Fats, Animals, Raw — Import quantity 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 — Import quantity is currently reported for 156 countries. The highest value is 1,532 1000 t in Netherlands (Kingdom of the); the lowest is 0 1000 t in Lao People's Democratic Republic.
The median across all reporting countries is 4 1000 t, and the mean is 47.04 1000 t.
Over the past decade 62 countries rose and 55 fell. The largest increase was in Malaysia (up 5,900.0%), and the largest decrease in Belize (down 100.0%).
Fats, Animals, Raw — Import quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Netherlands (Kingdom of the) | 1,532 1000 t | 2023 | up 135.0% | volatile |
| 2 | United States | 1,110 1000 t | 2023 | up 865.2% | volatile |
| 3 | France | 376 1000 t | 2023 | up 189.2% | rising |
| 4 | Germany | 364 1000 t | 2023 | up 24.2% | rising |
| 5 | Belgium | 291 1000 t | 2023 | up 18.3% | rising |
| 6 | China | 281 1000 t | 2023 | down 4.4% | falling |
| 7 | Malaysia | 240 1000 t | 2023 | up 5,900.0% | volatile |
| 8 | China, mainland | 233 1000 t | 2023 | up 8.9% | falling |
| 9 | Italy | 204 1000 t | 2023 | down 12.4% | flat |
| 10 | Mexico | 188 1000 t | 2023 | down 62.4% | falling |
| 11 | Poland | 178 1000 t | 2023 | up 89.4% | rising |
| 12 | Spain | 174 1000 t | 2023 | down 28.1% | falling |
| 13 | Philippines | 130 1000 t | 2023 | up 97.0% | rising |
| 14 | Canada | 108 1000 t | 2023 | up 24.1% | rising |
| 14 | Ireland | 108 1000 t | 2023 | up 272.4% | rising |
| 16 | United Kingdom | 104 1000 t | 2023 | down 9.6% | flat |
| 16 | United Kingdom of Great Britain and Northern Ireland | 104 1000 t | 2023 | down 9.6% | flat |
| 18 | Czechia | 78 1000 t | 2023 | up 8.3% | rising |
| 19 | Denmark | 70 1000 t | 2023 | up 16.7% | falling |
| 20 | Uruguay | 64 1000 t | 2023 | up 540.0% | volatile |
| 21 | Slovakia | 63 1000 t | 2023 | up 14.5% | rising |
| 22 | Nigeria | 61 1000 t | 2023 | up 96.8% | volatile |
| 23 | Brazil | 60 1000 t | 2023 | up 81.8% | rising |
| 24 | Vietnam | 59 1000 t | 2023 | up 90.3% | volatile |
| 24 | Viet Nam | 59 1000 t | 2023 | up 90.3% | volatile |
| 26 | Iraq | 54 1000 t | 2023 | — | volatile |
| 27 | Uzbekistan | 51 1000 t | 2023 | up 6.2% | volatile |
| 28 | Chile | 46 1000 t | 2023 | down 16.4% | rising |
| 29 | Thailand | 41 1000 t | 2023 | up 173.3% | rising |
| 30 | Ukraine | 39 1000 t | 2023 | down 62.1% | falling |
| 31 | China, Taiwan Province of | 37 1000 t | 2023 | down 30.2% | falling |
| 32 | Austria | 35 1000 t | 2023 | up 52.2% | rising |
| 33 | Guatemala | 33 1000 t | 2023 | up 94.1% | volatile |
| 33 | Republic of Korea | 33 1000 t | 2023 | up 22.2% | volatile |
| 35 | Hungary | 30 1000 t | 2023 | down 28.6% | falling |
| 36 | Russia | 28 1000 t | 2023 | down 91.7% | volatile |
| 36 | Russian Federation | 28 1000 t | 2023 | down 91.7% | volatile |
| 38 | Azerbaijan | 27 1000 t | 2023 | up 350.0% | rising |
| 39 | United Arab Emirates | 26 1000 t | 2023 | up 116.7% | rising |
| 40 | Romania | 25 1000 t | 2023 | up 25.0% | falling |
| 41 | Portugal | 22 1000 t | 2023 | up 37.5% | rising |
| 42 | Lithuania | 21 1000 t | 2023 | up 31.2% | rising |
| 43 | Serbia | 20 1000 t | 2023 | up 400.0% | volatile |
| 44 | Nepal | 19 1000 t | 2023 | up 137.5% | rising |
| 44 | Syria | 19 1000 t | 2023 | down 47.2% | falling |
| 44 | South Africa | 19 1000 t | 2023 | down 20.8% | rising |
| 44 | Syrian Arab Republic | 19 1000 t | 2023 | down 47.2% | falling |
| 48 | Bulgaria | 18 1000 t | 2023 | up 12.5% | rising |
| 49 | Greece | 17 1000 t | 2023 | up 466.7% | volatile |
