Fats, Animals, Raw — Residuals 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
Fats, Animals, Raw — Residuals is currently reported for 91 countries. The highest value is 224 1000 t in Argentina; the lowest is -187 1000 t in Indonesia.
The median across all reporting countries is -1 1000 t, and the mean is -8.38 1000 t.
Over the past decade 14 countries rose and 36 fell. The largest increase was in Guatemala (up 500.0%), and the largest decrease in Spain (down 13,200.0%).
Fats, Animals, Raw — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Argentina | 224 1000 t | 2023 | — | volatile |
| 2 | Guatemala | 12 1000 t | 2023 | up 500.0% | volatile |
| 3 | Bolivia (Plurinational State of) | 6 1000 t | 2023 | up 500.0% | volatile |
| 4 | Ecuador | 5 1000 t | 2023 | — | volatile |
| 5 | Ireland | 3 1000 t | 2023 | down 80.0% | volatile |
| 6 | Uzbekistan | 2 1000 t | 2023 | — | volatile |
| 7 | Bulgaria | 1 1000 t | 2023 | — | volatile |
| 7 | Mexico | 1 1000 t | 2023 | down 50.0% | volatile |
| 9 | Afghanistan | 0 1000 t | 2023 | — | volatile |
| 9 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 9 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Chile | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 9 | Germany | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 9 | Dominican Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Egypt | 0 1000 t | 2023 | — | volatile |
| 9 | Estonia | 0 1000 t | 2023 | — | volatile |
| 9 | Georgia | 0 1000 t | 2023 | — | volatile |
| 9 | Gambia | 0 1000 t | 2023 | — | volatile |
| 9 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 9 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 9 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 9 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 9 | Lithuania | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Namibia | 0 1000 t | 2023 | — | volatile |
| 9 | Norway | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Oman | 0 1000 t | 2023 | up 100.0% | volatile |
| 9 | Pakistan | 0 1000 t | 2023 | — | volatile |
| 9 | Panama | 0 1000 t | 2023 | — | volatile |
| 9 | Paraguay | 0 1000 t | 2023 | — | volatile |
| 9 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 9 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 9 | Syria | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Ukraine | 0 1000 t | 2023 | — | volatile |
| 9 | United States | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Caribbean | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | China, Hong Kong SAR | 0 1000 t | 2023 | up 100.0% | volatile |
| 9 | Republic of Korea | 0 1000 t | 2023 | up 100.0% | volatile |
| 9 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 9 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | volatile |
| 9 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 149 | Azerbaijan | -1 1000 t | 2023 | — | volatile |
| 149 | Colombia | -1 1000 t | 2023 | — | volatile |
| 149 | Costa Rica | -1 1000 t | 2023 | — | volatile |
| 149 | Czechia | -1 1000 t | 2023 | down 133.3% | volatile |
| 149 | Croatia | -1 1000 t | 2023 | up 50.0% | volatile |
| 149 | Mongolia | -1 1000 t | 2023 | up 66.7% | volatile |
| 149 | Thailand | -1 1000 t | 2023 | up 87.5% | volatile |
| 149 | Netherlands (Kingdom of the) | -1 1000 t | 2023 | up 98.7% | volatile |
| 157 | Botswana | -2 1000 t | 2023 | — | volatile |
| 157 | Switzerland | -2 1000 t | 2023 | — | volatile |
| 157 | Latvia | -2 1000 t | 2023 | — | volatile |
| 157 | Tunisia | -2 1000 t | 2023 | — | volatile |
| 161 | Bosnia and Herzegovina | -3 1000 t | 2023 | — | volatile |
| 161 | Canada | -3 1000 t | 2023 | down 120.0% | volatile |
| 161 | Greece | -3 1000 t | 2023 | unchanged | volatile |
| 161 | Iceland | -3 1000 t | 2023 | — | volatile |
| 161 | Portugal | -3 1000 t | 2023 | up 50.0% | volatile |
| 166 | Austria | -4 1000 t | 2023 | up 71.4% | volatile |
| 166 | Russia | -4 1000 t | 2023 | down 144.4% | volatile |
| 166 | Uruguay | -4 1000 t | 2023 | up 73.3% | volatile |
| 166 | Russian Federation | -4 1000 t | 2023 | down 144.4% | volatile |
| 170 | Denmark | -5 1000 t | 2023 | up 79.2% | volatile |
| 170 | Turkey | -5 1000 t | 2023 | — | volatile |
| 170 | Türkiye | -5 1000 t | 2023 | — | volatile |
| 173 | Hungary | -6 1000 t | 2023 | down 100.0% | volatile |
| 174 | Sweden | -7 1000 t | 2023 | up 36.4% | volatile |
| 175 | Finland | -8 1000 t | 2023 | down 14.3% | volatile |
| 175 | Slovenia | -8 1000 t | 2023 | — | volatile |
| 177 | Italy | -14 1000 t | 2023 | down 158.3% | volatile |
| 178 | Romania | -16 1000 t | 2023 | — | volatile |
| 179 | Australia | -18 1000 t | 2023 | down 300.0% | volatile |
| 179 | Vietnam | -18 1000 t | 2023 | down 357.1% | volatile |
| 179 | Viet Nam | -18 1000 t | 2023 | down 357.1% | volatile |
| 179 | Australia and New Zealand | -18 1000 t | 2023 | down 162.1% | flat |
| 183 | United Kingdom | -19 1000 t | 2023 | down 733.3% | volatile |
| 183 | United Kingdom of Great Britain and Northern Ireland | -19 1000 t | 2023 | down 733.3% | volatile |
| 185 | Poland | -26 1000 t | 2023 | down 262.5% | volatile |
| 186 | Malaysia | -32 1000 t | 2023 | — | volatile |
| 187 | South Africa | -45 1000 t | 2023 | down 2,150.0% | volatile |
| 188 | China, mainland | -48 1000 t | 2023 | down 336.4% | volatile |
| 189 | China | -49 1000 t | 2023 | down 226.7% | volatile |
| 190 | Belgium | -69 1000 t | 2023 | down 130.0% | volatile |
| 191 | France | -76 1000 t | 2023 | down 38.2% | falling |
| 192 | Brazil | -121 1000 t | 2023 | — | volatile |
| 193 | Spain | -133 1000 t | 2023 | down 13,200.0% | volatile |
| 194 | Indonesia | -187 1000 t | 2023 | down 450.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Americas 119 1000 t
- South America 110 1000 t
- Central America 12 1000 t
- Land Locked Developing Countries (LLDCs) 4 1000 t
- Central Asia 2 1000 t
- Low Income Food Deficit Countries (LIFDCs) 1 1000 t
- Small island developing States (SIDS) 0 1000 t
- Least Developed Countries (LDCs) 0 1000 t
- Eastern Africa 0 1000 t
- Western Africa 0 1000 t
- United States of America 0 1000 t
- Southern Asia -1 1000 t
- Northern America -3 1000 t
- Northern Africa -3 1000 t
- Net Food Importing Developing Countries (NFIDCs) -5 1000 t
- Western Asia -7 1000 t
- Oceania -18 1000 t
- Northern Europe -41 1000 t
- Southern Africa -47 1000 t
- Africa -49 1000 t
- Eastern Asia -49 1000 t
- Eastern Europe -52 1000 t
- Western Europe -151 1000 t
- Southern Europe -165 1000 t
- South-Eastern Asia -238 1000 t
- Asia -292 1000 t
- European Union (27) -378 1000 t
- Europe -410 1000 t
- World -651 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.