Food environments are defined as ‘the collective physical, economic, policy and sociocultural surroundings, opportunities and conditions that influence people’s food and beverage choices and nutritional status’(Reference Swinburn, Sacks and Vandevijvere1). Currently, these environments are characterised by easily available unhealthy food products(Reference Swinburn and Egger2–Reference Baker, Machado and Santos4) with ultra-processed foods contributing to 10 % up to 51 % of the purchased dietary energy across Europe(Reference Monteiro, Moubarac and Levy5). Ultra-processed foods are products such as soft drinks and confectionery that contain substances that are not commonly found at home(Reference Monteiro, Cannon and Levy6). A growing body of literature shows an association between overweight and the consumption of such ultra-processed foods(Reference Baker, Machado and Santos4,Reference Monteiro, Moubarac and Levy5,Reference Hall, Ayuketah and Brychta7,Reference Vandevijvere, Jaacks and Monteiro8) . Nonetheless, ultra-processed foods are extensively promoted, with markets expanding and several political strategies being used to protect ultra-processed food markets(Reference Moodie, Bennett and Kwong9,Reference Popkin and Ng10) .
Market structure describes the degree at which competition takes place between different companies for specific goods and services within (product) markets(Reference Wood, Williams and Baker11,Reference Pavic, Galetic and Piplica12) . A key metric to assess the market structure and power of companies is market concentration(Reference Chris13). When concentration increases, this translates into an increasing part of the market being held by a decreasing number of companies(Reference Baker, Machado and Santos4,Reference Van Dam, Wood and Sacks14) . Other market structure indicators, measuring the market diversity, are the number of companies with ≥1 % market share (MS) and the number of unique companies having presence in only one European country(Reference Van Dam, Wood and Sacks14).
Across countries in Europe, packaged food and non-alcoholic beverage product markets have shown to be moderately to highly concentrated with a low number of unique companies and companies with ≥1 % MS(Reference Van Dam, Wood and Sacks14). While the food industry publicly positions itself as part of the solution to create healthier food environments(Reference Gomes and Lobstein15,Reference Clapp and Scrinis16) , they at the same time shape markets in ways that fit their private interests(Reference Wood, Williams and Baker11). High levels of market concentration and reduced diversity may provide dominant companies with the opportunity to shape markets in ways that benefit them financially and economically (e.g. through the increased sales of ultra-processed foods), something that does not benefit population health(Reference Wood, Williams and Nagarajan3,Reference Baker, Machado and Santos4,Reference Wood, Williams and Baker11,Reference Pavic, Galetic and Piplica12,Reference Corfe and Gicheva17–19) . Examples of how the food industry may influence food environments include the framing of policy debates, intensive marketing, nutritional positioning (i.e. focus on single nutrients instead of whole foods, an approach that could promote the sales of heavily processed foods), focus on individual responsibility and unenforceable self-regulatory codes(Reference Baker, Machado and Santos4,Reference Gomes and Lobstein15,Reference Clapp and Scrinis16) . Nonetheless, research assessing the influence of market structure on food environments remains limited.
This study sets out to assess whether market structure, assessed by levels of market concentration and diversity within the packaged food and non-alcoholic beverage industry across European countries, is associated with the healthiness of products sold, measured by the proportion of sales of ultra-processed food products according to the NOVA classification.
Methods
The Euromonitor International Passport database was used to obtain MS data per European single market member state, per packaged food and drink product category and per year(20). Data were obtained at the most fine-grained Euromonitor product categorisation level over the period 2009–2018. For Cyprus, Iceland, Liechtenstein, Luxembourg and Malta, no Euromonitor data were available. A total of twenty-seven European countries were included in the analysis.
Market concentration
Levels of market concentration and its changes over time (2009–2018) were assessed by calculating the four firm concentration ratio (CR4) per country for fourteen packaged food product markets and eight non-alcoholic beverage product markets (Table 1; Annex 1). The CR4 is calculated by combining the MS of the top four firms per country active within a product market. The higher the CR4, the more concentrated the product market. CR4 values below 40 are considered to represent a competitive market. Values above 40 are considered to represent markets with limited competition and above 60 limited competition with potential dominant firms(Reference Naldi and Flamini21).
Table 1 The proportion of sales from ultra-processed products (NOVA) and levels of market concentration according to the four firm concentration ratio (CR4) per country and product category. Euromonitor data 2018
Red indicates CR4 values >60 % and proportion of sales >80 %.
Yellow indicates CR4 values >40 %.
