Food Processing and Public Health Impacts

Food processing has evolved from simple preservation and culinary techniques to sophisticated industrial systems that transform raw agricultural produce into a vast array of products. This continuum—from minimal treatments that enhance safety and nutrient bioavailability to intensive operations that introduce refined ingredients and multiple additives—profoundly affects nutritional quality, safety, shelf life and consumer accessibility. While processing can reduce foodborne illness, extend supply chain stability and improve global food security, it often increases energy density, diminishes micronutrient content and alters the native food matrix. These shifts have been implicated in the rising prevalence of obesity, metabolic disorders and other non-communicable diseases worldwide. Balancing these outcomes requires optimising processing methods, limiting potentially harmful additives and equipping consumers with clear information. Emerging digital tools and classification frameworks are enabling detailed characterisation of processing levels and driving policy actions, front-of-pack labelling and reformulation strategies. A nuanced appreciation of the spectrum from whole foods to ultra-processed products is essential for designing evidence-based dietary guidelines, regulatory measures and public health interventions that support nutrition, sustainability and equity.

Research from Nature Portfolio

Recent studies have employed machine learning algorithms to quantify the degree of processing across national food supplies, accurately classifying thousands of products according to their industrial treatments. These analyses reveal that ultra-processed items represent the majority of many commercial offerings and are associated with higher incidence of metabolic syndrome markers, cardiovascular risk factors and reduced vitamin bioavailability. Concurrently, large-scale assessments of market databases have mapped the distribution and co-occurrence of over 300 authorised food additives, identifying distinct clusters of chemical agents prevalent in specific product categories. This foundational work paves the way for epidemiological investigations into additive combinations and their long-term impacts on chronic disease risk.

Food Processing and Public Health Impacts publication trend

The graph below shows the total number of articles in food processing and public health impacts across all publications each year (not limited to Nature Index journals).

Technical terms

Ultra-processed foods: Products undergoing multiple industrial processes and containing refined ingredients, additives and little of the original food’s structure.

Machine learning algorithm: A computational model that learns from data patterns to make classifications or predictions, here used to assess processing levels.

Food additive: A substance added during manufacturing to preserve, flavour, colour or alter the texture of food products.

NOVA classification: A framework categorising foods into unprocessed, minimally processed, processed and ultra-processed groups based on processing degree and purpose.

References

1. Food Processing at a Crossroad. Frontiers in Nutrition (2019).
2. Characterizing Ultra-Processed Foods by Energy Density, Nutrient Density, and Cost. Frontiers in Nutrition (2019).
3. A new classification of foods based on the extent and purpose of their processing. Cadernos de Saúde Pública (2010).
4. Machine learning prediction of the degree of food processing. Nature Communications (2023).
5. Food additives: distribution and co-occurrence in 126,000 food products of the French market. Scientific Reports (2020).
6. Robustness of Food Processing Classification Systems. Nutrients (2019).
7. Processed food classification: Conceptualisation and challenges. Trends in Food Science & Technology (2021).
8. Ultraprocessed Foods and Obesity Risk: A Critical Review of Reported Mechanisms. Advances in Nutrition (2023).