norwegian grocery stores. Increases in expenditure on ultra-processed foods were mainly due to increased expenditures on soft drinks, sweets and potato products.

CONCLUSIONS

A high share of expenditure on ultra-processed food was found in Norway, which may imply a high consumption of these foods. The change in expenditure of NOVA groups between 2013 and 2019 was small. Carbonated and non-carbonated soft drinks were the most frequently purchased products in Norwegian grocery stores and contributed to most of the expenditures.

Real-life experiments in supermarkets to encourage healthy dietary-related behaviours: opportunities, challenges and lessons learned

BACKGROUND

Supermarkets are the primary source of food for many people yet their full potential as a setting to encourage healthy dietary-related behaviours remains underutilised. Sharing the experiences from research groups who have worked with supermarket chains to evaluate strategies that promote healthy eating could improve the efficiency of building such relationships and enhance the design quality of future research studies.

METHODS

A collective case study approach was used to synthesise experiences of engaging and sustaining research collaborations with national supermarket chains to test the effectiveness of health-focused in-store interventions. The collective narrative covers studies conducted in three high-income countries: Australia, the Netherlands and the United Kingdom.

RESULTS

We have distilled our experiences and lessons learned into six recommendations for conducting high quality public health research with commercial supermarket chains. These include: (i) using personal contacts, knowledge of supermarket activities and engaging executive management to establish a partnership and allowing time to build trust; (ii) using scientifically robust study designs with appropriate sample size calculations; (iii) formalising data exchange arrangements and allocating adequate resource for data extraction and re-categorisation; (iv) assessing effects at individual/households level where possible; (v) designing a mixed-methods process evaluation to measure intervention fidelity, dose and unintended consequences; and (vi) ensuring scientific independence through formal contract agreements.

CONCLUSIONS

Our collective experiences of working in non-financial partnerships with national supermarket chains could be useful for other research groups looking to develop and implement supermarket studies in an efficient manner. Further evidence from real-life supermarket interventions is necessary to identify sustainable strategies that can improve population diet and maintain necessary commercial outcomes.

Nutritional Epidemiology and Dietary Assessment for Patients With Kidney Disease: A Primer

Nutritional epidemiology seeks to understand nutritional determinants of disease in human populations using experimental and observational study designs. Though randomized controlled trials provide the strongest evidence of causality, the expense and difficulty of sustaining adherence to dietary interventions are substantial barriers to investigating dietary determinants of kidney disease. Therefore, nutritional epidemiology commonly employs observational study designs, particularly prospective cohort studies, to investigate long-term associations between dietary exposures and kidney disease. Due to the covarying nature and synergistic effects of dietary components, holistic characterizations of dietary exposures that simultaneously consider patterns of foods and nutrients regularly consumed are generally more relevant to disease etiology than single nutrients or foods. Dietary intakes have traditionally been self-reported and are subject to bias. Statistical methods including energy adjustment and regression calibration can reduce random and systematic measurement errors associated with self-reported diet. Novel approaches that assess diet more objectively are gaining popularity but have not yet fully replaced self-report and require refinement and validation in populations with chronic kidney disease. More accurate and frequent diet assessment in existing and future studies will yield evidence to better personalize dietary recommendations for the prevention and treatment of kidney disease.

An umbrella review of the effectiveness of fiscal and pricing policies on food and non-alcoholic beverages to improve health

Poor quality diets represent major risk factors for the global burden of disease. Modeling studies indicate a potential for diet-related fiscal and pricing policies (FPs) to improve health. There is real-world evidence (RWE) that such policies can change behavior; however, the evidence regarding health is less clear. We conducted an umbrella review of the effectiveness of FPs on food and non-alcoholic beverages in influencing health or intermediate outcomes like consumption. We considered FPs applied to an entire population within a jurisdiction and included four systematic reviews in our final sample. Quality appraisal, an examination of excluded reviews, and a literature review of recent primary studies assessed the robustness of our results. Taxes and, to some extent, subsidies are effective in changing consumption of taxed/subsidized items; however, substitution is likely to occur. There is a lack of RWE supporting the effectiveness of FPs in improving health but this does not mean that they are ineffective. FPs may be important for improving health but their design is critical. Poorly designed FPs may fail to improve health and could reduce support for such policies or be used to support their repeal. More high-quality RWE on the impact of FPs on health is needed.

Discrepancies between two long-term dietary datasets in the United Kingdom (UK)

Background: Studying dietary trends can help monitor progress towards healthier and more sustainable diets but longitudinal data are often confounded by lack of standardized methods. Two main data sources are used for longitudinal analysis of diets: food balance sheets on food supply (FBS) and household budget surveys on food purchased (HBS). Methods: We used UK longitudinal dietary data on food supply, provided by the Food and Agriculture Organisation (FAO) (FAO-FBS, 1961-2018), and food purchases, provided by the Department for Environment, Food and Rural Affairs (Defra) (Defra-HBS, 1942-2018). We assessed how trends in dietary change per capita compared between FAO-FBS and Defra-HBS for calories, meat and fish, nuts and pulses, and dairy, and how disparities have changed over time. Results: Estimates made by FAO-FBS were significantly higher (p<0.001) than Defra-HBS for calorie intake and all food types, except nuts and pulses which were significantly lower (p<0.001). These differences are partly due to inclusion of retail waste in FAO-FBS data and under-reporting in Defra- HBS data. The disparities between the two datasets increased over time for calories, meat and dairy; did not change for fish; and decreased for nuts and pulses. Between 1961 and 2018, both FAO-FBS and Defra-FBS showed an increase in meat intake (+23.4% and +1.4%, respectively) and a decrease in fish (-7.1% and -3.2%, respectively). Temporal trends did not agree between the two datasets for dairy, calories, and nuts and pulses. Conclusions: Our finding raises questions over the robustness of both data sources for monitoring UK dietary change, especially when used for evidence-based decision making around health, climate change and sustainability.

Discrepancies between two long-term dietary datasets in the United Kingdom (UK)

Background: Studying dietary trends can help monitor progress towards healthier and more sustainable diets but longitudinal data are often confounded by lack of standardized methods. Two main data sources are used for longitudinal analysis of diets: food balance sheets on food supply (FBS) and household budget surveys on food purchased (HBS). Methods: We used UK longitudinal dietary data on food supply, provided by the Food and Agriculture Organisation (FAO) (FAO-FBS, 1961-2018), and food purchases, provided by the Department for Environment, Food and Rural Affairs (Defra) (Defra-HBS, 1942-2018). We assessed how trends in dietary change per capita compared between FAO-FBS and Defra-HBS for calories, meat and fish, nuts and pulses, and dairy, and how disparities have changed over time. Results: Estimates made by FAO-FBS were significantly higher (p<0.001) than Defra-HBS for calorie intake and all food types, except nuts and pulses which were significantly lower (p<0.001). These differences are partly due to inclusion of retail waste in FAO-FBS data and under-reporting in Defra- HBS data. The disparities between the two datasets increased over time for calories, meat and dairy; did not change for fish; and decreased for nuts and pulses. Between 1961 and 2018, both FAO-FBS and Defra-FBS showed an increase in meat intake (+11.5% and +1.4%, respectively) and a decrease in fish (-3.3% and -3.2%, respectively) and dairy intake (-11.2% and -22.4%). Temporal trends did not agree between the two datasets for calories, and nuts and pulses. Conclusions: Our finding raises questions over the robustness of both data sources for monitoring UK dietary change, especially when used for evidence-based decision making around health, climate change and sustainability.

