Molluscs, Other — 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
Molluscs, Other — Import quantity is currently reported for 180 countries. The highest value is 765 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 18.57 1000 t.
Over the past decade 31 countries rose and 28 fell. The largest increase was in Viet Nam (up 533.3%), and the largest decrease in Angola (down 100.0%).
Molluscs, Other — Import quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 765 1000 t | 2023 | up 42.2% | flat |
| 2 | China, mainland | 523 1000 t | 2023 | up 86.1% | volatile |
| 3 | Italy | 229 1000 t | 2023 | down 18.2% | falling |
| 4 | France | 207 1000 t | 2023 | down 11.9% | falling |
| 5 | Spain | 193 1000 t | 2023 | down 21.2% | falling |
| 6 | Republic of Korea | 163 1000 t | 2023 | down 23.8% | falling |
| 7 | Russian Federation | 140 1000 t | 2023 | up 8.5% | rising |
| 8 | China, Hong Kong SAR | 138 1000 t | 2023 | down 10.4% | falling |
| 9 | Thailand | 96 1000 t | 2023 | up 159.5% | rising |
| 10 | Portugal | 94 1000 t | 2023 | up 46.9% | rising |
| 11 | China, Taiwan Province of | 91 1000 t | 2023 | down 6.2% | rising |
| 12 | Netherlands (Kingdom of the) | 69 1000 t | 2023 | up 7.8% | rising |
| 13 | Malaysia | 66 1000 t | 2023 | up 200.0% | rising |
| 14 | Australia and New Zealand | 60 1000 t | 2023 | up 3.4% | falling |
| 15 | Australia | 57 1000 t | 2023 | up 1.8% | falling |
| 16 | Canada | 54 1000 t | 2023 | down 10.0% | falling |
| 17 | Belgium | 51 1000 t | 2023 | down 27.1% | falling |
| 18 | Germany | 46 1000 t | 2023 | up 4.5% | falling |
| 19 | Ukraine | 40 1000 t | 2023 | down 31.0% | rising |
| 20 | United Kingdom of Great Britain and Northern Ireland | 38 1000 t | 2023 | down 26.9% | falling |
| 21 | Viet Nam | 19 1000 t | 2023 | up 533.3% | volatile |
| 22 | Poland | 14 1000 t | 2023 | up 366.7% | volatile |
| 23 | Mexico | 13 1000 t | 2023 | up 225.0% | rising |
| 23 | China, Macao SAR | 13 1000 t | 2023 | up 85.7% | rising |
| 25 | Denmark | 12 1000 t | 2023 | down 14.3% | falling |
| 26 | Switzerland | 10 1000 t | 2023 | unchanged | falling |
| 27 | Belarus | 9 1000 t | 2023 | up 125.0% | volatile |
| 28 | United Arab Emirates | 8 1000 t | 2023 | up 14.3% | rising |
| 28 | Romania | 8 1000 t | 2023 | up 166.7% | rising |
| 30 | Argentina | 7 1000 t | 2023 | down 36.4% | falling |
| 30 | Sweden | 7 1000 t | 2023 | up 16.7% | flat |
| 32 | Austria | 5 1000 t | 2023 | unchanged | falling |
| 32 | Greece | 5 1000 t | 2023 | down 37.5% | falling |
| 32 | Indonesia | 5 1000 t | 2023 | unchanged | rising |
| 35 | Czechia | 4 1000 t | 2023 | up 100.0% | rising |
| 35 | Panama | 4 1000 t | 2023 | up 100.0% | rising |
| 35 | Caribbean | 4 1000 t | 2023 | unchanged | falling |
| 38 | Bulgaria | 3 1000 t | 2023 | up 200.0% | rising |
| 38 | Brazil | 3 1000 t | 2023 | down 72.7% | volatile |
| 38 | Colombia | 3 1000 t | 2023 | up 50.0% | rising |
| 38 | Croatia | 3 1000 t | 2023 | up 50.0% | falling |
| 38 | Ireland | 3 1000 t | 2023 | unchanged | rising |
| 38 | Iceland | 3 1000 t | 2023 | — | volatile |
| 38 | Israel | 3 1000 t | 2023 | up 50.0% | rising |
| 38 | Luxembourg | 3 1000 t | 2023 | up 50.0% | rising |
| 38 | New Zealand | 3 1000 t | 2023 | unchanged | flat |
| 38 | Slovenia | 3 1000 t | 2023 | up 200.0% | rising |
| 38 | Türkiye | 3 1000 t | 2023 | up 200.0% | volatile |
| 49 | Chile | 2 1000 t | 2023 | unchanged | rising |
| 49 | Costa Rica | 2 1000 t | 2023 | unchanged | falling |
| 49 | Cyprus | 2 1000 t | 2023 | down 33.3% | rising |
| 49 | Hungary | 2 1000 t | 2023 | up 100.0% | rising |
