Infant food — Export 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
Infant food — Export quantity is currently reported for 147 countries. The highest value is 169 1000 t in Netherlands (Kingdom of the); the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 0 1000 t, and the mean is 8.31 1000 t.
Over the past decade 24 countries rose and 20 fell. The largest increase was in Saudi Arabia (up 400.0%), and the largest decrease in Finland (down 100.0%).
Infant food — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Netherlands (Kingdom of the) | 169 1000 t | 2023 | up 0.6% | rising |
| 2 | France | 164 1000 t | 2023 | up 23.3% | rising |
| 3 | Germany | 105 1000 t | 2023 | up 52.2% | rising |
| 4 | Australia and New Zealand | 95 1000 t | 2023 | up 93.9% | volatile |
| 5 | Ireland | 89 1000 t | 2023 | down 18.3% | flat |
| 6 | New Zealand | 80 1000 t | 2023 | up 90.5% | rising |
| 7 | Mexico | 58 1000 t | 2023 | up 7.4% | rising |
| 8 | Spain | 57 1000 t | 2023 | down 3.4% | rising |
| 8 | Poland | 57 1000 t | 2023 | up 216.7% | rising |
| 10 | Switzerland | 34 1000 t | 2023 | down 12.8% | rising |
| 11 | Thailand | 23 1000 t | 2023 | up 228.6% | volatile |
| 12 | Belgium | 22 1000 t | 2023 | unchanged | rising |
| 12 | Denmark | 22 1000 t | 2023 | down 12.0% | rising |
| 14 | United Arab Emirates | 19 1000 t | 2023 | up 375.0% | volatile |
| 15 | Rwanda | 16 1000 t | 2023 | — | volatile |
| 16 | Australia | 15 1000 t | 2023 | up 114.3% | volatile |
| 16 | Indonesia | 15 1000 t | 2023 | up 275.0% | volatile |
| 16 | Russian Federation | 15 1000 t | 2023 | up 7.1% | rising |
| 19 | Brazil | 13 1000 t | 2023 | up 62.5% | rising |
| 19 | Chile | 13 1000 t | 2023 | down 40.9% | rising |
| 21 | Kenya | 9 1000 t | 2023 | — | volatile |
| 21 | Malaysia | 9 1000 t | 2023 | down 67.9% | falling |
| 21 | Portugal | 9 1000 t | 2023 | down 57.1% | falling |
| 21 | Sweden | 9 1000 t | 2023 | up 80.0% | rising |
| 25 | Austria | 8 1000 t | 2023 | up 14.3% | rising |
| 25 | China | 8 1000 t | 2023 | up 300.0% | volatile |
| 25 | Ghana | 8 1000 t | 2023 | up 166.7% | volatile |
| 25 | United Kingdom of Great Britain and Northern Ireland | 8 1000 t | 2023 | up 33.3% | rising |
| 29 | Philippines | 7 1000 t | 2023 | down 50.0% | volatile |
| 30 | Croatia | 6 1000 t | 2023 | down 25.0% | flat |
| 30 | China, mainland | 6 1000 t | 2023 | — | volatile |
| 32 | Saudi Arabia | 5 1000 t | 2023 | up 400.0% | volatile |
| 33 | Czechia | 4 1000 t | 2023 | up 300.0% | volatile |
| 33 | Italy | 4 1000 t | 2023 | — | volatile |
| 35 | Argentina | 3 1000 t | 2023 | down 88.0% | volatile |
| 35 | Egypt | 3 1000 t | 2023 | — | volatile |
| 35 | Hungary | 3 1000 t | 2023 | up 50.0% | rising |
| 35 | India | 3 1000 t | 2023 | down 57.1% | falling |
| 35 | Republic of Korea | 3 1000 t | 2023 | down 75.0% | falling |
| 40 | Belarus | 2 1000 t | 2023 | unchanged | rising |
| 40 | Estonia | 2 1000 t | 2023 | unchanged | volatile |
| 40 | Oman | 2 1000 t | 2023 | — | volatile |
| 40 | Pakistan | 2 1000 t | 2023 | up 100.0% | rising |
| 40 | Serbia | 2 1000 t | 2023 | — | volatile |
| 40 | Slovenia | 2 1000 t | 2023 | down 60.0% | falling |
| 40 | China, Hong Kong SAR | 2 1000 t | 2023 | up 100.0% | volatile |
| 40 | Iran (Islamic Republic of) | 2 1000 t | 2023 | unchanged | rising |
| 40 | Türkiye | 2 1000 t | 2023 | up 100.0% | rising |
| 49 | Canada | 1 1000 t | 2023 | unchanged | falling |
| 49 | Georgia | 1 1000 t | 2023 | — | volatile |
| 49 | Greece | 1 1000 t | 2023 | unchanged | falling |
| 49 | Jordan | 1 1000 t | 2023 | unchanged | volatile |
| 49 | Lithuania | 1 1000 t | 2023 | — | volatile |
| 49 | Latvia | 1 1000 t | 2023 | unchanged | rising |
| 49 | Ukraine | 1 1000 t | 2023 | — | volatile |
| 56 | Afghanistan | 0 1000 t | 2023 | — | flat |
| 56 | Angola | 0 1000 t | 2022 | — | flat |
| 56 | Albania | 0 1000 t | 2019 | — | flat |
| 56 | Armenia | 0 1000 t | 2023 | — | flat |
| 56 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 56 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 56 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 56 | Bulgaria | 0 1000 t | 2023 | — | flat |
| 56 | Bahrain | 0 1000 t | 2023 | — | flat |
| 56 | Bahamas | 0 1000 t | 2023 | — | flat |
| 56 | Bosnia and Herzegovina | 0 1000 t | 2019 | — | flat |
| 56 | Belize | 0 1000 t | 2014 | — | flat |
