Alcohol, Non-Food — 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
Alcohol, Non-Food — Import quantity is currently reported for 154 countries. The highest value is 2,410 1000 t in Canada; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 5 1000 t, and the mean is 98.72 1000 t.
Over the past decade 61 countries rose and 41 fell. The largest increase was in Democratic Republic of the Congo (up 2,400.0%), and the largest decrease in Armenia (down 100.0%).
Alcohol, Non-Food — Import quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Canada | 2,410 1000 t | 2023 | up 115.4% | rising |
| 2 | Netherlands (Kingdom of the) | 1,434 1000 t | 2023 | up 123.4% | rising |
| 3 | Germany | 1,178 1000 t | 2023 | up 10.8% | rising |
| 4 | Republic of Korea | 1,131 1000 t | 2023 | up 421.2% | volatile |
| 5 | United Kingdom | 999 1000 t | 2023 | up 46.9% | rising |
| 5 | United Kingdom of Great Britain and Northern Ireland | 999 1000 t | 2023 | up 46.9% | rising |
| 7 | France | 814 1000 t | 2023 | up 367.8% | volatile |
| 8 | Belgium | 574 1000 t | 2023 | up 250.0% | volatile |
| 9 | United States | 558 1000 t | 2023 | down 72.8% | falling |
| 10 | Philippines | 468 1000 t | 2023 | up 77.3% | rising |
| 11 | Mexico | 344 1000 t | 2023 | up 164.6% | rising |
| 12 | Sweden | 318 1000 t | 2023 | up 40.7% | rising |
| 13 | India | 273 1000 t | 2023 | up 702.9% | volatile |
| 14 | Spain | 272 1000 t | 2023 | up 169.3% | rising |
| 15 | Colombia | 251 1000 t | 2023 | up 126.1% | volatile |
| 16 | Italy | 246 1000 t | 2023 | up 7.0% | rising |
| 17 | Peru | 188 1000 t | 2023 | up 102.2% | rising |
| 18 | Denmark | 184 1000 t | 2023 | up 41.5% | rising |
| 19 | Romania | 150 1000 t | 2023 | up 158.6% | rising |
| 20 | Poland | 133 1000 t | 2023 | up 41.5% | rising |
| 21 | United Arab Emirates | 124 1000 t | 2023 | down 48.1% | volatile |
| 22 | Switzerland | 118 1000 t | 2023 | up 187.8% | rising |
| 23 | Nigeria | 117 1000 t | 2023 | down 25.5% | rising |
| 24 | Caribbean | 104 1000 t | 2023 | down 65.1% | volatile |
| 25 | Saudi Arabia | 102 1000 t | 2023 | up 500.0% | volatile |
| 26 | Greece | 85 1000 t | 2023 | up 240.0% | volatile |
| 27 | Turkey | 84 1000 t | 2023 | up 25.4% | rising |
| 27 | Türkiye | 84 1000 t | 2023 | up 25.4% | rising |
| 29 | Lithuania | 81 1000 t | 2023 | up 478.6% | volatile |
| 30 | Jamaica | 79 1000 t | 2023 | down 73.0% | volatile |
| 31 | Czechia | 77 1000 t | 2023 | up 541.7% | rising |
| 32 | Finland | 75 1000 t | 2023 | up 226.1% | volatile |
| 33 | Austria | 71 1000 t | 2023 | up 129.0% | rising |
| 34 | Portugal | 58 1000 t | 2023 | up 427.3% | rising |
| 35 | Norway | 57 1000 t | 2023 | up 29.5% | rising |
| 36 | Angola | 56 1000 t | 2023 | up 51.4% | rising |
| 36 | Cameroon | 56 1000 t | 2023 | up 133.3% | rising |
| 38 | Ireland | 53 1000 t | 2023 | up 178.9% | rising |
| 39 | Brazil | 47 1000 t | 2023 | down 54.8% | volatile |
| 40 | Kenya | 46 1000 t | 2023 | up 1,433.3% | volatile |
| 41 | China | 44 1000 t | 2023 | down 48.2% | volatile |
| 42 | China, Taiwan Province of | 43 1000 t | 2023 | down 48.8% | falling |
| 43 | Ghana | 40 1000 t | 2023 | up 5.3% | rising |
| 44 | Chile | 34 1000 t | 2023 | up 21.4% | rising |
| 45 | Hungary | 30 1000 t | 2023 | up 3.4% | falling |
| 45 | United Republic of Tanzania | 30 1000 t | 2023 | up 20.0% | falling |
| 47 | Cote d'Ivoire | 25 1000 t | 2023 | up 316.7% | volatile |
| 47 | Democratic Republic of the Congo | 25 1000 t | 2023 | up 2,400.0% | volatile |
| 47 | Côte d'Ivoire | 25 1000 t | 2023 | up 316.7% | volatile |
