Aquatic Animals, Others — Food 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
Aquatic Animals, Others — Food is currently reported for 170 countries. The highest value is 1,400 1000 t in China; the lowest is 0 1000 t in Micronesia (Federated States of).
The median across all reporting countries is 0 1000 t, and the mean is 17.62 1000 t.
Over the past decade 11 countries rose and 13 fell. The largest increase was in Russian Federation (up 1,200.0%), and the largest decrease in Belgium (down 100.0%).
Aquatic Animals, Others — Food: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 1,400 1000 t | 2023 | up 48.1% | rising |
| 2 | China, mainland | 1,382 1000 t | 2023 | up 48.8% | rising |
| 3 | Republic of Korea | 38 1000 t | 2023 | up 11.8% | falling |
| 4 | Indonesia | 29 1000 t | 2023 | up 262.5% | volatile |
| 5 | Saudi Arabia | 21 1000 t | 2023 | — | volatile |
| 6 | Chile | 16 1000 t | 2023 | up 23.1% | rising |
| 7 | Malaysia | 15 1000 t | 2023 | up 87.5% | rising |
| 8 | Russian Federation | 13 1000 t | 2023 | up 1,200.0% | volatile |
| 8 | Viet Nam | 13 1000 t | 2023 | up 333.3% | volatile |
| 10 | Mexico | 12 1000 t | 2023 | down 50.0% | volatile |
| 11 | Canada | 9 1000 t | 2023 | up 28.6% | rising |
| 11 | China, Taiwan Province of | 9 1000 t | 2023 | down 25.0% | falling |
| 13 | China, Hong Kong SAR | 8 1000 t | 2023 | up 166.7% | rising |
| 14 | Nicaragua | 4 1000 t | 2023 | — | volatile |
| 15 | Sri Lanka | 3 1000 t | 2023 | unchanged | volatile |
| 15 | Thailand | 3 1000 t | 2023 | down 95.8% | volatile |
| 15 | Australia and New Zealand | 3 1000 t | 2023 | down 57.1% | volatile |
| 18 | Australia | 2 1000 t | 2023 | down 66.7% | volatile |
| 18 | Myanmar | 2 1000 t | 2023 | down 60.0% | volatile |
| 18 | Pakistan | 2 1000 t | 2023 | up 100.0% | rising |
| 21 | Switzerland | 1 1000 t | 2023 | — | volatile |
| 21 | Germany | 1 1000 t | 2023 | — | volatile |
| 21 | Spain | 1 1000 t | 2023 | down 50.0% | volatile |
| 21 | France | 1 1000 t | 2023 | down 75.0% | volatile |
| 21 | Italy | 1 1000 t | 2023 | — | volatile |
| 21 | Madagascar | 1 1000 t | 2023 | down 66.7% | volatile |
| 21 | New Zealand | 1 1000 t | 2023 | unchanged | flat |
| 21 | Peru | 1 1000 t | 2023 | — | volatile |
| 21 | Philippines | 1 1000 t | 2023 | unchanged | volatile |
| 21 | United Kingdom of Great Britain and Northern Ireland | 1 1000 t | 2023 | unchanged | volatile |
| 21 | China, Macao SAR | 1 1000 t | 2023 | — | volatile |
| 32 | Angola | 0 1000 t | 2023 | — | flat |
| 32 | Albania | 0 1000 t | 2023 | — | flat |
| 32 | United Arab Emirates | 0 1000 t | 2023 | — | flat |
| 32 | Argentina | 0 1000 t | 2023 | — | flat |
| 32 | Armenia | 0 1000 t | 2023 | — | flat |
| 32 | Austria | 0 1000 t | 2023 | — | volatile |
| 32 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 32 | Belgium | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 32 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 32 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 32 | Bahrain | 0 1000 t | 2023 | — | flat |
| 32 | Bahamas | 0 1000 t | 2023 | — | flat |
| 32 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 32 | Belarus | 0 1000 t | 2023 | — | flat |
| 32 | Belize | 0 1000 t | 2023 | — | flat |
| 32 | Brazil | 0 1000 t | 2023 | — | volatile |
| 32 | Barbados | 0 1000 t | 2023 | — | flat |
| 32 | Botswana | 0 1000 t | 2023 | — | flat |
| 32 | Cameroon | 0 1000 t | 2023 | — | flat |
| 32 | Congo | 0 1000 t | 2023 | — | flat |
| 32 | Colombia | 0 1000 t | 2023 | — | flat |
| 32 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 32 | Cuba | 0 1000 t | 2019 | — | flat |
| 32 | Cyprus | 0 1000 t | 2023 | — | flat |
| 32 | Czechia | 0 1000 t | 2023 | — | volatile |
| 32 | Djibouti | 0 1000 t | 2023 | — | flat |
| 32 | Denmark | 0 1000 t | 2023 | — | volatile |
| 32 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 32 | Algeria | 0 1000 t | 2023 | — | flat |
| 32 | Ecuador | 0 1000 t | 2023 | — | volatile |
| 32 | Egypt | 0 1000 t | 2023 | — | flat |
| 32 | Estonia | 0 1000 t | 2023 | — | volatile |
| 32 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 32 | Finland | 0 1000 t | 2023 | — | flat |
| 32 | Fiji | 0 1000 t | 2023 | — | flat |
| 32 | Gabon | 0 1000 t | 2023 | — | flat |
| 32 | Georgia | 0 1000 t | 2023 | — | flat |
| 32 | Ghana | 0 1000 t | 2023 | — | flat |
| 32 | Guinea | 0 1000 t | 2023 | — | flat |
| 32 | Greece | 0 1000 t | 2023 | — | flat |
| 32 | Grenada | 0 1000 t | 2023 | — | flat |
| 32 | Guatemala | 0 1000 t | 2023 | — | flat |
| 32 | Guyana | 0 1000 t | 2023 | — | flat |
| 32 | Honduras | 0 1000 t | 2023 | — | volatile |
| 32 | Croatia | 0 1000 t | 2023 | — | flat |
| 32 | Haiti | 0 1000 t | 2023 | — | flat |
| 32 | Hungary | 0 1000 t | 2023 | — | flat |
| 32 | India | 0 1000 t | 2023 | — | flat |