Discrepancies between two long-term dietary datasets in the United Kingdom (UK)

Background: Studying dietary trends can help monitor progress towards healthier and more sustainable diets but longitudinal data are often confounded by lack of standardized methods. Two main data sources are           used for longitudinal analysis of diets: food balance sheets on food supply (FBS) and household budget surveys on food purchased (HBS). Methods: We used UK longitudinal dietary data on food supply, provided by the Food and Agriculture Organisation (FAO) (FAO-FBS, 1961-2018), and food purchases, provided by Defra (Defra-HBS, 1942-2018). We assessed how trends in dietary change per capita compared between FAO-FBS and Defra-HBS for calories, meat and fish, nuts and pulses, and dairy, and how disparities have changed over time. Results: FAO-FBS estimates were significantly higher (p<0.001) than Defra-HBS for calorie intake and all food types, except nuts and pulses which were significantly lower (p<0.001). These differences are partly due to inclusion of retail waste in FAO-FBS data and under-reporting in Defra- HBS data. The disparities between the two datasets increased over time for calories, meat and dairy; did not change for fish; and decreased for nuts and pulses . Between 1961 and 2018, both FAO-FBS and Defra-FBS showed an increase in meat intake (+11.5% and +1.4%, respectively) and a decrease in fish (-3.3% and -3.2%, respectively) and dairy intake (-11.2% and -22.4%). Temporal trends did not agree between the two datasets for calories, and nuts and pulses. Conclusions: Our finding raises questions over the robustness of both data sources for monitoring UK dietary change, especially when used for evidence-based decision making around health, climate change and sustainability.

The revised Healthy Purchase Index (r-HPI): a validated tool for exploring the nutritional quality of household food purchases

BACKGROUND

The Healthy Purchase Index (HPI) assesses the nutritional quality of food purchases (FP) from food group expenditure shares only. However, it was developed from the FP of a disadvantaged population.

OBJECTIVE

To adapt and validate the HPI for a general population.

METHODS

FP were obtained from a representative sample of French households (Kantar WorldPanel) subdivided into two subsamples. The first sample (n = 4375) was used to adapt and validate the score; the second sample (n = 2188) was used to test external validity. The revised-HPI (r-HPI) includes 2 subscores: the diversity subscore and the quality subscore. Diversity subscore points were awarded when expenditure shares were above the 25th percentile for 5 food groups ("Fruits", "Vegetables", "Starches", "Dairy", "Meat, Fish and Eggs"). Regression models between the expenditure shares of each food group and the Mean Adequacy Ratio (MAR) and the Mean Excess Ratio (MER) of FP were used to select quality subscore components and define cut-offs for point allocation. Construct validity was assessed on the first sample using Spearman's correlations between the r-HPI and the four nutritional quality indicators (NRF9.3, MAR, MER, energy density), and also by comparing the r-HPI of monthly FP of sub-populations defined by criteria known to influence diet quality (age, gender, income, education) and between households having a monthly food basket of higher (MAR > median and MER and energy density < median) vs. lower nutritional quality within the population, using Wilcoxon tests or pairwise comparisons of contrasts. External validity was tested by performing the same analyses on the 2nd sample of 2188 households.

RESULTS

The adaptation led to include new components (e.g. red meat) and define new cut-offs (e.g. - 1 point when budget share for red meat > 21%). The r-HPI (mean = 6.50 ± 3.58) was strongly correlated with NRF9.3, MAR, MER and energy density (0.59, 0.52, - 0.41 and - 0.65, respectively, p < 0.01) and poorly correlated with total energy content (- 0.096, p < 0.001). The r-HPI was significantly higher in women (β = 1.41 [0.20], p < 0.01), households having a food basket of higher nutritional quality (β = 4.15 [0.11], p < 0.001), and increased significantly with age, income and education levels. Similar results were obtained in the 2nd sample.

CONCLUSION

We showed the validity of the r-HPI in a large sample of French households. As it does not require food quantity or nutrient content, it can be used as a valuable tool to explore FP behaviours. Cut-offs can be used in health promotion to provide nutri-economic counselling.

Longitudinal trends in produce purchasing behavior: a descriptive study of transaction level data from loyalty card households

Background

Household food purchases (HFP) are in the pathway between the community food environment and the foods available in households for consumption. As such, HFP data have emerged as alternatives to monitor population dietary trends over-time. In this paper, we investigate the use of loyalty card datasets as unexplored sources of continuously collected HFP data to describe temporal trends in household produce purchases.

Methods

We partnered with a grocery store chain to obtain a loyalty card database with grocery transactions by household from January 2016-October 2018. We included households in an urban county with complete observations for head of household age group, household income group, and family size. Data were summarized as weighted averages (95% CI) of percent produce purchased out of all foods purchased by household per month. We modeled seasonal and linear trends in the proportion of produce purchases by age group and income while accounting for repeated observations per household using generalized estimating equations.

Results

There are 290,098 households in the database (88% of all county households). At baseline, the smallest and largest percent produce purchases are observed among the youngest and lowest income (12.2%, CI 11.1; 13.3) and the oldest and highest income households (19.3, CI 18.9; 19.6); respectively. The seasonal variations are consistent in all age and income groups with an April-June peak gradually descending until December. However, the average linear change in percent produce purchased per household per year varies by age and income being the steepest among the youngest households at each income level (from 1.42%, CI 0.98;1.8 to 0.69%, CI 0.42;0.95) while the oldest households experience almost no annual change.

Conclusions

 We explored the potential of a collaboration with a food retailer to use continuously collected loyalty card data for public health nutrition purposes. Our findings suggest a trend towards a healthier pattern in long-term food purchases and household food availability among the youngest households that may lessen the population chronic disease burden if sustained. Understanding the foods available for consumption within households allows public health advocates to develop and evaluate policies and programs promoting foods and nutrients along the life course.

Processed foods purchase profiles in urban India in 2013 and 2016: a cluster and multivariate analysis

OBJECTIVES

Sales of ultraprocessed foods (UPFs) and beverages are rising in low-income and middle-income countries. Such foods are often linked with weight gain, obesity, type 2 diabetes and hypertension-diseases that are on the rise in India. This paper analysed patterns in purchases of processed and UPF by urban Indian households.

SETTING

Panel data from Kantar -Worldpanel Division, India for 2013 and 2016.

PARTICIPANTS

58 878 urban Indian households.

METHODS

We used K-mean partition clustering and multivariate regression to analyse patterns in processed food (PF) and UPF purchase for urban India.

RESULTS

Three-quarters of urban Indian households purchased over ten PF groups. Mean per person annual PF purchase was 150 kg. UPF purchase was low at 6.4 kg in 2016 but had grown by 6% since 2013. Cluster analysis identified three patterns of consumption, characterised by low (54% of the households in 2016), medium (36%) and high (10%) PF purchase quantities. High cluster households purchased over three times as much PFs and UPF as the low cluster households. Notably, salt purchases were persistently high across clusters in both years (>3.3 kg), while sweet snack and ready-to-eat food purchases grew consistently in all clusters between 2013 and 2016. A positive and significant association was found between household purchases of UPF and their socioeconomic status as well as ownership of durables, such as refrigerator, colour television and washing machine (all p<0.001). Spatial characteristics including size of town (p<0.05) in which the household is located were also positively associated with the purchase of UPF.

