Pulse Brain · Growing Health Evidence Index
Tier 1 — Meta-analysis / systematic reviewPeer-reviewed

Global, regional, and national consumption of animal-source foods between 1990 and 2018: findings from the Global Dietary Database

Victoria Miller, Julia Reedy, Frederick Cudhea, Jianyi Zhang, Peilin Shi, Josh Erndt-Marino, Jennifer Coates, Renata Micha, Patrick Webb, Dariush Mozaffarian, Pamela Abbott, Morteza Abdollahi, Parvin Abedi, Suhad Abumweis, Linda Adair, Mohannad Al Nsour, Nasser Al-Daghri, Nawal Al-Hamad, Suad Al-Hooti, Sameer Al-Zenki, Iftikhar Alam, Jemal H Ali, Eman Alissa, Simon Anderson, Karim Anzid, Carukshi Arambepola, Mustafa Arici, Joanne Arsenault, Renzo Asciak, Helene E Barbieri, Noël Barengo, Simon Barquera, Murat Bas, Wulf Becker, Sigrid Beer-Borst, Per Bergman, Lajos Biró, Sesikeran Boindala, Pascal Bovet, Debbie Bradshaw, Noriklil BI Bukhary, Kanitta Bundhamcharoen, Mauricio Caballero, Neville Calleja, Xia Cao, Mario Capanzana, Jan Carmikle, Katia Castetbon, Michelle Castro, Corazon Cerdena, Hsing-Yi Chang, Karen Charlton, Yu Chen, Mei F Chen, Shashi Chiplonkar, Yoonsu Cho, Khun-Aik Chuah, Simona Costanzo, Melanie Cowan, Albertino Damasceno, Saeed Dastgiri, Stefaan De Henauw, Karin DeRidder, Eric Ding, Rivera Dommarco, Rokiah Don, Charmaine Duante, Vesselka Duleva, Samuel Duran Aguero, Veena Ekbote, Jalila El Ati, Asmaa El Hamdouchi, Tatyana El-kour, Alison Eldridge, Ibrahim Elmadfa, Alireza Esteghamati, Zohreh Etemad, Fariza Fadzil, Farshad Farzadfar, Anne Fernandez, Dulitha Fernando, Regina Fisberg, Simon Forsyth, Edna Gamboa-Delgado, Didier Garriguet, Jean-Michel Gaspoz, Dorothy Gauci, Marianne Geleijnse, Brahmam Ginnela, Giuseppe Grosso, Idris Guessous, Martin Gulliford, Ingibjorg Gunnarsdottir, Wilbur Hadden, Aida Hadziomeragic, Christian Haerpfer, Rubina Hakeem, Aminul Haque, Maryam Hashemian, Rajkumar Hemalatha

The Lancet Planetary Health · 2022

Read source ↗ All evidence

Summary

This comprehensive meta-analysis synthesised 499 dietary surveys from 134 countries to quantify global consumption of animal-source foods between 1990 and 2018. Using Bayesian hierarchical modelling to standardise intake estimates across diverse survey methods, the study found substantial regional heterogeneity in consumption patterns, with global mean intakes ranging from 8 g/day for cheese to 88 g/day for milk, and fewer than 1% of the global population consuming ≥1 serving per day of processed meat, cheese, eggs, milk, seafood or yoghurt. The findings provide evidence to inform dietary intervention, surveillance, and policy priorities at global and national scales.

Regional applicability

The UK, as one of 134 countries included in this meta-analysis, contributed data to these global estimates. However, the abstract does not provide UK-specific findings; application would require accessing country-level results to assess how UK consumption patterns compare to global means and regional peers, and to inform national dietary guidance and public health nutrition policy.

Key measures

Mean global daily intake (grams per person per day) with 95% uncertainty intervals for: unprocessed red meat (51 g/day), processed meat (17 g/day), seafood (28 g/day), eggs (21 g/day), milk (88 g/day), cheese (8 g/day), and yoghurt (20 g/day); proportion of global population consuming ≥1 serving per day by food category; regional and national variation in intakes

Outcomes reported

The study quantified global, regional, and national consumption levels of seven animal-source food categories (unprocessed red meat, processed meat, eggs, seafood, milk, cheese, and yoghurt) across 134 countries representing 95.2% of the global population in 2018. Mean daily intakes per person were estimated for each food category, stratified by age, sex, education level, and rural versus urban residence.

Theme
Nutrition & health
Subject
Food composition & nutrient databases
Study type
Meta-analysis
Study design
Meta-analysis
Source type
Peer-reviewed study
Status
Published
Geography
Global
System type
Food supply chain
DOI
10.1016/s2542-5196(21)00352-1
Catalogue ID
SNmoi1q7mr-4wpx8p

Topic tags

Pulse AI · ask about this record

Dig deeper with Pulse AI.

Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.