Fish, Liver Oil — 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
Fish, Liver Oil — Import quantity is currently reported for 158 countries. The highest value is 5 1000 t in France; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 0 1000 t, and the mean is 0.0633 1000 t.
Over the past decade 1 countries rose and 9 fell. The largest increase was in France (up 400.0%), and the largest decrease in Belgium (down 100.0%).
Fish, Liver Oil — Import quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | France | 5 1000 t | 2023 | up 400.0% | volatile |
| 2 | China | 1 1000 t | 2023 | unchanged | rising |
| 2 | Spain | 1 1000 t | 2023 | — | volatile |
| 2 | China, mainland | 1 1000 t | 2023 | unchanged | volatile |
| 2 | Netherlands (Kingdom of the) | 1 1000 t | 2023 | — | rising |
| 2 | United Kingdom of Great Britain and Northern Ireland | 1 1000 t | 2023 | down 75.0% | volatile |
| 7 | Albania | 0 1000 t | 2023 | — | flat |
| 7 | United Arab Emirates | 0 1000 t | 2017 | — | flat |
| 7 | Argentina | 0 1000 t | 2023 | — | flat |
| 7 | Armenia | 0 1000 t | 2020 | — | flat |
| 7 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 7 | Australia | 0 1000 t | 2023 | — | volatile |
| 7 | Austria | 0 1000 t | 2023 | — | flat |
| 7 | Azerbaijan | 0 1000 t | 2020 | — | flat |
| 7 | Belgium | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 7 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 7 | Bulgaria | 0 1000 t | 2023 | — | flat |
| 7 | Bahrain | 0 1000 t | 2023 | — | flat |
| 7 | Bahamas | 0 1000 t | 2018 | — | flat |
| 7 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 7 | Belarus | 0 1000 t | 2023 | — | flat |
| 7 | Belize | 0 1000 t | 2023 | — | flat |
| 7 | Brazil | 0 1000 t | 2023 | — | flat |
| 7 | Barbados | 0 1000 t | 2023 | — | flat |
| 7 | Botswana | 0 1000 t | 2023 | — | flat |
| 7 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Switzerland | 0 1000 t | 2023 | — | flat |
| 7 | Chile | 0 1000 t | 2023 | — | flat |
| 7 | Cameroon | 0 1000 t | 2023 | — | flat |
| 7 | Congo | 0 1000 t | 2023 | — | flat |
| 7 | Colombia | 0 1000 t | 2023 | — | flat |
| 7 | Comoros | 0 1000 t | 2017 | — | flat |
| 7 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 7 | Cuba | 0 1000 t | 2015 | — | flat |
| 7 | Cyprus | 0 1000 t | 2023 | — | flat |
| 7 | Czechia | 0 1000 t | 2023 | — | flat |
| 7 | Germany | 0 1000 t | 2023 | — | volatile |
| 7 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Dominican Republic | 0 1000 t | 2019 | — | flat |
| 7 | Algeria | 0 1000 t | 2023 | — | flat |
| 7 | Ecuador | 0 1000 t | 2023 | — | flat |
| 7 | Egypt | 0 1000 t | 2023 | — | flat |
| 7 | Estonia | 0 1000 t | 2023 | — | flat |
| 7 | Ethiopia | 0 1000 t | 2020 | — | flat |
| 7 | Finland | 0 1000 t | 2023 | — | flat |
| 7 | Fiji | 0 1000 t | 2018 | — | flat |
| 7 | Gabon | 0 1000 t | 2023 | — | flat |
| 7 | Ghana | 0 1000 t | 2023 | — | flat |
| 7 | Guinea | 0 1000 t | 2023 | — | flat |
| 7 | Gambia | 0 1000 t | 2020 | — | flat |
| 7 | Greece | 0 1000 t | 2023 | — | flat |
| 7 | Grenada | 0 1000 t | 2023 | — | flat |
| 7 | Guatemala | 0 1000 t | 2023 | — | flat |
| 7 | Guyana | 0 1000 t | 2016 | — | flat |
| 7 | Honduras | 0 1000 t | 2023 | — | flat |
| 7 | Croatia | 0 1000 t | 2023 | — | flat |
| 7 | Haiti | 0 1000 t | 2018 | — | flat |
| 7 | Hungary | 0 1000 t | 2023 | — | flat |
| 7 | Indonesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Ireland | 0 1000 t | 2023 | — | flat |
| 7 | Iraq | 0 1000 t | 2023 | — | flat |
| 7 | Iceland | 0 1000 t | 2023 | — | volatile |
| 7 | Israel | 0 1000 t | 2023 | — | flat |
| 7 | Italy | 0 1000 t | 2023 | — | flat |
| 7 | Jamaica | 0 1000 t | 2023 | — | flat |
| 7 | Jordan | 0 1000 t | 2023 | — | flat |
| 7 | Kazakhstan | 0 1000 t | 2023 | — | flat |
| 7 | Kenya | 0 1000 t | 2023 | — | flat |
| 7 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 7 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 7 | Kuwait | 0 1000 t | 2023 | — | flat |
| 7 | Lebanon | 0 1000 t | 2023 | — | flat |
| 7 | Liberia | 0 1000 t | 2023 | — | flat |
| 7 | Saint Lucia | 0 1000 t | 2020 | — | flat |
| 7 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 7 | Lesotho | 0 1000 t | 2023 | — | flat |
| 7 | Lithuania | 0 1000 t | 2023 | — | flat |