CONCLUSION

Results suggest the need for tailored regional and city level interventions to curb the low but growing purchase of UPF. New data on obesity and rise of non-communicable diseases, the results are concerning given the links between lifestyle changes and the speed of urbanisation in Indian cities.

Changes in the salt content of packaged foods sold in supermarkets between 2015-2020 in the United Kingdom: A repeated cross-sectional study

BACKGROUND

Excess consumption of salt is linked to an increased risk of hypertension and cardiovascular disease. The United Kingdom has had a comprehensive salt reduction programme since 2003, setting a series of progressively lower, product-specific reformulation targets for the food industry, combined with advice to consumers to reduce salt. The aim of this study was to assess the changes in the sales-weighted mean salt content of grocery foods sold through retail between 2015 and 2020 by category and company.

METHODS AND FINDINGS

Information for products, including salt content (g/100 g), was collected online from retailer websites for 6 consecutive years (2015 to 2020) and was matched with brand-level retail sales data from Euromonitor for 395 brands. The sales-weighted mean salt content and total volume of salt sold were calculated by category and company. The mean salt content of included foods fell by 0.05 g/100 g, from 1.04 g/100 g in 2015 to 0.90 g/100 g in 2020, equivalent to -4.2% (p = 0.13). The categories with the highest salt content in 2020 were savoury snacks (1.6 g/100 g) and cheese (1.6 g/100 g), and the categories that saw the greatest reductions in mean salt content over time were breakfast cereals (-16.0%, p = 0.65); processed beans, potatoes, and vegetables (-10.6%, p = 0.11); and meat, seafood, and alternatives (-9.2%, p = 0.56). The total volume of salt sold fell from 2.41 g per person per day to 2.25 g per person per day, a reduction of 0.16 g or 6.7% (p = 0.54). The majority (63%) of this decrease was attributable to changes in mean salt content, with the remaining 37% accounted for by reductions in sales. Across the top 5 companies in each of 9 categories, the volume of salt sold decreased in 26 and increased in 19 cases. This study is limited by its exclusion of foods purchased out of the home, including at restaurants, cafes, and takeaways. It also does not include salt added at the table, or that naturally occurring in foods, meaning the findings underrepresent the population's total salt intake. The assumption was also made that the products matched with the sales data were entirely representative of the brand, which may not be the case if products are sold exclusively in convenience stores or markets, which are not included in this database.

CONCLUSIONS

There has been a small decline in the salt content of foods and total volume of salt sold between 2015 and 2020, but observed changes were not statistically significant so could be due to random variations over time. We suggest that mandatory reporting of salt sales by large food companies would increase the transparency of how individual businesses are progressing towards the salt reduction targets.

Health surveillance indicators for diet and physical activity: what is available in European data sets for policy evaluation?

BACKGROUND

Policies targeting diet and physical activity have the potential to improve health and well-being at a population level. However, the impact of these policies in Europe is currently unknown. Based on existing data, as well as on a needs assessment, we derived a catalogue of indicators that can be employed to evaluate such policies. These indicators may also inform the further development and harmonization of surveillance systems.

METHODS

Forty EU experts agreed on a list of key indicators and ranked their priority for future surveillance. We mapped these indicators onto variables provided by ongoing European surveillance systems. Using a Likert scale (well matched, somewhat matched, poorly matched, unmatched), we assessed the suitability of these variables as measures for the indicators.

RESULTS

Key indicators included behaviour outcome indicators relating to diet (n = 72) and physical activity and sedentary behaviour (n = 67) as well as upstream determinants of these behaviours. It was possible to map 72% of diet indicators and 86% of physical activity and sedentary behaviour indicators onto at least one variable in an ongoing surveillance system.

CONCLUSIONS

Current monitoring and surveillance systems focus mainly on measuring 'downstream' indicators, while gaps exist in policy and environmental level data in dimensions such as inequality, funding and resources and governance.

Prospects and Pitfalls of Machine Learning in Nutritional Epidemiology

Nutritional epidemiology employs observational data to discover associations between diet and disease risk. However, existing analytic methods of dietary data are often sub-optimal, with limited incorporation and analysis of the correlations between the studied variables and nonlinear behaviours in the data. Machine learning (ML) is an area of artificial intelligence that has the potential to improve modelling of nonlinear associations and confounding which are found in nutritional data. These opportunities notwithstanding, the applications of ML in nutritional epidemiology must be approached cautiously to safeguard the scientific quality of the results and provide accurate interpretations. Given the complex scenario around ML, judicious application of such tools is necessary to offer nutritional epidemiology a novel analytical resource for dietary measurement and assessment and a tool to model the complexity of dietary intake and its relation to health. This work describes the applications of ML in nutritional epidemiology and provides guidelines to avoid common pitfalls encountered in applying predictive statistical models to nutritional data. Furthermore, it helps unfamiliar readers better assess the significance of their results and provides new possible future directions in the field of ML in nutritional epidemiology.

The nutrition transition, food retail transformations, and policy responses to overnutrition in the East Asia region: A descriptive review

BACKGROUND

The East Asia region is facing an increasing burden of overweight, obesity and related noncommunicable diseases, resulting from an ongoing nutrition transition. This study aimed to document the growing burden of overweight and obesity, and the accompanying dietary shifts, in the East Asia region and describe the policy responses to this.

METHODS

We present noncommunicable disease risk factor collaboration data on trends in the burden of malnutrition, and Euromonitor International data on trends in dietary purchases, in the East Asia region. We searched the NOURISHING and GINA databases to identify food and nutrition policies implemented in these countries.

RESULTS

There is an ongoing nutrition transition in the East Asia region, notably in upper-middle and lower-middle income countries. The prevalence of overweight, obesity, and accompanying health conditions, purchases of ultra-processed foods and beverages, and purchasing from supermarkets, fast-food and takeaway outlets, and other convenience retailers, are increasing. The policy response to this nutrition transition is limited, with the majority of policies implemented in higher-income countries.

CONCLUSIONS

East Asian countries are facing a growing burden of malnutrition, due in part to the dietary shifts occurring here. An ecological approach to policy intervention is needed to drive transformative food systems change.

Algorithm-based mapping of products in a branded Canadian food and beverage database to their equivalents in Health Canada's Canadian Nutrient File

Introduction

There is increasing recognition of the value of linking food sales databases to national food composition tables for population nutrition research.

Objectives

Expanding upon automated and manual database mapping approaches in the literature, our aim was to match 1,179 food products in the Canadian data subset of Euromonitor International's Passport Nutrition to their closest respective equivalents in Health Canada's Canadian Nutrient File (CNF).

Methods

Matching took place in two major steps. First, an algorithm based on thresholds of maximal nutrient difference (between Euromonitor and CNF foods) and fuzzy matching was executed to offer match options. If a nutritionally appropriate match was available among the algorithm suggestions, it was selected. When the suggested set contained no nutritionally sound matches, the Euromonitor product was instead manually matched to a CNF food or deemed unmatchable, with the unique addition of expert validation to maximize meticulousness in matching. Both steps were independently performed by at least two team members with dietetics expertise.