| 32 | Ireland | 0 1000 t | 2023 | — | flat |
| 32 | Iraq | 0 1000 t | 2023 | — | flat |
| 32 | Iceland | 0 1000 t | 2023 | — | flat |
| 32 | Israel | 0 1000 t | 2023 | — | flat |
| 32 | Jamaica | 0 1000 t | 2023 | — | flat |
| 32 | Jordan | 0 1000 t | 2023 | — | flat |
| 32 | Kazakhstan | 0 1000 t | 2023 | — | flat |
| 32 | Kenya | 0 1000 t | 2023 | — | flat |
| 32 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 32 | Cambodia | 0 1000 t | 2023 | — | flat |
| 32 | Kiribati | 0 1000 t | 2023 | — | flat |
| 32 | Kuwait | 0 1000 t | 2023 | — | flat |
| 32 | Lebanon | 0 1000 t | 2023 | — | flat |
| 32 | Liberia | 0 1000 t | 2023 | — | flat |
| 32 | Libya | 0 1000 t | 2023 | — | flat |
| 32 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 32 | Lesotho | 0 1000 t | 2023 | — | flat |
| 32 | Lithuania | 0 1000 t | 2023 | — | flat |
| 32 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 32 | Latvia | 0 1000 t | 2023 | — | flat |
| 32 | Morocco | 0 1000 t | 2023 | — | flat |
| 32 | Maldives | 0 1000 t | 2023 | — | flat |
| 32 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 32 | North Macedonia | 0 1000 t | 2020 | — | flat |
| 32 | Malta | 0 1000 t | 2023 | — | flat |
| 32 | Montenegro | 0 1000 t | 2023 | — | flat |
| 32 | Mongolia | 0 1000 t | 2023 | — | flat |
| 32 | Mozambique | 0 1000 t | 2023 | — | flat |
| 32 | Mauritania | 0 1000 t | 2018 | — | flat |
| 32 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 32 | Malawi | 0 1000 t | 2020 | — | flat |
| 32 | Namibia | 0 1000 t | 2023 | — | flat |
| 32 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 32 | Niger | 0 1000 t | 2020 | — | flat |
| 32 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 32 | Norway | 0 1000 t | 2023 | — | flat |
| 32 | Nepal | 0 1000 t | 2020 | — | flat |
| 32 | Oman | 0 1000 t | 2023 | — | flat |
| 32 | Panama | 0 1000 t | 2023 | — | volatile |
| 32 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 32 | Poland | 0 1000 t | 2023 | — | flat |
| 32 | Portugal | 0 1000 t | 2023 | — | flat |
| 32 | Paraguay | 0 1000 t | 2020 | — | flat |
| 32 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 32 | Qatar | 0 1000 t | 2023 | — | flat |
| 32 | Romania | 0 1000 t | 2023 | — | flat |
| 32 | Rwanda | 0 1000 t | 2023 | — | flat |
| 32 | Senegal | 0 1000 t | 2023 | — | flat |
| 32 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 32 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 32 | El Salvador | 0 1000 t | 2023 | — | flat |
| 32 | Serbia | 0 1000 t | 2023 | — | volatile |
| 32 | Slovakia | 0 1000 t | 2023 | — | flat |
| 32 | Slovenia | 0 1000 t | 2023 | — | flat |
| 32 | Sweden | 0 1000 t | 2023 | — | flat |
| 32 | Eswatini | 0 1000 t | 2018 | — | flat |
| 32 | Seychelles | 0 1000 t | 2023 | — | flat |
| 32 | Tajikistan | 0 1000 t | 2018 | — | flat |
| 32 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 32 | Tonga | 0 1000 t | 2023 | — | flat |
| 32 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 32 | Tunisia | 0 1000 t | 2023 | — | flat |
| 32 | Uganda | 0 1000 t | 2020 | — | flat |
| 32 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Uruguay | 0 1000 t | 2020 | — | flat |
| 32 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 32 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 32 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 32 | Samoa | 0 1000 t | 2023 | — | flat |
| 32 | Yemen | 0 1000 t | 2023 | — | flat |
| 32 | Zambia | 0 1000 t | 2023 | — | flat |
| 32 | Zimbabwe | 0 1000 t | 2020 | — | flat |
| 32 | Micronesia | 0 1000 t | 2023 | — | flat |
| 32 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 32 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 32 | Melanesia | 0 1000 t | 2023 | — | volatile |
| 32 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 32 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 32 | Bolivia (Plurinational State of) | 0 1000 t | 2020 | — | flat |
| 32 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 32 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 32 | Syrian Arab Republic | 0 1000 t | 2017 | — | flat |
| 32 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 32 | Türkiye | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 32 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 32 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 32 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 32 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,625 1000 t
- Asia 1,546 1000 t
- Eastern Asia 1,457 1000 t
- South-Eastern Asia 62 1000 t
- Americas 52 1000 t
- Western Asia 22 1000 t
- Europe 21 1000 t
- Northern America 18 1000 t
- South America 17 1000 t
- Central America 17 1000 t
- Eastern Europe 14 1000 t
- Net Food Importing Developing Countries (NFIDCs) 11 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.