Infant food — Stock Variation 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 — Stock Variation is currently reported for 96 countries. The highest value is 19 1000 t in China; the lowest is -15 1000 t in Russian Federation.
The median across all reporting countries is 0 1000 t, and the mean is 0.3125 1000 t.
Over the past decade 12 countries rose and 27 fell. The largest increase was in Saudi Arabia (up 133.3%), and the largest decrease in Russia (down 350.0%).
Infant food — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 19 1000 t | 2023 | down 24.0% | volatile |
| 1 | China, mainland | 19 1000 t | 2023 | down 20.8% | volatile |
| 3 | Uzbekistan | 5 1000 t | 2023 | — | volatile |
| 4 | Kenya | 4 1000 t | 2023 | — | volatile |
| 5 | Cambodia | 3 1000 t | 2023 | — | volatile |
| 6 | Algeria | 2 1000 t | 2023 | — | volatile |
| 6 | Oman | 2 1000 t | 2023 | — | volatile |
| 6 | Republic of Korea | 2 1000 t | 2023 | — | volatile |
| 9 | Botswana | 1 1000 t | 2023 | — | volatile |
| 9 | Jamaica | 1 1000 t | 2023 | — | volatile |
| 9 | Kuwait | 1 1000 t | 2023 | unchanged | volatile |
| 9 | Philippines | 1 1000 t | 2023 | up 116.7% | volatile |
| 9 | Saudi Arabia | 1 1000 t | 2023 | up 133.3% | volatile |
| 9 | Sierra Leone | 1 1000 t | 2023 | — | volatile |
| 9 | Caribbean | 1 1000 t | 2023 | — | volatile |
| 16 | Afghanistan | 0 1000 t | 2023 | — | volatile |
| 16 | Angola | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | United Arab Emirates | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Argentina | 0 1000 t | 2023 | — | flat |
| 16 | Australia | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 16 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 16 | Bangladesh | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 16 | Belize | 0 1000 t | 2023 | — | volatile |
| 16 | Brazil | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Canada | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 16 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 16 | Congo | 0 1000 t | 2023 | — | volatile |
| 16 | Colombia | 0 1000 t | 2023 | — | volatile |
| 16 | Costa Rica | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | Czechia | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Germany | 0 1000 t | 2023 | — | flat |
| 16 | Dominican Republic | 0 1000 t | 2023 | — | volatile |
| 16 | Ecuador | 0 1000 t | 2023 | — | flat |
| 16 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Ethiopia | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | Finland | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | United Kingdom | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Guinea | 0 1000 t | 2023 | — | volatile |
| 16 | Greece | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 16 | Honduras | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | Hungary | 0 1000 t | 2023 | — | volatile |
| 16 | Indonesia | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | Iraq | 0 1000 t | 2023 | — | volatile |
| 16 | Italy | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 16 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 16 | Libya | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Morocco | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 16 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 16 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 16 | Malawi | 0 1000 t | 2023 | — | volatile |
| 16 | Malaysia | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Namibia | 0 1000 t | 2023 | — | volatile |
| 16 | Niger | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 16 | Nicaragua | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | Panama | 0 1000 t | 2023 | — | flat |
| 16 | Peru | 0 1000 t | 2023 | — | volatile |
| 16 | Poland | 0 1000 t | 2023 | — | volatile |
| 16 | Portugal | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Senegal | 0 1000 t | 2023 | — | volatile |
| 16 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 16 | Serbia | 0 1000 t | 2023 | — | volatile |
| 16 | Suriname | 0 1000 t | 2023 | — | volatile |
| 16 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 16 | Sweden | 0 1000 t | 2023 | — | volatile |
| 16 | Thailand | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 16 | Turkey | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Ukraine | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | United States | 0 1000 t | 2023 | — | volatile |
| 16 | Vietnam | 0 1000 t | 2023 | — | volatile |
| 16 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | South Africa | 0 1000 t | 2023 | up 100.0% | flat |
| 16 | Zambia | 0 1000 t | 2023 | — | volatile |
| 16 | Zimbabwe | 0 1000 t | 2023 | — | volatile |
| 16 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 16 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 16 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Viet Nam | 0 1000 t | 2023 | — | volatile |
| 16 | Türkiye | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Australia and New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 16 | United Republic of Tanzania | 0 1000 t | 2023 | — | volatile |
| 16 | China, Taiwan Province of | 0 1000 t | 2023 | down 100.0% | flat |
| 16 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | China, Macao SAR | 0 1000 t | 2023 | up 100.0% | volatile |
| 187 | Austria | -1 1000 t | 2023 | — | volatile |
| 188 | Belgium | -2 1000 t | 2023 | — | volatile |
| 189 | Russia | -15 1000 t | 2023 | down 350.0% | volatile |
| 189 | Russian Federation | -15 1000 t | 2023 | down 350.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Asia 34 1000 t
- World 31 1000 t
- Eastern Asia 20 1000 t
- Net Food Importing Developing Countries (NFIDCs) 15 1000 t
- Low Income Food Deficit Countries (LIFDCs) 14 1000 t
- Africa 13 1000 t
- Least Developed Countries (LDCs) 8 1000 t
- Eastern Africa 7 1000 t
- Land Locked Developing Countries (LLDCs) 7 1000 t
- Central Asia 5 1000 t
- South-Eastern Asia 4 1000 t
- Western Asia 4 1000 t
- Northern Africa 2 1000 t
- Western Africa 2 1000 t
- Americas 1 1000 t
- Small island developing States (SIDS) 1 1000 t
- Southern Africa 1 1000 t
- Oceania 0 1000 t
- South America 0 1000 t
- Northern America 0 1000 t
- Central America 0 1000 t
- Northern Europe 0 1000 t
- Southern Europe 0 1000 t
- Middle Africa 0 1000 t
- Southern Asia 0 1000 t
- United States of America 0 1000 t
- European Union (27) -2 1000 t
- Western Europe -3 1000 t
- Eastern Europe -15 1000 t
- Europe -17 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.