Results

Of 1,111 Euromonitor products run through the algorithm, an accurate CNF match was offered for 65% of them; missing or zero-calorie data precluded 68 products from being run in the algorithm. Products with 2 or more algorithm-suggested CNF matches had higher match accuracy than those with one (71 vs. 50%, respectively). Overall, inter-rater agreement (reliability) rates were robust for matches chosen among algorithm options (51%) and even higher regarding whether manual selection would be required (71%); among manually selected CNF matches, reliability was 33%. Ultimately, 1,152 (98%) Euromonitor products were matched to a CNF equivalent.

Conclusion

Our reported matching process successfully bridged a food sales database's products to their respective CNF matches for use in future nutritional epidemiological studies of branded foods sold in Canada. Our team's novel utilization of dietetics expertise aided in match validation at both steps, ensuring rigor and quality of resulting match selections.

The European Food Regulatory Environment Index: a tool to monitor progress in implementing food environment policies

Background

Evidence based health policy, such as that put forward in the European Food and Nutrition Action Plan 2015–2020 and the WHO Global Action Plan on the Prevention and Control of Noncommunicable Diseases, has a role in curbing the consumption of unhealthful foods and drink. We ask how countries are performing in the adoption of these policies and how the comprehensiveness of their food environment policies explains variations in consumption of unhealthful products across Europe.

Methods

In order to assess the state of policy adoption, we developed a composite indicator—the Food Regulatory Environment Index (FREI) for which we calculated unweighted and weighted formulations according to the strength of the evidence base. We used linear regression models to explain variations in the consumption of unhealthful products as well as variations in a composite indicator of obesogenic diets.

Results

Overall, wealthier countries in the Region perform better. The weighting of the constituent policies does not affect the rankings. We find negative associations between unweighted and weighted formulations of the Index and household consumption of sugary and carbonate drinks as well as with the composite indicator for obesogenic diets.

Conclusions

The main strength of this study is the comprehensiveness and comparability of the policy data across the relatively large number of countries covered. There is a negative association that is statistically significant, between all formulations of the FREI and the household consumption of sugary and carbonated drinks. There is also a negative association between some FREI formulations and obesogenic diets.

Does the prevalence of promotions on foods and beverages vary by product healthiness? A population-based study of household food and drink purchases in New Zealand

OBJECTIVE

To assess the prevalence of promotions on foods and non-alcoholic drinks purchased by New Zealand households and to determine if they vary according to healthiness of products.

DESIGN

We undertook a cross-sectional analysis of Nielsen New Zealand Homescan® 2018/19 panel data. We conducted multivariate analyses to examine the variability in quantities of healthy v. unhealthy food and beverage products purchased on promotion. Promotion was self-reported by the panellist. Healthiness of products was measured by the Health Star Rating (HSR) system. We also carried out a subgroup analysis for beverages according to the threshold of < 5 g v. ≥ 5 g sugar per 100 ml content of products.

SETTING

The Nielsen New Zealand Homescan® data were linked with two New Zealand Food Composition Databases (Nutritrack and the FOODfiles).

PARTICIPANTS

Food and beverage purchases data by 1800 panel households were used.

RESULTS

Overall, 46 % (1 803 601/3 940 458) of all purchases made were on promotion. Compared with purchases of food and beverage products with HSR < 3·5 (unhealthy), food and beverage products with HSR ≥ 3·5 (healthy) were significantly less likely to be on promotion (OR = 0·78, 95 % CI 0·77, 0·79). The subgroup analysis for beverages shows that products with < 5 g sugar per 100 ml were significantly less likely to be on promotion than those with ≥ 5 g sugar per 100 ml (OR = 0·77, 95 % CI 0·75, 0·79).

CONCLUSIONS

Policies to improve healthy food retailing should focus on increasing the promotion of healthier food and drink options in stores and supermarkets.

A Proposed Research Agenda for Promoting Healthy Retail Food Environments in the East Asia-Pacific Region

PURPOSE OF REVIEW

This paper aimed to summarise existing literature on strategies to improve the healthiness of retail food environments in the East Asia and Pacific (EAP) region, and propose a prioritised research agenda on this topic.

RECENT FINDINGS

Little research on retail food environments has been conducted in the EAP region. Several approaches for measuring retail food environments were identified, although none have been tailored to the EAP context. A small number of policies and initiatives to promote healthy retail food environments have been implemented in EAP. Lessons learnt from successful implementation of initiatives in other regions could be applied in EAP. Retail food environments have a strong influence on food choices and health outcomes. Research can contribute to efforts to improve the healthiness of retail food environments in EAP by (1) describing the current state of retail food environments to highlight areas of good practice and concern and (2) identifying policies and initiatives that are likely to be effective, and mechanisms for their successful implementation.

A systematic review of supermarket automated electronic sales data for population dietary surveillance

Context

Most dietary assessment methods are limited by self-report biases, how long they take for participants to complete, and cost of time for dietitians to extract content. Electronically recorded, supermarket-obtained transactions are an objective measure of food purchases, with reduced bias and improved timeliness and scale.

Objective

The use, breadth, context, and utility of electronic purchase records for dietary research is assessed and discussed in this systematic review.

Data sources

Four electronic databases (MEDLINE, EMBASE, PsycINFO, Global Health) were searched. Included studies used electronically recorded supermarket transactions to investigate the diet of healthy, free-living adults.

Data extraction

Searches identified 3422 articles, of which 145 full texts were retrieved and 72 met inclusion criteria. Study quality was assessed using the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.

Data analysis

Purchase records were used in observational studies, policy evaluations, and experimental designs. Nutrition outcomes included dietary patterns, nutrients, and food category sales. Transactions were linked to nutrient data from retailers, commercial data sources, and national food composition databases.

Conclusion

Electronic sales data have the potential to transform dietary assessment and worldwide understanding of dietary behavior. Validation studies are warranted to understand limits to agreement and extrapolation to individual-level diets.

Systematic Review Registration

PROSPERO registration no. CRD42018103470

Optimizing the use of technology to support people with diabetes: research recommendations from Diabetes UK's 2019 diabetes and technology workshop

AIMS

To identify key gaps in the research evidence base that could help improve how technology supports people with diabetes, and provide recommendations to researchers and research funders on how best to address them.

METHODS

A research workshop was conducted, bringing together research experts in diabetes, research experts in technology, people living with diabetes and healthcare professionals.

RESULTS

The following key areas within this field were identified, and research recommendations for each were developed: Matching the pace of research with that of technology development Time in range as a measure Health inequalities and high-risk groups How to train people to use technology most effectively Impact of technology usage on mental health CONCLUSIONS: This position statement outlines recommendations through which research could improve how technology is employed to care for and support people living with diabetes, and calls on the research community and funders to address them in future research programmes and strategies.