| 49 | Lithuania | 2 1000 t | 2023 | up 100.0% | rising |
| 49 | Latvia | 2 1000 t | 2023 | unchanged | rising |
| 49 | Morocco | 2 1000 t | 2023 | up 100.0% | volatile |
| 49 | Malta | 2 1000 t | 2023 | unchanged | rising |
| 49 | Norway | 2 1000 t | 2023 | down 33.3% | falling |
| 49 | Saudi Arabia | 2 1000 t | 2023 | up 100.0% | volatile |
| 59 | Bangladesh | 1 1000 t | 2023 | — | volatile |
| 59 | Cuba | 1 1000 t | 2019 | — | rising |
| 59 | Dominican Republic | 1 1000 t | 2023 | unchanged | rising |
| 59 | Estonia | 1 1000 t | 2023 | unchanged | rising |
| 59 | Finland | 1 1000 t | 2023 | unchanged | falling |
| 59 | Guatemala | 1 1000 t | 2023 | — | volatile |
| 59 | Jamaica | 1 1000 t | 2023 | down 50.0% | falling |
| 59 | Kazakhstan | 1 1000 t | 2023 | — | volatile |
| 59 | Kuwait | 1 1000 t | 2023 | — | volatile |
| 59 | Maldives | 1 1000 t | 2023 | — | volatile |
| 59 | Mauritius | 1 1000 t | 2023 | — | volatile |
| 59 | Namibia | 1 1000 t | 2023 | — | volatile |
| 59 | New Caledonia | 1 1000 t | 2023 | unchanged | flat |
| 59 | Peru | 1 1000 t | 2023 | unchanged | volatile |
| 59 | Philippines | 1 1000 t | 2023 | unchanged | volatile |
| 59 | French Polynesia | 1 1000 t | 2023 | unchanged | flat |
| 59 | Qatar | 1 1000 t | 2023 | — | flat |
| 59 | Uruguay | 1 1000 t | 2023 | down 50.0% | falling |
| 59 | Melanesia | 1 1000 t | 2023 | down 50.0% | falling |
| 59 | Polynesia | 1 1000 t | 2023 | unchanged | flat |
| 59 | Iran (Islamic Republic of) | 1 1000 t | 2018 | — | volatile |
| 59 | Republic of Moldova | 1 1000 t | 2023 | — | volatile |
| 59 | Lao People's Democratic Republic | 1 1000 t | 2023 | — | volatile |
| 82 | Angola | 0 1000 t | 2023 | down 100.0% | volatile |
| 82 | Albania | 0 1000 t | 2023 | — | flat |
| 82 | Armenia | 0 1000 t | 2023 | — | flat |
| 82 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 82 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 82 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 82 | Bahrain | 0 1000 t | 2023 | — | flat |
| 82 | Bahamas | 0 1000 t | 2023 | — | volatile |
| 82 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 82 | Belize | 0 1000 t | 2023 | — | flat |
| 82 | Barbados | 0 1000 t | 2023 | — | flat |
| 82 | Bhutan | 0 1000 t | 2023 | — | flat |
| 82 | Botswana | 0 1000 t | 2023 | — | flat |
| 82 | Cameroon | 0 1000 t | 2023 | — | flat |
| 82 | Congo | 0 1000 t | 2023 | — | volatile |
| 82 | Comoros | 0 1000 t | 2023 | — | flat |
| 82 | Djibouti | 0 1000 t | 2023 | — | flat |
| 82 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 82 | Ecuador | 0 1000 t | 2023 | — | volatile |
| 82 | Egypt | 0 1000 t | 2023 | — | volatile |
| 82 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 82 | Fiji | 0 1000 t | 2023 | — | flat |
| 82 | Gabon | 0 1000 t | 2023 | — | flat |
| 82 | Georgia | 0 1000 t | 2023 | — | flat |
| 82 | Ghana | 0 1000 t | 2023 | — | flat |
| 82 | Guinea | 0 1000 t | 2023 | — | flat |
| 82 | Gambia | 0 1000 t | 2023 | — | flat |
| 82 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 82 | Grenada | 0 1000 t | 2023 | — | flat |
| 82 | Guyana | 0 1000 t | 2023 | — | flat |
| 82 | Honduras | 0 1000 t | 2023 | — | flat |
| 82 | Haiti | 0 1000 t | 2023 | — | flat |
| 82 | India | 0 1000 t | 2023 | — | flat |
| 82 | Iraq | 0 1000 t | 2023 | — | flat |
| 82 | Jordan | 0 1000 t | 2023 | — | flat |
| 82 | Kenya | 0 1000 t | 2023 | — | flat |
| 82 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 82 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 82 | Kiribati | 0 1000 t | 2023 | — | flat |