| 47 | Democratic People's Republic of Korea | 25 1000 t | 2018 | — | rising |
| 51 | Ecuador | 19 1000 t | 2023 | up 90.0% | volatile |
| 52 | Dominican Republic | 18 1000 t | 2023 | up 157.1% | rising |
| 52 | Thailand | 18 1000 t | 2023 | down 14.3% | rising |
| 54 | Argentina | 17 1000 t | 2023 | up 1,600.0% | volatile |
| 54 | Georgia | 17 1000 t | 2023 | up 183.3% | volatile |
| 56 | Vietnam | 15 1000 t | 2023 | — | volatile |
| 56 | Venezuela (Bolivarian Republic of) | 15 1000 t | 2023 | — | volatile |
| 56 | Viet Nam | 15 1000 t | 2023 | — | volatile |
| 59 | Slovakia | 14 1000 t | 2023 | up 40.0% | rising |
| 60 | Rwanda | 12 1000 t | 2023 | up 500.0% | volatile |
| 61 | Israel | 10 1000 t | 2023 | down 41.2% | falling |
| 61 | Mozambique | 10 1000 t | 2023 | down 79.6% | volatile |
| 61 | Malaysia | 10 1000 t | 2023 | down 16.7% | volatile |
| 61 | Serbia | 10 1000 t | 2023 | up 900.0% | volatile |
| 61 | Australia and New Zealand | 10 1000 t | 2023 | down 28.6% | volatile |
| 66 | Iraq | 9 1000 t | 2023 | up 800.0% | volatile |
| 66 | Madagascar | 9 1000 t | 2023 | unchanged | rising |
| 66 | El Salvador | 9 1000 t | 2023 | down 80.0% | volatile |
| 69 | Bulgaria | 8 1000 t | 2023 | up 60.0% | volatile |
| 69 | Croatia | 8 1000 t | 2023 | up 166.7% | volatile |
| 69 | Latvia | 8 1000 t | 2023 | down 50.0% | falling |
| 72 | Egypt | 6 1000 t | 2023 | up 500.0% | volatile |
| 72 | Honduras | 6 1000 t | 2023 | up 500.0% | volatile |
| 72 | Liberia | 6 1000 t | 2023 | up 50.0% | rising |
| 72 | New Zealand | 6 1000 t | 2023 | unchanged | volatile |
| 76 | Congo | 5 1000 t | 2023 | up 66.7% | rising |
| 76 | Estonia | 5 1000 t | 2023 | up 66.7% | rising |
| 76 | Jordan | 5 1000 t | 2023 | down 28.6% | volatile |
| 76 | Slovenia | 5 1000 t | 2023 | unchanged | rising |
| 76 | Uruguay | 5 1000 t | 2023 | down 16.7% | falling |
| 76 | Zambia | 5 1000 t | 2023 | down 16.7% | volatile |
| 82 | Haiti | 4 1000 t | 2023 | up 300.0% | volatile |
| 82 | Indonesia | 4 1000 t | 2023 | — | volatile |
| 84 | Australia | 3 1000 t | 2023 | down 62.5% | volatile |
| 84 | Burkina Faso | 3 1000 t | 2023 | down 50.0% | falling |
| 84 | Kazakhstan | 3 1000 t | 2023 | — | volatile |
| 84 | Luxembourg | 3 1000 t | 2023 | up 200.0% | rising |
| 84 | Trinidad and Tobago | 3 1000 t | 2023 | down 25.0% | volatile |
| 89 | Albania | 2 1000 t | 2023 | down 50.0% | volatile |
| 89 | Azerbaijan | 2 1000 t | 2023 | — | rising |
| 89 | Algeria | 2 1000 t | 2023 | down 33.3% | volatile |
| 89 | Guinea | 2 1000 t | 2023 | down 71.4% | falling |
| 89 | Iceland | 2 1000 t | 2023 | up 100.0% | volatile |
| 89 | Lebanon | 2 1000 t | 2023 | down 33.3% | rising |
| 89 | Nicaragua | 2 1000 t | 2023 | — | volatile |
| 89 | Oman | 2 1000 t | 2023 | up 100.0% | volatile |
| 89 | Senegal | 2 1000 t | 2023 | — | volatile |
| 89 | Sierra Leone | 2 1000 t | 2023 | down 75.0% | rising |
| 89 | Uganda | 2 1000 t | 2023 | down 90.9% | volatile |
| 89 | Zimbabwe | 2 1000 t | 2023 | — | volatile |
| 89 | Melanesia | 2 1000 t | 2023 | up 100.0% | volatile |
| 102 | Costa Rica | 1 1000 t | 2023 | down 97.8% | volatile |
| 102 | Cyprus | 1 1000 t | 2023 | — | volatile |
| 102 | Ethiopia | 1 1000 t | 2023 | — | volatile |
| 102 | Gabon | 1 1000 t | 2023 | unchanged | volatile |
| 102 | Guinea-Bissau | 1 1000 t | 2023 | unchanged | falling |
| 102 | Guyana | 1 1000 t | 2023 | — | volatile |
| 102 | Kuwait | 1 1000 t | 2023 | unchanged | volatile |
| 102 | Morocco | 1 1000 t | 2023 | unchanged | volatile |
| 102 | North Macedonia | 1 1000 t | 2023 | unchanged | volatile |