Simulation Modeling for the Economic Evaluation of Population-Based Dietary Policies: A Systematic Scoping Review

Simulation modeling can be useful to estimate the long-term health and economic impacts of population-based dietary policies. We conducted a systematic scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guideline to map and critically appraise economic evaluations of population-based dietary policies using simulation models. We searched Medline, Embase, and EconLit for studies published in English after 2005. Modeling studies were mapped based on model type, dietary policy, and nutritional target, and modeled risk factor-outcome pathways were analyzed. We included 56 studies comprising 136 model applications evaluating dietary policies in 21 countries. The policies most often assessed were reformulation (34/136), taxation (27/136), and labeling (20/136); the most common targets were salt/sodium (60/136), sugar-sweetened beverages (31/136), and fruit and vegetables (15/136). Model types included Markov-type (35/56), microsimulation (11/56), and comparative risk assessment (7/56) models. Overall, the key diet-related risk factors and health outcomes were modeled, but only 1 study included overall diet quality as a risk factor. Information about validation was only reported in 19 of 56 studies and few studies (14/56) analyzed the equity impacts of policies. Commonly included cost components were health sector (52/56) and public sector implementation costs (35/56), as opposed to private sector (18/56), lost productivity (11/56), and informal care costs (3/56). Most dietary policies (103/136) were evaluated as cost-saving independent of the applied costing perspective. An analysis of the main limitations reported by authors revealed that model validity, uncertainty of dietary effect estimates, and long-term intervention assumptions necessitate a careful interpretation of results. In conclusion, simulation modeling is widely applied in the economic evaluation of population-based dietary policies but rarely takes dietary complexity and the equity dimensions of policies into account. To increase relevance for policymakers and support diet-related disease prevention, economic effects beyond the health sector should be considered, and transparent conduct and reporting of model validation should be improved.

The utility of household Grocery Purchase Quality Index scores as an individual diet quality metric

The Grocery Purchase Quality Index (GPQI) reflects concordance between household grocery purchases and US dietary recommendations. However, it is unclear whether GPQI scores calculated from partial purchasing records reflect individual-level diet quality. This secondary analysis of a 9-month randomised controlled trial examined concordance between the GPQI (range 0-75, scaled to 100) calculated from 3 months of loyalty-card linked partial (≥50 %) household grocery purchasing data and individual-level Healthy Eating Index (HEI) scores at baseline and 3 months calculated from FFQ (n 209). Concordance was assessed with overall and demographic-stratified partially adjusted correlations; covariate-adjusted percentage score differences, cross-classification and weighted κ coefficients assessed concordance across GPQI tertiles (T). Participants were middle aged (55·4 (13·9) years), female (90·3 %), from non-smoking households (96·4 %) and without children (70·7 %). Mean GPQI (54·8 (9·1) %) scores were lower than HEI scores (baseline: 73·2 (9·1) %, 3 months: 72·4 (9·4) %) and moderately correlated (baseline r 0·41 v. 3 months r 0·31, P < 0·001). Correlations were stronger among participants with ≤ bachelor's degree, obesity and children. Scores showed moderate agreement (κ = 0·25); concordance was highest in T3. Participants with high (T3) v. low (T1) GPQI scores had 7·3-10·6 higher odds of having HEI scores >80 % at both time points. Household-level GPQI was moderately correlated with self-reported intake, indicating their promise for evaluating diet quality. Partial purchasing data appear to moderately reflect individual diet quality and may be useful in interventions monitoring changes in diet quality.

Comparison of Healthiness, Labelling, and Price between Private and Branded Label Packaged Foods in New Zealand (2015-2019)

We aimed to compare New Zealand private label (PL) and branded label (BL) packaged food products in relation to their current (2019) healthiness (sodium and sugar contents, and estimated Health Star Rating (HSR) score), display of the voluntary HSR nutrition label on the package, and price. Healthiness and HSR display of products were also explored over time (2015 to 2019). Data were obtained from Nutritrack, a brand-specific food composition database. Means and proportions were compared using Student t-tests and Pearson chi-square tests, respectively. Changes over time were assessed using linear regression and chi-square tests for trends (Mantel–Haenzel tests). Altogether, 4266 PL and 19,318 BL products across 21 food categories were included. Overall, PL products in 2019 had a significantly lower mean sodium content and price, a higher proportion of products with estimated HSR ≥ 3.5/5 (48.9% vs. 38.5%) and were more likely to display the HSR on the pack compared with BL products (92.4% vs. 17.2%, respectively). However, for most food categories, no significant difference was found in mean sodium or sugar content between PL and BL products. In the period 2015–2019, there were no consistent changes in estimated HSR score, sodium or sugar contents of PL or BL products, but there was an increase in the proportion of both PL and BL products displaying HSR labels. In most food categories, there were PL options available which were similar in nutritional composition, more likely to be labelled with the HSR, and lower in cost than their branded counterparts.

Sugars, Salt, Saturated Fat and Fibre Purchased through Packaged Food and Soft Drinks in Europe 2015-2018: Are We Making Progress?

The availability, purchase and consumption of foods high in fat, sugars and salt and low in fibre are linked to the high health and economic burden of noncommunicable diseases, including cancer, in Europe. Therefore, assessing the quality of the food offer is key as feedback to decision makers, as well as to identify good practices and areas of the food supply still requiring urgent action. We combined detailed market share and sales data with nutrition composition data to evaluate the nutritional quality of 14 packaged food and soft drinks categories sold across 22 European countries over the 2015–2018 period. Our analysis shows great variability of the nutritional composition within and among packaged food and soft drinks categories across European countries. Our estimates of the market-share weighted mean, a measure that integrates possible changes in nutrient content with the amount of a product sold to consumers, as well as daily per capita nutrient sale estimates, suggest a small but statistically significant progress in certain food categories only. Overall, the amounts of sugars, saturated fat, salt and fibre being sold to European citizens through these products is not improving to an extent to meet public health objectives.

Scenario Analysis of a Municipality’s Food Purchase to Simultaneously Improve Nutritional Quality and Lower Carbon Emission for Child-Care Centers

Public procurement has been highlighted as an important strategic tool to drive sustainable development. The present study aimed at providing direction for decreasing greenhouse gas emissions (GHGE) by 25% for the food purchased by child-care centers in the City of Copenhagen while simultaneously providing nutritionally adequate, affordable and tasty menus. Baseline data were provided by compiling food purchase data with datasets matching each food item to a proxy food item and further with databases containing nutrient and GHGE information. For each food item, the edible amount was estimated in order to evaluate nutritional content and GHGE per 10 MJ. Two scenarios were modeled, i.e., a plant-rich diet and a lacto-ovo vegetarian diet directed at children two to five years old based on current purchase practice. Finally, the diets were translated into guidelines for menu planning. Amounts of pulses, nuts and seeds, as well as dark green vegetables and plant-based fats, were increased substantially in the two scenarios, while animal fat was decreased and the amount of meat was either reduced or eliminated in the plant-rich and lacto-ovo vegetarian diets, respectively. These kinds of changes in public food procurement have the power to significantly affect the transition toward a more healthy and sustainable food system.

The sugar content of foods in the UK by category and company: A repeated cross-sectional study, 2015-2018

BACKGROUND

Consumption of free sugars in the UK greatly exceeds dietary recommendations. Public Health England (PHE) has set voluntary targets for industry to reduce the sales-weighted mean sugar content of key food categories contributing to sugar intake by 5% by 2018 and 20% by 2020. The aim of this study was to assess changes in the sales-weighted mean sugar content and total volume sales of sugar in selected food categories among UK companies between 2015 and 2018.