| 7 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 7 | Latvia | 0 1000 t | 2023 | — | flat |
| 7 | Morocco | 0 1000 t | 2023 | — | flat |
| 7 | Madagascar | 0 1000 t | 2023 | — | flat |
| 7 | Maldives | 0 1000 t | 2023 | — | flat |
| 7 | Mexico | 0 1000 t | 2023 | — | flat |
| 7 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 7 | Malta | 0 1000 t | 2023 | — | flat |
| 7 | Myanmar | 0 1000 t | 2017 | — | flat |
| 7 | Montenegro | 0 1000 t | 2023 | — | flat |
| 7 | Mongolia | 0 1000 t | 2017 | — | flat |
| 7 | Mozambique | 0 1000 t | 2020 | — | flat |
| 7 | Mauritius | 0 1000 t | 2023 | — | flat |
| 7 | Malawi | 0 1000 t | 2020 | — | flat |
| 7 | Malaysia | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Namibia | 0 1000 t | 2023 | — | volatile |
| 7 | New Caledonia | 0 1000 t | 2020 | — | flat |
| 7 | Niger | 0 1000 t | 2023 | — | flat |
| 7 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 7 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 7 | Norway | 0 1000 t | 2023 | — | volatile |
| 7 | Nepal | 0 1000 t | 2023 | — | flat |
| 7 | New Zealand | 0 1000 t | 2023 | — | flat |
| 7 | Oman | 0 1000 t | 2023 | — | flat |
| 7 | Pakistan | 0 1000 t | 2023 | — | flat |
| 7 | Panama | 0 1000 t | 2023 | — | flat |
| 7 | Peru | 0 1000 t | 2023 | — | flat |
| 7 | Philippines | 0 1000 t | 2018 | — | flat |
| 7 | Papua New Guinea | 0 1000 t | 2017 | — | flat |
| 7 | Poland | 0 1000 t | 2023 | — | flat |
| 7 | Portugal | 0 1000 t | 2023 | — | volatile |
| 7 | Paraguay | 0 1000 t | 2020 | — | flat |
| 7 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 7 | Qatar | 0 1000 t | 2023 | — | flat |
| 7 | Romania | 0 1000 t | 2023 | — | flat |
| 7 | Saudi Arabia | 0 1000 t | 2023 | — | flat |
| 7 | Senegal | 0 1000 t | 2023 | — | flat |
| 7 | Solomon Islands | 0 1000 t | 2017 | — | flat |
| 7 | El Salvador | 0 1000 t | 2017 | — | flat |
| 7 | Serbia | 0 1000 t | 2023 | — | flat |
| 7 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 7 | Slovakia | 0 1000 t | 2023 | — | flat |
| 7 | Slovenia | 0 1000 t | 2023 | — | flat |
| 7 | Sweden | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Eswatini | 0 1000 t | 2023 | — | flat |
| 7 | Seychelles | 0 1000 t | 2023 | — | flat |
| 7 | Thailand | 0 1000 t | 2023 | — | flat |
| 7 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 7 | Tunisia | 0 1000 t | 2023 | — | flat |
| 7 | Uganda | 0 1000 t | 2023 | — | flat |
| 7 | Ukraine | 0 1000 t | 2023 | — | flat |
| 7 | Uruguay | 0 1000 t | 2023 | — | flat |
| 7 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 7 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 7 | Vanuatu | 0 1000 t | 2016 | — | flat |
| 7 | Yemen | 0 1000 t | 2023 | — | flat |
| 7 | Zambia | 0 1000 t | 2019 | — | flat |
| 7 | Zimbabwe | 0 1000 t | 2020 | — | flat |
| 7 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 7 | Melanesia | 0 1000 t | 2020 | — | flat |
| 7 | Polynesia | 0 1000 t | 2023 | — | flat |
| 7 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 7 | Caribbean | 0 1000 t | 2023 | — | flat |
| 7 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 7 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 7 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | flat |
| 7 | Republic of Korea | 0 1000 t | 2023 | — | volatile |
| 7 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 7 | Russian Federation | 0 1000 t | 2023 | — | flat |
| 7 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 7 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 7 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 7 | Türkiye | 0 1000 t | 2023 | — | flat |
| 7 | Australia and New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 7 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 7 | China, Taiwan Province of | 0 1000 t | 2018 | — | flat |
| 7 | Democratic People's Republic of Korea | 0 1000 t | 2017 | — | flat |
| 7 | China, Macao SAR | 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 16 1000 t
- Europe 10 1000 t
- European Union (27) 9 1000 t
- Western Europe 6 1000 t
- Asia 3 1000 t
- Americas 2 1000 t
- Southern Europe 2 1000 t
- Eastern Asia 2 1000 t
- Northern America 1 1000 t
- Least Developed Countries (LDCs) 1 1000 t
- Eastern Europe 1 1000 t
- Northern Europe 1 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.