| 102 | Montenegro | 1 1000 t | 2023 | — | volatile |
| 102 | Malawi | 1 1000 t | 2023 | down 66.7% | volatile |
| 102 | Nepal | 1 1000 t | 2023 | down 87.5% | falling |
| 102 | Pakistan | 1 1000 t | 2023 | — | volatile |
| 102 | Panama | 1 1000 t | 2023 | unchanged | volatile |
| 102 | Papua New Guinea | 1 1000 t | 2023 | — | volatile |
| 102 | Seychelles | 1 1000 t | 2023 | — | volatile |
| 102 | Syria | 1 1000 t | 2023 | down 66.7% | volatile |
| 102 | Yemen | 1 1000 t | 2023 | — | volatile |
| 102 | China, Hong Kong SAR | 1 1000 t | 2023 | unchanged | flat |
| 102 | Syrian Arab Republic | 1 1000 t | 2023 | down 66.7% | volatile |
| 122 | Afghanistan | 0 1000 t | 2023 | — | volatile |
| 122 | Armenia | 0 1000 t | 2023 | down 100.0% | volatile |
| 122 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 122 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 122 | Bahamas | 0 1000 t | 2023 | — | volatile |
| 122 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 122 | Belarus | 0 1000 t | 2023 | — | volatile |
| 122 | Botswana | 0 1000 t | 2023 | down 100.0% | volatile |
| 122 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 122 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 122 | Laos | 0 1000 t | 2023 | — | volatile |
| 122 | Libya | 0 1000 t | 2023 | — | volatile |
| 122 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 122 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | volatile |
| 122 | Moldova | 0 1000 t | 2023 | — | volatile |
| 122 | Marshall Islands | 0 1000 t | 2023 | — | volatile |
| 122 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 122 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 122 | Namibia | 0 1000 t | 2023 | down 100.0% | volatile |
| 122 | Paraguay | 0 1000 t | 2023 | — | volatile |
| 122 | Qatar | 0 1000 t | 2023 | — | volatile |
| 122 | Russia | 0 1000 t | 2023 | — | volatile |
| 122 | Turkmenistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 122 | Tunisia | 0 1000 t | 2023 | down 100.0% | falling |
| 122 | Ukraine | 0 1000 t | 2023 | — | volatile |
| 122 | South Africa | 0 1000 t | 2023 | down 100.0% | volatile |
| 122 | Micronesia | 0 1000 t | 2023 | — | volatile |
| 122 | Iran (Islamic Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 122 | Republic of Moldova | 0 1000 t | 2023 | — | volatile |
| 122 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 122 | China, mainland | 0 1000 t | 2023 | — | volatile |
| 122 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 122 | China, Macao SAR | 0 1000 t | 2023 | down 100.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 14,741 1000 t
- Europe 7,074 1000 t
- European Union (27) 5,885 1000 t
- Western Europe 4,192 1000 t
- Americas 4,014 1000 t
- Asia 3,141 1000 t
- Northern America 2,968 1000 t
- Eastern Asia 1,987 1000 t
- Northern Europe 1,782 1000 t
- Southern Europe 688 1000 t
- Net Food Importing Developing Countries (NFIDCs) 608 1000 t
- South America 578 1000 t
- United States of America 558 1000 t
- South-Eastern Asia 515 1000 t
- Africa 499 1000 t
- Eastern Europe 412 1000 t
- Central America 364 1000 t
- Western Asia 361 1000 t
- Southern Asia 275 1000 t
- Low Income Food Deficit Countries (LIFDCs) 252 1000 t
- Western Africa 224 1000 t
- Least Developed Countries (LDCs) 202 1000 t
- Middle Africa 143 1000 t
- Eastern Africa 121 1000 t
- Small island developing States (SIDS) 109 1000 t
- Land Locked Developing Countries (LLDCs) 35 1000 t
- Oceania 12 1000 t
- Northern Africa 10 1000 t
- Central Asia 3 1000 t
- Southern Africa 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.