The number of companies with ≥1 % MS and the number of unique companies per country were assessed to estimate levels of diversity within packaged food and non-alcoholic beverage product markets. Unique companies were defined as companies having presence in only one European single market member state. Similar to previous research, the higher the number of companies with ≥1 % MS and unique companies, the more diverse the industry was assumed to be(Reference Van Dam, Wood and Sacks14).
Products sold
To assess the proportion of sales coming from ultra-processed products, the NOVA classification(Reference Monteiro, Cannon and Levy6) was applied to the most fine-grained Euromonitor product subcategory sales data within abovementioned packaged food and non-alcoholic beverage product categories. An overview of how the Euromonitor product subcategories were classified according to the NOVA classification can be found in Annex 1. For five countries (Croatia, Estonia, Latvia, Lithuania and Slovenia), data were only available for the most fine-grained product subcategories within eight (out of the twenty-two) Euromonitor product categories (‘Baked Goods’, ‘Concentrates’, ‘Dairy’, ‘Energy Drinks’; ‘Ice Cream and Frozen Desserts’, ‘RTD Coffee’, ‘Rice, Pasta and Noodles’ and ‘Sports Drinks’).
The NOVA classification makes a distinction between products based on the level of processing, namely non-ultra-processed (unprocessed/minimally processed foods, processed culinary ingredients and processed foods) and ultra-processed products(Reference Monteiro, Cannon and Levy6). Per Euromonitor product category, the proportion of sales coming from ultra-processed subcategories was calculated by expressing the ultra-processed sales per country and product category on the total sales within the same country and product category. Finally, also the change over the past 10 years (2009–2018) of the proportion of sales coming from ultra-processed products was assessed.
The relationship between market concentration, diversity and healthiness of packaged food and drink products sold across European countries
Analyses were conducted separately for packaged food and non-alcoholic beverage product categories. A multiple linear regression was calculated across selected countries and product categories to assess whether and to what extent market concentration measured by the CR4 influences the proportion of sales of ultra-processed products. The product categories containing 100 % ultra-processed products were removed from the analysis. Among packaged food products these were ‘Confectionary’, ‘Ice Cream and Frozen Desserts’ and ‘Soup’. Among the non-alcoholic beverages, all product categories were 100 % ultra-processed apart from ‘Juice’. Consequently, there was not enough variability in the model and no multiple linear regression was calculated for non-alcoholic beverages. The final multiple regression model for packaged foods included the CR4, a country fixed effect and a category fixed effect as predictor variables (Table 2). The product category ‘Rice, Pasta and Noodles’ was used as reference category as, on average, this was the least processed product category.
Table 2 Results of the two multiple linear regressions and the predictor variables included
No significant correlations were detected between changes over the past 10 years in levels of market concentration and the proportion of sales of ultra-processed products (data not shown).
Simple linear regression analyses were performed to determine whether the number of companies per country with ≥1 % MS and the number of unique companies within packaged food and non-alcoholic beverage product markets significantly predicted the proportion of sales from ultra-processed products at country level in 2018.
Correlations of changes over time in the proportion of sales from ultra-processed products with changes in levels of market concentration were assessed. R-values >0·5 were considered to represent a strong correlation. P-values <0·05 were considered statistically significant.
All analyses were performed using Microsoft Excel and SAS 9.4 (2018).
Results
The product categories ‘Asian Speciality Drinks’, ‘Carbonates’, ‘Concentrates’, ‘Confectionary’, ‘Energy Drinks’, ‘Ice Cream and Frozen Desserts’, ‘RTD Coffee’, ‘RTD Tea’, ‘Soup’ and ‘Sports Drinks’ were for 100 % ultra-processed across all European countries. Within the remaining twelve product categories, the proportion of ultra-processed sales varied per country. The level of market concentration, as measured by the CR4, varied per product category and country (Table 1). Several companies were included in the CR4 in multiple countries and across multiple product categories. Detailed information on the companies included in the CR4 of more than one product category as well as the number of countries in which the company was within the CR4 of this product category can be found in Annex 3.
Market concentration and sales of less healthy products
A multiple linear regression model including the CR4, a country fixed effect and a product category fixed effect (Table 2) was significant and explained 93 % of the variance in sales of ultra-processed packaged foods (F(37 219) = 78·13, P < 0·0001).
The CR4 (P = 0·046), the country (P = 0·004) and the product category (P < 0·0001) were all significant predictors of sales of ultra-processed packaged food products. It was estimated that the proportion of sales of ultra-processed packaged food products increased with 0·13 for a one unit increase of the CR4, in addition to the increase caused by product category or the decrease caused by country, relative to the product category ‘Rice, Pasta and Noodles’ and the United Kingdom as reference country (Table 2, Annex 2). The fixed effect estimates, together with the P-values and 95 % CI, per product category and per country can be found in Annex 2.