METHODS AND FINDINGS

We used sales data from Euromonitor, which estimates total annual retail sales of packaged foods, for 5 categories-biscuits and cereal bars, breakfast cereals, chocolate confectionery, sugar confectionery, and yoghurts-for 4 consecutive years (2015-2018). This analysis includes 353 brands (groups of products with the same name) sold by 99 different companies. These data were linked with nutrient composition data collected online from supermarket websites over 2015-2018 by Edge by Ascential. The main outcome measures were sales volume, sales-weighted mean sugar content, and total volume of sugar sold by category and company. Our results show that between 2015 and 2018 the sales-weighted mean sugar content of all included foods fell by 5.2% (95% CI -9.4%, -1.4%), from 28.7 g/100 g (95% CI 27.2, 30.4) to 27.2 g/100 g (95% CI 25.8, 28.4). The greatest change seen was in yoghurts (-17.0% [95% CI -26.8%, -7.1%]) and breakfast cereals (-13.3% [95% CI -19.2%, -7.4%]), with only small reductions in sugar confectionery (-2.4% [95% CI -4.2%, -0.6%]) and chocolate confectionery (-1.0% [95% CI -3.1, 1.2]). Our results show that total volume of sugars sold per capita fell from 21.4 g/d (95% CI 20.3, 22.7) to 19.7 g/d (95% CI 18.8, 20.7), a reduction of 7.5% (95% CI -13.1%, -2.8%). Of the 50 companies representing the top 10 companies in each category, 24 met the 5% reduction target set by PHE for 2018. The key limitations of this study are that it does not encompass the whole food market and is limited by its use of brand-level sales data, rather than individual product sales data.

CONCLUSIONS

Our findings show there has been a small reduction in total volume sales of sugar in the included categories, primarily due to reductions in the sugar content of yoghurts and breakfast cereals. Additional policy measures may be needed to accelerate progress in categories such as sugar confectionery and chocolate confectionery if the 2020 PHE voluntary sugar reduction targets are to be met.

Dietary Patterns Derived from UK Supermarket Transaction Data with Nutrient and Socioeconomic Profiles

Poor diet is a leading cause of death in the United Kingdom (UK) and around the world. Methods to collect quality dietary information at scale for population research are time consuming, expensive and biased. Novel data sources offer potential to overcome these challenges and better understand population dietary patterns. In this research we will use 12 months of supermarket sales transaction data, from 2016, for primary shoppers residing in the Yorkshire and Humber region of the UK (n = 299,260), to identify dietary patterns and profile these according to their nutrient composition and the sociodemographic characteristics of the consumer purchasing with these patterns. Results identified seven dietary purchase patterns that we named: Fruity; Meat alternatives; Carnivores; Hydrators; Afternoon tea; Beer and wine lovers; and Sweet tooth. On average the daily energy intake of loyalty card holders -who may buy as an individual or for a household- is less than the adult reference intake, but this varies according to dietary purchase pattern. In general loyalty card holders meet the recommended salt intake, do not purchase enough carbohydrates, and purchase too much fat and protein, but not enough fibre. The dietary purchase pattern containing the highest amount of fibre (as an indicator of healthiness) is bought by the least deprived customers and the pattern with lowest fibre by the most deprived. In conclusion, supermarket sales data offer significant potential for understanding population dietary patterns.

Assessing nutritional value of ready-to-eat breakfast cereals in the province of Quebec (Canada): a study from the Food Quality Observatory

OBJECTIVE

The Food Quality Observatory was created in the province of Quebec (Canada) in 2016. In this study, the Observatory aimed to generate a methodology to (1) test the use of sales data combined with nutrient values to characterise the nutritional composition of ready-to-eat (RTE) breakfast cereals offered and purchased in the province of Quebec (Canada) and (2) verify the extent to which a front-of-pack label based on the percentage of daily value (DV) for total sugar, as a strategy to improve the food supply, would be distributed in this food category.

DESIGN

Nutritional information were obtained by purchasing each RTE breakfast cereal available in the Greater Montreal area. Cereals were then classified according to their processing type.

SETTING

The nutritional values of 331 RTE breakfast cereals available in Quebec were merged with sales data covering the period between May 2016 and May 2017. A total of 306 products were successfully cross-referenced.

RESULTS

Granola and sweetened cereals were the most available (36·6 % and 19·6 %, respectively) and purchased (19·8 % and 40·9 % of sales, respectively). When compared with other types of cereals, granola cereals had a higher energy, fat, saturated fat, protein content and a lower Na content. A larger proportion of chocolate (65 %) and sweetened cereals (49 %) were above 15 % of the DV for sugar.

CONCLUSIONS

This study showed that the methodology developed generates important data to monitor nutritional quality of the food supply and ultimately contribute to improve the nutritional quality of processed foods.

Healthiness of foods and non-alcoholic beverages according to store type: A population-based study of household food and drink purchases in New Zealand

Background

Obesity and diet-related noncommunicable diseases (NCDs) account for the largest proportion of disease burden worldwide, and an unhealthy food environment is a key driver. Food retailers play an important role in food environments through the availability and purchases of healthy food products at various stores.

Objectives

To assess whether the healthiness of food and non-alcoholic drink product purchases vary according to retail store type.

Methods

We undertook a cross-sectional analysis of Nielsen New Zealand Homescan® panel data, which is a nationally representative sample of 2500 households in terms of certain key household demographic and socioeconomic characteristics. Panel members were asked to record all food and beverage products that were purchased and brought back to the home between October 2018 and October 2019. Household food and non-alcoholic drink purchases were linked with two food composition databases (Nutritrack, a New Zealand packaged food composition database, and the FOODfiles New Zealand Food Composition Database) to extract data on the nutrient profile of products purchased. We developed a store classification tool, and classified stores as supermarkets, grocery stores, convenience stores, fruit and vegetable stores, meat and fish stores, or bakeries. We estimated the Health Star Rating (HSR) for all products and defined a product with HSR ≥ 3.5 as ‘healthy’. We computed estimated mean HSR and conducted multivariate regression analyses.

Results

In total, 3,940,458 product purchases were included in the analyses, consisting of 20,491 unique products purchased at different stores over the one-year period by 1800 panellist households. Supermarket products made up the majority of household food and drink purchases (3,545,141 of 3,940,458; 90%). Overall, the estimated mean HSR was 3.5 stars. In comparison to the reference group of supermarkets, the odds ratio for healthy products purchased at fruit and vegetable stores was 4.62, at grocery stores it was 2.36, and at meat and fish stores it was 1.99. In contrast, the odds ratios from convenience stores and bakeries were 0.58 and 0.03. Except for convenience stores, these differences were statistically significant (p < 0.05).

Discussion

We found significant differences in household purchases of healthy food and beverages according to food retail store type, with healthier food much more likely to be purchased from fruit and vegetable stores, meat and fish stores and grocery stores, and much less likely to be purchased from bakeries and convenience stores as compared with supermarkets.

Conclusion

Policies to improve healthy food retailing should consider all retail store types and focus particularly on increasing the availability of healthy food options at convenience stores and bakeries. Given that supermarkets are the source of most household food purchases (both healthy and unhealthy), strategies are also warranted to increase the relative availability and purchases of healthy foods from supermarkets.