| 49 | Caribbean | 17 1000 t | 2023 | down 69.1% | volatile |
| 51 | Jordan | 16 1000 t | 2023 | up 100.0% | rising |
| 51 | Kazakhstan | 16 1000 t | 2023 | up 45.5% | rising |
| 51 | Tajikistan | 16 1000 t | 2023 | — | volatile |
| 54 | Switzerland | 15 1000 t | 2023 | up 50.0% | rising |
| 54 | Croatia | 15 1000 t | 2023 | up 36.4% | rising |
| 56 | Sweden | 14 1000 t | 2023 | down 50.0% | volatile |
| 57 | Argentina | 13 1000 t | 2023 | up 62.5% | falling |
| 57 | El Salvador | 13 1000 t | 2023 | up 44.4% | rising |
| 59 | Angola | 12 1000 t | 2023 | up 300.0% | volatile |
| 59 | Georgia | 12 1000 t | 2023 | up 100.0% | volatile |
| 59 | Pakistan | 12 1000 t | 2023 | down 61.3% | volatile |
| 62 | Armenia | 11 1000 t | 2023 | up 83.3% | rising |
| 62 | Cuba | 11 1000 t | 2019 | up 266.7% | volatile |
| 62 | Finland | 11 1000 t | 2023 | down 67.6% | volatile |
| 65 | Norway | 9 1000 t | 2023 | down 10.0% | falling |
| 65 | China, Hong Kong SAR | 9 1000 t | 2023 | down 65.4% | falling |
| 67 | Ethiopia | 8 1000 t | 2023 | up 166.7% | volatile |
| 67 | Slovenia | 8 1000 t | 2023 | up 300.0% | volatile |
| 67 | Australia and New Zealand | 8 1000 t | 2023 | down 65.2% | falling |
| 70 | Colombia | 7 1000 t | 2023 | down 63.2% | volatile |
| 70 | Ecuador | 7 1000 t | 2023 | up 75.0% | rising |
| 72 | Afghanistan | 5 1000 t | 2023 | up 400.0% | volatile |
| 72 | Albania | 5 1000 t | 2023 | up 400.0% | volatile |
| 72 | Australia | 5 1000 t | 2023 | down 73.7% | falling |
| 72 | Zimbabwe | 5 1000 t | 2023 | down 44.4% | volatile |
| 76 | Cameroon | 4 1000 t | 2023 | up 33.3% | falling |
| 76 | Estonia | 4 1000 t | 2023 | up 100.0% | rising |
| 76 | Honduras | 4 1000 t | 2023 | down 89.5% | volatile |
| 76 | Haiti | 4 1000 t | 2023 | unchanged | volatile |
| 76 | Israel | 4 1000 t | 2023 | down 88.6% | volatile |
| 76 | Kyrgyzstan | 4 1000 t | 2023 | up 100.0% | volatile |
| 76 | Latvia | 4 1000 t | 2023 | up 33.3% | rising |
| 76 | Mozambique | 4 1000 t | 2023 | — | volatile |
| 76 | Trinidad and Tobago | 4 1000 t | 2023 | down 33.3% | falling |
| 76 | Bolivia (Plurinational State of) | 4 1000 t | 2023 | up 33.3% | rising |
| 86 | Dominican Republic | 3 1000 t | 2023 | down 91.2% | volatile |
| 86 | Indonesia | 3 1000 t | 2023 | up 200.0% | volatile |
| 86 | Madagascar | 3 1000 t | 2023 | up 50.0% | flat |
| 86 | New Zealand | 3 1000 t | 2023 | down 40.0% | falling |
| 86 | Panama | 3 1000 t | 2023 | up 50.0% | rising |
| 86 | Peru | 3 1000 t | 2023 | down 76.9% | volatile |
| 86 | Senegal | 3 1000 t | 2023 | down 25.0% | volatile |
| 86 | Tunisia | 3 1000 t | 2023 | up 200.0% | rising |
| 86 | Turkey | 3 1000 t | 2023 | down 95.9% | volatile |
| 86 | Yemen | 3 1000 t | 2023 | up 50.0% | volatile |
| 86 | Zambia | 3 1000 t | 2023 | up 50.0% | volatile |
| 86 | Türkiye | 3 1000 t | 2023 | down 95.9% | volatile |
| 86 | China, Macao SAR | 3 1000 t | 2023 | — | volatile |
| 99 | Bangladesh | 2 1000 t | 2023 | up 100.0% | volatile |
| 99 | Bosnia and Herzegovina | 2 1000 t | 2023 | unchanged | flat |
| 99 | Belarus | 2 1000 t | 2023 | down 87.5% | falling |
| 99 | India | 2 1000 t | 2023 | up 100.0% | volatile |
| 99 | North Macedonia | 2 1000 t | 2023 | up 100.0% | rising |
| 99 | Mongolia | 2 1000 t | 2023 | unchanged | rising |
| 99 | Paraguay | 2 1000 t | 2023 | — | volatile |
| 106 | Burkina Faso | 1 1000 t | 2023 | unchanged | volatile |
| 106 | Costa Rica | 1 1000 t | 2023 | unchanged | volatile |
| 106 | Cyprus | 1 1000 t | 2023 | — | volatile |
| 106 | Egypt | 1 1000 t | 2023 | down 66.7% | volatile |
