Animal fats — 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
Animal fats — Stock Variation is currently reported for 105 countries. The highest value is 184 1000 t in United States; the lowest is -59 1000 t in Germany.
The median across all reporting countries is 0 1000 t, and the mean is 3.55 1000 t.
The gap between the highest and lowest reporting country is a factor of about 3.
Over the past decade 25 countries rose and 30 fell. The largest increase was in France (up 2,825.0%), and the largest decrease in Australia and New Zealand (down 1,450.0%).
Animal fats — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | United States | 184 1000 t | 2023 | up 1,740.0% | volatile |
| 2 | Netherlands (Kingdom of the) | 157 1000 t | 2023 | up 218.0% | volatile |
| 3 | France | 117 1000 t | 2023 | up 2,825.0% | volatile |
| 4 | China | 20 1000 t | 2023 | up 281.8% | volatile |
| 4 | China, mainland | 20 1000 t | 2023 | up 266.7% | volatile |
| 6 | Ireland | 16 1000 t | 2023 | up 223.1% | volatile |
| 7 | United Kingdom | 10 1000 t | 2023 | — | volatile |
| 7 | United Kingdom of Great Britain and Northern Ireland | 10 1000 t | 2023 | — | volatile |
| 9 | Ukraine | 9 1000 t | 2023 | up 125.0% | volatile |
| 10 | Mexico | 7 1000 t | 2023 | down 58.8% | volatile |
| 11 | Norway | 4 1000 t | 2023 | up 300.0% | volatile |
| 11 | Republic of Korea | 4 1000 t | 2023 | up 500.0% | volatile |
| 13 | Denmark | 3 1000 t | 2023 | down 40.0% | volatile |
| 13 | Uruguay | 3 1000 t | 2023 | — | volatile |
| 15 | Angola | 2 1000 t | 2023 | up 150.0% | volatile |
| 15 | Ecuador | 2 1000 t | 2023 | — | volatile |
| 15 | Kazakhstan | 2 1000 t | 2023 | up 100.0% | volatile |
| 15 | Russia | 2 1000 t | 2023 | — | volatile |
| 15 | Trinidad and Tobago | 2 1000 t | 2023 | — | volatile |
| 15 | Caribbean | 2 1000 t | 2023 | up 300.0% | volatile |
| 15 | Russian Federation | 2 1000 t | 2023 | — | volatile |
| 22 | Albania | 1 1000 t | 2023 | — | volatile |
| 22 | Chile | 1 1000 t | 2023 | — | volatile |
| 22 | Czechia | 1 1000 t | 2023 | — | volatile |
| 22 | Croatia | 1 1000 t | 2023 | — | volatile |
| 22 | Hungary | 1 1000 t | 2023 | — | flat |
| 22 | Namibia | 1 1000 t | 2023 | up 200.0% | volatile |
| 22 | Philippines | 1 1000 t | 2023 | — | volatile |
| 22 | Vietnam | 1 1000 t | 2023 | down 83.3% | volatile |
| 22 | Zambia | 1 1000 t | 2023 | — | volatile |
| 22 | Viet Nam | 1 1000 t | 2023 | down 83.3% | volatile |
| 32 | Afghanistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Austria | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Azerbaijan | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Belgium | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 32 | Botswana | 0 1000 t | 2023 | — | volatile |
| 32 | Switzerland | 0 1000 t | 2023 | — | volatile |
| 32 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 32 | Colombia | 0 1000 t | 2023 | — | volatile |
| 32 | Egypt | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Spain | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Estonia | 0 1000 t | 2023 | — | volatile |
| 32 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Finland | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Georgia | 0 1000 t | 2023 | — | volatile |
| 32 | Guinea | 0 1000 t | 2023 | — | volatile |
| 32 | Greece | 0 1000 t | 2023 | — | volatile |
| 32 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 32 | Honduras | 0 1000 t | 2023 | — | flat |
| 32 | Haiti | 0 1000 t | 2023 | — | volatile |
| 32 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Iraq | 0 1000 t | 2023 | — | volatile |
| 32 | Italy | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 32 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 32 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 32 | Latvia | 0 1000 t | 2023 | — | volatile |
| 32 | Myanmar | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Nigeria | 0 1000 t | 2023 | — | flat |
| 32 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 32 | Nepal | 0 1000 t | 2023 | — | volatile |
| 32 | Oman | 0 1000 t | 2023 | — | flat |
| 32 | Pakistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Panama | 0 1000 t | 2023 | — | volatile |
| 32 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Portugal | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Paraguay | 0 1000 t | 2023 | — | volatile |
| 32 | Romania | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 32 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 32 | Syria | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Thailand | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 32 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 32 | Turkey | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Uzbekistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Yemen | 0 1000 t | 2023 | — | volatile |
| 32 | South Africa | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Zimbabwe | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 32 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | volatile |
| 32 | Türkiye | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | United Republic of Tanzania | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | China, Taiwan Province of | 0 1000 t | 2023 | — | flat |
| 176 | United Arab Emirates | -1 1000 t | 2023 | up 66.7% | volatile |
| 176 | Morocco | -1 1000 t | 2023 | up 80.0% | volatile |
| 176 | Mongolia | -1 1000 t | 2023 | — | volatile |
| 176 | Sweden | -1 1000 t | 2023 | — | volatile |
| 180 | Belarus | -3 1000 t | 2023 | down 400.0% | volatile |
| 181 | Canada | -4 1000 t | 2023 | down 100.0% | volatile |
| 181 | Indonesia | -4 1000 t | 2023 | — | volatile |
| 183 | Slovakia | -6 1000 t | 2023 | down 200.0% | volatile |
| 184 | New Zealand | -9 1000 t | 2023 | down 80.0% | volatile |
| 185 | Australia | -22 1000 t | 2023 | down 833.3% | volatile |
| 186 | Peru | -28 1000 t | 2023 | down 153.8% | volatile |
| 187 | Australia and New Zealand | -31 1000 t | 2023 | down 1,450.0% | volatile |
| 188 | Malaysia | -45 1000 t | 2023 | — | volatile |
| 189 | Germany | -59 1000 t | 2023 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 361 1000 t
- Europe 253 1000 t
- European Union (27) 230 1000 t
- Western Europe 215 1000 t
- United States of America 184 1000 t
- Northern America 180 1000 t
- Americas 167 1000 t
- Northern Europe 32 1000 t
- Eastern Asia 14 1000 t
- Central America 7 1000 t
- Eastern Europe 4 1000 t
- Africa 3 1000 t
- Least Developed Countries (LDCs) 3 1000 t
- Land Locked Developing Countries (LLDCs) 3 1000 t
- Central Asia 2 1000 t
- Southern Europe 2 1000 t
- Middle Africa 2 1000 t
- Small island developing States (SIDS) 1 1000 t
- Eastern Africa 1 1000 t
- Southern Africa 1 1000 t
- Western Africa 0 1000 t
- Southern Asia 0 1000 t
- Low Income Food Deficit Countries (LIFDCs) 0 1000 t
- Northern Africa -1 1000 t
- Western Asia -1 1000 t
- South America -22 1000 t
- Net Food Importing Developing Countries (NFIDCs) -25 1000 t
- Asia -31 1000 t
- Oceania -31 1000 t
- South-Eastern Asia -47 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.