Protein-Based Films and Coatings for Food Industry Applications

Food packaging is an area of interest not just for food producers or food marketing, but also for consumers who are more and more aware about the fact that food packaging has a great impact on food product quality and on the environment. The most used materials for the packaging of food are plastic, glass, metal, and paper. Still, over time edible films have become widely used for a variety of different products and different food categories such as meat products, vegetables, or dairy products. For example, proteins are excellent materials used for obtaining edible or non-edible coatings and films. The scope of this review is to overview the literature on protein utilization in food packages and edible packages, their functionalization, antioxidant, antimicrobial and antifungal activities, and economic perspectives. Different vegetable (corn, soy, mung bean, pea, grass pea, wild and Pasankalla quinoa, bitter vetch) and animal (whey, casein, keratin, collagen, gelatin, surimi, egg white) protein sources are discussed. Mechanical properties, thickness, moisture content, water vapor permeability, sensorial properties, and suitability for the environment also have a significant impact on protein-based packages utilization.

Perspective: Big Data and Machine Learning Could Help Advance Nutritional Epidemiology

The field of nutritional epidemiology faces challenges posed by measurement error, diet as a complex exposure, and residual confounding. The objective of this perspective article is to highlight how developments in big data and machine learning can help address these challenges. New methods of collecting 24-h dietary recalls and recording diet could enable larger samples and more repeated measures to increase statistical power and measurement precision. In addition, use of machine learning to automatically classify pictures of food could become a useful complimentary method to help improve precision and validity of dietary measurements. Diet is complex due to thousands of different foods that are consumed in varying proportions, fluctuating quantities over time, and differing combinations. Current dietary pattern methods may not integrate sufficient dietary variation, and most traditional modeling approaches have limited incorporation of interactions and nonlinearity. Machine learning could help better model diet as a complex exposure with nonadditive and nonlinear associations. Last, novel big data sources could help avoid unmeasured confounding by offering more covariates, including both omics and features derived from unstructured data with machine learning methods. These opportunities notwithstanding, application of big data and machine learning must be approached cautiously to ensure quality of dietary measurements, avoid overfitting, and confirm accurate interpretations. Greater use of machine learning and big data would also require substantial investments in training, collaborations, and computing infrastructure. Overall, we propose that judicious application of big data and machine learning in nutrition science could offer new means of dietary measurement, more tools to model the complexity of diet and its relations with diseases, and additional potential ways of addressing confounding.

Contributions of Food Environments to Dietary Quality and Cardiovascular Disease Risk

PURPOSE OF REVIEW

To evaluate the multidimensional influence of food environments on food choice, dietary quality, and diet-related health and identify critical gaps necessary to develop effective population interventions that influence food choice.

RECENT FINDINGS

Multicomponent interventions that interact with multiple layers of the food environment show limited but consistent effects on dietary behaviors and may have wider and substantive population-level reach with greater incorporation of validated, holistic measurement tools. Opportunities to use smartphone technology to measure multiple components of the food environment will facilitate future interventions, particularly as food environments expand into online settings and interact with consumers in novel ways to shape food choice. While studies suggest that all dimensions of the food environment influence diet and health outcomes, robust and consistent measurements of food environments that integrate objective and subjective components are essential for developing stronger evidence needed to shift public policies.

A Systematic Review of Economic Evaluations of Health-Promoting Food Retail-Based Interventions

BACKGROUND

While the number of retail interventions with impacts on diet- and/or health-related outcomes is increasing, the economic evaluation literature is limited. This review investigated (i) the cost-effectiveness of health-promoting food retail interventions and (ii) key assumptions adopted in these evaluations.

METHODS

A systematic review of published academic studies was undertaken (CRD42020153763). Fourteen databases were searched. Eligible studies were identified, analysed, and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.

RESULTS

Eight studies that evaluated 30 retail interventions were included in the review. Common outcomes reported were cost per healthy food item purchased/served or cost per disability-adjusted life year (DALY) averted. Four studies undertook cost-utility analyses and half of these studies concluded that retail interventions were cost-effective in improving health outcomes. Most studies did not state any assumptions regarding compensatory behaviour (i.e., purchases/consumption of non-intervention foods or food purchases/consumption from non-intervention settings) and presumed that sales data were indicative of consumption.

CONCLUSION

The cost-effectiveness of retail-based health-promoting interventions is inconclusive. Future health-promoting retail interventions should regularly include an economic evaluation which addresses key assumptions related to compensatory behaviour and the use of sales data as a proxy for consumption.

Setting the standard for healthy eating: Continuous quality improvement for health promotion at Nova Scotia Health

Healthcare organizations engage in continuous quality improvement to improve performance and value-for-performance, but the pathway to change is often rooted in challenging the way things are "normally" done. In an effort to propel system-wide change to support healthy eating, Nova Scotia Health developed and implemented a healthy eating policy as a benchmark to create a food environment supportive of health. This article describes the healthy eating policy and its role as a benchmark in the quality improvement process. The policy, rooted in health promotion, sets a standard for healthy eating and applies to stakeholders both inside and outside of health. We explain how the policy offers nutrition but also cultural benchmarks around healthy eating, bringing practitioners throughout Nova Scotia Health together and sustaining collaborative efforts to improve upon the status quo.

Price impact of taxes on sugary drinks in Brazil

Sugary drink consumption is an important contributor to the current global epidemic of obesity. In recent years, 50 countries or jurisdictions have implemented taxes on sugary drinks as an instrument to discourage consumption. Against the tide, Brazil reduced taxes on these beverages in 2017 and 2018. However, a recent debate - raised by the federal government - has started over taxation of sugary and alcoholic beverages (sin taxes). The effectiveness of this policy will depend on how the taxes are transferred to prices. In this sense, this paper we aim to quantify the impacts of the tax reduction on prices of sugary drinks in Brazil, and therefore to contribute to the debate by calculating the pass-through of taxes to prices of these products in the Brazilian context. We analyze the Brazilian market using a panel data of products, by brand, collected by Euromonitor from 2013 to 2018. Our results suggest that the transfer of taxes to prices depends on the firm size and the type of product, with pass-through rates ranging from 15% to 124%.

Diet Quality and Food Prices Modify Associations between Genetic Susceptibility to Obesity and Adiposity Outcomes

The role of the retail food environment in obesity risk is unclear, which may be due in part to the lack of consideration of individual differences in the responsivity to food cues. This cross-sectional investigation geo-temporally linked the CARTaGENE biobank (including genetic, dietary, lifestyle, and anthropometric data) with in-store retail food environment data to examine interactions between a polygenic risk score (PRS) for obesity and (1) diet quality (n = 6807) and (2) in-store retail food measures (n = 3718). The outcomes included adiposity-related measures and diet quality assessed using the 2010 Canadian-adapted Healthy Eating Index. A vegetable:soft drink ratio was constructed for each retail measure to assess the relative healthfulness of exposures. Generalized linear models adjusted for individual and neighborhood socio-demographic factors were used to evaluate main and interactive effects. Diet quality significantly modified the association between polygenic risk of obesity and body mass index, waist circumference, and body fat percent. A significant interaction was also observed between PRS and frequency of price discount of vegetables in relation to soft drinks on waist circumference. These results replicate previous reports of diet moderating polygenic risk of obesity and suggest that prices of low vs. high-energy density foods are an intervention target to address population obesity rates.