| 106 | Jamaica | 1 1000 t | 2023 | unchanged | flat |
| 106 | Cambodia | 1 1000 t | 2023 | unchanged | volatile |
| 106 | Lebanon | 1 1000 t | 2023 | unchanged | volatile |
| 106 | Saint Lucia | 1 1000 t | 2023 | — | volatile |
| 106 | Sri Lanka | 1 1000 t | 2023 | down 66.7% | volatile |
| 106 | Luxembourg | 1 1000 t | 2023 | down 50.0% | flat |
| 106 | Montenegro | 1 1000 t | 2023 | unchanged | falling |
| 106 | Nicaragua | 1 1000 t | 2023 | down 85.7% | volatile |
| 106 | Saudi Arabia | 1 1000 t | 2023 | down 50.0% | volatile |
| 106 | Eswatini | 1 1000 t | 2023 | — | volatile |
| 106 | Turkmenistan | 1 1000 t | 2023 | down 85.7% | volatile |
| 106 | Melanesia | 1 1000 t | 2023 | down 75.0% | volatile |
| 106 | Polynesia | 1 1000 t | 2023 | — | volatile |
| 106 | Venezuela (Bolivarian Republic of) | 1 1000 t | 2023 | down 93.3% | volatile |
| 106 | United Republic of Tanzania | 1 1000 t | 2023 | unchanged | volatile |
| 106 | Democratic People's Republic of Korea | 1 1000 t | 2018 | — | volatile |
| 126 | Belize | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Barbados | 0 1000 t | 2023 | — | volatile |
| 126 | Botswana | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Congo | 0 1000 t | 2023 | — | volatile |
| 126 | Comoros | 0 1000 t | 2023 | — | volatile |
| 126 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 126 | Algeria | 0 1000 t | 2023 | — | volatile |
| 126 | Fiji | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Ghana | 0 1000 t | 2023 | — | volatile |
| 126 | Guinea | 0 1000 t | 2023 | — | volatile |
| 126 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 126 | Laos | 0 1000 t | 2023 | — | volatile |
| 126 | Libya | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Morocco | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Myanmar | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Mauritania | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Malawi | 0 1000 t | 2023 | — | volatile |
| 126 | Namibia | 0 1000 t | 2023 | — | volatile |
| 126 | Niger | 0 1000 t | 2023 | — | volatile |
| 126 | Oman | 0 1000 t | 2023 | — | volatile |
| 126 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 126 | Solomon Islands | 0 1000 t | 2023 | — | volatile |
| 126 | Uganda | 0 1000 t | 2023 | — | volatile |
| 126 | Samoa | 0 1000 t | 2023 | — | volatile |
| 126 | Cabo Verde | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 126 | Republic of Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 126 | Lao People's Democratic Republic | 0 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 6,897 1000 t
- Europe 3,891 1000 t
- European Union (27) 3,664 1000 t
- Western Europe 2,614 1000 t
- Americas 1,684 1000 t
- Northern America 1,219 1000 t
- Asia 1,171 1000 t
- United States of America 1,110 1000 t
- South-Eastern Asia 474 1000 t
- Southern Europe 469 1000 t
- Eastern Europe 463 1000 t
- Eastern Asia 390 1000 t
- Northern Europe 345 1000 t
- Central America 242 1000 t
- South America 206 1000 t
- Land Locked Developing Countries (LLDCs) 180 1000 t
- Western Asia 177 1000 t
- Low Income Food Deficit Countries (LIFDCs) 161 1000 t
- Net Food Importing Developing Countries (NFIDCs) 151 1000 t
- Africa 142 1000 t
- Central Asia 89 1000 t
- Least Developed Countries (LDCs) 80 1000 t
- Western Africa 66 1000 t
- Southern Asia 41 1000 t
- Eastern Africa 25 1000 t
- Southern Africa 21 1000 t
- Small island developing States (SIDS) 19 1000 t
- Middle Africa 16 1000 t
- Northern Africa 13 1000 t
- Oceania 10 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.