Beverages, Fermented — Stock Variation by country
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply...
What the numbers show
Beverages, Fermented — Stock Variation is currently reported for 99 countries. The highest value is 202 1000 t in Cameroon; the lowest is -6 1000 t in China, mainland.
The median across all reporting countries is 0 1000 t, and the mean is 5.09 1000 t.
The gap between the highest and lowest reporting country is a factor of about 34.
Over the past decade 21 countries rose and 29 fell. The largest increase was in Denmark (up 400.0%), and the largest decrease in Poland (down 150.0%).
Beverages, Fermented — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Cameroon | 202 1000 t | 2023 | up 65.6% | volatile |
| 2 | Malawi | 80 1000 t | 2023 | up 166.7% | volatile |
| 3 | Zambia | 44 1000 t | 2023 | up 29.4% | rising |
| 4 | United Kingdom | 33 1000 t | 2023 | up 32.0% | volatile |
| 4 | United Kingdom of Great Britain and Northern Ireland | 33 1000 t | 2023 | up 32.0% | volatile |
| 6 | Ghana | 22 1000 t | 2023 | up 175.0% | volatile |
| 6 | Italy | 22 1000 t | 2023 | — | volatile |
| 8 | Philippines | 12 1000 t | 2023 | — | volatile |
| 8 | United Republic of Tanzania | 12 1000 t | 2023 | down 95.5% | volatile |
| 10 | Vietnam | 9 1000 t | 2023 | — | volatile |
| 10 | Viet Nam | 9 1000 t | 2023 | — | volatile |
| 12 | Botswana | 7 1000 t | 2023 | — | volatile |
| 13 | Canada | 6 1000 t | 2023 | up 200.0% | volatile |
| 14 | Denmark | 5 1000 t | 2023 | up 400.0% | volatile |
| 14 | Zimbabwe | 5 1000 t | 2023 | down 66.7% | volatile |
| 16 | Hungary | 4 1000 t | 2023 | down 81.8% | volatile |
| 17 | Lithuania | 3 1000 t | 2023 | — | volatile |
| 18 | Norway | 2 1000 t | 2023 | — | volatile |
| 19 | Spain | 1 1000 t | 2023 | — | volatile |
| 19 | Finland | 1 1000 t | 2023 | — | volatile |
| 19 | Guinea-Bissau | 1 1000 t | 2023 | down 50.0% | volatile |
| 19 | Guyana | 1 1000 t | 2023 | up 200.0% | volatile |
| 19 | New Zealand | 1 1000 t | 2023 | — | volatile |
| 19 | Portugal | 1 1000 t | 2023 | — | volatile |
| 19 | Eswatini | 1 1000 t | 2023 | up 200.0% | volatile |
| 19 | Turkey | 1 1000 t | 2023 | — | volatile |
| 19 | United States | 1 1000 t | 2023 | up 125.0% | volatile |
| 19 | Türkiye | 1 1000 t | 2023 | — | volatile |
| 19 | Australia and New Zealand | 1 1000 t | 2023 | down 75.0% | volatile |
| 19 | China, Macao SAR | 1 1000 t | 2023 | — | volatile |
| 31 | Angola | 0 1000 t | 2023 | — | volatile |
| 31 | United Arab Emirates | 0 1000 t | 2023 | — | volatile |
| 31 | Argentina | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Armenia | 0 1000 t | 2023 | — | flat |
| 31 | Australia | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Austria | 0 1000 t | 2023 | down 100.0% | flat |
| 31 | Belgium | 0 1000 t | 2023 | — | volatile |
| 31 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | flat |
| 31 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 31 | Bosnia and Herzegovina | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Belarus | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Brazil | 0 1000 t | 2023 | — | volatile |
| 31 | Switzerland | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Cote d'Ivoire | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Colombia | 0 1000 t | 2023 | — | volatile |
| 31 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 31 | Czechia | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Germany | 0 1000 t | 2023 | — | volatile |
| 31 | Estonia | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | France | 0 1000 t | 2023 | — | volatile |
| 31 | Gambia | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Greece | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Grenada | 0 1000 t | 2023 | — | volatile |
| 31 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 31 | Honduras | 0 1000 t | 2023 | — | volatile |
| 31 | Croatia | 0 1000 t | 2023 | — | flat |
| 31 | Haiti | 0 1000 t | 2023 | — | volatile |
| 31 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Jamaica | 0 1000 t | 2023 | — | volatile |
| 31 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 31 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 31 | Liberia | 0 1000 t | 2023 | — | volatile |
| 31 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 31 | Lesotho | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 31 | Latvia | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Mexico | 0 1000 t | 2023 | — | volatile |
| 31 | Mozambique | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Malaysia | 0 1000 t | 2023 | — | flat |
| 31 | Namibia | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Nigeria | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Pakistan | 0 1000 t | 2023 | — | volatile |
| 31 | Romania | 0 1000 t | 2023 | — | volatile |
| 31 | Russia | 0 1000 t | 2023 | — | volatile |
| 31 | Rwanda | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Slovakia | 0 1000 t | 2023 | down 100.0% | flat |
| 31 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 31 | Sweden | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Thailand | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 31 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 31 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 31 | South Africa | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Democratic Republic of the Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 31 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 31 | Republic of Korea | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 31 | Côte d'Ivoire | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | volatile |
| 181 | China, Taiwan Province of | -1 1000 t | 2023 | unchanged | volatile |
| 182 | Poland | -5 1000 t | 2023 | down 150.0% | volatile |
| 183 | China | -6 1000 t | 2023 | up 72.7% | volatile |
| 183 | China, mainland | -6 1000 t | 2023 | up 71.4% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 476 1000 t
- Africa 382 1000 t
- Low Income Food Deficit Countries (LIFDCs) 307 1000 t
- Middle Africa 202 1000 t
- Net Food Importing Developing Countries (NFIDCs) 153 1000 t
- Eastern Africa 146 1000 t
- Least Developed Countries (LDCs) 144 1000 t
- Land Locked Developing Countries (LLDCs) 143 1000 t
- Europe 68 1000 t
- Northern Europe 44 1000 t
- European Union (27) 32 1000 t
- Southern Europe 25 1000 t
- Western Africa 24 1000 t
- South-Eastern Asia 21 1000 t
- Asia 17 1000 t
- Americas 8 1000 t
- Southern Africa 8 1000 t
- Northern America 6 1000 t
- Small island developing States (SIDS) 2 1000 t
- Western Asia 2 1000 t
- Oceania 1 1000 t
- South America 1 1000 t
- United States of America 1 1000 t
- Central Asia 0 1000 t
- Western Europe 0 1000 t
- Northern Africa 0 1000 t
- Central America 0 1000 t
- Southern Asia 0 1000 t
- Eastern Europe -1 1000 t
- Eastern Asia -6 1000 t
About this data
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per capita food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.