| 82 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 82 | Lebanon | 0 1000 t | 2023 | down 100.0% | volatile |
| 82 | Liberia | 0 1000 t | 2023 | — | flat |
| 82 | Libya | 0 1000 t | 2023 | — | volatile |
| 82 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 82 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 82 | Lesotho | 0 1000 t | 2023 | — | flat |
| 82 | Madagascar | 0 1000 t | 2023 | — | flat |
| 82 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 82 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 82 | Myanmar | 0 1000 t | 2023 | — | flat |
| 82 | Montenegro | 0 1000 t | 2023 | — | flat |
| 82 | Mongolia | 0 1000 t | 2023 | — | flat |
| 82 | Mozambique | 0 1000 t | 2023 | — | flat |
| 82 | Mauritania | 0 1000 t | 2023 | — | flat |
| 82 | Malawi | 0 1000 t | 2023 | — | flat |
| 82 | Niger | 0 1000 t | 2023 | — | flat |
| 82 | Nigeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 82 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 82 | Nepal | 0 1000 t | 2023 | — | flat |
| 82 | Oman | 0 1000 t | 2023 | — | volatile |
| 82 | Pakistan | 0 1000 t | 2023 | — | flat |
| 82 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 82 | Paraguay | 0 1000 t | 2023 | — | flat |
| 82 | Rwanda | 0 1000 t | 2023 | — | flat |
| 82 | Senegal | 0 1000 t | 2023 | — | flat |
| 82 | Solomon Islands | 0 1000 t | 2023 | — | volatile |
| 82 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 82 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 82 | Serbia | 0 1000 t | 2023 | — | volatile |
| 82 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 82 | Suriname | 0 1000 t | 2017 | — | flat |
| 82 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 82 | Eswatini | 0 1000 t | 2023 | — | flat |
| 82 | Seychelles | 0 1000 t | 2023 | — | flat |
| 82 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 82 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 82 | Tonga | 0 1000 t | 2023 | — | flat |
| 82 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 82 | Tunisia | 0 1000 t | 2023 | down 100.0% | volatile |
| 82 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 82 | Uganda | 0 1000 t | 2023 | — | flat |
| 82 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 82 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 82 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 82 | Samoa | 0 1000 t | 2023 | — | flat |
| 82 | Yemen | 0 1000 t | 2023 | — | flat |
| 82 | Zambia | 0 1000 t | 2023 | — | flat |
| 82 | Zimbabwe | 0 1000 t | 2023 | — | volatile |
| 82 | Micronesia | 0 1000 t | 2023 | — | flat |
| 82 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 82 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 82 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 82 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 82 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 82 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 82 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 82 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 82 | Democratic People's Republic of Korea | 0 1000 t | 2018 | down 100.0% | volatile |
| 82 | 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 3,217 1000 t
- Asia 1,414 1000 t
- Europe 1,212 1000 t
- Eastern Asia 1,199 1000 t
- European Union (27) 971 1000 t
- Southern Europe 530 1000 t
- Americas 517 1000 t
- Northern America 475 1000 t
- United States of America 421 1000 t
- Western Europe 391 1000 t
- Eastern Europe 219 1000 t
- South-eastern Asia 188 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.