Market diversity and sales of less healthy products
The number of companies with ≥1 % MS and the number of unique companies per country both significantly predicted sales of ultra-processed packaged food products (β = -2·73, P = 0·004 and β = -3·06, P = 0·003, respectively). This was not the case for non-alcoholic beverages. Concretely, when per country the number of packaged food companies with ≥1 % MS and the number of unique packaged food companies increased, the sales of ultra-processed foods significantly decreased. Results are visually represented in Fig. 1.
Fig. 1 Regression of sales ultra-processed packaged food products (NOVA) with the number of companies with ≥1 % market share (MS) (blue) and the number of unique companies (orange). Countries are indicated to the right of the blue dots (the number of companies with ≥1 % MS) and to the left of the orange dots (the number of unique companies. NA means no sales of that category in that country in 2018 according to the Euromonitor data. Empty cells are countries for which no data were available at the most detailed level of the Euromonitor product categorisation system and as such products could not be classified. 
, Companies with ≥ 1% market share; 
, unique companies
Discussion
This study set out to assess if market concentration, as measured by the CR4, and market diversity, assessed by the number of companies with ≥1 % MS and the number of unique companies per country, can predict the proportion of sales from ultra-processed products. A multiple linear regression model with the CR4, the country and the product category as predictor variables found that all three predictor variables significantly predicted the proportion of sales attributed to ultra-processed packaged food products. Increased market diversity in turn showed to significantly reduce sales of ultra-processed packaged food products but not non-alcoholic beverages. These results imply that increased market concentration, as measured by the CR4, may favour the increase in sales of ultra-processed packaged food products when taking into account both the product category and country. In contrast, increased market diversity in turn might be able to reduce sales of ultra-processed packaged food products.
Similar to our findings, a study in Asia found that market forces, including market concentration, were significant but variable drivers of the increase in sales of ultra-processed products. This study also observed that concentration was highest in ultra-processed product markets such as soft drinks, biscuits and snack foods(Reference Baker and Friel22). This matches our finding that the product category had a strong effect in predicting sales of ultra-processed packaged food products.
A potential explanation for the decreased sales of ultra-processed products when more companies with ≥1 % MS and unique companies are present on the market could be that smaller companies lack both the financial and political resources to shape food environments and undermine public health(Reference Wood, Williams and Nagarajan3,Reference Baron23) . Nonetheless, the sales of ultra-processed products is expanding worldwide, according to a study at global level using Euromonitor data(Reference Baker, Machado and Santos4). To increase the healthiness of food environments, the food industry would need to reduce marketing and sales of ultra-processed products. This however inherently opposes the aim to maximise profits, especially for companies that rely on the sales of ultra-processed foods(Reference Moodie, Stuckler and Monteiro24,Reference Mialon, Swinburn and Sacks25) . This conflict of interest may result in the food industry resorting to political activities to protect their markets and profitability(Reference Baker, Machado and Santos4,Reference Moodie, Bennett and Kwong9,Reference Moodie, Stuckler and Monteiro24) , something that becomes more attainable for dominant companies in highly concentrated markets with low market diversity(Reference Moodie, Bennett and Kwong9).
This study documents the possible impact of market structure on the healthiness of packaged foods and non-alcoholic beverages while highlighting the importance of looking beyond food policy to improve the healthiness of food environments. Nevertheless, this study has several limitations. Levels of market concentration may be an underestimation. The Euromonitor database focuses on brand ownership rather than companies. Consequently, companies that are considered independent in Euromonitor (and for the calculation of market concentration) may still sell brands from other companies through licensing agreements. Due to the lack of nutritional data at European level, there was insufficient variability to formulate conclusions for non-alcoholic beverages. Towards the future, more research is required using country-level data and detailed nutritional information to strengthen our understanding of the nutritional implications of market structures across Europe.
In conclusion, our results suggest that increased market concentration and reduced market diversity may predict increased sales of ultra-processed packaged food products across Europe. It is therefore recommended to take into account the market structure, in addition to policy effectiveness, when developing policies to improve food environments.
Acknowledgements
Acknowledgements: None. Financial support: This study and the authors received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 774548. The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Authorship: S.V. and I.V.D. designed the study, I.V.D. collected and analysed the data and wrote the article. All authors contributed to the interpretation of the data and critically reviewed draft versions of the article. All authors approved the final version of the article for submission. Ethics of human subject participation: Not applicable.
Conflicts of interest:
The authors declare that they have no competing interests.
Supplementary material
For supplementary material accompanying this paper visit https://doi.org/10.1017/S1368980022001926
Open access