| 56 | Barbados | 0 1000 t | 2023 | — | flat |
| 56 | Botswana | 0 1000 t | 2023 | — | flat |
| 56 | Cameroon | 0 1000 t | 2023 | — | flat |
| 56 | Congo | 0 1000 t | 2022 | — | flat |
| 56 | Colombia | 0 1000 t | 2023 | — | volatile |
| 56 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 56 | Cyprus | 0 1000 t | 2023 | — | flat |
| 56 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 56 | Algeria | 0 1000 t | 2023 | — | volatile |
| 56 | Ecuador | 0 1000 t | 2022 | — | flat |
| 56 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 56 | Finland | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Fiji | 0 1000 t | 2023 | — | flat |
| 56 | Gabon | 0 1000 t | 2023 | — | flat |
| 56 | Guinea | 0 1000 t | 2023 | — | flat |
| 56 | Gambia | 0 1000 t | 2023 | — | flat |
| 56 | Guatemala | 0 1000 t | 2023 | — | flat |
| 56 | Guyana | 0 1000 t | 2023 | — | flat |
| 56 | Honduras | 0 1000 t | 2021 | — | flat |
| 56 | Iceland | 0 1000 t | 2021 | — | flat |
| 56 | Israel | 0 1000 t | 2023 | — | flat |
| 56 | Jamaica | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Kyrgyzstan | 0 1000 t | 2022 | down 100.0% | volatile |
| 56 | Cambodia | 0 1000 t | 2023 | — | flat |
| 56 | Saint Kitts and Nevis | 0 1000 t | 2017 | — | flat |
| 56 | Kuwait | 0 1000 t | 2023 | — | flat |
| 56 | Lebanon | 0 1000 t | 2023 | — | flat |
| 56 | Liberia | 0 1000 t | 2019 | — | flat |
| 56 | Saint Lucia | 0 1000 t | 2021 | — | flat |
| 56 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 56 | Lesotho | 0 1000 t | 2023 | — | flat |
| 56 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 56 | Morocco | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Madagascar | 0 1000 t | 2023 | — | flat |
| 56 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 56 | Malta | 0 1000 t | 2022 | — | flat |
| 56 | Myanmar | 0 1000 t | 2023 | — | flat |
| 56 | Montenegro | 0 1000 t | 2023 | — | flat |
| 56 | Mongolia | 0 1000 t | 2022 | — | flat |
| 56 | Mozambique | 0 1000 t | 2023 | — | flat |
| 56 | Mauritius | 0 1000 t | 2023 | — | flat |
| 56 | Malawi | 0 1000 t | 2023 | — | flat |
| 56 | Namibia | 0 1000 t | 2023 | — | flat |
| 56 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 56 | Niger | 0 1000 t | 2020 | — | flat |
| 56 | Nigeria | 0 1000 t | 2023 | — | flat |
| 56 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 56 | Norway | 0 1000 t | 2023 | — | flat |
| 56 | Nepal | 0 1000 t | 2021 | — | flat |
| 56 | Panama | 0 1000 t | 2020 | — | volatile |
| 56 | Peru | 0 1000 t | 2023 | — | flat |
| 56 | Paraguay | 0 1000 t | 2015 | — | flat |
| 56 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 56 | Romania | 0 1000 t | 2023 | — | flat |
| 56 | Senegal | 0 1000 t | 2023 | — | flat |
| 56 | El Salvador | 0 1000 t | 2023 | — | flat |
| 56 | Suriname | 0 1000 t | 2018 | — | flat |
| 56 | Slovakia | 0 1000 t | 2023 | — | flat |
| 56 | Eswatini | 0 1000 t | 2023 | — | flat |
| 56 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 56 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 56 | Uganda | 0 1000 t | 2023 | — | volatile |
| 56 | Uruguay | 0 1000 t | 2020 | — | flat |
| 56 | Yemen | 0 1000 t | 2017 | — | flat |
| 56 | Zambia | 0 1000 t | 2023 | — | flat |
| 56 | Zimbabwe | 0 1000 t | 2022 | — | flat |
| 56 | Melanesia | 0 1000 t | 2023 | — | flat |
| 56 | Polynesia | 0 1000 t | 2023 | — | flat |
| 56 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 56 | Caribbean | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Bolivia (Plurinational State of) | 0 1000 t | 2020 | — | flat |
| 56 | Republic of Moldova | 0 1000 t | 2022 | — | flat |
| 56 | Syrian Arab Republic | 0 1000 t | 2020 | — | flat |
| 56 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 56 | Viet Nam | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 56 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 56 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 56 | China, Macao SAR | 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 1,166 1000 t
- Europe 794 1000 t
- European Union (27) 733 1000 t
- Western Europe 501 1000 t
- Northern Europe 131 1000 t
- Americas 117 1000 t
- Asia 109 1000 t
- Oceania 95 1000 t
- Eastern Europe 82 1000 t
- Southern Europe 80 1000 t
- Central America 58 1000 t
- South-eastern Asia 53 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.