Understanding the Intersection of Race/Ethnicity, Socioeconomic Status, and Geographic Location: A Scoping Review of U.S. Consumer Food Purchasing

Disparities in diet quality persist in the U.S. Examining consumer food purchasing can provide unique insight into the nutritional inequities documented by race/ethnicity, socioeconomic status (SES), and geographic location (i.e., urban vs. rural). There remains limited understanding of how these three factors intersect to influence consumer food purchasing. This study aimed to summarize peer-reviewed scientific studies that provided an intersectional perspective on U.S. consumer food purchasing. Thirty-four studies were examined that presented objectively measured data on purchasing outcomes of interest (e.g., fruits, vegetables, salty snacks, sugar-sweetened beverages, Healthy Eating Index, etc.). All studies were of acceptable or high quality. Only six studies (17.6%) assessed consumer food purchases at the intersection of race/ethnicity, SES, or geographic location. Other studies evaluated racial/ethnic or SES differences in food purchasing or described the food and/or beverage purchases of a targeted population (example: low-income non-Hispanic Black households). No study assessed geographic differences in food or beverage purchases or examined purchases at the intersection of all three factors. Overall, this scoping review highlights the scarcity of literature on the role of intersectionality in consumer food and beverage purchasing and provides recommendations for future studies to grow this important area of research.

Grocery purchase data in the study of alcohol use - A validity study

BACKGROUND

Alcohol use epidemiology is facing challenges as survey response rates decline. In addition, population surveys fail to capture a large proportion of alcohol consumed and are expensive to conduct. This study aims to aid in complementing traditional epidemiological methods by validate grocery purchase data in the research on population alcohol use.

METHODS

The LoCard study subjects were loyalty card holders of a grocery retail co-operative, which possessed more than 45 % market share in Finland. One third of those who consented to the analyses of their grocery purchases were presented a questionnaire including a Food Frequency Questionnaire on the web; N = 11,818 responded. The relationship between beer purchase frequency and self-reported beer drinking frequency was studied for association and agreement in different subgroups using crosstabulations and Poisson regression modeling.

RESULTS

The association between beer purchase frequency and self-reported beer drinking frequency was good (Gamma = .556). The agreement between beer purchase frequency and drinking frequency was only fair (Kappa = .189). Limiting the data to those single adult households that reported making at least 61 % of their grocery purchases from this grocery retailer and collapsing the frequency categories to three instead of six increased the agreement to good (Kappa = .463).

CONCLUSIONS

Information on beer purchase frequency from the loyalty card database can be used to rank people according to their drinking frequency and to estimate beer drinking frequency with fair to good accuracy, depending on what share of grocery purchases they make from the grocery retailer in question.

The effect of a shelf placement intervention on sales of healthier and less healthy breakfast cereals in supermarkets: A co-designed pilot study

Supermarkets are the principal source of grocery food in many high-income countries. Choice architecture strategies show promise to improve the healthiness of food choices. A retailer-academic collaboration was formed to co-design and pilot selected commercially sustainable strategies to increase sales of healthier foods relative to less healthy foods in supermarkets. Two co-design workshops, involving supermarket corporate staff and public health nutrition academics, identified potential interventions. One intervention, more prominent shelf placement of healthier products within one category (breakfast cereals), was selected for testing. A pilot study (baseline, intervention and follow-up, 12-weeks each) was undertaken in six supermarkets (three intervention and three control) in Auckland, New Zealand. Products were ranked by nutrient levels and profile, and after accounting for the supermarkets' space management principles, healthier products were placed at adult eye level. The primary outcome was change in sales of healthier products relative to total category sales. Secondary outcomes were nutrient profile of category sales, in-store product promotions, customer perceptions, and retailer feedback. There was no difference in proportional sales of more prominently positioned healthier products between intervention (56%) and control (56%) stores during the intervention. There were no differences in the nutrient profile of category sales. A higher proportion of less healthy breakfast cereals were displayed in intervention versus control stores (57% vs 43%). Most customers surveyed supported shelf placement as a strategy (265, 88%) but noted brand preferences and price were more salient determinants of purchases. Retailers were similarly supportive but balancing profit, health/nutrition and customer satisfaction was challenging. Shelf placement alone was not an effective strategy to increase purchases of healthier breakfast cereals. This study showed co-design of a healthy eating intervention with a commercial retailer is feasible, but concurrent retail environment factors likely limited the public health impact of the intervention.

Energy-dense, nutrient-poor food and beverage sales in Australia: where and when products are sold, and how sales are changing over time

OBJECTIVE

To quantify sales trends for key energy-dense, nutrient-poor (EDNP) foods and beverages over 5 years in Australia.

DESIGN

The Euromonitor Global Market Information Database and linear regression models were used to estimate average annual change in sales per capita of thirteen EDNP food categories and two EDNP beverage categories (defined using Australian Dietary Guidelines) over 5 years (2012-2017 for foods and 2011-2016 for beverages). The average annual change in sales was divided by the observed sales in 2012 (foods) or 2011 (beverages) to estimate the average percentage-change in sales per capita per annum.

SETTING

All major retail outlets in Australia.

PARTICIPANTS

Euromonitor Global Market Information Database sales data.

RESULTS

Between 2012 and 2017, sales per capita per annum of frozen pizza (6 %), pastries (5 %), potato chips (crisps) (5 %), tortilla chips (3 %), chocolate confectionery (2 %), frozen processed potatoes (2 %), ice cream (2 %) and sugar confectionery (0·2 %) increased. There were no changes in sales of sweet biscuits, chocolate spreads and cakes, and sales of savoury biscuits and processed meat decreased (-2 and -1 %, respectively). Between 2011 and 2016, sales per capita per annum of sports and energy drinks increased (4 %), sales of regular (sugar-sweetened) cola (-6 %) and all non-cola soft drinks (-1 %) decreased and sales of diet cola did not change.

CONCLUSIONS

Sales of EDNP foods and beverages generally increased or remained stable relative to population growth. Our results demonstrate the need for public health policies to reduce sales of EDNP foods and beverages.

A critical review of diet-related surveys in England, 1970-2018

Background

Many diet-related surveys have been conducted in England over the past four to five decades. Yet, diet-related ill-health is estimated to cost the NHS £5.8 billion annually. There has been no recent assessment of the diet-related surveys currently available in England. This paper aims to fill this gap in the literature by providing researchers, especially those interested in conducting secondary (quantitative) research on diet, with a detailed overview of the major repeated cross-sectional and longitudinal surveys conducted in England over the last 48 years (1970–2018).

Method

A three-stage review process was used to identify and assess surveys and synthesise the information necessary for achieving the paper’s aim. Surveys were identified using the UK Data Service, Cohort and Longitudinal Studies Enhancement Resources (CLOSER), the Medical Research Council (MRC) Cohort Directory and the Consumer Data Research Centre (CDRC) online data repositories/directories. Surveys were summarised to include a brief background, the survey design and methodology used, variables captured, the target population, level of geography covered, the type of dietary assessment method(s) used, primary data users, data accessibility, availability and costs, as well as key survey features and considerations.

Results

The key considerations identified across the various surveys following the review include: the overall survey design and the different dietary assessment method(s) used in each survey; methodological changes and general inconsistencies in the type and quantity of diet-related questions posed across and within surveys over time; and differences in the level of geography and target groups captured.

Conclusion

It is highly unlikely that any survey dataset will meet all the needs of researchers. Nevertheless, researchers are encouraged to make good use of the secondary data currently available, in order to conduct the research necessary for the creation of more evidence-based diet-related policies and interventions in England. The review process used in this paper is one that can be easily replicated and one which future studies can use to update and expand upon to assist researchers in identifying the survey(s) most aligned to their research questions.